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US20200255911A1 - Method for Using Gene Expression to Determine Prognosis of Prostate Cancer - Google Patents

Method for Using Gene Expression to Determine Prognosis of Prostate Cancer Download PDF

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US20200255911A1
US20200255911A1 US16/800,292 US202016800292A US2020255911A1 US 20200255911 A1 US20200255911 A1 US 20200255911A1 US 202016800292 A US202016800292 A US 202016800292A US 2020255911 A1 US2020255911 A1 US 2020255911A1
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gene
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Steven Shak
Frederick L. Baehner
Tara Maddala
Mark Lee
Robert J. Pelham
Wayne Cowens
Diana Cherbavaz
Michael C. Kiefer
Michael Crager
Audrey Goddard
Joffre B. Baker
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MDxHealth SA
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Genomic Health Inc
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Assigned to GENOMIC HEALTH, INC. reassignment GENOMIC HEALTH, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: COWENS, WAYNE, BAKER, JOFFRE B., PELHAM, ROBERT J., GODDARD, AUDREY, KIEFER, MICHAEL C., LEE, MARK, SHAK, STEVEN, BAEHNER, FREDERICK L., CHERBAVAZ, DIANA, CRAGER, MICHAEL, MADDALA, TARA
Assigned to MDXHEALTH SA reassignment MDXHEALTH SA ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GENOMIC HEALTH, INC.
Priority to US17/820,987 priority patent/US20220396842A1/en
Priority to US18/782,817 priority patent/US20250129432A1/en
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present disclosure relates to molecular diagnostic assays that provide information concerning methods to use gene expression profiles to determine prognostic information for cancer patients.
  • the present disclosure provides genes and microRNAs, the expression levels of which may be used to determine the likelihood that a prostate cancer patient will experience a local or distant cancer recurrence.
  • Prostate cancer is the most common solid malignancy in men and the second most common cause of cancer-related death in men in North America and the European Union (EU). In 2008, over 180,000 patients will be diagnosed with prostate cancer in the United States alone and nearly 30,000 will die of this disease. Age is the single most important risk factor for the development of prostate cancer, and applies across all racial groups that have been studied. With the aging of the U.S. population, it is projected that the annual incidence of prostate cancer will double by 2025 to nearly 400,000 cases per year.
  • PSA prostate-specific antigen
  • This application discloses molecular assays that involve measurement of expression level(s) of one or more genes, gene subsets, microRNAs, or one or more microRNAs in combination with one or more genes or gene subsets, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likelihood of cancer recurrence.
  • the likelihood of cancer recurrence could be described in terms of a score based on clinical or biochemical recurrence-free interval.
  • this application discloses molecular assays that involve measurement of expression level(s) of one or more genes, gene subsets, microRNAs, or one or more microRNAs in combination with one or more genes or gene subsets, from a biological sample obtained to identify a risk classification for a prostate cancer patient.
  • patients may be stratified using expression level(s) of one or more genes or microRNAs associated, positively or negatively, with cancer recurrence or death from cancer, or with a prognostic factor.
  • the prognostic factor is Gleason pattern.
  • the biological sample may be obtained from standard methods, including surgery, biopsy, or bodily fluids. It may comprise tumor tissue or cancer cells, and, in some cases, histologically normal tissue, e.g., histologically normal tissue adjacent the tumor tissue. In exemplary embodiments, the biological sample is positive or negative for a TMPRSS2 fusion.
  • expression level(s) of one or more genes and/or microRNAs that are associated, positively or negatively, with a particular clinical outcome in prostate cancer are used to determine prognosis and appropriate therapy.
  • the genes disclosed herein may be used alone or arranged in functional gene subsets, such as cell adhesion/migration, immediate-early stress response, and extracellular matrix-associated. Each gene subset comprises the genes disclosed herein, as well as genes that are co-expressed with one or more of the disclosed genes. The calculation may be performed on a computer, programmed to execute the gene expression analysis.
  • the microRNAs disclosed herein may also be used alone or in combination with any one or more of the microRNAs and/or genes disclosed.
  • the molecular assay may involve expression levels for at least two genes.
  • the genes, or gene subsets, may be weighted according to strength of association with prognosis or tumor microenvironment.
  • the molecular assay may involve expression levels of at least one gene and at least one microRNA.
  • the gene-microRNA combination may be selected based on the likelihood that the gene-microRNA combination functionally interact.
  • FIG. 1 shows the distribution of clinical and pathology assessments of biopsy Gleason score, baseline PSA level, and clinical T-stage.
  • tumor tissue sample refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues.
  • a tumor tissue sample may comprise multiple biological elements, such as one or more cancer cells, partial or fragmented cells, tumors in various stages, surrounding histologically normal-appearing tissue, and/or macro or micro-dissected tissue.
  • cancer and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth.
  • Examples of cancer in the present disclosure include cancer of the urogenital tract, such as prostate cancer.
  • the “pathology” of cancer includes all phenomena that compromise the well-being of the patient. This includes, without limitation, abnormal or uncontrollable cell growth, metastasis, interference with the normal functioning of neighboring cells, release of cytokines or other secretory products at abnormal levels, suppression or aggravation of inflammatory or immunological response, neoplasia, premalignancy, malignancy, invasion of surrounding or distant tissues or organs, such as lymph nodes, etc.
  • prostate cancer is used interchangeably and in the broadest sense refers to all stages and all forms of cancer arising from the tissue of the prostate gland.
  • T1 clinically inapparent tumor not palpable or visible by imaging
  • T1a tumor incidental histological finding in 5% or less of tissue resected
  • T1b tumor incidental histological finding in more than 5% of tissue resected
  • T1c tumor identified by needle biopsy
  • T2 tumor confined within prostate
  • T2a tumor involves one half of one lobe or less
  • T2b tumor involves more than half of one lobe, but not both lobes
  • T2c tumor involves both lobes
  • T3 tumor extends through the prostatic capsule
  • T3a extracapsular extension (unilateral or bilateral)
  • T3b tumor invades seminal vesicle(s)
  • T4 tumor is fixed or invades adjacent structures other than seminal ves
  • the Gleason Grading system is used to help evaluate the prognosis of men with prostate cancer. Together with other parameters, it is incorporated into a strategy of prostate cancer staging, which predicts prognosis and helps guide therapy.
  • a Gleason “score” or “grade” is given to prostate cancer based upon its microscopic appearance. Tumors with a low Gleason score typically grow slowly enough that they may not pose a significant threat to the patients in their lifetimes. These patients are monitored (“watchful waiting” or “active surveillance”) over time.
  • Gleason scores comprise grades of the two most common tumor patterns. These patterns are referred to as Gleason patterns 1-5, with pattern 1 being the most well-differentiated. Most have a mixture of patterns. To obtain a Gleason score or grade, the dominant pattern is added to the second most prevalent pattern to obtain a number between 2 and 10.
  • the Gleason Grades include: G1: well differentiated (slight anaplasia) (Gleason 2-4); G2: moderately differentiated (moderate anaplasia) (Gleason 5-6); G3-4: poorly differentiated/undifferentiated (marked anaplasia) (Gleason 7-10).
  • Stage groupings Stage I: T1a N0 M0 G1; Stage II: (T1a N0 M0 G2-4) or (T1b, c, T1, T2, N0 M0 Any G); Stage III: T3 N0 M0 Any G; Stage IV: (T4 N0 M0 Any G) or (Any T N1 M0 Any G) or (Any T Any N M1 Any G).
  • tumor tissue refers to a biological sample containing one or more cancer cells, or a fraction of one or more cancer cells.
  • biological sample may additionally comprise other biological components, such as histologically appearing normal cells (e.g., adjacent the tumor), depending upon the method used to obtain the tumor tissue, such as surgical resection, biopsy, or bodily fluids.
  • AUA risk group refers to the 2007 updated American Urological Association (AUA) guidelines for management of clinically localized prostate cancer, which clinicians use to determine whether a patient is at low, intermediate, or high risk of biochemical (PSA) relapse after local therapy.
  • AUA American Urological Association
  • adjacent tissue refers to histologically “normal” cells that are adjacent a tumor.
  • the AT expression profile may be associated with disease recurrence and survival.
  • non-tumor prostate tissue refers to histologically normal-appearing tissue adjacent a prostate tumor.
  • Prognostic factors are those variables related to the natural history of cancer, which influence the recurrence rates and outcome of patients once they have developed cancer. Clinical parameters that have been associated with a worse prognosis include, for example, increased tumor stage, PSA level at presentation, and Gleason grade or pattern. Prognostic factors are frequently used to categorize patients into subgroups with different baseline relapse risks.
  • prognosis is used herein to refer to the likelihood that a cancer patient will have a cancer-attributable death or progression, including recurrence, metastatic spread, and drug resistance, of a neoplastic disease, such as prostate cancer.
  • a “good prognosis” would include long term survival without recurrence and a “bad prognosis” would include cancer recurrence.
  • expression level refers to the normalized level of a gene product, e.g. the normalized value determined for the RNA expression level of a gene or for the polypeptide expression level of a gene.
  • gene product or “expression product” are used herein to refer to the RNA (ribonucleic acid) transcription products (transcripts) of the gene, including mRNA, and the polypeptide translation products of such RNA transcripts.
  • a gene product can be, for example, an unspliced RNA, an mRNA, a splice variant mRNA, a microRNA, a fragmented RNA, a polypeptide, a post-translationally modified polypeptide, a splice variant polypeptide, etc.
  • RNA transcript refers to the RNA transcription products of a gene, including, for example, mRNA, an unspliced RNA, a splice variant mRNA, a microRNA, and a fragmented RNA.
  • microRNA is used herein to refer to a small, non-coding, single-stranded RNA of ⁇ 18-25 nucleotides that may regulate gene expression.
  • RISC RNA-induced silencing complex
  • the complex binds to specific mRNA targets and causes translation repression or cleavage of these mRNA sequences.
  • each gene name used herein corresponds to the Official Symbol assigned to the gene and provided by Entrez Gene (URL: www.ncbi.nlm.nih.gov/sites/entrez) as of the filing date of this application.
  • the terms “correlated” and “associated” are used interchangeably herein to refer to the association between two measurements (or measured entities).
  • the disclosure provides genes, gene subsets, microRNAs, or microRNAs in combination with genes or gene subsets, the expression levels of which are associated with tumor stage.
  • the increased expression level of a gene or microRNA may be positively correlated (positively associated) with a good or positive prognosis.
  • Such a positive correlation may be demonstrated statistically in various ways, e.g. by a cancer recurrence hazard ratio less than one.
  • the increased expression level of a gene or microRNA may be negatively correlated (negatively associated) with a good or positive prognosis. In that case, for example, the patient may experience a cancer recurrence.
  • good prognosis or “positive prognosis” as used herein refer to a beneficial clinical outcome, such as long-term survival without recurrence.
  • bad prognosis or “negative prognosis” as used herein refer to a negative clinical outcome, such as cancer recurrence.
  • risk classification means a grouping of subjects by the level of risk (or likelihood) that the subject will experience a particular clinical outcome.
  • a subject may be classified into a risk group or classified at a level of risk based on the methods of the present disclosure, e.g. high, medium, or low risk.
  • a “risk group” is a group of subjects or individuals with a similar level of risk for a particular clinical outcome.
  • long-term survival is used herein to refer to survival for a particular time period, e.g., for at least 5 years, or for at least 10 years.
  • recurrence is used herein to refer to local or distant recurrence (i.e., metastasis) of cancer.
  • prostate cancer can recur locally in the tissue next to the prostate or in the seminal vesicles.
  • the cancer may also affect the surrounding lymph nodes in the pelvis or lymph nodes outside this area.
  • Prostate cancer can also spread to tissues next to the prostate, such as pelvic muscles, bones, or other organs.
  • Recurrence can be determined by clinical recurrence detected by, for example, imaging study or biopsy, or biochemical recurrence detected by, for example, sustained follow-up prostate-specific antigen (PSA) levels ⁇ 0.4 ng/mL or the initiation of salvage therapy as a result of a rising PSA level.
  • PSA prostate-specific antigen
  • cRFI clinical recurrence-free interval
  • biochemical recurrence-free interval bRFI
  • bRFI biological recurrence-free interval
  • OS Overall Survival
  • PCSS Prostate Cancer-Specific Survival
  • upgrading or “upstaging” as used herein refers to a change in Gleason grade from 3+3 at the time of biopsy to 3+4 or greater at the time of radical prostatectomy (RP), or Gleason grade 3+4 at the time of biopsy to 4+3 or greater at the time of RP, or seminal vessical involvement (SVI), or extracapsular involvement (ECE) at the time of RP.
  • RP radical prostatectomy
  • SVI seminal vessical involvement
  • ECE extracapsular involvement
  • microarray refers to an ordered arrangement of hybridizable array elements, e.g. oligonucleotide or polynucleotide probes, on a substrate.
  • polynucleotide generally refers to any polyribonucleotide or polydeoxribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA.
  • polynucleotides as defined herein include, without limitation, single- and double-stranded DNA, DNA including single- and double-stranded regions, single- and double-stranded RNA, and RNA including single- and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded or, more typically, double-stranded or include single- and double-stranded regions.
  • polynucleotide refers to triple-stranded regions comprising RNA or DNA or both RNA and DNA.
  • the strands in such regions may be from the same molecule or from different molecules.
  • the regions may include all of one or more of the molecules, but more typically involve only a region of some of the molecules.
  • One of the molecules of a triple-helical region often is an oligonucleotide.
  • polynucleotide specifically includes cDNAs.
  • the term includes DNAs (including cDNAs) and RNAs that contain one or more modified bases.
  • DNAs or RNAs with backbones modified for stability or for other reasons are “polynucleotides” as that term is intended herein.
  • DNAs or RNAs comprising unusual bases, such as inosine, or modified bases, such as tritiated bases are included within the term “polynucleotides” as defined herein.
  • polynucleotide embraces all chemically, enzymatically and/or metabolically modified forms of unmodified polynucleotides, as well as the chemical forms of DNA and RNA characteristic of viruses and cells, including simple and complex cells.
  • oligonucleotide refers to a relatively short polynucleotide, including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RNArDNA hybrids and double-stranded DNAs. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available. However, oligonucleotides can be made by a variety of other methods, including in vitro recombinant DNA-mediated techniques and by expression of DNAs in cells and organisms.
  • Ct refers to threshold cycle, the cycle number in quantitative polymerase chain reaction (qPCR) at which the fluorescence generated within a reaction well exceeds the defined threshold, i.e. the point during the reaction at which a sufficient number of amplicons have accumulated to meet the defined threshold.
  • qPCR quantitative polymerase chain reaction
  • Cp refers to “crossing point.”
  • the Cp value is calculated by determining the second derivatives of entire qPCR amplification curves and their maximum value.
  • the Cp value represents the cycle at which the increase of fluorescence is highest and where the logarithmic phase of a PCR begins.
  • threshold or “thresholding” refer to a procedure used to account for non-linear relationships between gene expression measurements and clinical response as well as to further reduce variation in reported patient scores. When thresholding is applied, all measurements below or above a threshold are set to that threshold value. Non-linear relationship between gene expression and outcome could be examined using smoothers or cubic splines to model gene expression in Cox PH regression on recurrence free interval or logistic regression on recurrence status. D. Cox, Journal of the Royal Statistical Society, Series B 34:187-220 (1972). Variation in reported patient scores could be examined as a function of variability in gene expression at the limit of quantitation and/or detection for a particular gene.
  • amplicon refers to pieces of DNA that have been synthesized using amplification techniques, such as polymerase chain reactions (PCR) and ligase chain reactions.
  • PCR polymerase chain reactions
  • ligase chain reactions ligase chain reactions
  • “Stringency” of hybridization reactions is readily determinable by one of ordinary skill in the art, and generally is an empirical calculation dependent upon probe length, washing temperature, and salt concentration. In general, longer probes require higher temperatures for proper annealing, while shorter probes need lower temperatures. Hybridization generally depends on the ability of denatured DNA to re-anneal when complementary strands are present in an environment below their melting temperature. The higher the degree of desired homology between the probe and hybridizable sequence, the higher the relative temperature which can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while lower temperatures less so. For additional details and explanation of stringency of hybridization reactions, see Ausubel et al., Current Protocols in Molecular Biology (Wiley Interscience Publishers, 1995).
  • “Stringent conditions” or “high stringency conditions”, as defined herein, typically: (1) employ low ionic strength and high temperature for washing, for example 0.015 M sodium chloride/0.0015 M sodium citrate/0.1% sodium dodecyl sulfate at 50° C.; (2) employ during hybridization a denaturing agent, such as formamide, for example, 50% (v/v) formamide with 0.1% bovine serum albumin/0.1% Ficoll/0.1% polyvinylpyrrolidone/50 mM sodium phosphate buffer at pH 6.5 with 750 mM sodium chloride, 75 mM sodium citrate at 42° C.; or (3) employ 50% formamide, 5 ⁇ SSC (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5 ⁇ Denhardt's solution, sonicated salmon sperm DNA (50 ⁇ g/ml), 0.1% SDS, and 10% dextran sulfate at
  • Modely stringent conditions may be identified as described by Sambrook et al., Molecular Cloning: A Laboratory Manual, New York: Cold Spring Harbor Press, 1989, and include the use of washing solution and hybridization conditions (e.g., temperature, ionic strength and % SDS) less stringent that those described above.
  • washing solution and hybridization conditions e.g., temperature, ionic strength and % SDS
  • An example of moderately stringent conditions is overnight incubation at 37° C.
  • splicing and “RNA splicing” are used interchangeably and refer to RNA processing that removes introns and joins exons to produce mature mRNA with continuous coding sequence that moves into the cytoplasm of an eukaryotic cell.
  • co-express and “co-expressed”, as used herein, refer to a statistical correlation between the amounts of different transcript sequences across a population of different patients. Pairwise co-expression may be calculated by various methods known in the art, e.g., by calculating Pearson correlation coefficients or Spearman correlation coefficients. Co-expressed gene cliques may also be identified using graph theory. An analysis of co-expression may be calculated using normalized expression data. A gene is said to be co-expressed with a particular disclosed gene when the expression level of the gene exhibits a Pearson correlation coefficient greater than or equal to 0.6.
  • a “computer-based system” refers to a system of hardware, software, and data storage medium used to analyze information.
  • the minimum hardware of a patient computer-based system comprises a central processing unit (CPU), and hardware for data input, data output (e.g., display), and data storage.
  • CPU central processing unit
  • the data storage medium may comprise any manufacture comprising a recording of the present information as described above, or a memory access device that can access such a manufacture.
  • Record data programming or other information on a computer readable medium refers to a process for storing information, using any such methods as known in the art. Any convenient data storage structure may be chosen, based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, e.g. word processing text file, database format, etc.
  • a “processor” or “computing means” references any hardware and/or software combination that will perform the functions required of it.
  • a suitable processor may be a programmable digital microprocessor such as available in the form of an electronic controller, mainframe, server or personal computer (desktop or portable).
  • suitable programming can be communicated from a remote location to the processor, or previously saved in a computer program product (such as a portable or fixed computer readable storage medium, whether magnetic, optical or solid state device based).
  • a magnetic medium or optical disk may carry the programming, and can be read by a suitable reader communicating with each processor at its corresponding station.
  • active surveillance and “watchful waiting” mean closely monitoring a patient's condition without giving any treatment until symptoms appear or change.
  • watchful waiting is usually used in older men with other medical problems and early-stage disease.
  • the term “surgery” applies to surgical methods undertaken for removal of cancerous tissue, including pelvic lymphadenectomy, radical prostatectomy, transurethral resection of the prostate (TURP), excision, dissection, and tumor biopsy/removal.
  • the tumor tissue or sections used for gene expression analysis may have been obtained from any of these methods.
  • the term “therapy” includes radiation, hormonal therapy, cryosurgery, chemotherapy, biologic therapy, and high-intensity focused ultrasound.
  • TMPRSS fusion and “TMPRSS2 fusion” are used interchangeably and refer to a fusion of the androgen-driven TMPRSS2 gene with the ERG oncogene, which has been demonstrated to have a significant association with prostate cancer.
  • positive TMPRSS fusion status indicates that the TMPRSS fusion is present in a tissue sample
  • negative TMPRSS fusion status indicates that the TMPRSS fusion is not present in a tissue sample.
  • TMPRSS fusion status there are numerous ways to determine TMPRSS fusion status, such as real-time, quantitative PCR or high-throughput sequencing. See, e.g., K. Mertz, et al., Neoplasis 9(3):200-206 (2007); C. Maher, Nature 458(7234):97-101 (2009).
  • the present disclosure provides molecular assays that involve measurement of expression level(s) of one or more genes, gene subsets, microRNAs, or one or more microRNAs in combination with one or more genes or gene subsets, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likelihood of cancer recurrence.
  • the present disclosure further provides methods to classify a prostate tumor based on expression level(s) of one or more genes and/or microRNAs.
  • the disclosure further provides genes and/or microRNAs that are associated, positively or negatively, with a particular prognostic outcome.
  • the clinical outcomes include cRFI and bRFI.
  • patients may be classified in risk groups based on the expression level(s) of one or more genes and/or microRNAs that are associated, positively or negatively, with a prognostic factor.
  • that prognostic factor is Gleason pattern.
  • the expression level of each gene or microRNA may be determined in relation to various features of the expression products of the gene including exons, introns, protein epitopes and protein activity.
  • the expression level(s) of one or more genes and/or microRNAs may be measured in tumor tissue.
  • the tumor tissue may obtained upon surgical removal or resection of the tumor, or by tumor biopsy.
  • the tumor tissue may be or include histologically “normal” tissue, for example histologically “normal” tissue adjacent to a tumor.
  • the expression level of genes and/or microRNAs may also be measured in tumor cells recovered from sites distant from the tumor, for example circulating tumor cells, body fluid (e.g., urine, blood, blood fraction, etc.).
  • the expression product that is assayed can be, for example, RNA or a polypeptide.
  • the expression product may be fragmented.
  • the assay may use primers that are complementary to target sequences of an expression product and could thus measure full transcripts as well as those fragmented expression products containing the target sequence. Further information is provided in Table A (inserted in specification prior to claims).
  • RNA expression product may be assayed directly or by detection of a cDNA product resulting from a PCR-based amplification method, e.g., quantitative reverse transcription polymerase chain reaction (qRT-PCR). (See e.g., U.S. Pat. No. 7,587,279).
  • Polypeptide expression product may be assayed using immunohistochemistry (IHC). Further, both RNA and polypeptide expression products may also be is assayed using microarrays.
  • Prostate cancer is currently diagnosed using a digital rectal exam (DRE) and Prostate-specific antigen (PSA) test. If PSA results are high, patients will generally undergo a prostate tissue biopsy. The pathologist will review the biopsy samples to check for cancer cells and determine a Gleason score. Based on the Gleason score, PSA, clinical stage, and other factors, the physician must make a decision whether to monitor the patient, or treat the patient with surgery and therapy.
  • DRE digital rectal exam
  • PSA Prostate-specific antigen
  • tumor factors such as clinical stage (e.g. T1, T2), PSA level at presentation, and Gleason grade, that are very strong prognostic factors in determining outcome
  • host factors such as age at diagnosis and co-morbidity
  • T1 prostate cancer Patients with T1 prostate cancer have disease that is not clinically apparent but is discovered either at transurethral resection of the prostate (TURP, T1a, T1b) or at biopsy performed because of an elevated PSA (>4 ng/mL, T1c). Approximately 80% of the cases presenting in 2007 are clinical T1 at diagnosis. In a Scandinavian trial, OS at 10 years was 85% for patients with early stage prostate cancer (T1/T2) and Gleason score ⁇ 7, after radical prostatectomy.
  • T2 prostate cancer patients with T2 prostate cancer have disease that is clinically evident and is organ confined; patients with T3 tumors have disease that has penetrated the prostatic capsule and/or has invaded the seminal vesicles. It is known from surgical series that clinical staging underestimates pathological stage, so that about 20% of patients who are clinically T2 will be pT3 after prostatectomy. Most of patients with T2 or T3 prostate cancer are treated with local therapy, either prostatectomy or radiation. The data from the Scandinavian trial suggest that for T2 patients with Gleason grade ⁇ 7, the effect of prostatectomy on survival is at most 5% at 10 years; the majority of patients do not benefit from surgical treatment at the time of diagnosis.
  • the gene/microRNA expression assay and associated information provided by the practice of the methods disclosed herein provide a molecular assay method to facilitate optimal treatment decision-making in early stage prostate cancer.
  • An exemplary embodiment provides genes and microRNAs, the expression levels of which are associated (positively or negatively) with prostate cancer recurrence. For example, such a clinical tool would enable physicians to identify T2/T3 patients who are likely to recur following definitive therapy and need adjuvant treatment.
  • the methods disclosed herein may allow physicians to classify tumors, at a molecular level, based on expression level(s) of one or more genes and/or microRNAs that are significantly associated with prognostic factors, such as Gleason pattern and TMPRSS fusion status. These methods would not be impacted by the technical difficulties of intra-patient variability, histologically determining Gleason pattern in biopsy samples, or inclusion of histologically normal appearing tissue adjacent to tumor tissue. Multi-analyte gene/microRNA expression tests can be used to measure the expression level of one or more genes and/or microRNAs involved in each of several relevant physiologic processes or component cellular characteristics. The methods disclosed herein may group the genes and/or microRNAs.
  • the grouping of genes and microRNAs may be performed at least in part based on knowledge of the contribution of those genes and/or microRNAs according to physiologic functions or component cellular characteristics, such as in the groups discussed above. Furthermore, one or more microRNAs may be combined with one or moregenes. The gene-microRNA combination may be selected based on the likelihood that the gene-microRNA combination functionally interact.
  • the formation of groups (or gene subsets), in addition, can facilitate the mathematical weighting of the contribution of various expression levels to cancer recurrence. The weighting of a gene/microRNA group representing a physiological process or component cellular characteristic can reflect the contribution of that process or characteristic to the pathology of the cancer and clinical outcome.
  • the methods disclosed may be used to classify patients by risk, for example risk of recurrence.
  • Patients can be partitioned into subgroups (e.g., tertiles or quartiles) and the values chosen will define subgroups of patients with respectively greater or lesser risk.
  • the utility of a disclosed gene marker in predicting prognosis may not be unique to that marker.
  • An alternative marker having an expression pattern that is parallel to that of a disclosed gene may be substituted for, or used in addition to, that co-expressed gene or microRNA. Due to the co-expression of such genes or microRNAs, substitution of expression level values should have little impact on the overall utility of the test.
  • the closely similar expression patterns of two genes or microRNAs may result from involvement of both genes or microRNAs in the same process and/or being under common regulatory control in prostate tumor cells.
  • the present disclosure thus contemplates the use of such co-expressed genes, gene subsets, or microRNAs as substitutes for, or in addition to, genes of the present disclosure.
  • Methods of gene expression profiling include methods based on hybridization analysis of polynucleotides, methods based on sequencing of polynucleotides, and proteomics-based methods.
  • Exemplary methods known in the art for the quantification of RNA expression in a sample include northern blotting and in situ hybridization (Parker & Barnes, Methods in Molecular Biology 106:247-283 (1999)); RNAse protection assays (Hod, Biotechniques 13:852-854 (1992)); and PCR-based methods, such as reverse transcription PCT (RT-PCR) (Weis et al., Trends in Genetics 8:263-264 (1992)).
  • RT-PCR reverse transcription PCT
  • Antibodies may be employed that can recognize sequence-specific duplexes, including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-protein duplexes.
  • Representative methods for sequencing-based gene expression analysis include Serial Analysis of Gene Expression (SAGE), and gene expression analysis by massively parallel signature sequencing (MPSS).
  • RT-PCR Reverse Transcriptase PCR
  • mRNA or microRNA is isolated from a test sample.
  • the starting material is typically total RNA isolated from a human tumor, usually from a primary tumor.
  • normal tissues from the same patient can be used as an internal control.
  • Such normal tissue can be histologically-appearing normal tissue adjacent a tumor.
  • mRNA or microRNA can be extracted from a tissue sample, e.g., from a sample that is fresh, frozen (e.g. fresh frozen), or paraffin-embedded and fixed (e.g. formalin-fixed).
  • RNA isolation can be performed using a purification kit, buffer set and protease from commercial manufacturers, such as Qiagen, according to the manufacturer's instructions. For example, total RNA from cells in culture can be isolated using Qiagen RNeasy mini-columns.
  • RNA isolation kits include MasterPureTM Complete DNA and RNA Purification Kit (EPICENTRE®, Madison, Wis.), and Paraffin Block RNA Isolation Kit (Ambion, Inc.). Total RNA from tissue samples can be isolated using RNA Stat-60 (Tel-Test). RNA prepared from tumor can be isolated, for example, by cesium chloride density gradient centrifugation.
  • the sample containing the RNA is then subjected to reverse transcription to produce cDNA from the RNA template, followed by exponential amplification in a PCR reaction.
  • the two most commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLV-RT).
  • AMV-RT avilo myeloblastosis virus reverse transcriptase
  • MMLV-RT Moloney murine leukemia virus reverse transcriptase
  • the reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances and the goal of expression profiling.
  • extracted RNA can be reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, CA, USA), following the manufacturer's instructions.
  • the derived cDNA can then be used as a template in the subsequent PCR reaction.
  • PCR-based methods use a thermostable DNA-dependent DNA polymerase, such as a Taq DNA polymerase.
  • TaqMan® PCR typically utilizes the 5′-nuclease activity of Taq or Tth polymerase to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5′ nuclease activity can be used.
  • Two oligonucleotide primers are used to generate an amplicon typical of a PCR reaction product.
  • a third oligonucleotide, or probe can be designed to facilitate detection of a nucleotide sequence of the amplicon located between the hybridization sites the two PCR primers.
  • the probe can be detectably labeled, e.g., with a reporter dye, and can further be provided with both a fluorescent dye, and a quencher fluorescent dye, as in a Taqman® probe configuration.
  • a Taqman® probe is used, during the amplification reaction, the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore.
  • One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of the data.
  • TaqMan® RT-PCR can be performed using commercially available equipment, such as, for example, high-throughput platforms such as the ABI PRISM 7700 Sequence Detection System® (Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany).
  • high-throughput platforms such as the ABI PRISM 7700 Sequence Detection System® (Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany).
  • the procedure is run on a LightCycler® 480 (Roche Diagnostics) real-time PCR system, which is a microwell plate-based cycler platform.
  • C T 5′-Nuclease assay data are commonly initially expressed as a threshold cycle (“C T ”). Fluorescence values are recorded during every cycle and represent the amount of product amplified to that point in the amplification reaction.
  • the threshold cycle (C T ) is generally described as the point when the fluorescent signal is first recorded as statistically significant. Alternatively, data may be expressed as a crossing point (“Cp”).
  • the Cp value is calculated by determining the second derivatives of entire qPCR amplification curves and their maximum value. The Cp value represents the cycle at which the increase of fluorescence is highest and where the logarithmic phase of a PCR begins.
  • RT-PCR is usually performed using an internal standard.
  • the ideal internal standard gene (also referred to as a reference gene) is expressed at a quite constant level among cancerous and non-cancerous tissue of the same origin (i.e., a level that is not significantly different among normal and cancerous tissues), and is not significantly affected by the experimental treatment (i.e., does not exhibit a significant difference in expression level in the relevant tissue as a result of exposure to chemotherapy), and expressed at a quite constant level among the same tissue taken from different patients.
  • reference genes useful in the methods disclosed herein should not exhibit significantly different expression levels in cancerous prostate as compared to normal prostate tissue.
  • RNAs frequently used to normalize patterns of gene expression are mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and (3-actin.
  • exemplary reference genes used for normalization comprise one or more of the following genes: AAMP, ARF1, ATP5E, CLTC, GPS1, and PGK1.
  • Gene expression measurements can be normalized relative to the mean of one or more (e.g., 2, 3, 4, 5, or more) reference genes.
  • Reference-normalized expression measurements can range from 2 to 15, where a one unit increase generally reflects a 2-fold increase in RNA quantity.
  • Real time PCR is compatible both with quantitative competitive PCR, where internal competitor for each target sequence is used for normalization, and with quantitative comparative PCR using a normalization gene contained within the sample, or a housekeeping gene for RT-PCR.
  • quantitative competitive PCR where internal competitor for each target sequence is used for normalization
  • quantitative comparative PCR using a normalization gene contained within the sample, or a housekeeping gene for RT-PCR.
  • RNA isolation, purification, primer extension and amplification can be performed according to methods available in the art. (see, e.g., Godfrey et al. J. Molec. Diagnostics 2: 84-91 (2000); Specht et al., Am. J. Pathol. 158: 419-29 (2001)). Briefly, a representative process starts with cutting about 10 ⁇ m thick sections of paraffin-embedded tumor tissue samples. The RNA is then extracted, and protein and DNA depleted from the RNA-containing sample. After analysis of the RNA concentration, RNA is reverse transcribed using gene specific primers followed by RT-PCR to provide for cDNA amplification products.
  • PCR primers and probes can be designed based upon exon or intron sequences present in the mRNA transcript of the gene of interest.
  • Primer/probe design can be performed using publicly available software, such as the DNA BLAT software developed by Kent, W. J., Genome Res. 12(4):656-64 (2002), or by the BLAST software including its variations.
  • repetitive sequences of the target sequence can be masked to mitigate non-specific signals.
  • exemplary tools to accomplish this include the Repeat Masker program available on-line through the Baylor College of Medicine, which screens DNA sequences against a library of repetitive elements and returns a query sequence in which the repetitive elements are masked.
  • the masked intron sequences can then be used to design primer and probe sequences using any commercially or otherwise publicly available primer/probe design packages, such as Primer Express (Applied Biosystems); MGB assay-by-design (Applied Biosystems); Primer3 (Steve Rozen and Helen J. Skaletsky (2000) Primer3 on the WWW for general users and for biologist programmers. See S. Rrawetz, S. Misener, Bioinformatics Methods and Protocols: Methods in Molecular Biology, pp. 365-386 (Humana Press).
  • PCR primer design Other factors that can influence PCR primer design include primer length, melting temperature (Tm), and G/C content, specificity, complementary primer sequences, and 3′-end sequence.
  • optimal PCR primers are generally 17-30 bases in length, and contain about 20-80%, such as, for example, about 50-60% G+C bases, and exhibit Tm's between 50 and 80° C., e.g. about 50 to 70° C.
  • Table A provides further information concerning the primer, probe, and amplicon sequences associated with the Examples disclosed herein.
  • the obtained cDNA is spiked with a synthetic DNA molecule (competitor), which matches the targeted cDNA region in all positions, except a single base, and serves as an internal standard.
  • the cDNA/competitor mixture is PCR amplified and is subjected to a post-PCR shrimp alkaline phosphatase (SAP) enzyme treatment, which results in the dephosphorylation of the remaining nucleotides.
  • SAP post-PCR shrimp alkaline phosphatase
  • the PCR products from the competitor and cDNA are subjected to primer extension, which generates distinct mass signals for the competitor- and cDNA-derives PCR products. After purification, these products are dispensed on a chip array, which is pre-loaded with components needed for analysis with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis.
  • MALDI-TOF MS matrix-assisted laser desorption ionization time-of-flight mass spectrometry
  • the cDNA present in the reaction is then quantified by analyzing the ratios of the peak areas in the mass spectrum generated. For further details see, e.g. Ding and Cantor, Proc. Natl. Acad. Sci. USA 100:3059-3064 (2003).
  • PCR-based techniques that can find use in the methods disclosed herein include, for example, BeadArray® technology (Illumina, San Diego, Calif.; Oliphant et al., Discovery of Markers for Disease (Supplement to Biotechniques), June 2002; Ferguson et al., Analytical Chemistry 72:5618 (2000)); BeadsArray for Detection of Gene Expression® (BADGE), using the commercially available LuminexlOO LabMAP® system and multiple color-coded microspheres (Luminex Corp., Austin, Tex.) in a rapid assay for gene expression (Yang et al., Genome Res. 11:1888-1898 (2001)); and high coverage expression profiling (HiCEP) analysis (Fukumura et al., Nucl. Acids. Res. 31(16) e94 (2003).
  • BeadArray® technology Illumina, San Diego, Calif.; Oliphant et al., Discovery of Markers for Disease (Supplement to Biotechniques
  • RNA expression levels of a gene or microArray of interest can also be assessed using the microarray technique.
  • polynucleotide sequences of interest including cDNAs and oligonucleotides
  • the arrayed sequences are then contacted under conditions suitable for specific hybridization with detectably labeled cDNA generated from RNA of a test sample.
  • the source of RNA typically is total RNA isolated from a tumor sample, and optionally from normal tissue of the same patient as an internal control or cell lines.
  • RNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g. formalin-fixed) tissue samples.
  • PCR amplified inserts of cDNA clones of a gene to be assayed are applied to a substrate in a dense array. Usually at least 10,000 nucleotide sequences are applied to the substrate.
  • the microarrayed genes, immobilized on the microchip at 10,000 elements each are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array.
  • the chip After washing under stringent conditions to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding RNA abundance.
  • Serial analysis of gene expression is a method that allows the simultaneous and quantitative analysis of a large number of gene transcripts, without the need of providing an individual hybridization probe for each transcript.
  • a short sequence tag (about 10-14 bp) is generated that contains sufficient information to uniquely identify a transcript, provided that the tag is obtained from a unique position within each transcript.
  • many transcripts are linked together to form long serial molecules, that can be sequenced, revealing the identity of the multiple tags simultaneously.
  • the expression pattern of any population of transcripts can be quantitatively evaluated by determining the abundance of individual tags, and identifying the gene corresponding to each tag. For more details see, e.g. Velculescu et al., Science 270:484-487 (1995); and Velculescu et al., Cell 88:243-51 (1997).
  • Nucleic acid sequencing technologies are suitable methods for analysis of gene expression.
  • the principle underlying these methods is that the number of times a cDNA sequence is detected in a sample is directly related to the relative expression of the RNA corresponding to that sequence.
  • DGE Digital Gene Expression
  • Early methods applying this principle were Serial Analysis of Gene Expression (SAGE) and Massively Parallel Signature Sequencing (MPSS). See, e.g., S. Brenner, et al., Nature Biotechnology 18(6):630-634 (2000). More recently, the advent of “next-generation” sequencing technologies has made DGE simpler, higher throughput, and more affordable.
  • RNA for expression analysis from blood, plasma and serum (see, e.g., K. Enders, et al., Clin Chem 48, 1647-53 (2002) (and references cited therein) and from urine (see, e.g., R. Boom, et al., J Clin Microbiol. 28, 495-503 (1990) and references cited therein) have been described.
  • Immunohistochemistry methods are also suitable for detecting the expression levels of genes and applied to the method disclosed herein.
  • Antibodies e.g., monoclonal antibodies
  • the antibodies can be detected by direct labeling of the antibodies themselves, for example, with radioactive labels, fluorescent labels, hapten' labels such as, biotin, or an enzyme such as horse radish peroxidase or alkaline phosphatase.
  • unlabeled primary antibody can be used in conjunction with a labeled secondary antibody specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available.
  • proteome is defined as the totality of the proteins present in a sample (e.g. tissue, organism, or cell culture) at a certain point of time.
  • Proteomics includes, among other things, study of the global changes of protein expression in a sample (also referred to as “expression proteomics”).
  • Proteomics typically includes the following steps: (1) separation of individual proteins in a sample by 2-D gel electrophoresis (2-D PAGE); (2) identification of the individual proteins recovered from the gel, e.g. my mass spectrometry or N-terminal sequencing, and (3) analysis of the data using bioinformatics.
  • RNA sample section e.g. about 10 ⁇ m thick sections of a paraffin-embedded tumor tissue sample.
  • RNA is then extracted, and protein and DNA are removed. After analysis of the RNA concentration, RNA repair is performed if desired.
  • the sample can then be subjected to analysis, e.g., by reverse transcribed using gene specific promoters followed by RT-PCR.
  • the present invention provides a stratified cohort sampling design (a form of case-control sampling) using tissue and data from prostate cancer patients. Selection of specimens was stratified by T stage (T1, T2), year cohort ( ⁇ 1993, ⁇ 1993), and prostatectomy Gleason Score (low/intermediate, high). All patients with clinical recurrence were selected and a sample of patients who did not experience a clinical recurrence was selected. For each patient, up to two enriched tumor specimens and one normal-appearing tissue sample was assayed.
  • the present disclosure provides a method to determine tumor stage based on the expression of staging genes, or genes that co-express with particular staging genes.
  • genes often work together in a concerted way, i.e. they are co-expressed.
  • Co-expressed gene groups identified for a disease process like cancer can serve as biomarkers for tumor status and disease progression. Such co-expressed genes can be assayed in lieu of, or in addition to, assaying of the staging gene with which they are co-expressed.
  • the joint correlation of gene expression levels among prostate cancer specimens under study may be assessed.
  • the correlation structures among genes and specimens may be examined through hierarchical cluster methods. This information may be used to confirm that genes that are known to be highly correlated in prostate cancer specimens cluster together as expected. Only genes exhibiting a nominally significant (unadjusted p ⁇ 0.05) relationship with cRFI in the univariate Cox PH regression analysis will be included in these analyses.
  • co-expression analysis methods now known or later developed will fall within the scope and spirit of the present invention. These methods may incorporate, for example, correlation coefficients, co-expression network analysis, clique analysis, etc., and may be based on expression data from RT-PCR, microarrays, sequencing, and other similar technologies.
  • gene expression clusters can be identified using pair-wise analysis of correlation based on Pearson or Spearman correlation coefficients. (See, e.g., Pearson K. and Lee A., Biometrika 2, 357 (1902); C. Spearman, Amer. J. Psychol 15:72-101 (1904); J. Myers, A. Well, Research Design and Statistical Analysis, p. 508 (2nd Ed., 2003).)
  • Normalization refers to a process to correct for (normalize away), for example, differences in the amount of RNA assayed and variability in the quality of the RNA used, to remove unwanted sources of systematic variation in Ct or Cp measurements, and the like.
  • sources of systematic variation are known to include the degree of RNA degradation relative to the age of the patient sample and the type of fixative used to store the sample. Other sources of systematic variation are attributable to laboratory processing conditions.
  • Assays can provide for normalization by incorporating the expression of certain normalizing genes, which do not significantly differ in expression levels under the relevant conditions.
  • Exemplary normalization genes disclosed herein include housekeeping genes. (See, e.g., E. Eisenberg, et al., Trends in Genetics 19(7):362-365 (2003).) Normalization can be based on the mean or median signal (Ct or Cp) of all of the assayed genes or a large subset thereof (global normalization approach).
  • the normalizing genes also referred to as reference genes should be genes that are known not to exhibit significantly different expression in prostate cancer as compared to non-cancerous prostate tissue, and are not significantly affected by various sample and process conditions, thus provide for normalizing away extraneous effects.
  • one or more of the following genes are used as references by which the mRNA or microRNA expression data is normalized: AAMP, ARF1, ATP5E, CLTC, GPS1, and PGK1.
  • one or more of the following microRNAs are used as references by which the expression data of microRNAs are normalized: hsa-miR-106a; hsa-miR-146b-5p; hsa-miR-191; hsa-miR-19b; and hsa-miR-92a.
  • the calibrated weighted average C T or Cp measurements for each of the prognostic and predictive genes or microRNAs may be normalized relative to the mean of five or more reference genes or microRNAs.
  • Standardization refers to a process to effectively put all the genes or microRNAs on a comparable scale. This is performed because some genes or microRNAs will exhibit more variation (a broader range of expression) than others. Standardization is performed by dividing each expression value by its standard deviation across all samples for that gene or microRNA. Hazard ratios are then interpreted as the relative risk of recurrence per 1 standard deviation increase in expression.
  • kits comprising agents, which may include gene (or microRNA)-specific or gene (or microRNA)-selective probes and/or primers, for quantifying the expression of the disclosed genes or microRNAs for predicting prognostic outcome or response to treatment.
  • agents may include gene (or microRNA)-specific or gene (or microRNA)-selective probes and/or primers, for quantifying the expression of the disclosed genes or microRNAs for predicting prognostic outcome or response to treatment.
  • kits may optionally contain reagents for the extraction of RNA from tumor samples, in particular fixed paraffin-embedded tissue samples and/or reagents for RNA amplification.
  • the kits may optionally comprise the reagent(s) with an identifying description or label or instructions relating to their use in the methods of the present invention.
  • kits may comprise containers (including microliter plates suitable for use in an automated implementation of the method), each with one or more of the various materials or reagents (typically in concentrated form) utilized in the methods, including, for example, chromatographic columns, pre-fabricated microarrays, buffers, the appropriate nucleotide triphosphates (e.g., dATP, dCTP, dGTP and dTTP; or rATP, rCTP, rGTP and UTP), reverse transcriptase, DNA polymerase, RNA polymerase, and one or more probes and primers of the present invention (e.g., appropriate length poly(T) or random primers linked to a promoter reactive with the RNA polymerase).
  • nucleotide triphosphates e.g., dATP, dCTP, dGTP and dTTP; or rATP, rCTP, rGTP and UTP
  • reverse transcriptase DNA polymerase
  • RNA polymerase
  • a report may include information concerning expression levels of one or more genes and/or microRNAs, classification of the tumor or the patient's risk of recurrence, the patient's likely prognosis or risk classification, clinical and pathologic factors, and/or other information.
  • the methods and reports of this invention can further include storing the report in a database.
  • the method can create a record in a database for the subject and populate the record with data.
  • the report may be a paper report, an auditory report, or an electronic record.
  • the report may be displayed and/or stored on a computing device (e.g., handheld device, desktop computer, smart device, website, etc.). It is contemplated that the report is provided to a physician and/or the patient.
  • the receiving of the report can further include establishing a network connection to a server computer that includes the data and report and requesting the data and report from the server computer.
  • the values from the assays described above, such as expression data, can be calculated and stored manually. Alternatively, the above-described steps can be completely or partially performed by a computer program product.
  • the present invention thus provides a computer program product including a computer readable storage medium having a computer program stored on it.
  • the program can, when read by a computer, execute relevant calculations based on values obtained from analysis of one or more biological sample from an individual (e.g., gene expression levels, normalization, standardization, thresholding, and conversion of values from assays to a score and/or text or graphical depiction of tumor stage and related information).
  • the computer program product has stored therein a computer program for performing the calculation.
  • the present disclosure provides systems for executing the program described above, which system generally includes: a) a central computing environment; b) an input device, operatively connected to the computing environment, to receive patient data, wherein the patient data can include, for example, expression level or other value obtained from an assay using a biological sample from the patient, or microarray data, as described in detail above; c) an output device, connected to the computing environment, to provide information to a user (e.g., medical personnel); and d) an algorithm executed by the central computing environment (e.g., a processor), where the algorithm is executed based on the data received by the input device, and wherein the algorithm calculates an expression score, thresholding, or other functions described herein.
  • the methods provided by the present invention may also be automated in whole or in part.
  • All aspects of the present invention may also be practiced such that a limited number of additional genes and/or microRNAs that are co-expressed or functionally related with the disclosed genes, for example as evidenced by statistically meaningful Pearson and/or Spearman correlation coefficients, are included in a test in addition to and/or in place of disclosed genes.
  • RNA extraction yields and gene expression profiles using an RT-PCR assay to characterize RNA from manually micro-dissected fixed paraffin embedded (FPE) prostate cancer needle biopsy cores. It also investigated the association of RNA yields and gene expression profiles with Gleason score in these specimens.
  • FPE fixed paraffin embedded
  • RNA from enriched tumor samples was extracted using a manual RNA extraction process. RNA was quantitated using the RiboGreen® assay and tested for the presence of genomic DNA contamination. Samples with sufficient RNA yield and free of genomic DNA tested for gene expression levels of a 24-gene panel of reference and cancer-related genes using quantitative RT-PCR. The expression was normalized to the average of 6 reference genes (AAMP, ARF1, ATP5E, CLTC, EEF1A1, and GPX1).
  • Descriptive statistics and graphical displays were used to summarize standard pathology metrics and gene expression, with stratification for Gleason Score category and percentage tumor involvement category. Ordinal logistic regression was used to evaluate the relationship between gene expression and Gleason Score category.
  • this gene expression study included tissue and data from 111 patients with clinical recurrence and 330 patients without clinical recurrence after radical prostatectomies performed between 1987 and 2004 for treatment of early stage (T1, T2) prostate cancer.
  • FPE tissue specimens Two fixed paraffin embedded (FPE) tissue specimens were obtained from prostate tumor specimens in each patient.
  • the sampling method (sampling method A or B) depended on whether the highest Gleason pattern is also the primary Gleason pattern.
  • the invasive cancer cells were at least 5.0 mm in dimension, except in the instances of pattern 5, where 2.2 mm was accepted. Specimens were spatially distinct where possible.
  • NAT Histologically normal appearing tissue adjacent to the tumor specimen
  • non-tumor tissue Histologically normal appearing tissue adjacent to the tumor specimen
  • Adjacent tissue was collected 3 mm from the tumor to 3 mm from the edge of the FPET block.
  • NAT was preferentially sampled adjacent to the primary Gleason pattern. In cases where there was insufficient NAT adjacent to the primary Gleason pattern, then NAT was sampled adjacent to the secondary or highest Gleason pattern (A2 or B1) per the method set forth in Table 2.
  • Six (6) 10 ⁇ m sections with beginning H&E at 5 ⁇ m and ending unstained slide at 5 ⁇ m were prepared from each fixed paraffin-embedded tumor (FPET) block included in the study. All cases were histologically reviewed and manually micro-dissected to yield two enriched tumor samples and, where possible, one normal tissue sample adjacent to the tumor specimen.
  • RT-PCR analysis was used to determine RNA expression levels for 738 genes and chromosomal rearrangements (e.g., TMPRSS2-ERG fusion or other ETS family genes) in prostate cancer tissue and surrounding NAT in patients with early-stage prostate cancer treated with radical prostatectomy.
  • 738 genes and chromosomal rearrangements e.g., TMPRSS2-ERG fusion or other ETS family genes
  • the samples were quantified using the RiboGreen assay and a subset tested for presence of genomic DNA contamination. Samples were taken into reverse transcription (RT) and quantitative polymerase chain reaction (qPCR). All analyses were conducted on reference-normalized gene expression levels using the average of the of replicate well crossing point (CP) values for the 6 reference genes (AAMP, ARF1, ATP5E, CLTC, GPS1, PGK1).
  • RT reverse transcription
  • qPCR quantitative polymerase chain reaction
  • a patient was included in a specified analysis if at least one sample for that patient was evaluable. Unless otherwise stated, all hypothesis tests were reported using two-sided p-values.
  • Tables 3A and 3B provide genes significantly associated (p ⁇ 0.05), positively or negatively, with Gleason pattern in the primary and/or highest Gleason pattern. Increased expression of genes in Table 3A is positively associated with higher Gleason score, while increased expression of genes in Table 3B are negatively associated with higher Gleason score.
  • Tables 4A and 4B provide genes that were associated, positively or negatively, with cRFI and/or bRFI in the primary and/or highest Gleason pattern. Increased expression of genes in Table 4A is negatively associated with good prognosis, while increased expression of genes in Table 4B is positively associated with good prognosis.
  • Tables 5A and 5B provide genes that were significantly associated (p ⁇ 0.05), positively or negatively, with recurrence (cRFI, bRFI) after adjusting for AUA risk group in the primary and/or highest Gleason pattern. Increased expression of genes in Table 5A is negatively associated with good prognosis, while increased expression of genes in Table 5B is positively associated with good prognosis.
  • Tables 6A and 6B provide genes that were significantly associated (p ⁇ 0.05), positively or negatively, with recurrence (cRFI, bRFI) after adjusting for Gleason pattern in the primary and/or highest Gleason pattern. Increased expression of genes in Table 6A is negatively associated with good prognosis, while increased expression of gene in Table 6B is positively associated with good prognosis.
  • Tables 7A and 7B provide genes significantly associated (p ⁇ 0.05), positively or negatively, with clinical recurrence (cRFI) in negative TMPRSS fusion specimens in the primary or highest Gleason pattern specimen. Increased expression of genes in Table 7A is negatively associated with good prognosis, while increased expression of genes in Table 7B is positively associated with good prognosis.
  • Tables 8A and 8B provide genes that were significantly associated (p ⁇ 0.05), positively or negatively, with clinical recurrence (cRFI) in positive TMPRSS fusion specimens in the primary or highest Gleason pattern specimen. Increased expression of genes in Table 8A is negatively associated with good prognosis, while increased expression of genes in Table 8B is positively associated with good prognosis.
  • cRFI clinical recurrence
  • Tables 9A and 9B provide genes significantly associated (p ⁇ 0.05), positively or negatively, with TMPRSS fusion status in the primary Gleason pattern. Increased expression of genes in Table 9A are positively associated with TMPRSS fusion positivity, while increased expression of genes in Table 10A are negatively associated with TMPRSS fusion positivity.
  • Tables 10A and 10B provide genes significantly associated (p ⁇ 0.05), positively or negatively, with cRFI or bRFI in non-tumor samples. Table 10A is negatively associated with good prognosis, while increased expression of genes in Table 10B is positively associated with good prognosis.
  • Table 11 provides genes that are significantly associated (p ⁇ 0.05) with cRFI or bRFI after adjustment for Gleason pattern or highest Gleason pattern.
  • Tables 12A and 12B provide genes that are significantly associated (p ⁇ 0.05) with prostate cancer specific survival (PCSS) in the primary Gleason pattern. Increased expression of genes in Table 12A is negatively associated with good prognosis, while increased expression of genes in Table 12B is positively associated with good prognosis.
  • PCSS prostate cancer specific survival
  • Tables 13A and 13B provide genes significantly associated (p ⁇ 0.05), positively or negatively, with upgrading/upstaging in the primary and/or highest Gleason pattern. Increased expression of genes in Table 13A is positively associated with higher risk of upgrading/upstaging (poor prognosis), while increased expression of genes in Table 13B is negatively associated with risk of upgrading/upstaging (good prognosis).
  • COL6A1 0.62 0.0125 0.60 0.0050 COL6A3 0.65 0.0080 0.68 0.0181 CSRP1 0.43 0.0001 0.40 0.0002 CTSB 0.66 0.0042 0.67 0.0051 CTSD 0.64 0.0355 . . CTSK 0.69 0.0171 . . CTSL1 0.72 0.0402 . . CUL1 0.61 0.0024 0.70 0.0120 CXCL12 0.69 0.0287 0.63 0.0053 CYP3A5 0.68 0.0099 0.62 0.0026 DDR2 0.68 0.0324 0.62 0.0050 DES 0.54 0.0013 0.46 0.0002 DHX9 0.67 0.0164 . . DLGAP1 . .
  • OLFML3 0.56 0.0035 0.51 0.0011 OMD 0.61 0.0011 0.73 0.0357
  • PAGE4 0.42 ⁇ 0.0001 0.36 ⁇ 0.0001 PAK6 0.72 0.0335 .
  • PCDHGB7 0.70 0.0262 0.55 0.0004 PGF 0.72 0.0358 0.71 0.0270 PLP2 0.66 0.0088 0.63 0.0041 PPAP2B 0.44 ⁇ 0.0001 0.50 0.0001 PPP1R12A 0.45 0.0001 0.40 ⁇ 0.0001 PRIMA1 . . 0.63 0.0102 PRKAR2B 0.71 0.0226 . . PRKCA 0.34 ⁇ 0.0001 0.42 ⁇ 0.0001 PRKCB 0.66 0.0120 0.49 ⁇ 0.0001 PROM1 0.61 0.0030 . .
  • TRAF3IP2 0.62 0.0064 0.59 0.0053 TRO 0.57 0.0003 0.51 0.0001 VCL 0.52 0.0005 0.52 0.0004 VIM 0.65 0.0072 0.65 0.0045 WDR19 0.66 0.0097 . . WFDC1 0.58 0.0023 0.60 0.0026 ZFHX3 0.69 0.0144 0.62 0.0046 ZNF827 0.62 0.0030 0.53 0.0001
  • MicroRNAs function by binding to portions of messenger RNA (mRNA) and changing how frequently the mRNA is translated into protein. They can also influence the turnover of mRNA and thus how long the mRNA remains intact in the cell. Since microRNAs function primarily as an adjunct to mRNA, this study evaluated the joint prognostic value of microRNA expression and gene (mRNA) expression. Since the expression of certain microRNAs may be a surrogate for expression of genes that are not in the assessed panel, we also evaluated the prognostic value of microRNA expression by itself.
  • Samples from the 127 patients with clinical recurrence and 374 patients without clinical recurrence after radical prostatectomy described in Example 2 were used in this study.
  • the final analysis set comprised 416 samples from patients in which both gene expression and microRNA expression were successfully assayed. Of these, 106 patients exhibited clinical recurrence and 310 did not have clinical recurrence.
  • Tissue samples were taken from each prostate sample representing (1) the primary Gleason pattern in the sample, and (2) the highest Gleason pattern in the sample.
  • NAT histologically normal-appearing tissue adjacent to the tumor
  • test microRNAs and 5 reference microRNAs were determined from RNA extracted from fixed paraffin-embedded (FPE) tissue.
  • MicroRNA expression in all three tissue type was quantified by reverse transcriptase polymerase chain reaction (RT-PCR) using the crossing point (C p ) obtained from the Taqman® MicroRNA Assay kit (Applied Biosystems, Inc., Carlsbad, Calif.).
  • microRNA expression normalized by the average expression for the 5 reference microRNAs hsa-miR-106a, hsa-miR-146b-5p, hsa-miR-191, hsa-miR-19b, and hsa-miR-92a, and reference-normalized gene expression of the 733 genes (including the reference genes) discussed above, were assessed for association with clinical recurrence and death due to prostate cancer. Standardized hazard ratios (the proportional change in the hazard associated with a change of one standard deviation in the covariate value) were calculated.
  • the four tiers were pre-determined based on the likelihood (Tier 1 representing the highest likelihood) that the gene-microRNA pair functionally interacted or that the microRNA was related to prostate cancer based on a review of the literature and existing microarray data sets.
  • False discovery rates (FDR) (Benjamini and Hochberg, Journal of the Royal Statistical Society, Series B 57:289-300, 1995) were assessed using Efron's separate class methodology (Efron, Annals of Applied Statistics 2:197-223, 2008).
  • the false discovery rate is the expected proportion of the rejected null hypotheses that are rejected incorrectly (and thus are false discoveries).
  • Efron's methodology allows separate FDR assessment (q-values) (Storey, Journal of the Royal Statistical Society, Series B 64:479-498, 2002) within each class while utilizing the data from all the classes to improve the accuracy of the calculation.
  • the q-value for a microRNA or microRNA-gene pair can be interpreted as the empirical Bayes probability that the microRNA or microRNA-gene pair identified as being associated with clinical outcome is in fact a false discovery given the data.
  • the separate class approach was applied to a true discovery rate degree of association (TDRDA) analysis (Crager, Statistics in Medicine 29:33-45, 2010) to determine sets of microRNAs or microRNA-gene pairs that have standardized hazard ratio for clinical recurrence or prostate cancer-specific death of at least a specified amount while controlling the FDR at 10%.
  • TDRDA true discovery rate degree of association
  • a maximum lower bound (MLB) standardized hazard ratio was computed, showing the highest lower bound for which the microRNA or microRNA-gene pair was included in a TDRDA set with 10% FDR. Also calculated was an estimate of the true standardized hazard ratio corrected for regression to the mean (RM) that occurs in subsequent studies when the best predictors are selected from a long list (Crager, 2010 above).
  • the RM-corrected estimate of the standardized hazard ratio is a reasonable estimate of what could be expected if the selected microRNA or microRNA-gene pair were studied in a separate, subsequent study.
  • microRNAs assayed from primary Gleason pattern tumor tissue that were associated with clinical recurrence of prostate cancer after radical prostatectomy, allowing a false discovery rate of 10% (Table 15).
  • Results were similar for microRNAs assessed from highest Gleason pattern tumor tissue (Table 16), suggesting that the association of microRNA expression with clinical recurrence does not change markedly depending on the location within a tumor tissue sample.
  • No microRNA assayed from normal adjacent tissue was associated with the risk of clinical recurrence at a false discovery rate of 10%.
  • the sequences of the microRNAs listed in Tables 15-21 are shown in Table B.
  • Table 17 shows microRNAs assayed from primary Gleason pattern tissue that were identified as being associated with the risk of prostate-cancer-specific death, with a false discovery rate of 10%.
  • Table 18 shows the corresponding analysis for microRNAs assayed from highest Gleason pattern tissue. No microRNA assayed from normal adjacent tissue was associated with the risk of prostate-cancer-specific death at a false discovery rate of 10%.
  • Table 19 and Table 20 shows the microRNAs that can be identified as being associated with the risk of clinical recurrence while adjusting for the clinical and pathology covariates of biopsy Gleason score, baseline PSA level, and clinical T-stage. The distributions of these covariates are shown in FIG. 1 . Fifteen (15) of the microRNAs identified in Table 15 are also present in Table 19, indicating that these microRNAs have predictive value for clinical recurrence that is independent of the Gleason score, baseline PSA, and clinical T-stage.
  • the normalized expression levels of hsa-miR-93; hsa-miR-106b; hsa-miR-21; hsa-miR-449a; hsa-miR-182; hsa-miR-27a; hsa-miR-103; hsa-miR-141; hsa-miR-92a; hsa-miR-22; hsa-miR-29b; hsa-miR-210; hsa-miR-331; hsa-miR-191; hsa-miR-425; and hsa-miR-200c are positively associated with an increased risk of recurrence; and hsa-miR-30e-5p; hsa-miR-133a; hsa-miR-30a; hsa-miR-222; hsa
  • Table 22 shows the number of microRNA-gene pairs that were grouped in each tier (Tiers 1-4) and the number and percentage of those that were predictive of clinical recurrence at a false discovery rate of 10%.
  • Tier 1 80 46 57.5%) Tier 2 719 591 (82.2%) Tier 3 3,850 2,792 (72.5%) Tier 4 54,724 38,264 (69.9%)

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Abstract

Molecular assays that involve measurement of expression levels of prognostic biomarkers, or co-expressed biomarkers, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likely prognosis for said patient, and likelihood that said patient will have a recurrence of prostate cancer, or to classify the tumor by likelihood of clinical outcome or TMPRSS2 fusion status, are provided herein.

Description

  • This application is a continuation of U.S. application Ser. No. 16/282,540, filed Feb. 22, 2019, which is a continuation of U.S. application Ser. No. 14/887,605, filed Oct. 20, 2015, now U.S. Pat. No. 10,260,104, issued Apr. 16, 2019, which is a continuation of U.S. application Ser. No. 13/190,391, filed Jul. 25, 2011, which claims the benefit of priority to U.S. Provisional Application Nos. 61/368,217, filed Jul. 27, 2010; 61/414,310, filed Nov. 16, 2010; and 61/485,536, filed May 12, 2011, all of which are hereby incorporated by reference.
    • TECHNICAL FIELD
  • The present disclosure relates to molecular diagnostic assays that provide information concerning methods to use gene expression profiles to determine prognostic information for cancer patients. Specifically, the present disclosure provides genes and microRNAs, the expression levels of which may be used to determine the likelihood that a prostate cancer patient will experience a local or distant cancer recurrence.
    • INTRODUCTION
  • Prostate cancer is the most common solid malignancy in men and the second most common cause of cancer-related death in men in North America and the European Union (EU). In 2008, over 180,000 patients will be diagnosed with prostate cancer in the United States alone and nearly 30,000 will die of this disease. Age is the single most important risk factor for the development of prostate cancer, and applies across all racial groups that have been studied. With the aging of the U.S. population, it is projected that the annual incidence of prostate cancer will double by 2025 to nearly 400,000 cases per year.
  • Since the introduction of prostate-specific antigen (PSA) screening in the 1990's, the proportion of patients presenting with clinically evident disease has fallen dramatically such that patients categorized as “low risk” now constitute half of new diagnoses today. PSA is used as a tumor marker to determine the presence of prostate cancer as high PSA levels are associated with prostate cancer. Despite a growing proportion of localized prostate cancer patients presenting with low-risk features such as low stage (T1) disease, greater than 90% of patients in the US still undergo definitive therapy, including prostatectomy or radiation. Only about 15% of these patients would develop metastatic disease and die from their prostate cancer, even in the absence of definitive therapy. A. Bill-Axelson, et al., J Nat'l Cancer Inst. 100(16):1144-1154 (2008). Therefore, the majority of prostate cancer patients are being over-treated.
  • Estimates of recurrence risk and treatment decisions in prostate cancer are currently based primarily on PSA levels and/or tumor stage. Although tumor stage has been demonstrated to have significant association with outcome sufficient to be included in pathology reports, the College of American Pathologists Consensus Statement noted that variations in approach to the acquisition, interpretation, reporting, and analysis of this information exist. C. Compton, et al., Arch Pathol Lab Med 124:979-992 (2000). As a consequence, existing pathologic staging methods have been criticized as lacking reproducibility and therefore may provide imprecise estimates of individual patient risk.
    • SUMMARY
  • This application discloses molecular assays that involve measurement of expression level(s) of one or more genes, gene subsets, microRNAs, or one or more microRNAs in combination with one or more genes or gene subsets, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likelihood of cancer recurrence. For example, the likelihood of cancer recurrence could be described in terms of a score based on clinical or biochemical recurrence-free interval.
  • In addition, this application discloses molecular assays that involve measurement of expression level(s) of one or more genes, gene subsets, microRNAs, or one or more microRNAs in combination with one or more genes or gene subsets, from a biological sample obtained to identify a risk classification for a prostate cancer patient. For example, patients may be stratified using expression level(s) of one or more genes or microRNAs associated, positively or negatively, with cancer recurrence or death from cancer, or with a prognostic factor. In an exemplary embodiment, the prognostic factor is Gleason pattern.
  • The biological sample may be obtained from standard methods, including surgery, biopsy, or bodily fluids. It may comprise tumor tissue or cancer cells, and, in some cases, histologically normal tissue, e.g., histologically normal tissue adjacent the tumor tissue. In exemplary embodiments, the biological sample is positive or negative for a TMPRSS2 fusion.
  • In exemplary embodiments, expression level(s) of one or more genes and/or microRNAs that are associated, positively or negatively, with a particular clinical outcome in prostate cancer are used to determine prognosis and appropriate therapy. The genes disclosed herein may be used alone or arranged in functional gene subsets, such as cell adhesion/migration, immediate-early stress response, and extracellular matrix-associated. Each gene subset comprises the genes disclosed herein, as well as genes that are co-expressed with one or more of the disclosed genes. The calculation may be performed on a computer, programmed to execute the gene expression analysis. The microRNAs disclosed herein may also be used alone or in combination with any one or more of the microRNAs and/or genes disclosed.
  • In exemplary embodiments, the molecular assay may involve expression levels for at least two genes. The genes, or gene subsets, may be weighted according to strength of association with prognosis or tumor microenvironment. In another exemplary embodiment, the molecular assay may involve expression levels of at least one gene and at least one microRNA. The gene-microRNA combination may be selected based on the likelihood that the gene-microRNA combination functionally interact.
    • BRIEF DESCRIPTION OF THE DRAWING
  • FIG. 1 shows the distribution of clinical and pathology assessments of biopsy Gleason score, baseline PSA level, and clinical T-stage.
    •  DEFINITIONS
  • Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed., J. Wiley & Sons (New York, N.Y. 1994), and March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 4th ed., John Wiley & Sons (New York, N.Y. 1992), provide one skilled in the art with a general guide to many of the terms used in the present application.
  • One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. Indeed, the present invention is in no way limited to the methods and materials described herein. For purposes of the invention, the following terms are defined below.
  • The terms “tumor” and “lesion” as used herein, refer to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. Those skilled in the art will realize that a tumor tissue sample may comprise multiple biological elements, such as one or more cancer cells, partial or fragmented cells, tumors in various stages, surrounding histologically normal-appearing tissue, and/or macro or micro-dissected tissue.
  • The terms “cancer” and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Examples of cancer in the present disclosure include cancer of the urogenital tract, such as prostate cancer.
  • The “pathology” of cancer includes all phenomena that compromise the well-being of the patient. This includes, without limitation, abnormal or uncontrollable cell growth, metastasis, interference with the normal functioning of neighboring cells, release of cytokines or other secretory products at abnormal levels, suppression or aggravation of inflammatory or immunological response, neoplasia, premalignancy, malignancy, invasion of surrounding or distant tissues or organs, such as lymph nodes, etc.
  • As used herein, the term “prostate cancer” is used interchangeably and in the broadest sense refers to all stages and all forms of cancer arising from the tissue of the prostate gland.
  • According to the tumor, node, metastasis (TNM) staging system of the American Joint Committee on Cancer (AJCC), AJCC Cancer Staging Manual (7th Ed., 2010), the various stages of prostate cancer are defined as follows: Tumor: T1: clinically inapparent tumor not palpable or visible by imaging, T1a: tumor incidental histological finding in 5% or less of tissue resected, T1b: tumor incidental histological finding in more than 5% of tissue resected, T1c: tumor identified by needle biopsy; T2: tumor confined within prostate, T2a: tumor involves one half of one lobe or less, T2b: tumor involves more than half of one lobe, but not both lobes, T2c: tumor involves both lobes; T3: tumor extends through the prostatic capsule, T3a: extracapsular extension (unilateral or bilateral), T3b: tumor invades seminal vesicle(s); T4: tumor is fixed or invades adjacent structures other than seminal vesicles (bladder neck, external sphincter, rectum, levator muscles, or pelvic wall). Node: NO: no regional lymph node metastasis; N1: metastasis in regional lymph nodes. Metastasis: M0: no distant metastasis; M1: distant metastasis present.
  • The Gleason Grading system is used to help evaluate the prognosis of men with prostate cancer. Together with other parameters, it is incorporated into a strategy of prostate cancer staging, which predicts prognosis and helps guide therapy. A Gleason “score” or “grade” is given to prostate cancer based upon its microscopic appearance. Tumors with a low Gleason score typically grow slowly enough that they may not pose a significant threat to the patients in their lifetimes. These patients are monitored (“watchful waiting” or “active surveillance”) over time. Cancers with a higher Gleason score are more aggressive and have a worse prognosis, and these patients are generally treated with surgery (e.g., radical prostectomy) and, in some cases, therapy (e.g., radiation, hormone, ultrasound, chemotherapy). Gleason scores (or sums) comprise grades of the two most common tumor patterns. These patterns are referred to as Gleason patterns 1-5, with pattern 1 being the most well-differentiated. Most have a mixture of patterns. To obtain a Gleason score or grade, the dominant pattern is added to the second most prevalent pattern to obtain a number between 2 and 10. The Gleason Grades include: G1: well differentiated (slight anaplasia) (Gleason 2-4); G2: moderately differentiated (moderate anaplasia) (Gleason 5-6); G3-4: poorly differentiated/undifferentiated (marked anaplasia) (Gleason 7-10).
  • Stage groupings: Stage I: T1a N0 M0 G1; Stage II: (T1a N0 M0 G2-4) or (T1b, c, T1, T2, N0 M0 Any G); Stage III: T3 N0 M0 Any G; Stage IV: (T4 N0 M0 Any G) or (Any T N1 M0 Any G) or (Any T Any N M1 Any G).
  • As used herein, the term “tumor tissue” refers to a biological sample containing one or more cancer cells, or a fraction of one or more cancer cells. Those skilled in the art will recognize that such biological sample may additionally comprise other biological components, such as histologically appearing normal cells (e.g., adjacent the tumor), depending upon the method used to obtain the tumor tissue, such as surgical resection, biopsy, or bodily fluids.
  • As used herein, the term “AUA risk group” refers to the 2007 updated American Urological Association (AUA) guidelines for management of clinically localized prostate cancer, which clinicians use to determine whether a patient is at low, intermediate, or high risk of biochemical (PSA) relapse after local therapy.
  • As used herein, the term “adjacent tissue (AT)” refers to histologically “normal” cells that are adjacent a tumor. For example, the AT expression profile may be associated with disease recurrence and survival.
  • As used herein “non-tumor prostate tissue” refers to histologically normal-appearing tissue adjacent a prostate tumor.
  • Prognostic factors are those variables related to the natural history of cancer, which influence the recurrence rates and outcome of patients once they have developed cancer. Clinical parameters that have been associated with a worse prognosis include, for example, increased tumor stage, PSA level at presentation, and Gleason grade or pattern. Prognostic factors are frequently used to categorize patients into subgroups with different baseline relapse risks.
  • The term “prognosis” is used herein to refer to the likelihood that a cancer patient will have a cancer-attributable death or progression, including recurrence, metastatic spread, and drug resistance, of a neoplastic disease, such as prostate cancer. For example, a “good prognosis” would include long term survival without recurrence and a “bad prognosis” would include cancer recurrence.
  • As used herein, the term “expression level” as applied to a gene refers to the normalized level of a gene product, e.g. the normalized value determined for the RNA expression level of a gene or for the polypeptide expression level of a gene.
  • The term “gene product” or “expression product” are used herein to refer to the RNA (ribonucleic acid) transcription products (transcripts) of the gene, including mRNA, and the polypeptide translation products of such RNA transcripts. A gene product can be, for example, an unspliced RNA, an mRNA, a splice variant mRNA, a microRNA, a fragmented RNA, a polypeptide, a post-translationally modified polypeptide, a splice variant polypeptide, etc.
  • The term “RNA transcript” as used herein refers to the RNA transcription products of a gene, including, for example, mRNA, an unspliced RNA, a splice variant mRNA, a microRNA, and a fragmented RNA.
  • The term “microRNA” is used herein to refer to a small, non-coding, single-stranded RNA of ˜18-25 nucleotides that may regulate gene expression. For example, when associated with the RNA-induced silencing complex (RISC), the complex binds to specific mRNA targets and causes translation repression or cleavage of these mRNA sequences.
  • Unless indicated otherwise, each gene name used herein corresponds to the Official Symbol assigned to the gene and provided by Entrez Gene (URL: www.ncbi.nlm.nih.gov/sites/entrez) as of the filing date of this application.
  • The terms “correlated” and “associated” are used interchangeably herein to refer to the association between two measurements (or measured entities). The disclosure provides genes, gene subsets, microRNAs, or microRNAs in combination with genes or gene subsets, the expression levels of which are associated with tumor stage. For example, the increased expression level of a gene or microRNA may be positively correlated (positively associated) with a good or positive prognosis. Such a positive correlation may be demonstrated statistically in various ways, e.g. by a cancer recurrence hazard ratio less than one. In another example, the increased expression level of a gene or microRNA may be negatively correlated (negatively associated) with a good or positive prognosis. In that case, for example, the patient may experience a cancer recurrence.
  • The terms “good prognosis” or “positive prognosis” as used herein refer to a beneficial clinical outcome, such as long-term survival without recurrence. The terms “bad prognosis” or “negative prognosis” as used herein refer to a negative clinical outcome, such as cancer recurrence.
  • The term “risk classification” means a grouping of subjects by the level of risk (or likelihood) that the subject will experience a particular clinical outcome. A subject may be classified into a risk group or classified at a level of risk based on the methods of the present disclosure, e.g. high, medium, or low risk. A “risk group” is a group of subjects or individuals with a similar level of risk for a particular clinical outcome.
  • The term “long-term” survival is used herein to refer to survival for a particular time period, e.g., for at least 5 years, or for at least 10 years.
  • The term “recurrence” is used herein to refer to local or distant recurrence (i.e., metastasis) of cancer. For example, prostate cancer can recur locally in the tissue next to the prostate or in the seminal vesicles. The cancer may also affect the surrounding lymph nodes in the pelvis or lymph nodes outside this area. Prostate cancer can also spread to tissues next to the prostate, such as pelvic muscles, bones, or other organs. Recurrence can be determined by clinical recurrence detected by, for example, imaging study or biopsy, or biochemical recurrence detected by, for example, sustained follow-up prostate-specific antigen (PSA) levels ≥0.4 ng/mL or the initiation of salvage therapy as a result of a rising PSA level.
  • The term “clinical recurrence-free interval (cRFI)” is used herein as time (in months) from surgery to first clinical recurrence or death due to clinical recurrence of prostate cancer. Losses due to incomplete follow-up, other primary cancers or death prior to clinical recurrence are considered censoring events; when these occur, the only information known is that up through the censoring time, clinical recurrence has not occurred in this subject. Biochemical recurrences are ignored for the purposes of calculating cRFI.
  • The term “biochemical recurrence-free interval (bRFI)” is used herein to mean the time (in months) from surgery to first biochemical recurrence of prostate cancer. Clinical recurrences, losses due to incomplete follow-up, other primary cancers, or death prior to biochemical recurrence are considered censoring events.
  • The term “Overall Survival (OS)” is used herein to refer to the time (in months) from surgery to death from any cause. Losses due to incomplete follow-up are considered censoring events. Biochemical recurrence and clinical recurrence are ignored for the purposes of calculating OS.
  • The term “Prostate Cancer-Specific Survival (PCSS)” is used herein to describe the time (in years) from surgery to death from prostate cancer. Losses due to incomplete follow-up or deaths from other causes are considered censoring events. Clinical recurrence and biochemical recurrence are ignored for the purposes of calculating PCSS.
  • The term “upgrading” or “upstaging” as used herein refers to a change in Gleason grade from 3+3 at the time of biopsy to 3+4 or greater at the time of radical prostatectomy (RP), or Gleason grade 3+4 at the time of biopsy to 4+3 or greater at the time of RP, or seminal vessical involvement (SVI), or extracapsular involvement (ECE) at the time of RP.
  • In practice, the calculation of the measures listed above may vary from study to study depending on the definition of events to be considered censored.
  • The term “microarray” refers to an ordered arrangement of hybridizable array elements, e.g. oligonucleotide or polynucleotide probes, on a substrate.
  • The term “polynucleotide” generally refers to any polyribonucleotide or polydeoxribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. Thus, for instance, polynucleotides as defined herein include, without limitation, single- and double-stranded DNA, DNA including single- and double-stranded regions, single- and double-stranded RNA, and RNA including single- and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded or, more typically, double-stranded or include single- and double-stranded regions. In addition, the term “polynucleotide” as used herein refers to triple-stranded regions comprising RNA or DNA or both RNA and DNA. The strands in such regions may be from the same molecule or from different molecules. The regions may include all of one or more of the molecules, but more typically involve only a region of some of the molecules. One of the molecules of a triple-helical region often is an oligonucleotide. The term “polynucleotide” specifically includes cDNAs. The term includes DNAs (including cDNAs) and RNAs that contain one or more modified bases. Thus, DNAs or RNAs with backbones modified for stability or for other reasons, are “polynucleotides” as that term is intended herein. Moreover, DNAs or RNAs comprising unusual bases, such as inosine, or modified bases, such as tritiated bases, are included within the term “polynucleotides” as defined herein. In general, the term “polynucleotide” embraces all chemically, enzymatically and/or metabolically modified forms of unmodified polynucleotides, as well as the chemical forms of DNA and RNA characteristic of viruses and cells, including simple and complex cells.
  • The term “oligonucleotide” refers to a relatively short polynucleotide, including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RNArDNA hybrids and double-stranded DNAs. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available. However, oligonucleotides can be made by a variety of other methods, including in vitro recombinant DNA-mediated techniques and by expression of DNAs in cells and organisms.
  • The term “Ct” as used herein refers to threshold cycle, the cycle number in quantitative polymerase chain reaction (qPCR) at which the fluorescence generated within a reaction well exceeds the defined threshold, i.e. the point during the reaction at which a sufficient number of amplicons have accumulated to meet the defined threshold.
  • The term “Cp” as used herein refers to “crossing point.” The Cp value is calculated by determining the second derivatives of entire qPCR amplification curves and their maximum value. The Cp value represents the cycle at which the increase of fluorescence is highest and where the logarithmic phase of a PCR begins.
  • The terms “threshold” or “thresholding” refer to a procedure used to account for non-linear relationships between gene expression measurements and clinical response as well as to further reduce variation in reported patient scores. When thresholding is applied, all measurements below or above a threshold are set to that threshold value. Non-linear relationship between gene expression and outcome could be examined using smoothers or cubic splines to model gene expression in Cox PH regression on recurrence free interval or logistic regression on recurrence status. D. Cox, Journal of the Royal Statistical Society, Series B 34:187-220 (1972). Variation in reported patient scores could be examined as a function of variability in gene expression at the limit of quantitation and/or detection for a particular gene.
  • As used herein, the term “amplicon,” refers to pieces of DNA that have been synthesized using amplification techniques, such as polymerase chain reactions (PCR) and ligase chain reactions.
  • “Stringency” of hybridization reactions is readily determinable by one of ordinary skill in the art, and generally is an empirical calculation dependent upon probe length, washing temperature, and salt concentration. In general, longer probes require higher temperatures for proper annealing, while shorter probes need lower temperatures. Hybridization generally depends on the ability of denatured DNA to re-anneal when complementary strands are present in an environment below their melting temperature. The higher the degree of desired homology between the probe and hybridizable sequence, the higher the relative temperature which can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while lower temperatures less so. For additional details and explanation of stringency of hybridization reactions, see Ausubel et al., Current Protocols in Molecular Biology (Wiley Interscience Publishers, 1995).
  • “Stringent conditions” or “high stringency conditions”, as defined herein, typically: (1) employ low ionic strength and high temperature for washing, for example 0.015 M sodium chloride/0.0015 M sodium citrate/0.1% sodium dodecyl sulfate at 50° C.; (2) employ during hybridization a denaturing agent, such as formamide, for example, 50% (v/v) formamide with 0.1% bovine serum albumin/0.1% Ficoll/0.1% polyvinylpyrrolidone/50 mM sodium phosphate buffer at pH 6.5 with 750 mM sodium chloride, 75 mM sodium citrate at 42° C.; or (3) employ 50% formamide, 5×SSC (0.75 M NaCl, 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0.1% sodium pyrophosphate, 5×Denhardt's solution, sonicated salmon sperm DNA (50 μg/ml), 0.1% SDS, and 10% dextran sulfate at 42° C., with washes at 42° C. in 0.2×SSC (sodium chloride/sodium citrate) and 50% formamide, followed by a high-stringency wash consisting of 0.1×SSC containing EDTA at 55° C.
  • “Moderately stringent conditions” may be identified as described by Sambrook et al., Molecular Cloning: A Laboratory Manual, New York: Cold Spring Harbor Press, 1989, and include the use of washing solution and hybridization conditions (e.g., temperature, ionic strength and % SDS) less stringent that those described above. An example of moderately stringent conditions is overnight incubation at 37° C. in a solution comprising: 20% formamide, 5×SSC (150 mM NaCl, 15 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6), 5×Denhardt's solution, 10% dextran sulfate, and 20 mg/ml denatured sheared salmon sperm DNA, followed by washing the filters in 1×SSC at about 37-50° C. The skilled artisan will recognize how to adjust the temperature, ionic strength, etc. as necessary to accommodate factors such as probe length and the like.
  • The terms “splicing” and “RNA splicing” are used interchangeably and refer to RNA processing that removes introns and joins exons to produce mature mRNA with continuous coding sequence that moves into the cytoplasm of an eukaryotic cell.
  • The terms “co-express” and “co-expressed”, as used herein, refer to a statistical correlation between the amounts of different transcript sequences across a population of different patients. Pairwise co-expression may be calculated by various methods known in the art, e.g., by calculating Pearson correlation coefficients or Spearman correlation coefficients. Co-expressed gene cliques may also be identified using graph theory. An analysis of co-expression may be calculated using normalized expression data. A gene is said to be co-expressed with a particular disclosed gene when the expression level of the gene exhibits a Pearson correlation coefficient greater than or equal to 0.6.
  • A “computer-based system” refers to a system of hardware, software, and data storage medium used to analyze information. The minimum hardware of a patient computer-based system comprises a central processing unit (CPU), and hardware for data input, data output (e.g., display), and data storage. An ordinarily skilled artisan can readily appreciate that any currently available computer-based systems and/or components thereof are suitable for use in connection with the methods of the present disclosure. The data storage medium may comprise any manufacture comprising a recording of the present information as described above, or a memory access device that can access such a manufacture.
  • To “record” data, programming or other information on a computer readable medium refers to a process for storing information, using any such methods as known in the art. Any convenient data storage structure may be chosen, based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, e.g. word processing text file, database format, etc.
  • A “processor” or “computing means” references any hardware and/or software combination that will perform the functions required of it. For example, a suitable processor may be a programmable digital microprocessor such as available in the form of an electronic controller, mainframe, server or personal computer (desktop or portable). Where the processor is programmable, suitable programming can be communicated from a remote location to the processor, or previously saved in a computer program product (such as a portable or fixed computer readable storage medium, whether magnetic, optical or solid state device based). For example, a magnetic medium or optical disk may carry the programming, and can be read by a suitable reader communicating with each processor at its corresponding station.
  • As used herein, the terms “active surveillance” and “watchful waiting” mean closely monitoring a patient's condition without giving any treatment until symptoms appear or change. For example, in prostate cancer, watchful waiting is usually used in older men with other medical problems and early-stage disease.
  • As used herein, the term “surgery” applies to surgical methods undertaken for removal of cancerous tissue, including pelvic lymphadenectomy, radical prostatectomy, transurethral resection of the prostate (TURP), excision, dissection, and tumor biopsy/removal. The tumor tissue or sections used for gene expression analysis may have been obtained from any of these methods.
  • As used herein, the term “therapy” includes radiation, hormonal therapy, cryosurgery, chemotherapy, biologic therapy, and high-intensity focused ultrasound.
  • As used herein, the term “TMPRSS fusion” and “TMPRSS2 fusion” are used interchangeably and refer to a fusion of the androgen-driven TMPRSS2 gene with the ERG oncogene, which has been demonstrated to have a significant association with prostate cancer. S. Perner, et al., Urologe A. 46(7):754-760 (2007); S. A. Narod, et al., Br J Cancer 99(6):847-851 (2008). As used herein, positive TMPRSS fusion status indicates that the TMPRSS fusion is present in a tissue sample, whereas negative TMPRSS fusion status indicates that the TMPRSS fusion is not present in a tissue sample. Experts skilled in the art will recognize that there are numerous ways to determine TMPRSS fusion status, such as real-time, quantitative PCR or high-throughput sequencing. See, e.g., K. Mertz, et al., Neoplasis 9(3):200-206 (2007); C. Maher, Nature 458(7234):97-101 (2009).
    • Gene Expression Methods Using Genes, Gene Subsets, and MicroRNAs
  • The present disclosure provides molecular assays that involve measurement of expression level(s) of one or more genes, gene subsets, microRNAs, or one or more microRNAs in combination with one or more genes or gene subsets, from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likelihood of cancer recurrence.
  • The present disclosure further provides methods to classify a prostate tumor based on expression level(s) of one or more genes and/or microRNAs. The disclosure further provides genes and/or microRNAs that are associated, positively or negatively, with a particular prognostic outcome. In exemplary embodiments, the clinical outcomes include cRFI and bRFI. In another embodiment, patients may be classified in risk groups based on the expression level(s) of one or more genes and/or microRNAs that are associated, positively or negatively, with a prognostic factor. In an exemplary embodiment, that prognostic factor is Gleason pattern.
  • Various technological approaches for determination of expression levels of the disclosed genes and microRNAs are set forth in this specification, including, without limitation, RT-PCR, microarrays, high-throughput sequencing, serial analysis of gene expression (SAGE) and Digital Gene Expression (DGE), which will be discussed in detail below. In particular aspects, the expression level of each gene or microRNA may be determined in relation to various features of the expression products of the gene including exons, introns, protein epitopes and protein activity.
  • The expression level(s) of one or more genes and/or microRNAs may be measured in tumor tissue. For example, the tumor tissue may obtained upon surgical removal or resection of the tumor, or by tumor biopsy. The tumor tissue may be or include histologically “normal” tissue, for example histologically “normal” tissue adjacent to a tumor. The expression level of genes and/or microRNAs may also be measured in tumor cells recovered from sites distant from the tumor, for example circulating tumor cells, body fluid (e.g., urine, blood, blood fraction, etc.).
  • The expression product that is assayed can be, for example, RNA or a polypeptide. The expression product may be fragmented. For example, the assay may use primers that are complementary to target sequences of an expression product and could thus measure full transcripts as well as those fragmented expression products containing the target sequence. Further information is provided in Table A (inserted in specification prior to claims).
  • The RNA expression product may be assayed directly or by detection of a cDNA product resulting from a PCR-based amplification method, e.g., quantitative reverse transcription polymerase chain reaction (qRT-PCR). (See e.g., U.S. Pat. No. 7,587,279). Polypeptide expression product may be assayed using immunohistochemistry (IHC). Further, both RNA and polypeptide expression products may also be is assayed using microarrays.
    • Clinical Utility
  • Prostate cancer is currently diagnosed using a digital rectal exam (DRE) and Prostate-specific antigen (PSA) test. If PSA results are high, patients will generally undergo a prostate tissue biopsy. The pathologist will review the biopsy samples to check for cancer cells and determine a Gleason score. Based on the Gleason score, PSA, clinical stage, and other factors, the physician must make a decision whether to monitor the patient, or treat the patient with surgery and therapy.
  • At present, clinical decision-making in early stage prostate cancer is governed by certain histopathologic and clinical factors. These include: (1) tumor factors, such as clinical stage (e.g. T1, T2), PSA level at presentation, and Gleason grade, that are very strong prognostic factors in determining outcome; and (2) host factors, such as age at diagnosis and co-morbidity. Because of these factors, the most clinically useful means of stratifying patients with localized disease according to prognosis has been through multifactorial staging, using the clinical stage, the serum PSA level, and tumor grade (Gleason grade) together. In the 2007 updated American Urological Association (AUA) guidelines for management of clinically localized prostate cancer, these parameters have been grouped to determine whether a patient is at low, intermediate, or high risk of biochemical (PSA) relapse after local therapy. I. Thompson, et al., Guideline for the management of clinically localized prostate cancer, J Urol. 177(6):2106-31 (2007).
  • Although such classifications have proven to be helpful in distinguishing patients with localized disease who may need adjuvant therapy after surgery/radiation, they have less ability to discriminate between indolent cancers, which do not need to be treated with local therapy, and aggressive tumors, which require local therapy. In fact, these algorithms are of increasingly limited use for deciding between conservative management and definitive therapy because the bulk of prostate cancers diagnosed in the PSA screening era now present with clinical stage T1c and PSA ≤10 ng/mL.
  • Patients with T1 prostate cancer have disease that is not clinically apparent but is discovered either at transurethral resection of the prostate (TURP, T1a, T1b) or at biopsy performed because of an elevated PSA (>4 ng/mL, T1c). Approximately 80% of the cases presenting in 2007 are clinical T1 at diagnosis. In a Scandinavian trial, OS at 10 years was 85% for patients with early stage prostate cancer (T1/T2) and Gleason score ≤7, after radical prostatectomy.
  • Patients with T2 prostate cancer have disease that is clinically evident and is organ confined; patients with T3 tumors have disease that has penetrated the prostatic capsule and/or has invaded the seminal vesicles. It is known from surgical series that clinical staging underestimates pathological stage, so that about 20% of patients who are clinically T2 will be pT3 after prostatectomy. Most of patients with T2 or T3 prostate cancer are treated with local therapy, either prostatectomy or radiation. The data from the Scandinavian trial suggest that for T2 patients with Gleason grade ≤7, the effect of prostatectomy on survival is at most 5% at 10 years; the majority of patients do not benefit from surgical treatment at the time of diagnosis. For T2 patients with Gleason >7 or for T3 patients, the treatment effect of prostatectomy is assumed to be significant but has not been determined in randomized trials. It is known that these patients have a significant risk (10-30%) of recurrence at 10 years after local treatment, however, there are no prospective randomized trials that define the optimal local treatment (radical prostatectomy, radiation) at diagnosis, which patients are likely to benefit from neo-adjuvant/adjuvant androgen deprivation therapy, and whether treatment (androgen deprivation, chemotherapy) at the time of biochemical failure (elevated PSA) has any clinical benefit.
  • Accurately determining Gleason scores from needle biopsies presents several technical challenges. First, interpreting histology that is “borderline” between Gleason pattern is highly subjective, even for urologic pathologists. Second, incomplete biopsy sampling is yet another reason why the “predicted” Gleason score on biopsy does not always correlate with the actual “observed” Gleason score of the prostate cancer in the gland itself. Hence, the accuracy of Gleason scoring is dependent upon not only the expertise of the pathologist reading the slides, but also on the completeness and adequacy of the prostate biopsy sampling strategy. T. Stamey, Urology 45:2-12 (1995). The gene/microRNA expression assay and associated information provided by the practice of the methods disclosed herein provide a molecular assay method to facilitate optimal treatment decision-making in early stage prostate cancer. An exemplary embodiment provides genes and microRNAs, the expression levels of which are associated (positively or negatively) with prostate cancer recurrence. For example, such a clinical tool would enable physicians to identify T2/T3 patients who are likely to recur following definitive therapy and need adjuvant treatment.
  • In addition, the methods disclosed herein may allow physicians to classify tumors, at a molecular level, based on expression level(s) of one or more genes and/or microRNAs that are significantly associated with prognostic factors, such as Gleason pattern and TMPRSS fusion status. These methods would not be impacted by the technical difficulties of intra-patient variability, histologically determining Gleason pattern in biopsy samples, or inclusion of histologically normal appearing tissue adjacent to tumor tissue. Multi-analyte gene/microRNA expression tests can be used to measure the expression level of one or more genes and/or microRNAs involved in each of several relevant physiologic processes or component cellular characteristics. The methods disclosed herein may group the genes and/or microRNAs. The grouping of genes and microRNAs may be performed at least in part based on knowledge of the contribution of those genes and/or microRNAs according to physiologic functions or component cellular characteristics, such as in the groups discussed above. Furthermore, one or more microRNAs may be combined with one or moregenes. The gene-microRNA combination may be selected based on the likelihood that the gene-microRNA combination functionally interact. The formation of groups (or gene subsets), in addition, can facilitate the mathematical weighting of the contribution of various expression levels to cancer recurrence. The weighting of a gene/microRNA group representing a physiological process or component cellular characteristic can reflect the contribution of that process or characteristic to the pathology of the cancer and clinical outcome.
  • Optionally, the methods disclosed may be used to classify patients by risk, for example risk of recurrence. Patients can be partitioned into subgroups (e.g., tertiles or quartiles) and the values chosen will define subgroups of patients with respectively greater or lesser risk.
  • The utility of a disclosed gene marker in predicting prognosis may not be unique to that marker. An alternative marker having an expression pattern that is parallel to that of a disclosed gene may be substituted for, or used in addition to, that co-expressed gene or microRNA. Due to the co-expression of such genes or microRNAs, substitution of expression level values should have little impact on the overall utility of the test. The closely similar expression patterns of two genes or microRNAs may result from involvement of both genes or microRNAs in the same process and/or being under common regulatory control in prostate tumor cells. The present disclosure thus contemplates the use of such co-expressed genes, gene subsets, or microRNAs as substitutes for, or in addition to, genes of the present disclosure.
    • Methods of Assaying Expression Levels of a Gene Product
  • The methods and compositions of the present disclosure will employ, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, and biochemistry, which are within the skill of the art. Exemplary techniques are explained fully in the literature, such as, “Molecular Cloning: A Laboratory Manual”, 2nd edition (Sambrook et al., 1989); “Oligonucleotide Synthesis” (M. J. Gait, ed., 1984); “Animal Cell Culture” (R. I. Freshney, ed., 1987); “Methods in Enzymology” (Academic Press, Inc.); “Handbook of Experimental Immunology”, 4th edition (D. M. Weir & C. C. Blackwell, eds., Blackwell Science Inc., 1987); “Gene Transfer Vectors for Mammalian Cells” (J. M. Miller & M. P. Calos, eds., 1987); “Current Protocols in Molecular Biology” (F. M. Ausubel et al., eds., 1987); and “PCR: The Polymerase Chain Reaction”, (Mullis et al., eds., 1994).
  • Methods of gene expression profiling include methods based on hybridization analysis of polynucleotides, methods based on sequencing of polynucleotides, and proteomics-based methods. Exemplary methods known in the art for the quantification of RNA expression in a sample include northern blotting and in situ hybridization (Parker & Barnes, Methods in Molecular Biology 106:247-283 (1999)); RNAse protection assays (Hod, Biotechniques 13:852-854 (1992)); and PCR-based methods, such as reverse transcription PCT (RT-PCR) (Weis et al., Trends in Genetics 8:263-264 (1992)). Antibodies may be employed that can recognize sequence-specific duplexes, including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-protein duplexes. Representative methods for sequencing-based gene expression analysis include Serial Analysis of Gene Expression (SAGE), and gene expression analysis by massively parallel signature sequencing (MPSS).
  • Reverse Transcriptase PCR (RT-PCR)
  • Typically, mRNA or microRNA is isolated from a test sample. The starting material is typically total RNA isolated from a human tumor, usually from a primary tumor. Optionally, normal tissues from the same patient can be used as an internal control. Such normal tissue can be histologically-appearing normal tissue adjacent a tumor. mRNA or microRNA can be extracted from a tissue sample, e.g., from a sample that is fresh, frozen (e.g. fresh frozen), or paraffin-embedded and fixed (e.g. formalin-fixed).
  • General methods for mRNA and microRNA extraction are well known in the art and are disclosed in standard textbooks of molecular biology, including Ausubel et al., Current Protocols of Molecular Biology, John Wiley and Sons (1997). Methods for RNA extraction from paraffin embedded tissues are disclosed, for example, in Rupp and Locker, Lab Invest. 56:A67 (1987), and De Andres et al., BioTechniques 18:42044 (1995). In particular, RNA isolation can be performed using a purification kit, buffer set and protease from commercial manufacturers, such as Qiagen, according to the manufacturer's instructions. For example, total RNA from cells in culture can be isolated using Qiagen RNeasy mini-columns. Other commercially available RNA isolation kits include MasterPure™ Complete DNA and RNA Purification Kit (EPICENTRE®, Madison, Wis.), and Paraffin Block RNA Isolation Kit (Ambion, Inc.). Total RNA from tissue samples can be isolated using RNA Stat-60 (Tel-Test). RNA prepared from tumor can be isolated, for example, by cesium chloride density gradient centrifugation.
  • The sample containing the RNA is then subjected to reverse transcription to produce cDNA from the RNA template, followed by exponential amplification in a PCR reaction. The two most commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLV-RT). The reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances and the goal of expression profiling. For example, extracted RNA can be reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, CA, USA), following the manufacturer's instructions. The derived cDNA can then be used as a template in the subsequent PCR reaction.
  • PCR-based methods use a thermostable DNA-dependent DNA polymerase, such as a Taq DNA polymerase. For example, TaqMan® PCR typically utilizes the 5′-nuclease activity of Taq or Tth polymerase to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5′ nuclease activity can be used. Two oligonucleotide primers are used to generate an amplicon typical of a PCR reaction product. A third oligonucleotide, or probe, can be designed to facilitate detection of a nucleotide sequence of the amplicon located between the hybridization sites the two PCR primers. The probe can be detectably labeled, e.g., with a reporter dye, and can further be provided with both a fluorescent dye, and a quencher fluorescent dye, as in a Taqman® probe configuration. Where a Taqman® probe is used, during the amplification reaction, the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore. One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of the data.
  • TaqMan® RT-PCR can be performed using commercially available equipment, such as, for example, high-throughput platforms such as the ABI PRISM 7700 Sequence Detection System® (Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA), or Lightcycler (Roche Molecular Biochemicals, Mannheim, Germany). In a preferred embodiment, the procedure is run on a LightCycler® 480 (Roche Diagnostics) real-time PCR system, which is a microwell plate-based cycler platform.
  • 5′-Nuclease assay data are commonly initially expressed as a threshold cycle (“CT”). Fluorescence values are recorded during every cycle and represent the amount of product amplified to that point in the amplification reaction. The threshold cycle (CT) is generally described as the point when the fluorescent signal is first recorded as statistically significant. Alternatively, data may be expressed as a crossing point (“Cp”). The Cp value is calculated by determining the second derivatives of entire qPCR amplification curves and their maximum value. The Cp value represents the cycle at which the increase of fluorescence is highest and where the logarithmic phase of a PCR begins.
  • To minimize errors and the effect of sample-to-sample variation, RT-PCR is usually performed using an internal standard. The ideal internal standard gene (also referred to as a reference gene) is expressed at a quite constant level among cancerous and non-cancerous tissue of the same origin (i.e., a level that is not significantly different among normal and cancerous tissues), and is not significantly affected by the experimental treatment (i.e., does not exhibit a significant difference in expression level in the relevant tissue as a result of exposure to chemotherapy), and expressed at a quite constant level among the same tissue taken from different patients. For example, reference genes useful in the methods disclosed herein should not exhibit significantly different expression levels in cancerous prostate as compared to normal prostate tissue. RNAs frequently used to normalize patterns of gene expression are mRNAs for the housekeeping genes glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and (3-actin. Exemplary reference genes used for normalization comprise one or more of the following genes: AAMP, ARF1, ATP5E, CLTC, GPS1, and PGK1. Gene expression measurements can be normalized relative to the mean of one or more (e.g., 2, 3, 4, 5, or more) reference genes. Reference-normalized expression measurements can range from 2 to 15, where a one unit increase generally reflects a 2-fold increase in RNA quantity.
  • Real time PCR is compatible both with quantitative competitive PCR, where internal competitor for each target sequence is used for normalization, and with quantitative comparative PCR using a normalization gene contained within the sample, or a housekeeping gene for RT-PCR. For further details see, e.g. Held et al., Genome Research 6:986-994 (1996).
  • The steps of a representative protocol for use in the methods of the present disclosure use fixed, paraffin-embedded tissues as the RNA source. For example, mRNA isolation, purification, primer extension and amplification can be performed according to methods available in the art. (see, e.g., Godfrey et al. J. Molec. Diagnostics 2: 84-91 (2000); Specht et al., Am. J. Pathol. 158: 419-29 (2001)). Briefly, a representative process starts with cutting about 10 μm thick sections of paraffin-embedded tumor tissue samples. The RNA is then extracted, and protein and DNA depleted from the RNA-containing sample. After analysis of the RNA concentration, RNA is reverse transcribed using gene specific primers followed by RT-PCR to provide for cDNA amplification products.
  • Design of Intron-Based PCR Primers and Probes
  • PCR primers and probes can be designed based upon exon or intron sequences present in the mRNA transcript of the gene of interest. Primer/probe design can be performed using publicly available software, such as the DNA BLAT software developed by Kent, W. J., Genome Res. 12(4):656-64 (2002), or by the BLAST software including its variations.
  • Where necessary or desired, repetitive sequences of the target sequence can be masked to mitigate non-specific signals. Exemplary tools to accomplish this include the Repeat Masker program available on-line through the Baylor College of Medicine, which screens DNA sequences against a library of repetitive elements and returns a query sequence in which the repetitive elements are masked. The masked intron sequences can then be used to design primer and probe sequences using any commercially or otherwise publicly available primer/probe design packages, such as Primer Express (Applied Biosystems); MGB assay-by-design (Applied Biosystems); Primer3 (Steve Rozen and Helen J. Skaletsky (2000) Primer3 on the WWW for general users and for biologist programmers. See S. Rrawetz, S. Misener, Bioinformatics Methods and Protocols: Methods in Molecular Biology, pp. 365-386 (Humana Press).
  • Other factors that can influence PCR primer design include primer length, melting temperature (Tm), and G/C content, specificity, complementary primer sequences, and 3′-end sequence. In general, optimal PCR primers are generally 17-30 bases in length, and contain about 20-80%, such as, for example, about 50-60% G+C bases, and exhibit Tm's between 50 and 80° C., e.g. about 50 to 70° C.
  • For further guidelines for PCR primer and probe design see, e.g. Dieffenbach, C W. et al, “General Concepts for PCR Primer Design” in: PCR Primer, A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York, 1995, pp. 133-155; Innis and Gelfand, “Optimization of PCRs” in: PCR Protocols, A Guide to Methods and Applications, CRC Press, London, 1994, pp. 5-11; and Plasterer, T.N. Primerselect: Primer and probe design. Methods Mol. Biol. 70:520-527 (1997), the entire disclosures of which are hereby expressly incorporated by reference.
  • Table A provides further information concerning the primer, probe, and amplicon sequences associated with the Examples disclosed herein.
  • MassARRAY® System
  • In MassARRAY-based methods, such as the exemplary method developed by Sequenom, Inc. (San Diego, Calif.) following the isolation of RNA and reverse transcription, the obtained cDNA is spiked with a synthetic DNA molecule (competitor), which matches the targeted cDNA region in all positions, except a single base, and serves as an internal standard. The cDNA/competitor mixture is PCR amplified and is subjected to a post-PCR shrimp alkaline phosphatase (SAP) enzyme treatment, which results in the dephosphorylation of the remaining nucleotides. After inactivarion of the alkaline phosphatase, the PCR products from the competitor and cDNA are subjected to primer extension, which generates distinct mass signals for the competitor- and cDNA-derives PCR products. After purification, these products are dispensed on a chip array, which is pre-loaded with components needed for analysis with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The cDNA present in the reaction is then quantified by analyzing the ratios of the peak areas in the mass spectrum generated. For further details see, e.g. Ding and Cantor, Proc. Natl. Acad. Sci. USA 100:3059-3064 (2003).
  • Other PCR-Based Methods
  • Further PCR-based techniques that can find use in the methods disclosed herein include, for example, BeadArray® technology (Illumina, San Diego, Calif.; Oliphant et al., Discovery of Markers for Disease (Supplement to Biotechniques), June 2002; Ferguson et al., Analytical Chemistry 72:5618 (2000)); BeadsArray for Detection of Gene Expression® (BADGE), using the commercially available LuminexlOO LabMAP® system and multiple color-coded microspheres (Luminex Corp., Austin, Tex.) in a rapid assay for gene expression (Yang et al., Genome Res. 11:1888-1898 (2001)); and high coverage expression profiling (HiCEP) analysis (Fukumura et al., Nucl. Acids. Res. 31(16) e94 (2003).
  • Microarrays
  • Expression levels of a gene or microArray of interest can also be assessed using the microarray technique. In this method, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are arrayed on a substrate. The arrayed sequences are then contacted under conditions suitable for specific hybridization with detectably labeled cDNA generated from RNA of a test sample. As in the RT-PCR method, the source of RNA typically is total RNA isolated from a tumor sample, and optionally from normal tissue of the same patient as an internal control or cell lines. RNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g. formalin-fixed) tissue samples.
  • For example, PCR amplified inserts of cDNA clones of a gene to be assayed are applied to a substrate in a dense array. Usually at least 10,000 nucleotide sequences are applied to the substrate. For example, the microarrayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After washing under stringent conditions to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding RNA abundance.
  • With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. The miniaturized scale of the hybridization affords a convenient and rapid evaluation of the expression pattern for large numbers of genes. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a few copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schena et at, Proc. Natl. Acad. ScL USA 93(2):106-149 (1996)). Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip® technology, or Incyte's microarray technology.
  • Serial Analysis of Gene Expression (SAGE)
  • Serial analysis of gene expression (SAGE) is a method that allows the simultaneous and quantitative analysis of a large number of gene transcripts, without the need of providing an individual hybridization probe for each transcript. First, a short sequence tag (about 10-14 bp) is generated that contains sufficient information to uniquely identify a transcript, provided that the tag is obtained from a unique position within each transcript. Then, many transcripts are linked together to form long serial molecules, that can be sequenced, revealing the identity of the multiple tags simultaneously. The expression pattern of any population of transcripts can be quantitatively evaluated by determining the abundance of individual tags, and identifying the gene corresponding to each tag. For more details see, e.g. Velculescu et al., Science 270:484-487 (1995); and Velculescu et al., Cell 88:243-51 (1997).
  • Gene Expression Analysis by Nucleic Acid Sequencing
  • Nucleic acid sequencing technologies are suitable methods for analysis of gene expression. The principle underlying these methods is that the number of times a cDNA sequence is detected in a sample is directly related to the relative expression of the RNA corresponding to that sequence. These methods are sometimes referred to by the term Digital Gene Expression (DGE) to reflect the discrete numeric property of the resulting data. Early methods applying this principle were Serial Analysis of Gene Expression (SAGE) and Massively Parallel Signature Sequencing (MPSS). See, e.g., S. Brenner, et al., Nature Biotechnology 18(6):630-634 (2000). More recently, the advent of “next-generation” sequencing technologies has made DGE simpler, higher throughput, and more affordable. As a result, more laboratories are able to utilize DGE to screen the expression of more genes in more individual patient samples than previously possible. See, e.g., J. Marioni, Genome Research 18(9):1509-1517 (2008); R. Morin, Genome Research 18(4):610-621 (2008); A. Mortazavi, Nature Methods 5(7):621-628 (2008); N. Cloonan, Nature Methods 5(7):613-619 (2008).
  • Isolating RNA from Body Fluids
  • Methods of isolating RNA for expression analysis from blood, plasma and serum (see, e.g., K. Enders, et al., Clin Chem 48, 1647-53 (2002) (and references cited therein) and from urine (see, e.g., R. Boom, et al., J Clin Microbiol. 28, 495-503 (1990) and references cited therein) have been described.
  • Immunohistochemistry
  • Immunohistochemistry methods are also suitable for detecting the expression levels of genes and applied to the method disclosed herein. Antibodies (e.g., monoclonal antibodies) that specifically bind a gene product of a gene of interest can be used in such methods. The antibodies can be detected by direct labeling of the antibodies themselves, for example, with radioactive labels, fluorescent labels, hapten' labels such as, biotin, or an enzyme such as horse radish peroxidase or alkaline phosphatase. Alternatively, unlabeled primary antibody can be used in conjunction with a labeled secondary antibody specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available.
  • Proteomics
  • The term “proteome” is defined as the totality of the proteins present in a sample (e.g. tissue, organism, or cell culture) at a certain point of time. Proteomics includes, among other things, study of the global changes of protein expression in a sample (also referred to as “expression proteomics”). Proteomics typically includes the following steps: (1) separation of individual proteins in a sample by 2-D gel electrophoresis (2-D PAGE); (2) identification of the individual proteins recovered from the gel, e.g. my mass spectrometry or N-terminal sequencing, and (3) analysis of the data using bioinformatics.
  • General Description of the mRNA/microRNA Isolation, Purification and Amplification
  • The steps of a representative protocol for profiling gene expression using fixed, paraffin-embedded tissues as the RNA source, including mRNA or microRNA isolation, purification, primer extension and amplification are provided in various published journal articles. (See, e.g., T. E. Godfrey, et al, J. Molec. Diagnostics 2: 84-91 (2000); K. Specht et al., Am. J. Pathol. 158: 419-29 (2001), M. Cronin, et al., Am J Pathol 164:35-42 (2004)). Briefly, a representative process starts with cutting a tissue sample section (e.g. about 10 μm thick sections of a paraffin-embedded tumor tissue sample). The RNA is then extracted, and protein and DNA are removed. After analysis of the RNA concentration, RNA repair is performed if desired. The sample can then be subjected to analysis, e.g., by reverse transcribed using gene specific promoters followed by RT-PCR.
    • Statistical Analysis of Expression Levels in Identification of Genes and MicroRNAs
  • One skilled in the art will recognize that there are many statistical methods that may be used to determine whether there is a significant relationship between a parameter of interest (e.g., recurrence) and expression levels of a marker gene/microRNA as described here. In an exemplary embodiment, the present invention provides a stratified cohort sampling design (a form of case-control sampling) using tissue and data from prostate cancer patients. Selection of specimens was stratified by T stage (T1, T2), year cohort (<1993, ≥1993), and prostatectomy Gleason Score (low/intermediate, high). All patients with clinical recurrence were selected and a sample of patients who did not experience a clinical recurrence was selected. For each patient, up to two enriched tumor specimens and one normal-appearing tissue sample was assayed.
  • All hypothesis tests were reported using two-sided p-values. To investigate if there is a significant relationship of outcomes (clinical recurrence-free interval (cRFI), biochemical recurrence-free interval (bRFI), prostate cancer-specific survival (PCSS), and overall survival (OS)) with individual genes and/or microRNAs, demographic or clinical covariates Cox Proportional Hazards (PH) models using maximum weighted pseudo partial-likelihood estimators were used and p-values from Wald tests of the null hypothesis that the hazard ratio (HR) is one are reported. To investigate if there is a significant relationship between individual genes and/or microRNAs and Gleason pattern of a particular sample, ordinal logistic regression models using maximum weighted likelihood methods were used and p-values from Wald tests of the null hypothesis that the odds ratio (OR) is one are reported.
    • Coexpression Analysis
  • The present disclosure provides a method to determine tumor stage based on the expression of staging genes, or genes that co-express with particular staging genes. To perform particular biological processes, genes often work together in a concerted way, i.e. they are co-expressed. Co-expressed gene groups identified for a disease process like cancer can serve as biomarkers for tumor status and disease progression. Such co-expressed genes can be assayed in lieu of, or in addition to, assaying of the staging gene with which they are co-expressed.
  • In an exemplary embodiment, the joint correlation of gene expression levels among prostate cancer specimens under study may be assessed. For this purpose, the correlation structures among genes and specimens may be examined through hierarchical cluster methods. This information may be used to confirm that genes that are known to be highly correlated in prostate cancer specimens cluster together as expected. Only genes exhibiting a nominally significant (unadjusted p<0.05) relationship with cRFI in the univariate Cox PH regression analysis will be included in these analyses.
  • One skilled in the art will recognize that many co-expression analysis methods now known or later developed will fall within the scope and spirit of the present invention. These methods may incorporate, for example, correlation coefficients, co-expression network analysis, clique analysis, etc., and may be based on expression data from RT-PCR, microarrays, sequencing, and other similar technologies. For example, gene expression clusters can be identified using pair-wise analysis of correlation based on Pearson or Spearman correlation coefficients. (See, e.g., Pearson K. and Lee A., Biometrika 2, 357 (1902); C. Spearman, Amer. J. Psychol 15:72-101 (1904); J. Myers, A. Well, Research Design and Statistical Analysis, p. 508 (2nd Ed., 2003).)
    • Normalization of Expression Levels
  • The expression data used in the methods disclosed herein can be normalized. Normalization refers to a process to correct for (normalize away), for example, differences in the amount of RNA assayed and variability in the quality of the RNA used, to remove unwanted sources of systematic variation in Ct or Cp measurements, and the like. With respect to RT-PCR experiments involving archived fixed paraffin embedded tissue samples, sources of systematic variation are known to include the degree of RNA degradation relative to the age of the patient sample and the type of fixative used to store the sample. Other sources of systematic variation are attributable to laboratory processing conditions.
  • Assays can provide for normalization by incorporating the expression of certain normalizing genes, which do not significantly differ in expression levels under the relevant conditions. Exemplary normalization genes disclosed herein include housekeeping genes. (See, e.g., E. Eisenberg, et al., Trends in Genetics 19(7):362-365 (2003).) Normalization can be based on the mean or median signal (Ct or Cp) of all of the assayed genes or a large subset thereof (global normalization approach). In general, the normalizing genes, also referred to as reference genes should be genes that are known not to exhibit significantly different expression in prostate cancer as compared to non-cancerous prostate tissue, and are not significantly affected by various sample and process conditions, thus provide for normalizing away extraneous effects.
  • In exemplary embodiments, one or more of the following genes are used as references by which the mRNA or microRNA expression data is normalized: AAMP, ARF1, ATP5E, CLTC, GPS1, and PGK1. In another exemplary embodiment, one or more of the following microRNAs are used as references by which the expression data of microRNAs are normalized: hsa-miR-106a; hsa-miR-146b-5p; hsa-miR-191; hsa-miR-19b; and hsa-miR-92a. The calibrated weighted average CT or Cp measurements for each of the prognostic and predictive genes or microRNAs may be normalized relative to the mean of five or more reference genes or microRNAs.
  • Those skilled in the art will recognize that normalization may be achieved in numerous ways, and the techniques described above are intended only to be exemplary, not exhaustive.
    • Standardization of Expression Levels
  • The expression data used in the methods disclosed herein can be standardized. Standardization refers to a process to effectively put all the genes or microRNAs on a comparable scale. This is performed because some genes or microRNAs will exhibit more variation (a broader range of expression) than others. Standardization is performed by dividing each expression value by its standard deviation across all samples for that gene or microRNA. Hazard ratios are then interpreted as the relative risk of recurrence per 1 standard deviation increase in expression.
    • Kits of the Invention
  • The materials for use in the methods of the present invention are suited for preparation of kits produced in accordance with well-known procedures. The present disclosure thus provides kits comprising agents, which may include gene (or microRNA)-specific or gene (or microRNA)-selective probes and/or primers, for quantifying the expression of the disclosed genes or microRNAs for predicting prognostic outcome or response to treatment. Such kits may optionally contain reagents for the extraction of RNA from tumor samples, in particular fixed paraffin-embedded tissue samples and/or reagents for RNA amplification. In addition, the kits may optionally comprise the reagent(s) with an identifying description or label or instructions relating to their use in the methods of the present invention. The kits may comprise containers (including microliter plates suitable for use in an automated implementation of the method), each with one or more of the various materials or reagents (typically in concentrated form) utilized in the methods, including, for example, chromatographic columns, pre-fabricated microarrays, buffers, the appropriate nucleotide triphosphates (e.g., dATP, dCTP, dGTP and dTTP; or rATP, rCTP, rGTP and UTP), reverse transcriptase, DNA polymerase, RNA polymerase, and one or more probes and primers of the present invention (e.g., appropriate length poly(T) or random primers linked to a promoter reactive with the RNA polymerase). Mathematical algorithms used to estimate or quantify prognostic or predictive information are also properly potential components of kits.
    • Reports
  • The methods of this invention, when practiced for commercial diagnostic purposes, generally produce a report or summary of information obtained from the herein-described methods. For example, a report may include information concerning expression levels of one or more genes and/or microRNAs, classification of the tumor or the patient's risk of recurrence, the patient's likely prognosis or risk classification, clinical and pathologic factors, and/or other information. The methods and reports of this invention can further include storing the report in a database. The method can create a record in a database for the subject and populate the record with data. The report may be a paper report, an auditory report, or an electronic record. The report may be displayed and/or stored on a computing device (e.g., handheld device, desktop computer, smart device, website, etc.). It is contemplated that the report is provided to a physician and/or the patient. The receiving of the report can further include establishing a network connection to a server computer that includes the data and report and requesting the data and report from the server computer.
    • Computer Program
  • The values from the assays described above, such as expression data, can be calculated and stored manually. Alternatively, the above-described steps can be completely or partially performed by a computer program product. The present invention thus provides a computer program product including a computer readable storage medium having a computer program stored on it. The program can, when read by a computer, execute relevant calculations based on values obtained from analysis of one or more biological sample from an individual (e.g., gene expression levels, normalization, standardization, thresholding, and conversion of values from assays to a score and/or text or graphical depiction of tumor stage and related information). The computer program product has stored therein a computer program for performing the calculation.
  • The present disclosure provides systems for executing the program described above, which system generally includes: a) a central computing environment; b) an input device, operatively connected to the computing environment, to receive patient data, wherein the patient data can include, for example, expression level or other value obtained from an assay using a biological sample from the patient, or microarray data, as described in detail above; c) an output device, connected to the computing environment, to provide information to a user (e.g., medical personnel); and d) an algorithm executed by the central computing environment (e.g., a processor), where the algorithm is executed based on the data received by the input device, and wherein the algorithm calculates an expression score, thresholding, or other functions described herein. The methods provided by the present invention may also be automated in whole or in part.
  • All aspects of the present invention may also be practiced such that a limited number of additional genes and/or microRNAs that are co-expressed or functionally related with the disclosed genes, for example as evidenced by statistically meaningful Pearson and/or Spearman correlation coefficients, are included in a test in addition to and/or in place of disclosed genes.
  • Having described the invention, the same will be more readily understood through reference to the following Examples, which are provided by way of illustration, and are not intended to limit the invention in any way.
    • EXAMPLES Example 1: RNA Yield and Gene Expression Profiles in Prostate Cancer Biopsy Cores
  • Clinical tools based on prostate needle core biopsies are needed to guide treatment planning at diagnosis for men with localized prostate cancer. Limiting tissue in needle core biopsy specimens poses significant challenges to the development of molecular diagnostic tests. This study examined RNA extraction yields and gene expression profiles using an RT-PCR assay to characterize RNA from manually micro-dissected fixed paraffin embedded (FPE) prostate cancer needle biopsy cores. It also investigated the association of RNA yields and gene expression profiles with Gleason score in these specimens.
  • Patients and Samples
  • This study determined the feasibility of gene expression profile analysis in prostate cancer needle core biopsies by evaluating the quantity and quality of RNA extracted from fixed paraffin-embedded (FPE) prostate cancer needle core biopsy specimens. Forty-eight (48) formalin-fixed blocks from prostate needle core biopsy specimens were used for this study. Classification of specimens was based on interpretation of the Gleason score (2005 Int'l Society of Urological Pathology Consensus Conference) and percentage tumor (<33%, 33-66%, >66%) involvement as assessed by pathologists.
  • TABLE 1
    Distribution of cases
    Gleason score ~<33% ~33-66% ~>66%
    Category Tumor Tumor Tumor
    Low (≤6) 5 5 6
    Intermediate (7) 5 5 6
    High (8, 9, 10) 5 5 6
    Total 15 15 18
  • Assay Methods
  • Fourteen (14) serial 5 μm unstained sections from each FPE tissue block were included in the study. The first and last sections for each case were H&E stained and histologically reviewed to confirm the presence of tumor and for tumor enrichment by manual micro-dissection.
  • RNA from enriched tumor samples was extracted using a manual RNA extraction process. RNA was quantitated using the RiboGreen® assay and tested for the presence of genomic DNA contamination. Samples with sufficient RNA yield and free of genomic DNA tested for gene expression levels of a 24-gene panel of reference and cancer-related genes using quantitative RT-PCR. The expression was normalized to the average of 6 reference genes (AAMP, ARF1, ATP5E, CLTC, EEF1A1, and GPX1).
  • Statistical Methods
  • Descriptive statistics and graphical displays were used to summarize standard pathology metrics and gene expression, with stratification for Gleason Score category and percentage tumor involvement category. Ordinal logistic regression was used to evaluate the relationship between gene expression and Gleason Score category.
  • Results
  • The RNA yield per unit surface area ranged from 16 to 2406 ng/mm2. Higher RNA yield was observed in samples with higher percent tumor involvement (p=0.02) and higher Gleason score (p=0.01). RNA yield was sufficient (>200 ng) in 71% of cases to permit 96-well RT-PCR, with 87% of cases having >100 ng RNA yield. The study confirmed that gene expression from prostate biopsies, as measured by qRT-PCR, was comparable to FPET samples used in commercial molecular assays for breast cancer. In addition, it was observed that greater biopsy RNA yields are found with higher Gleason score and higher percent tumor involvement. Nine genes were identified as significantly associated with Gleason score (p<0.05) and there was a large dynamic range observed for many test genes.
    • Example 2: Gene Expression Analysis for Genes Associated with Prognosis in Prostate Cancer
  • Patients and Samples
  • Approximately 2600 patients with clinical stage T1/T2 prostate cancer treated with radical prostatectomy (RP) at the Cleveland Clinic between 1987 and 2004 were identified. Patients were excluded from the study design if they received neo-adjuvant and/or adjuvant therapy, if pre-surgical PSA levels were missing, or if no tumor block was available from initial diagnosis. 127 patients with clinical recurrence and 374 patients without clinical recurrence after radical prostatectomy were randomly selected using a cohort sampling design. The specimens were stratified by T stage (T1, T2), year cohort (<1993, ≥1993), and prostatectomy Gleason score (low/intermediate, high). Of the 501 sampled patients, 51 were excluded for insufficient tumor; 7 were excluded due to clinical ineligibility; 2 were excluded due to poor quality of gene expression data; and 10 were excluded because primary Gleason pattern was unavailable. Thus, this gene expression study included tissue and data from 111 patients with clinical recurrence and 330 patients without clinical recurrence after radical prostatectomies performed between 1987 and 2004 for treatment of early stage (T1, T2) prostate cancer.
  • Two fixed paraffin embedded (FPE) tissue specimens were obtained from prostate tumor specimens in each patient. The sampling method (sampling method A or B) depended on whether the highest Gleason pattern is also the primary Gleason pattern. For each specimen selected, the invasive cancer cells were at least 5.0 mm in dimension, except in the instances of pattern 5, where 2.2 mm was accepted. Specimens were spatially distinct where possible.
  • TABLE 2
    Sampling Methods
    Sampling Method A Sampling Method B
    For patients whose prostatectomy For patients whose prostatectomy
    primary Gleason pattern is also primary Gleason pattern is not
    the highest Gleason pattern the highest Gleason pattern
    Specimen 1 (A1) = Specimen 1 (B1) =
    primary Gleason pattern highest Gleason pattern
    Select and mark largest focus Select highest Gleason pattern
    (greatest cross-sectional area) tissue from spatially distinct area
    of primary Gleason pattern from specimen B2, if
    tissue. Invasive cancer area possible. Invasive cancer area
    ≥5.0 mm. at least 5.0 mm if selecting
    secondary pattern, at least
    2.2 mm if selecting Gleason
    pattern
    5.
    Specimen 2 (A2) = Specimen 2 (B2) =
    secondary Gleason pattern primary Gleason pattern
    Select and mark secondary Select largest focus
    Gleason pattern tissue from (greatest cross-sectional area)
    spatially distinct area from of primary Gleason pattern tissue.
    specimen A1. Invasive cancer Invasive cancer area ≥5.0 mm.
    area ≥5.0 mm.
  • Histologically normal appearing tissue (NAT) adjacent to the tumor specimen (also referred to in these Examples as “non-tumor tissue”) was also evaluated. Adjacent tissue was collected 3 mm from the tumor to 3 mm from the edge of the FPET block. NAT was preferentially sampled adjacent to the primary Gleason pattern. In cases where there was insufficient NAT adjacent to the primary Gleason pattern, then NAT was sampled adjacent to the secondary or highest Gleason pattern (A2 or B1) per the method set forth in Table 2. Six (6) 10 μm sections with beginning H&E at 5 μm and ending unstained slide at 5 μm were prepared from each fixed paraffin-embedded tumor (FPET) block included in the study. All cases were histologically reviewed and manually micro-dissected to yield two enriched tumor samples and, where possible, one normal tissue sample adjacent to the tumor specimen.
  • Assay Method
  • In this study, RT-PCR analysis was used to determine RNA expression levels for 738 genes and chromosomal rearrangements (e.g., TMPRSS2-ERG fusion or other ETS family genes) in prostate cancer tissue and surrounding NAT in patients with early-stage prostate cancer treated with radical prostatectomy.
  • The samples were quantified using the RiboGreen assay and a subset tested for presence of genomic DNA contamination. Samples were taken into reverse transcription (RT) and quantitative polymerase chain reaction (qPCR). All analyses were conducted on reference-normalized gene expression levels using the average of the of replicate well crossing point (CP) values for the 6 reference genes (AAMP, ARF1, ATP5E, CLTC, GPS1, PGK1).
  • Statistical Analysis and Results
  • Primary statistical analyses involved 111 patients with clinical recurrence and 330 patients without clinical recurrence after radical prostatectomy for early-stage prostate cancer stratified by T-stage (T1, T2), year cohort (<1993, ≥1993), and prostatectomy Gleason score (low/intermediate, high). Gleason score categories are defined as follows: low (Gleason score ≤6), intermediate (Gleason score=7), and high (Gleason score ≥8). A patient was included in a specified analysis if at least one sample for that patient was evaluable. Unless otherwise stated, all hypothesis tests were reported using two-sided p-values. The method of Storey was applied to the resulting set of p-values to control the false discovery rate (FDR) at 20%. J. Storey, R. Tibshirani, Estimating the Positive False Discovery Rate Under Dependence, with Applications to DNA Microarrays, Dept. of Statistics, Stanford Univ. (2001).
  • Analysis of gene expression and recurrence-free interval was based on univariate Cox Proportional Hazards (PH) models using maximum weighted pseudo-partial-likelihood estimators for each evaluable gene in the gene list (727 test genes and 5 reference genes). P-values were generated using Wald tests of the null hypothesis that the hazard ratio (HR) is one. Both unadjusted p-values and the q-value (smallest FDR at which the hypothesis test in question is rejected) were reported. Un-adjusted p-values <0.05 were considered statistically significant. Since two tumor specimens were selected for each patient, this analysis was performed using the 2 specimens from each patient as follows: (1) analysis using the primary Gleason pattern specimen from each patient (Specimens A1 and B2 as described in Table 2); (2) analysis using the highest Gleason pattern specimen from each patient (Specimens A1 and B1 as described in Table 2).
  • Analysis of gene expression and Gleason pattern (3, 4, 5) was based on univariate ordinal logistic regression models using weighted maximum likelihood estimators for each gene in the gene list (727 test genes and 5 reference genes). P-values were generated using a Wald test of the null hypothesis that the odds ratio (OR) is one. Both unadjusted p-values and the q-value (smallest FDR at which the hypothesis test in question is rejected) were reported. Un-adjusted p-values <0.05 were considered statistically significant. Since two tumor specimens were selected for each patient, this analysis was performed using the 2 specimens from each patient as follows: (1) analysis using the primary Gleason pattern specimen from each patient (Specimens A1 and B2 as described in Table 2); (2) analysis using the highest Gleason pattern specimen from each patient (Specimens A1 and B1 as described in Table 2).
  • It was determined whether there is a significant relationship between cRFI and selected demographic, clinical, and pathology variables, including age, race, clinical tumor stage, pathologic tumor stage, location of selected tumor specimens within the prostate (peripheral versus transitional zone), PSA at the time of surgery, overall Gleason score from the radical prostatectomy, year of surgery, and specimen Gleason pattern. Separately for each demographic or clinical variable, the relationship between the clinical covariate and cRFI was modeled using univariate Cox PH regression using weighted pseudo partial-likelihood estimators and a p-value was generated using Wald's test of the null hypothesis that the hazard ratio (HR) is one. Covariates with unadjusted p-values <0.2 may have been included in the covariate-adjusted analyses.
  • It was determined whether there was a significant relationship between each of the individual cancer-related genes and cRFI after controlling for important demographic and clinical covariates. Separately for each gene, the relationship between gene expression and cRFI was modeled using multivariate Cox PH regression using weighted pseudo partial-likelihood estimators including important demographic and clinical variables as covariates. The independent contribution of gene expression to the prediction of cRFI was tested by generating a p-value from a Wald test using a model that included clinical covariates for each nodule (specimens as defined in Table 2). Un-adjusted p-values <0.05 were considered statistically significant.
  • Tables 3A and 3B provide genes significantly associated (p<0.05), positively or negatively, with Gleason pattern in the primary and/or highest Gleason pattern. Increased expression of genes in Table 3A is positively associated with higher Gleason score, while increased expression of genes in Table 3B are negatively associated with higher Gleason score.
  • TABLE 3A
    Gene significantly (p < 0.05) associated with Gleason pattern for
    all specimens in the primary Gleason pattern or highest Gleason
    pattern odds ratio (OR) >1.0 (Increased expression
    is positively associated with higher Gleason Score)
    Primary Pattern Highest Pattern
    Official Symbol OR p-value OR p-value
    ALCAM 1.73 <.001 1.36 0.009
    ANLN 1.35 0.027
    APOC1 1.47 0.005 1.61 <.001
    APOE 1.87 <.001 2.15 <.001
    ASAP2 1.53 0.005
    ASPN 2.62 <.001 2.13 <.001
    ATP5E 1.35 0.035
    AURKA 1.44 0.010
    AURKB 1.59 <.001 1.56 <.001
    BAX 1.43 0.006
    BGN 2.58 <.001 2.82 <.001
    BIRC5 1.45 0.003 1.79 <.001
    BMP6 2.37 <.001 1.68 <.001
    BMPR1B 1.58 0.002
    BRCA2 1.45 0.013
    BUB1 1.73 <.001 1.57 <.001
    CACNA1D 1.31 0.045 1.31 0.033
    CADPS 1.30 0.023
    CCNB1 1.43 0.023
    CCNE2 1.52 0.003 1.32 0.035
    CD276 2.20 <.001 1.83 <.001
    CD68 1.36 0.022
    CDC20 1.69 <.001 1.95 <.001
    CDC6 1.38 0.024 1.46 <.001
    CDH11 1.30 0.029
    CDKN2B 1.55 0.001 1.33 0.023
    CDKN2C 1.62 <.001 1.52 <.001
    CDKN3 1.39 0.010 1.50 0.002
    CENPF 1.96 <.001 1.71 <.001
    CHRAC1 1.34 0.022
    CLDN3 1.37 0.029
    COL1A1 2.23 <.001 2.22 <.001
    COL1A2 1.42 0.005
    COL3A1 1.90 <.001 2.13 <.001
    COL8A1 1.88 <.001 2.35 <.001
    CRISP3 1.33 0.040 1.26 0.050
    CTHRC1 2.01 <.001 1.61 <.001
    CTNND2 1.48 0.007 1.37 0.011
    DAPK1 1.44 0.014
    DIAPH1 1.34 0.032 1.79 <.001
    DIO2 1.56 0.001
    DLL4 1.38 0.026 1.53 <.001
    ECE1 1.54 0.012 1.40 0.012
    ENY2 1.35 0.046 1.35 0.012
    EZH2 1.39 0.040
    F2R 2.37 <.001 2.60 <.001
    FAM49B 1.57 0.002 1.33 0.025
    FAP 2.36 <.001 1.89 <.001
    FCGR3A 2.10 <.001 1.83 <.001
    GNPTAB 1.78 <.001 1.54 <.001
    GSK3B 1.39 0.018
    HRAS 1.62 0.003
    HSD17B4 2.91 <.001 1.57 <.001
    HSPA8 1.48 0.012 1.34 0.023
    IFI30 1.64 <.001 1.45 0.013
    IGFBP3 1.29 0.037
    IL11 1.52 0.001 1.31 0.036
    INHBA 2.55 <.001 2.30 <.001
    ITGA4 1.35 0.028
    JAG1 1.68 <.001 1.40 0.005
    KCNN2 1.50 0.004
    KCTD12 1.38 0.012
    KHDRBS3 1.85 <.001 1.72 <.001
    KIF4A 1.50 0.010 1.50 <.001
    KLK14 1.49 0.001 1.35 <.001
    KPNA2 1.68 0.004 1.65 0.001
    KRT2 1.33 0.022
    KRT75 1.27 0.028
    LAMC1 1.44 0.029
    LAPTM5 1.36 0.025 1.31 0.042
    LTBP2 1.42 0.023 1.66 <.001
    MANF 1.34 0.019
    MAOA 1.55 0.003 1.50 <.001
    MAP3K5 1.55 0.006 1.44 0.001
    MDK 1.47 0.013 1.29 0.041
    MDM2 1.31 0.026
    MELK 1.64 <.001 1.64 <.001
    MMP11 2.33 <.001 1.66 <.001
    MYBL2 1.41 0.007 1.54 <.001
    MYO6 1.32 0.017
    NETO2 1.36 0.018
    NOX4 1.84 <.001 1.73 <.001
    NPM1 1.68 0.001
    NRIP3 1.36 0.009
    NRP1 1.80 0.001 1.36 0.019
    OSM 1.33 0.046
    PATE1 1.38 0.032
    PECAM1 1.38 0.021 1.31 0.035
    PGD 1.56 0.010
    PLK1 1.51 0.004 1.49 0.002
    PLOD2 1.29 0.027
    POSTN 1.70 0.047 1.55 0.006
    PPP3CA 1.38 0.037 1.37 0.006
    PTK6 1.45 0.007 1.53 <.001
    PTTG1 1.51 <.001
    RAB31 1.31 0.030
    RAD21 2.05 <.001 1.38 0.020
    RAD51 1.46 0.002 1.26 0.035
    RAF1 1.46 0.017
    RALBP1 1.37 0.043
    RHOC 1.33 0.021
    ROBO2 1.52 0.003 1.41 0.006
    RRM2 1.77 <.001 1.50 <.001
    SAT1 1.67 0.002 1.61 <.001
    SDC1 1.66 0.001 1.46 0.014
    SEC14L1 1.53 0.003 1.62 <.001
    SESN3 1.76 <.001 1.45 <.001
    SFRP4 2.69 <.001 2.03 <.001
    SHMT2 1.69 0.007 1.45 0.003
    SKIL 1.46 0.005
    SOX4 1.42 0.016 1.27 0.031
    SPARC 1.40 0.024 1.55 <.001
    SPINK1 1.29 0.002
    SPP1 1.51 0.002 1.80 <.001
    TFDP1 1.48 0.014
    THBS2 1.87 <.001 1.65 <.001
    THY1 1.58 0.003 1.64 <.001
    TK1 1.79 <.001 1.42 0.001
    TOP2A 2.30 <.001 2.01 <.001
    TPD52 1.95 <.001 1.30 0.037
    TPX2 2.12 <.001 1.86 <.001
    TYMP 1.36 0.020
    TYMS 1.39 0.012 1.31 0.036
    UBE2C 1.66 <.001 1.65 <.001
    UBE2T 1.59 <.001 1.33 0.017
    UGDH 1.28 0.049
    UGT2B15 1.46 0.001 1.25 0.045
    UHRF1 1.95 <.001 1.62 <.001
    VDR 1.43 0.010 1.39 0.018
    WNT5A 1.54 0.001 1.44 0.013
  • TABLE 3B
    Gene significantly (p < 0.05) associated with Gleason pattern for all
    specimens in the primary Gleason pattern or highest Gleason pattern
    odds ratio (OR) < 1.0 (Increased expression is negatively associated
    with higher Gleason score)
    Table 3B Primary Pattern Highest Pattern
    Official Symbol OR p-value OR p-value
    ABCA5 0.78 0.041
    ABCG2 0.65 0.001 0.72 0.012
    ACOX2 0.44 <.001 0.53 <.001
    ADH5 0.45 <.001 0.42 <.001
    AFAP1 0.79 0.038
    AIG1 0.77 0.024
    AKAP1 0.63 0.002
    AKR1C1 0.66 0.003 0.63 <.001
    AKT3 0.68 0.006 0.77 0.010
    ALDH1A2 0.28 <.001 0.33 <.001
    ALKBH3 0.77 0.040 0.77 0.029
    AMPD3 0.67 0.007
    ANPEP 0.68 0.008 0.59 <.001
    ANXA2 0.72 0.018
    APC 0.69 0.002
    AXIN2 0.46 <.001 0.54 <.001
    AZGP1 0.52 <.001 0.53 <.001
    BIK 0.69 0.006 0.73 0.003
    BIN1 0.43 <.001 0.61 <.001
    BTG3 0.79 0.030
    BTRC 0.48 <.001 0.62 <.001
    C7 0.37 <.001 0.55 <.001
    CADM1 0.56 <.001 0.69 0.001
    CAV1 0.58 0.002 0.70 0.009
    CAV2 0.65 0.029
    CCNH 0.67 0.006 0.77 0.048
    CD164 0.59 0.003 0.57 <.001
    CDC25B 0.77 0.035
    CDH1 0.66 <.001
    CDK2 0.71 0.003
    CDKN1C 0.58 <.001 0.57 <.001
    CDS2 0.69 0.002
    CHN1 0.66 0.002
    COL6A1 0.44 <.001 0.66 <.001
    COL6A3 0.66 0.006
    CSRP1 0.42 0.006
    CTGF 0.74 0.043
    CTNNA1 0.70 <.001 0.83 0.018
    CTNNB1 0.70 0.019
    CTNND1 0.75 0.028
    CUL1 0.74 0.011
    CXCL12 0.54 <.001 0.74 0.006
    CYP3A5 0.52 <.001 0.66 0.003
    CYR61 0.64 0.004 0.68 0.005
    DDR2 0.57 0.002 0.73 0.004
    DES 0.34 <.001 0.58 <.001
    DLGAP1 0.54 <.001 0.62 <.001
    DNM3 0.67 0.004
    DPP4 0.41 <.001 0.53 <.001
    DPT 0.28 <.001 0.48 <.001
    DUSP1 0.59 <.001 0.63 <.001
    EDNRA 0.64 0.004 0.74 0.008
    EGF 0.71 0.012
    EGR1 0.59 <.001 0.67 0.009
    EGR3 0.72 0.026 0.71 0.025
    EIF5 0.76 0.025
    ELK4 0.58 0.001 0.70 0.008
    ENPP2 0.66 0.002 0.70 0.005
    EPHA3 0.65 0.006
    EPHB2 0.60 <.001 0.78 0.023
    EPHB4 0.75 0.046 0.73 0.006
    ERBB3 0.76 0.040 0.75 0.013
    ERBB4 0.74 0.023
    ERCC1 0.63 <.001 0.77 0.016
    FAAH 0.67 0.003 0.71 0.010
    FAM107A 0.35 <.001 0.59 <.001
    FAM13C 0.37 <.001 0.48 <.001
    FAS 0.73 0.019 0.72 0.008
    FGF10 0.53 <.001 0.58 <.001
    FGF7 0.52 <.001 0.59 <.001
    FGFR2 0.60 <.001 0.59 <.001
    FKBP5 0.70 0.039 0.68 0.003
    FLNA 0.39 <.001 0.56 <.001
    FLNC 0.33 <.001 0.52 <.001
    FOS 0.58 <.001 0.66 0.005
    FOXO1 0.57 <.001 0.67 <.001
    FOXQ1 0.74 0.023
    GADD45B 0.62 0.002 0.71 0.010
    GHR 0.62 0.002 0.72 0.009
    GNRH1 0.74 0.049 0.75 0.026
    GPM6B 0.48 <.001 0.68 <.001
    GPS1 0.68 0.003
    GSN 0.46 <.001 0.77 0.027
    GSTM1 0.44 <.001 0.62 <.001
    GSTM2 0.29 <.001 0.49 <.001
    HGD 0.77 0.020
    HIRIP3 0.75 0.034
    HK1 0.48 <.001 0.66 0.001
    HLF 0.42 <.001 0.55 <.001
    HNF1B 0.67 0.006 0.74 0.010
    HPS1 0.66 0.001 0.65 <.001
    HSP90AB1 0.75 0.042
    HSPA5 0.70 0.011
    HSPB2 0.52 <.001 0.70 0.004
    IGF1 0.35 <.001 0.59 <.001
    IGF2 0.48 <.001 0.70 0.005
    IGFBP2 0.61 <.001 0.77 0.044
    IGFBP5 0.63 <.001
    IGFBP6 0.45 <.001 0.64 <.001
    IL6ST 0.55 0.004 0.63 <.001
    ILK 0.40 <.001 0.57 <.001
    ING5 0.56 <.001 0.78 0.033
    ITGA1 0.56 0.004 0.61 <.001
    ITGA3 0.78 0.035
    ITGA5 0.71 0.019 0.75 0.017
    ITGA7 0.37 <.001 0.52 <.001
    ITGB3 0.63 0.003 0.70 0.005
    ITPR1 0.46 <.001 0.64 <.001
    ITPR3 0.70 0.013
    ITSN1 0.62 0.001
    JUN 0.48 <.001 0.60 <.001
    JUNB 0.72 0.025
    KIT 0.51 <.001 0.68 0.007
    KLC1 0.58 <.001
    KLK1 0.69 0.028 0.66 0.003
    KLK2 0.60 <.001
    KLK3 0.63 <.001 0.69 0.012
    KRT15 0.56 <.001 0.60 <.001
    KRT18 0.74 0.034
    KRT5 0.64 <.001 0.62 <.001
    LAMA4 0.47 <.001 0.73 0.010
    LAMB3 0.73 0.018 0.69 0.003
    LGALS3 0.59 0.003 0.54 <.001
    LIG3 0.75 0.044
    MAP3K7 0.66 0.003 0.79 0.031
    MCM3 0.73 0.013 0.80 0.034
    MGMT 0.61 0.001 0.71 0.007
    MGST1 0.75 0.017
    MLXIP 0.70 0.013
    MMP2 0.57 <.001 0.72 0.010
    MMP7 0.69 0.009
    MPPED2 0.70 0.009 0.59 <.001
    MSH6 0.78 0.046
    MTA1 0.69 0.007
    MTSS1 0.55 <.001 0.54 <.001
    MYBPC1 0.45 <.001 0.45 <.001
    NCAM1 0.51 <.001 0.65 <.001
    NCAPD3 0.42 <.001 0.53 <.001
    NCOR2 0.68 0.002
    NDUFS5 0.66 0.001 0.70 0.013
    NEXN 0.48 <.001 0.62 <.001
    NFAT5 0.55 <.001 0.67 0.001
    NFKBIA 0.79 0.048
    NRG1 0.58 0.001 0.62 0.001
    OLFML3 0.42 <.001 0.58 <.001
    OMD 0.67 0.004 0.71 0.004
    OR51E2 0.65 <.001 0.76 0.007
    PAGE4 0.27 <.001 0.46 <.001
    PCA3 0.68 0.004
    PCDHGB7 0.70 0.025 0.65 <.001
    PGF 0.62 0.001
    PGR 0.63 0.028
    PHTF2 0.69 0.033
    PLP2 0.54 <.001 0.71 0.003
    PPAP2B 0.41 <.001 0.54 <.001
    PPP1R12A 0.48 <.001 0.60 <.001
    PRIMA1 0.62 0.003 0.65 <.001
    PRKAR1B 0.70 0.009
    PRKAR2B 0.79 0.038
    PRKCA 0.37 <.001 0.55 <.001
    PRKCB 0.47 <.001 0.56 <.001
    PTCH1 0.70 0.021
    PTEN 0.66 0.010 0.64 <.001
    PTGER3 0.76 0.015
    PTGS2 0.70 0.013 0.68 0.005
    PTH1R 0.48 <.001
    PTK2B 0.67 0.014 0.69 0.002
    PYCARD 0.72 0.023
    RAB27A 0.76 0.017
    RAGE 0.77 0.040 0.57 <.001
    RARB 0.66 0.002 0.69 0.002
    RECK 0.65 <.001
    RHOA 0.73 0.043
    RHOB 0.61 0.005 0.62 <.001
    RND3 0.63 0.006 0.66 <.001
    SDHC 0.69 0.002
    SEC23A 0.61 <.001 0.74 0.010
    SEMA3A 0.49 <.001 0.55 <.001
    SERPINA3 0.70 0.034 0.75 0.020
    SH3RF2 0.33 <.001 0.42 <.001
    SLC22A3 0.23 <.001 0.37 <.001
    SMAD4 0.33 <.001 0.39 <.001
    SMARCC2 0.62 0.003 0.74 0.008
    SMO 0.53 <.001 0.73 0.009
    SORBS1 0.40 <.001 0.55 <.001
    SPARCL1 0.42 <.001 0.63 <.001
    SRD5A2 0.28 <.001 0.37 <.001
    STS 0.52 <.001 0.63 <.001
    STAT5A 0.60 <.001 0.75 0.020
    STAT5B 0.54 <.001 0.65 <.001
    STS 0.78 0.035
    SUMO1 0.75 0.017 0.71 0.002
    SVIL 0.45 <.001 0.62 <.001
    TARP 0.72 0.017
    TGFB1I1 0.37 <.001 0.53 <.001
    TGFB2 0.61 0.025 0.59 <.001
    TGFB3 0.46 <.001 0.60 <.001
    TIMP2 0.62 0.001
    TIMP3 0.55 <.001 0.76 0.019
    TMPRSS2 0.71 0.014
    TNF 0.65 0.010
    TNFRSF10A 0.71 0.014 0.74 0.010
    TNFRSF10B 0.74 0.030 0.73 0.016
    TNFSF10 0.69 0.004
    TP53 0.73 0.011
    TP63 0.62 <.001 0.68 0.003
    TPM1 0.43 <.001 0.47 <.001
    TPM2 0.30 <.001 0.47 <.001
    TPP2 0.58 <.001 0.69 0.001
    TRA2A 0.71 0.006
    TRAF3IP2 0.50 <.001 0.63 <.001
    TRO 0.40 <.001 0.59 <.001
    TRPC6 0.73 0.030
    TRPV6 0.80 0.047
    VCL 0.44 <.001 0.55 <.001
    VEGFB 0.73 0.029
    VIM 0.72 0.013
    VTI1B 0.78 0.046
    WDR19 0.65 <.001
    WFDC1 0.50 <.001 0.72 0.010
    YY1 0.75 0.045
    ZFHX3 0.52 <.001 0.54 <.001
    ZFP36 0.65 0.004 0.69 0.012
    ZNF827 0.59 <.001 0.69 0.004
  • To identify genes associated with recurrence (cRFI, bRFI) in the primary and the highest Gleason pattern, each of 727 genes were analyzed in univariate models using specimens A1 and B2 (see Table 2, above). Tables 4A and 4B provide genes that were associated, positively or negatively, with cRFI and/or bRFI in the primary and/or highest Gleason pattern. Increased expression of genes in Table 4A is negatively associated with good prognosis, while increased expression of genes in Table 4B is positively associated with good prognosis.
  • TABLE 4A
    Genes significantly (p < 0.05) associated with cRFI or bRFI in the primary
    Gleason pattern or highest Gleason pattern with hazard ratio (HR) > 1.0
    (increased expression is negatively associated with good prognosis)
    cRFI cRFI bRFI bRFI
    Official Primary Pattern Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value HR p-value
    AKR1C3 1.304 0.022 1.312 0.013
    ANLN 1.379 0.002 1.579 <.001 1.465 <.001 1.623 <.001
    AQP2 1.184 0.027 1.276 <.001
    ASAP2 1.442 0.006
    ASPN 2.272 <.001 2.106 <.001 1.861 <.001 1.895 <.001
    ATP5E 1.414 0.013 1.538 <.001
    BAG5 1.263 0.044
    BAX 1.332 0.026 1.327 0.012 1.438 0.002
    BGN 1.947 <.001 2.061 <.001 1.339 0.017
    BIRC5 1.497 <.001 1.567 <.001 1.478 <.001 1.575 <.001
    BMP6 1.705 <.001 2.016 <.001 1.418 0.004 1.541 <.001
    BMPR1B 1.401 0.013 1.325 0.016
    BRCA2 1.259 0.007
    BUB1 1.411 <.001 1.435 <.001 1.352 <.001 1.242 0.002
    CADPS 1.387 0.009 1.294 0.027
    CCNB1 1.296 0.016 1.376 0.002
    CCNE2 1.468 <.001 1.649 <.001 1.729 <.001 1.563 <.001
    CD276 1.678 <.001 1.832 <.001 1.581 <.001 1.385 0.002
    CDC20 1.547 <.001 1.671 <.001 1.446 <.001 1.540 <.001
    CDC6 1.400 0.003 1.290 0.030 1.403 0.002 1.276 0.019
    CDH7 1.403 0.003 1.413 0.002
    CDKN2B 1.569 <.001 1.752 <.001 1.333 0.017 1.347 0.006
    CDKN2C 1.612 <.001 1.780 <.001 1.323 0.005 1.335 0.004
    CDKN3 1.384 <.001 1.255 0.024 1.285 0.003 1.216 0.028
    CENPF 1.578 <.001 1.692 <.001 1.740 <.001 1.705 <.001
    CKS2 1.390 0.007 1.418 0.005 1.291 0.018
    CLTC 1.368 0.045
    COL1A1 1.873 <.001 2.103 <.001 1.491 <.001 1.472 <.001
    COL1A2 1.462 0.001
    COL3A1 1.827 <.001 2.005 <.001 1.302 0.012 1.298 0.018
    COL4A1 1.490 0.002 1.613 <.001
    COL8A1 1.692 <.001 1.926 <.001 1.307 0.013 1.317 0.010
    CRISP3 1.425 0.001 1.467 <.001 1.242 0.045
    CTHRC1 1.505 0.002 2.025 <.001 1.425 0.003 1.369 0.005
    CTNND2 1.412 0.003
    CXCR4 1.312 0.023 1.355 0.008
    DDIT4 1.543 <.001 1.763 <.001
    DYNLL1 1.290 0.039 1.201 0.004
    EIF3H 1.428 0.012
    ENY2 1.361 0.014 1.392 0.008 1.371 0.001
    EZH2 1.311 0.010
    F2R 1.773 <.001 1.695 <.001 1.495 <.001 1.277 0.018
    FADD 1.292 0.018
    FAM171B 1.285 0.036
    FAP 1.455 0.004 1.560 0.001 1.298 0.022 1.274 0.038
    FASN 1.263 0.035
    FCGR3A 1.654 <.001 1.253 0.033 1.350 0.007
    FGF5 1.219 0.030
    GNPTAB 1.388 0.007 1.503 0.003 1.355 0.005 1.434 0.002
    GPR68 1.361 0.008
    GREM1 1.470 0.003 1.716 <.001 1.421 0.003 1.316 0.017
    HDAC1 1.290 0.025
    HDAC9 1.395 0.012
    HRAS 1.424 0.006 1.447 0.020
    HSD17B4 1.342 0.019 1.282 0.026 1.569 <.001 1.390 0.002
    HSPA8 1.290 0.034
    IGFBP3 1.333 0.022 1.442 0.003 1.253 0.040 1.323 0.005
    INHBA 2.368 <.001 2.765 <.001 1.466 0.002 1.671 <.001
    JAG1 1.359 0.006 1.367 0.005 1.259 0.024
    KCNN2 1.361 0.011 1.413 0.005 1.312 0.017 1.281 0.030
    KHDRBS3 1.387 0.006 1.601 <.001 1.573 <.001 1.353 0.006
    KIAA0196 1.249 0.037
    KIF4A 1.212 0.016 1.149 0.040 1.278 0.003
    KLK14 1.167 0.023 1.180 0.007
    KPNA2 1.425 0.009 1.353 0.005 1.305 0.019
    KRT75 1.164 0.028
    LAMA3 1.327 0.011
    LAMB1 1.347 0.019
    LAMC1 1.555 0.001 1.310 0.030 1.349 0.014
    LIMS1 1.275 0.022
    LOX 1.358 0.003 1.410 <.001
    LTBP2 1.396 0.009 1.656 <.001 1.278 0.022
    LUM 1.315 0.021
    MANF 1.660 <.001 1.323 0.011
    MCM2 1.345 0.011 1.387 0.014
    MCM6 1.307 0.023 1.352 0.008 1.244 0.039
    MELK 1.293 0.014 1.401 <.001 1.501 <.001 1.256 0.012
    MMP11 1.680 <.001 1.474 <.001 1.489 <.001 1.257 0.030
    MRPL13 1.260 0.025
    MSH2 1.295 0.027
    MYBL2 1.664 <.001 1.670 <.001 1.399 <.001 1.431 <.001
    MYO6 1.301 0.033
    NETO2 1.412 0.004 1.302 0.027 1.298 0.009
    NFKB1 1.236 0.050
    NOX4 1.492 <.001 1.507 0.001 1.555 <.001 1.262 0.019
    NPM1 1.287 0.036
    NRIP3 1.219 0.031 1.218 0.018
    NRP1 1.482 0.002 1.245 0.041
    OLFML2B 1.362 0.015
    OR51E1 1.531 <.001 1.488 0.003
    PAK6 1.269 0.033
    PATE1 1.308 <.001 1.332 <.001 1.164 0.044
    PCNA 1.278 0.020
    PEX10 1.436 0.005 1.393 0.009
    PGD 1.298 0.048 1.579 <.001
    PGK1 1.274 0.023 1.262 0.009
    PLA2G7 1.315 0.011 1.346 0.005
    PLAU 1.319 0.010
    PLK1 1.309 0.021 1.563 <.001 1.410 0.002 1.372 0.003
    PLOD2 1.284 0.019 1.272 0.014 1.332 0.005
    POSTN 1.599 <.001 1.514 0.002 1.391 0.005
    PPP3CA 1.402 0.007 1.316 0.018
    PSMD13 1.278 0.040 1.297 0.033 1.279 0.017 1.373 0.004
    PTK6 1.640 <.001 1.932 <.001 1.369 0.001 1.406 <.001
    PTTG1 1.409 <.001 1.510 <.001 1.347 0.001 1.558 <.001
    RAD21 1.315 0.035 1.402 0.004 1.589 <.001 1.439 <.001
    RAF1 1.503 0.002
    RALA 1.521 0.004 1.403 0.007 1.563 <.001 1.229 0.040
    RALBP1 1.277 0.033
    RGS7 1.154 0.015 1.266 0.010
    RRM1 1.570 0.001 1.602 <.001
    RRM2 1.368 <.001 1.289 0.004 1.396 <.001 1.230 0.015
    SAT1 1.482 0.016 1.403 0.030
    SDC1 1.340 0.018 1.396 0.018
    SEC14L1 1.260 0.048 1.360 0.002
    SESN3 1.485 <.001 1.631 <.001 1.232 0.047 1.292 0.014
    SFRP4 1.800 <.001 1.814 <.001 1.496 <.001 1.289 0.027
    SHMT2 1.807 <.001 1.658 <.001 1.673 <.001 1.548 <.001
    SKIL 1.327 0.008
    SLC25A21 1.398 0.001 1.285 0.018
    SOX4 1.286 0.020 1.280 0.030
    SPARC 1.539 <.001 1.842 <.001 1.269 0.026
    SPP1 1.322 0.022
    SQLE 1.359 0.020 1.270 0.036
    STMN1 1.402 0.007 1.446 0.005 1.279 0.031
    SULF1 1.587 <.001
    TAF2 1.273 0.027
    TFDP1 1.328 0.021 1.400 0.005 1.416 0.001
    THBS2 1.812 <.001 1.960 <.001 1.320 0.012 1.256 0.038
    THY1 1.362 0.020 1.662 <.001
    TK1 1.251 0.011 1.377 <.001 1.401 <.001
    TOP2A 1.670 <.001 1.920 <.001 1.869 <.001 1.927 <.001
    TPD52 1.324 0.011 1.366 0.002 1.351 0.005
    TPX2 1.884 <.001 2.154 <.001 1.874 <.001 1.794 <.001
    UAP1 1.244 0.044
    UBE2C 1.403 <.001 1.541 <.001 1.306 0.002 1.323 <.001
    UBE2T 1.667 <.001 1.282 0.023 1.502 <.001 1.298 0.005
    UGT2B15 1.295 0.001 1.275 0.002
    UGT2B17 1.294 0.025
    UHRF1 1.454 <.001 1.531 <.001 1.257 0.029
    VCPIP1 1.390 0.009 1.414 0.004 1.294 0.021 1.283 0.021
    WNT5A 1.274 0.038 1.298 0.020
    XIAP 1.464 0.006
    ZMYND8 1.277 0.048
    ZWINT 1.259 0.047
  • TABLE 4B
    Genes significantly (p < 0.05) associated with cRFI or bRFI in the primary
    Gleason pattern or highest Gleason pattern with hazard ratio (HR) < 1.0
    (increased expression is positively associated with good prognosis)
    cRFI cRFI bRFI bRFI
    Official Primary Pattern Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value HR p-value
    AAMP 0.564 <.001 0.571 .001 0.764 0.037 0.786 0.034
    ABCA5 0.755 <.001 0.695 <.001 0.800 0.006
    ABCB1 0.777 0.026
    ABCG2 0.788 0.033 0.784 0.040 0.803 0.018 0.750 0.004
    ABHD2 0.734 0.011
    ACE 0.782 0.048
    ACOX2 0.639 <.001 0.631 <.001 0.713 <.001 0.716 0.002
    ADH5 0.625 <.001 0.637 <.001 0.753 0.026
    AKAP1 0.764 0.006 0.800 0.005 0.837 0.046
    AKR1C1 0.773 0.033 0.802 0.032
    AKT1 0.714 0.005
    AKT3 0.811 0.015 0.809 0.021
    ALDH1A2 0.606 <.001 0.498 <.001 0.613 <.001 0.624 <.001
    AMPD3 0.793 0.024
    ANPEP 0.584 <.001 0.493 <.001
    ANXA2 0.753 0.013 0.781 0.036 0.762 0.008 0.795 0.032
    APRT 0.758 0.026 0.780 0.044 0.746 0.008
    ATXN1 0.673 0.001 0.776 0.029 0.809 0.031 0.812 0.043
    AXIN2 0.674 <.001 0.571 <.001 0.776 0.005 0.757 0.005
    AZGP1 0.585 <.001 0.652 <.001 0.664 <.001 0.746 <.001
    BAD 0.765 0.023
    BCL2 0.788 0.033 0.778 0.036
    BDKRB1 0.728 0.039
    BIK 0.712 0.005
    BIN1 0.607 <.001 0.724 0.002 0.726 <.001 0.834 0.034
    BTG3 0.847 0.034
    BTRC 0.688 0.001 0.713 0.003
    C7 0.589 <.001 0.639 <.001 0.629 <.001 0.691 <.001
    CADM1 0.546 <.001 0.529 <.001 0.743 0.008 0.769 0.015
    CASP1 0.769 0.014 0.799 0.028 0.799 0.010 0.815 0.018
    CAV1 0.736 0.011 0.711 0.005 0.675 <.001 0.743 0.006
    CAV2 0.636 0.010 0.648 0.012 0.685 0.012
    CCL2 0.759 0.029 0.764 0.024
    CCNH 0.689 <.001 0.700 <.001
    CD164 0.664 <.001 0.651 <.001
    CD1A 0.687 0.004
    CD44 0.545 <.001 0.600 <.001 0.788 0.018 0.799 0.023
    CD82 0.771 0.009 0.748 0.004
    CDC25B 0.755 0.006 0.817 0.025
    CDK14 0.845 0.043
    CDK2 0.819 0.032
    CDK3 0.733 0.005 0.772 0.006 0.838 0.017
    CDKN1A 0.766 0.041
    CDKN1C 0.662 <.001 0.712 0.002 0.693 <.001 0.761 0.009
    CHN1 0.788 0.036
    COL6A1 0.608 <.001 0.767 0.013 0.706 <.001 0.775 0.007
    CSF1 0.626 <.001 0.709 0.003
    CSK 0.837 0.029
    C SRP1 0.793 0.024 0.782 0.019
    C TNNB 1 0.898 0.042 0.885 <.001
    CTSB 0.701 0.004 0.713 0.007 0.715 0.002 0.803 0.038
    CTSK 0.815 0.042
    CXCL12 0.652 <.001 0.802 0.044 0.711 0.001
    CYP3A5 0.463 <.001 0.436 <.001 0.727 0.003
    CYR61 0.652 0.002 0.676 0.002
    DAP 0.761 0.026 0.775 0.025 0.802 0.048
    DARC 0.725 0.005 0.792 0.032
    DDR2 0.719 0.001 0.763 0.008
    DES 0.619 <.001 0.737 0.005 0.638 <.001 0.793 0.017
    DHRS9 0.642 0.003
    DHX9 0.888 <.001
    DLC1 0.710 0.007 0.715 0.009
    DLGAP1 0.613 <.001 0.551 <.001 0.779 0.049
    DNIVI3 0.679 <.001 0.812 0.037
    DPP4 0.591 <.001 0.613 <.001 0.761 0.003
    DPT 0.613 <.001 0.576 <.001 0.647 <.001 0.677 <.001
    DUSP1 0.662 0.001 0.665 0.001 0.785 0.024
    DUSP6 0.713 0.005 0.668 0.002
    EDNRA 0.702 0.002 0.779 0.036
    EGF 0.738 0.028
    EGR1 0.569 <.001 0.577 <.001 0.782 0.022
    EGR3 0.601 <.001 0.619 <.001 0.800 0.038
    EIF253 0.756 0.015
    EIF5 0.776 0.023 0.787 0.028
    ELK4 0.628 <.001 0.658 <.001
    EPHA2 0.720 0.011 0.663 0.004
    EPHA3 0.727 0.003 0.772 0.005
    ERBB2 0.786 0.019 0.738 0.003 0.815 0.041
    ERBB3 0.728 0.002 0.711 0.002 0.828 0.043 0.813 0.023
    ERCC1 0.771 0.023 0.725 0.007 0.806 0.049 0.704 0.002
    EREG 0.754 0.016 0.777 0.034
    ESR2 0.731 0.026
    FAAH 0.708 0.004 0.758 0.012 0.784 0.031 0.774 0.007
    FAM107A 0.517 <.001 0.576 <.001 0.642 <.001 0.656 <.001
    FAM13C 0.568 <.001 0.526 <.001 0.739 0.002 0.639 <.001
    FAS 0.755 0.014
    FASLG 0.706 0.021
    FGF10 0.653 <.001 0.685 <.001 0.766 0.022
    FGF17 0.746 0.023 0.781 0.015 0.805 0.028
    FGF7 0.794 0.030 0.820 0.037 0.811 0.040
    FGFR2 0.683 <.001 0.686 <.001 0.674 <.001 0.703 <.001
    FKBP5 0.676 0.001
    FLNA 0.653 <.001 0.741 0.010 0.682 <.001 0.771 0.016
    FLNC 0.751 0.029 0.779 0.047 0.663 <.001 0.725 <.001
    FLT1 0.799 0.044
    FOS 0.566 <.001 0.543 <.001 0.757 0.006
    FOXO1 0.816 0.039 0.798 0.023
    FOXQ1 0.753 0.017 0.757 0.024 0.804 0.018
    FYN 0.779 0.031
    GADD45B 0.590 <.001 0.619 <.001
    GDF15 0.759 0.019 0.794 0.048
    GHR 0.702 0.005 0.630 <.001 0.673 <.001 0.590 <.001
    GNRH1 0.742 0.014
    GPM6B 0.653 <.001 0.633 <.001 0.696 <.001 0.768 0.007
    GSN 0.570 <.001 0.697 0.001 0.697 <.001 0.758 0.005
    GSTM1 0.612 <.001 0.588 <.001 0.718 <.001 0.801 0.020
    GSTM2 0.540 <.001 0.630 <.001 0.602 <.001 0.706 <.001
    HGD 0.796 0.020 0.736 0.002
    HIRIP3 0.753 0.011 0.824 0.050
    HK1 0.684 <.001 0.683 <.001 0.799 0.011 0.804 0.014
    HLA-G 0.726 0.022
    HLF 0.555 <.001 0.582 <.001 0.703 <.001 0.702 <.001
    HNF1B 0.690 <.001 0.585 <.001
    HPS1 0.744 0.003 0.784 0.020 0.836 0.047
    HSD3B2 0.733 0.016
    HSP90AB1 0.801 0.036
    HSPA5 0.776 0.034
    HSPB1 0.813 0.020
    HSPB2 0.762 0.037 0.699 0.002 0.783 0.034
    HSPG2 0.794 0.044
    ICAM1 0.743 0.024 0.768 0.040
    IER3 0.686 0.002 0.663 <.001
    IFIT1 0.649 <.001 0.761 0.026
    IGF1 0.634 <.001 0.537 <.001 0.696 <.001 0.688 <.001
    IGF2 0.732 0.004
    IGFBP2 0.548 <.001 0.620 <.001
    IGFBP5 0.681 <.001
    IGFBP6 0.577 <.001 0.675 <.001
    IL1B 0.712 0.005 0.742 0.009
    IL6 0.763 0.028
    IL6R 0.791 0.039
    IL6ST 0.585 <.001 0.639 <.001 0.730 0.002 0.768 0.006
    IL8 0.624 <.001 0.662 0.001
    ILK 0.712 0.009 0.728 0.012 0.790 0.047 0.790 0.042
    ING5 0.625 <.001 0.658 <.001 0.728 0.002
    ITGA5 0.728 0.006 0.803 0.039
    ITGA6 0.779 0.007 0.775 0.006
    ITGA7 0.584 <.001 0.700 0.001 0.656 <.001 0.786 0.014
    ITGAD 0.657 0.020
    ITGB4 0.718 0.007 0.689 <.001 0.818 0.041
    ITGB5 0.801 0.050
    ITPR1 0.707 0.001
    JUN 0.556 <.001 0.574 <.001 0.754 0.008
    JUNB 0.730 0.017 0.715 0.010
    KIT 0.644 0.004 0.705 0.019 0.605 <.001 0.659 0.001
    KLC1 0.692 0.003 0.774 0.024 0.747 0.008
    KLF6 0.770 0.032 0.776 0.039
    KLK1 0.646 <.001 0.652 0.001 0.784 0.037
    KLK10 0.716 0.006
    KLK2 0.647 <.001 0.628 <.001 0.786 0.009
    KLK3 0.706 <.001 0.748 <.001 0.845 0.018
    KRT1 0.734 0.024
    KRT15 0.627 <.001 0.526 <.001 0.704 <.001 0.782 0.029
    KRT18 0.624 <.001 0.617 <.001 0.738 0.005 0.760 0.005
    KRT5 0.640 <.001 0.550 <.001 0.740 <.001 0.798 0.023
    KRT8 0.716 0.006 0.744 0.008
    L1CAM 0.738 0.021 0.692 0.009 0.761 0.036
    LAG3 0.741 0.013 0.729 0.011
    LAMA4 0.686 0.011 0.592 0.003
    LAMA5 0.786 0.025
    LAMB3 0.661 <.001 0.617 <.001 0.734 <.001
    LGALS3 0.618 <.001 0.702 0.001 0.734 0.001 0.793 0.012
    LIG3 0.705 0.008 0.615 <.001
    LRP1 0.786 0.050 0.795 0.023 0.770 0.009
    MAP3K7 0.789 0.003
    MGMT 0.632 <.001 0.693 <.001
    MICA 0.781 0.014 0.653 <.001 0.833 0.043
    MPPED2 0.655 <.001 0.597 <.001 0.719 <.001 0.759 0.006
    MSH6 0.793 0.015
    MTSS1 0.613 <.001 0.746 0.008
    MVP 0.792 0.028 0.795 0.045 0.819 0.023
    MYBPC1 0.648 <.001 0.496 <.001 0.701 <.001 0.629 <.001
    NCAM1 0.773 0.015
    NCAPD3 0.574 <.001 0.463 <.001 0.679 <.001 0.640 <.001
    NEXN 0.701 0.002 0.791 0.035 0.725 0.002 0.781 0.016
    NFAT5 0.515 <.001 0.586 <.001 0.785 0.017
    NFATC2 0.753 0.023
    NFKB IA 0.778 0.037
    NRG1 0.644 0.004 0.696 0.017 0.698 0.012
    OAZ1 0.777 0.034 0.775 0.022
    OLFML3 0.621 <.001 0.720 0.001 0.600 <.001 0.626 <.001
    OMD 0.706 0.003
    OR51E2 0.820 0.037 0.798 0.027
    PAGE4 0.549 <.001 0.613 <.001 0.542 <.001 0.628 <.001
    PCA3 0.684 <.001 0.635 <.001
    PCDHGB7 0.790 0.045 0.725 0.002 0.664 <.001
    PGF 0.753 0.017
    PGR 0.740 0.021 0.728 0.018
    PIK3CG 0.803 0.024
    PLAUR 0.778 0.035
    PLG 0.728 0.028
    PPAP2B 0.575 <.001 0.629 <.001 0.643 <.001 0.699 <.001
    PPP1R12A 0.647 <.001 0.683 0.002 0.782 0.023 0.784 0.030
    PRIMA1 0.626 <.001 0.658 <.001 0.703 0.002 0.724 0.003
    PRKCA 0.642 <.001 0.799 0.029 0.677 0.001 0.776 0.006
    PRKCB 0.675 0.001 0.648 <.001 0.747 0.006
    PROM1 0.603 0.018 0.659 0.014 0.493 0.008
    PTCH1 0.680 0.001 0.753 0.010 0.789 0.018
    PTEN 0.732 0.002 0.747 0.005 0.744 <.001 0.765 0.002
    PTGS2 0.596 <.001 0.610 <.001
    PTH1R 0.767 0.042 0.775 0.028 0.788 0.047
    PTHLH 0.617 0.002 0.726 0.025 0.668 0.002 0.718 0.007
    PTK2B 0.744 0.003 0.679 <.001 0.766 0.002 0.726 <.001
    PTPN1 0.760 0.020 0.780 0.042
    PYCARD 0.748 0.012
    RAB27A 0.708 0.004
    RAB30 0.755 0.008
    RAGE 0.817 0.048
    RAP1B 0.818 0.050
    RARB 0.757 0.007 0.677 <.001 0.789 0.007 0.746 0.003
    RASSF1 0.816 0.035
    RHOB 0.725 0.009 0.676 0.001 0.793 0.039
    RLN1 0.742 0.033 0.762 0.040
    RND3 0.636 <.001 0.647 <.001
    RNF114 0.749 0.011
    SDC2 0.721 0.004
    SDHC 0.725 0.003 0.727 0.006
    SEMA3A 0.757 0.024 0.721 0.010
    SERPINA3 0.716 0.008 0.660 0.001
    SERPINB5 0.747 0.031 0.616 0.002
    SH3RF2 0.577 <.001 0.458 <.001 0.702 <.001 0.640 <.001
    SLC22A3 0.565 <.001 0.540 <.001 0.747 0.004 0.756 0.007
    SMAD4 0.546 <.001 0.573 <.001 0.636 <.001 0.627 <.001
    SMARCD1 0.718 <.001 0.775 0.017
    SMO 0.793 0.029 0.754 0.021 0.718 0.003
    SOD1 0.757 0.049 0.707 0.006
    SORBS1 0.645 <.001 0.716 0.003 0.693 <.001 0.784 0.025
    SPARCL1 0.821 0.028 0.829 0.014 0.781 0.030
    SPDEF 0.778 <.001
    SPINT1 0.732 0.009 0.842 0.026
    SRC 0.647 <.001 0.632 <.001
    SRD5A1 0.813 0.040
    SRD5A2 0.489 <.001 0.533 <.001 0.544 <.001 0.611 <.001
    STS 0.713 0.002 0.783 0.011 0.725 <.001 0.827 0.025
    STAT3 0.773 0.037 0.759 0.035
    STAT5A 0.695 <.001 0.719 0.002 0.806 0.020 0.783 0.008
    STAT5B 0.633 <.001 0.655 <.001 0.814 0.028
    SUMO1 0.790 0.015
    SVIL 0.659 <.001 0.713 0.002 0.711 0.002 0.779 0.010
    TARP 0.800 0.040
    TBP 0.761 0.010
    TFF3 0.734 0.010 0.659 <.001
    TGFB1I1 0.618 <.001 0.693 0.002 0.637 <.001 0.719 0.004
    TGFB2 0.679 <.001 0.747 0.005 0.805 0.030
    TGFB3 0.791 0.037
    TGFBR2 0.778 0.035
    TIMP3 0.751 0.011
    TMPRSS2 0.745 0.003 0.708 <.001
    TNF 0.670 0.013 0.697 0.015
    TNFRSF10A 0.780 0.018 0.752 0.006 0.817 0.032
    TNFRSF10B 0.576 <.001 0.655 <.001 0.766 0.004 0.778 0.002
    TNFRSF18 0.648 0.016 0.759 0.034
    TNFSF10 0.653 <.001 0.667 0.004
    TP53 0.729 0.003
    TP63 0.759 0.016 0.636 <.001 0.698 <.001 0.712 0.001
    TPM1 0.778 0.048 0.743 0.012 0.783 0.032 0.811 0.046
    TPM2 0.578 <.001 0.634 <.001 0.611 <.001 0.710 0.001
    TPP2 0.775 0.037
    TRAF3IP2 0.722 0.002 0.690 <.001 0.792 0.021 0.823 0.049
    TRO 0.744 0.003 0.725 0.003 0.765 0.002 0.821 0.041
    TUBB2A 0.639 <.001 0.625 <.001
    TYMP 0.786 0.039
    VCL 0.594 <.001 0.657 0.001 0.682 <.001
    VEGFA 0.762 0.024
    VEGFB 0.795 0.037
    VIM 0.739 0.009 0.791 0.021
    WDR19 0.776 0.015
    WFDC1 0.746 <.001
    YY1 0.683 0.001 0.728 0.002
    ZFHX3 0.684 <.001 0.661 <.001 0.801 0.010 0.762 0.001
    ZFP36 0.605 <.001 0.579 <.001 0.815 0.043
    ZNF827 0.624 <.001 0.730 0.007 0.738 0.004
  • Tables 5A and 5B provide genes that were significantly associated (p<0.05), positively or negatively, with recurrence (cRFI, bRFI) after adjusting for AUA risk group in the primary and/or highest Gleason pattern. Increased expression of genes in Table 5A is negatively associated with good prognosis, while increased expression of genes in Table 5B is positively associated with good prognosis.
  • TABLE 5A
    Genes significantly (p < 0.05) associated with cRFI or bRFI after adjustment for AIA
    risk grous in primary Gleason pattern or highest Gleason pattern with hazard
    ratio (HR) > 1.0 (increased expression is positively associated with good prognosis)
    cRFI cRFI bRFI bRFI
    Official Primary Pattern Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value HR p-value
    AKR1C3 1.315 0.018 1.283 0.024
    ALOX12 1.198 0.024
    ANLN 1.406 <.001 1.519 <.001 1.485 <.001 1.632 <.001
    AQP2 1.209 <.001 1.302 <.001
    ASAP2 1.582 <.001 1.333 0.011 1.307 0.019
    ASPN 1.872 <.001 1.741 <.001 1.638 <.001 1.691 <.001
    ATP5E 1.309 0.042 1.369 0.012
    BAG5 1.291 0.044
    BAX 1.298 0.025 1.420 0.004
    BGN 1.746 <.001 1.755 <.001
    BIRC5 1.480 <.001 1.470 <.001 1.419 <.001 1.503 <.001
    BMP6 1.536 <.001 1.815 <.001 1.294 0.033 1.429 0.001
    BRCA2 1.184 0.037
    BUB1 1.288 0.001 1.391 <.001 1.254 <.001 1.189 0.018
    CACNA1D 1.313 0.029
    CADPS 1.358 0.007 1.267 0.022
    CASP3 1.251 0.037
    CCNB1 1.261 0.033 1.318 0.005
    CCNE2 1.345 0.005 1.438 <.001 1.606 <.001 1.426 <.001
    CD276 1.482 0.002 1.668 <.001 1.451 <.001 1.302 0.011
    CDC20 1.417 <.001 1.547 <.001 1.355 <.001 1.446 <.001
    CDC6 1.340 0.011 1.265 0.046 1.367 0.002 1.272 0.025
    CDH7 1.402 0.003 1.409 0.002
    CDKN2B 1.553 <.001 1.746 <.001 1.340 0.014 1.369 0.006
    CDKN2C 1.411 <.001 1.604 <.001 1.220 0.033
    CDKN3 1.296 0.004 1.226 0.015
    CENPF 1.434 0.002 1.570 <.001 1.633 <.001 1.610 <.001
    CKS2 1.419 0.008 1.374 0.022 1.380 0.004
    COL1A1 1.677 <.001 1.809 <.001 1.401 <.001 1.352 0.003
    COL1A2 1.373 0.010
    COL3A1 1.669 <.001 1.781 <.001 1.249 0.024 1.234 0.047
    COL4A1 1.475 0.002 1.513 0.002
    COL8A1 1.506 0.001 1.691 <.001
    CRISP3 1.406 0.004 1.471 <.001
    CTHRC1 1.426 0.009 1.793 <.001 1.311 0.019
    CTNND2 1.462 <.001
    DDIT4 1.478 0.003 1.783 <.001 1.236 0.039
    DYNLL1 1.431 0.002 1.193 0.004
    EIF3H 1.372 0.027
    ENY2 1.325 0.023 1.270 0.017
    ERG 1.303 0.041
    EZH2 1.254 0.049
    F2R 1.540 0.002 1.448 0.006 1.286 0.023
    FADD 1.235 0.041 1.404 <.001
    FAP 1.386 0.015 1.440 0.008 1.253 0.048
    FASN 1.303 0.028
    FCGR3A 1.439 0.011 1.262 0.045
    FGF5 1.289 0.006
    GNPTAB 1.290 0.033 1.369 0.022 1.285 0.018 1.355 0.008
    GPR68 1.396 0.005
    GREM1 1.341 0.022 1.502 0.003 1.366 0.006
    HDAC1 1.329 0.016
    HDAC9 1.378 0.012
    HRAS 1.465 0.006
    HSD17B4 1.442 <.001 1.245 0.028
    IGFBP3 1.366 0.019 1.302 0.011
    INHBA 2.000 <.001 2.336 <.001 1.486 0.002
    JAG1 1.251 0.039
    KCNN2 1.347 0.020 1.524 <.001 1.312 0.023 1.346 0.011
    KHDRBS3 1.500 0.001 1.426 0.001 1.267 0.032
    KIAA0196 1.272 0.028
    KIF4A 1.199 0.022 1.262 0.004
    KPNA2 1.252 0.016
    LAMA3 1.332 0.004 1.356 0.010
    LAMB1 1.317 0.028
    LAMC1 1.516 0.003 1.302 0.040 1.397 0.007
    LIMS1 1.261 0.027
    LOX 1.265 0.016 1.372 0.001
    LTBP2 1.477 0.002
    LUM 1.321 0.020
    MANF 1.647 <.001 1.284 0.027
    MCM2 1.372 0.003 1.302 0.032
    MCM3 1.269 0.047
    MCM6 1.276 0.033 1.245 0.037
    MELK 1.294 0.005 1.394 <.001
    MK167 1.253 0.028 1.246 0.029
    MMP11 1.557 <.001 1.290 0.035 1.357 0.005
    MRPL13 1.275 0.003
    MSH2 1.355 0.009
    MYBL2 1.497 <.001 1.509 <.001 1.304 0.003 1.292 0.007
    MY06 1.367 0.010
    NDRG1 1.270 0.042 1.314 0.025
    NEK2 1.338 0.020 1.269 0.026
    NETO2 1.434 0.004 1.303 0.033 1.283 0.012
    NOX4 1.413 0.006 1.308 0.037 1.444 <.001
    NRIP3 1.171 0.026
    NRP1 1.372 0.020
    ODC1 1.450 <.001
    OR51E1 1.559 <.001 1.413 0.008
    PAK6 1.233 0.047
    PATE1 1.262 <.001 1.375 <.001 1.143 0.034 1.191 0.036
    PCNA 1.227 0.033 1.318 0.003
    PEX10 1.517 <.001 1.500 0.001
    PGD 1.363 0.028 1.316 0.039 1.652 <.001
    PGK1 1.224 0.034 1.206 0.024
    PIM1 1.205 0.042
    PLA2G7 1.298 0.018 1.358 0.005
    PLAU 1.242 0.032
    PLK1 1.464 0.001 1.299 0.018 1.275 0.031
    PLOD2 1.206 0.039 1.261 0.025
    POSTN 1.558 0.001 1.356 0.022 1.363 0.009
    PPP3CA 1.445 0.002
    PSMD13 1.301 0.017 1.411 0.003
    PTK2 1.318 0.031
    PTK6 1.582 <.001 1.894 <.001 1.290 0.011 1.354 0.003
    PTTG1 1.319 0.004 1.430 <.001 1.271 0.006 1.492 <.001
    RAD21 1.278 0.028 1.435 0.004 1.326 0.008
    RAF1 1.504 <.001
    RALA 1.374 0.028 1.459 0.001
    RGS7 1.203 0.031
    RRM1 1.535 0.001 1.525 <.001
    RRM2 1.302 0.003 1.197 0.047 1.342 <.001
    SAT1 1.374 0.043
    SDC1 1.344 0.011 1.473 0.008
    SEC14L1 1.297 0.006
    SESN3 1.337 0.002 1.495 <.001 1.223 0.038
    SFRP4 1.610 <.001 1.542 0.002 1.370 0.009
    SHMT2 1.567 0.001 1.522 <.001 1.485 0.001 1.370 <.001
    SKIL 1.303 0.008
    SLC25A21 1.287 0.020 1.306 0.017
    SLC44A1 1.308 0.045
    SNRPB2 1.304 0.018
    SOX4 1.252 0.031
    SPARC 1.445 0.004 1.706 <.001 1.269 0.026
    SPP1 1.376 0.016
    SQLE 1.417 0.007 1.262 0.035
    STAT1 1.209 0.029
    STMN1 1.315 0.029
    SULF1 1.504 0.001
    TAF2 1.252 0.048 1.301 0.019
    TFDP1 1.395 0.010 1.424 0.002
    THBS2 1.716 <.001 1.719 <.001
    THY1 1.343 0.035 1.575 0.001
    TK1 1.320 <.001 1.304 <.001
    TOP2A 1.464 0.001 1.688 <.001 1.715 <.001 1.761 <.001
    TPD52 1.286 0.006 1.258 0.023
    TPX2 1.644 <.001 1.964 <.001 1.699 <.001 1.754 <.001
    TYMS 1.315 0.014
    UBE2C 1.270 0.019 1.558 <.001 1.205 0.027 1.333 <.001
    UBE2G1 1.302 0.041
    UBE2T 1.451 <.001 1.309 0.003
    UGT2B15 1.222 0.025
    UHRF1 1.370 0.003 1.520 <.001 1.247 0.020
    VCPIP1 1.332 0.015
    VTI1B 1.237 0.036
    XIAP 1.486 0.008
    ZMYND8 1.408 0.007
    ZNF3 1.284 0.018
    ZWINT 1.289 0.028
  • TABLE 5B
    Genes significantly (p < 0.05) associated with cRFI or bRFI after adjustment for AUA
    risk group in the primary Gleason pattern or highest Gleason pattern with hazard
    ratio (HR) < 1.0 (increased expression is positively associated with good prognosis)
    Table 5B cRFI cRFI bRFI bRFI
    Official Primary Pattern Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value HR p-value
    AAMP 0.535 <.001 0.581 <.001 0.700 0.002 0.759 0.006
    ABCA5 0.798 0.007 0.745 0.002 0.841 0.037
    ABCC1 0.800 0.044
    ABCC4 0.787 0.022
    ABHD2 0.768 0.023
    ACOX2 0.678 0.002 0.749 0.027 0.759 0.004
    ADH5 0.645 <.001 0.672 0.001
    AGTR1 0.780 0.030
    AKAP1 0.815 0.045 0.758 <.001
    AKT1 0.732 0.010
    ALDH1A2 0.646 <.001 0.548 <.001 0.671 <.001 0.713 0.001
    ANPEP 0.641 <.001 0.535 <.001
    ANXA2 0.772 0.035 0.804 0.046
    ATXN1 0.654 <.001 0.754 0.020 0.797 0.017
    AURKA 0.788 0.030
    AXIN2 0.744 0.005 0.655 <.001
    AZGP1 0.656 <.001 0.676 <.001 0.754 0.001 0.791 0.004
    BAD 0.700 0.004
    BIN1 0.650 <.001 0.764 0.013 0.803 0.015
    BTG3 0.836 0.025
    BTRC 0.730 0.005
    C7 0.617 <.001 0.680 <.001 0.667 <.001 0.755 0.005
    CADM1 0.559 <.001 0.566 <.001 0.772 0.020 0.802 0.046
    CASP1 0.781 0.030 0.779 0.021 0.818 0.027 0.828 0.036
    CAV1 0.775 0.034
    CAV2 0.677 0.019
    CCL2 0.752 0.023
    CCNH 0.679 <.001 0.682 <.001
    CD164 0.721 0.002 0.724 0.005
    CD1A 0.710 0.014
    CD44 0.591 <.001 0.642 <.001
    CD82 0.779 0.021 0.771 0.024
    CDC25B 0.778 0.035 0.818 0.023
    CDK14 0.788 0.011
    CDK3 0.752 0.012 0.779 0.005 0.841 0.020
    CDKN1A 0.770 0.049 0.712 0.014
    CDKN1C 0.684 <.001 0.697 <.001
    CHN1 0.772 0.031
    COL6A1 0.648 <.001 0.807 0.046 0.768 0.004
    CSF1 0.621 <.001 0.671 0.001
    CTNNB1 0.905 0.008
    CTSB 0.754 0.030 0.716 0.011 0.756 0.014
    CXCL12 0.641 <.001 0.796 0.038 0.708 <.001
    CYP3A5 0.503 <.001 0.528 <.001 0.791 0.028
    CYR61 0.639 0.001 0.659 0.001 0.797 0.048
    DARC 0.707 0.004
    DDR2 0.750 0.011
    DES 0.657 <.001 0.758 0.022 0.699 <.001
    DHRS9 0.625 0.002
    DHX9 0.846 <.001
    DIAPH1 0.682 0.007 0.723 0.008 0.780 0.026
    DLC1 0.703 0.005 0.702 0.008
    DLGAP1 0.703 0.008 0.636 <.001
    DNM3 0.701 0.001 0.817 0.042
    DPP4 0.686 <.001 0.716 0.001
    DPT 0.636 <.001 0.633 <.001 0.709 0.006 0.773 0.024
    DUSP1 0.683 0.006 0.679 0.003
    DUSP6 0.694 0.003 0.605 <.001
    EDN1 0.773 0.031
    EDNRA 0.716 0.007
    EGR1 0.575 <.001 0.575 <.001 0.771 0.014
    EGR3 0.633 0.002 0.643 <.001 0.792 0.025
    EIF4E 0.722 0.002
    ELK4 0.710 0.009 0.759 0.027
    ENPP2 0.786 0.039
    EPHA2 0.593 0.001
    EPHA3 0.739 0.006 0.802 0.020
    ERBB2 0.753 0.007
    ERBB3 0.753 0.009 0.753 0.015
    ERCC1 0.727 0.001
    EREG 0.722 0.012 0.769 0.040
    ESR1 0.742 0.015
    FABP5 0.756 0.032
    FAM107A 0.524 <.001 0.579 <.001 0.688 <.001 0.699 0.001
    FAM13C 0.639 <.001 0.601 <.001 0.810 0.019 0.709 <.001
    FAS 0.770 0.033
    FASLG 0.716 0.028 0.683 0.017
    FGF10 0.798 0.045
    FGF17 0.718 0.018 0.793 0.024 0.790 0.024
    FGFR2 0.739 0.007 0.783 0.038 0.740 0.004
    FGFR4 0.746 0.050
    FKBP5 0.689 0.003
    FLNA 0.701 0.006 0.766 0.029 0.768 0.037
    FLNC 0.755 <.001 0.820 0.022
    FLT1 0.729 0.008
    FOS 0.572 <.001 0.536 <.001 0.750 0.005
    FOXQ1 0.778 0.033 0.820 0.018
    FYN 0.708 0.006
    GADD45B 0.577 <.001 0.589 <.001
    GDF15 0.757 0.013 0.743 0.006
    GHR 0.712 0.004 0.679 0.001
    GNRH1 0.791 0.048
    GPM6B 0.675 <.001 0.660 <.001 0.735 <.001 0.823 0.049
    GSK3B 0.783 0.042
    GSN 0.587 <.001 0.705 0.002 0.745 0.004 0.796 0.021
    GSTM1 0.686 0.001 0.631 <.001 0.807 0.018
    GSTM2 0.607 <.001 0.683 <.001 0.679 <.001 0.800 0.027
    HIRIP3 0.692 <.001 0.782 0.007
    HK1 0.724 0.002 0.718 0.002
    HLF 0.580 <.001 0.571 <.001 0.759 0.008 0.750 0.004
    HNF1B 0.669 <.001
    HPS1 0.764 0.008
    HSD17B10 0.802 0.045
    HSD17B2 0.723 0.048
    HSD3B2 0.709 0.010
    HSP90AB1 0.780 0.034 0.809 0.041
    HSPA5 0.738 0.017
    HSPB1 0.770 0.006 0.801 0.032
    HSPB2 0.788 0.035
    ICAM1 0.728 0.015 0.716 0.010
    IER3 0.735 0.016 0.637 <.001 0.802 0.035
    IFIT1 0.647 <.001 0.755 0.029
    IGF1 0.675 <.001 0.603 <.001 0.762 0.006 0.770 0.030
    IGF2 0.761 0.011
    IGFBP2 0.601 <.001 0.605 <.001
    IGFBP5 0.702 <.001
    IGFBP6 0.628 <.001 0.726 0.003
    IL1B 0.676 0.002 0.716 0.004
    IL6 0.688 0.005 0.766 0.044
    IL6R 0.786 0.036
    IL6ST 0.618 <.001 0.639 <.001 0.785 0.027 0.813 0.042
    IL8 0.635 <.001 0.628 <.001
    ILK 0.734 0.018 0.753 0.026
    ING5 0.684 <.001 0.681 <.001 0.756 0.006
    ITGA4 0.778 0.040
    ITGA5 0.762 0.026
    ITGA6 0.811 0.038
    ITGA7 0.592 <.001 0.715 0.006 0.710 0.002
    ITGAD 0.576 0.006
    ITGB4 0.693 0.003
    ITPR1 0.789 0.029
    JUN 0.572 <.001 0.581 <.001 0.777 0.019
    JUNB 0.732 0.030 0.707 0.016
    KCTD12 0.758 0.036
    KIT 0.691 0.009 0.738 0.028
    KLC1 0.741 0.024 0.781 0.024
    KLF6 0.733 0.018 0.727 0.014
    KLK1 0.744 0.028
    KLK2 0.697 0.002 0.679 <.001
    KLK3 0.725 <.001 0.715 <.001 0.841 0.023
    KRT15 0.660 <.001 0.577 <.001 0.750 0.002
    KRT18 0.623 <.001 0.642 <.001 0.702 <.001 0.760 0.006
    KRT2 0.740 0.044
    KRT5 0.674 <.001 0.588 <.001 0.769 0.005
    KRT8 0.768 0.034
    L1CAM 0.737 0.036
    LAG3 0.711 0.013 0.748 0.029
    LAMA4 0.649 0.009
    LAMB3 0.709 0.002 0.684 0.006 0.768 0.006
    LGALS3 0.652 <.001 0.752 0.015 0.805 0.028
    LIG3 0.728 0.016 0.667 <.001
    LRP1 0.811 0.043
    MDM2 0.788 0.033
    MGMT 0.645 <.001 0.766 0.015
    MICA 0.796 0.043 0.676 <.001
    NIPPED2 0.675 <.001 0.616 <.001 0.750 0.006
    MRC1 0.788 0.028
    MTSS1 0.654 <.001 0.793 0.036
    MYBPC1 0.706 <.001 0.534 <.001 0.773 0.004 0.692 <.001
    NCAPD3 0.658 <.001 0.566 <.001 0.753 0.011 0.733 0.009
    NCOR1 0.838 0.045
    NEXN 0.748 0.025 0.785 0.020
    NFAT5 0.531 <.001 0.626 <.001
    NFATC2 0.759 0.024
    OAZ1 0.766 0.024
    OLFML3 0.648 <.001 0.748 0.005 0.639 <.001 0.675 <.001
    OR51E2 0.823 0.034
    PAGE4 0.599 <.001 0.698 0.002 0.606 <.001 0.726 <.001
    PCA3 0.705 <.001 0.647 <.001
    PCDHGB7 0.712 <.001
    PGF 0.790 0.039
    PLG 0.764 0.048
    PLP2 0.766 0.037
    PPAP2B 0.589 <.001 0.647 <.001 0.691 <.001 0.765 0.013
    PPP1R12A 0.673 0.001 0.677 0.001 0.807 0.045
    PRIMA1 0.622 <.001 0.712 0.008 0.740 0.013
    PRKCA 0.637 <.001 0.694 <.001
    PRKCB 0.741 0.020 0.664 <.001
    PROM1 0.599 0.017 0.527 0.042 0.610 0.006 0.420 0.002
    PTCH1 0.752 0.027 0.762 0.011
    PTEN 0.779 0.011 0.802 0.030 0.788 0.009
    PTGS2 0.639 <.001 0.606 <.001
    PTHLH 0.632 0.007 0.739 0.043 0.654 0.002 0.740 0.015
    PTK2B 0.775 0.019 0.831 0.028 0.810 0.017
    PTPN1 0.721 0.012 0.737 0.024
    PYCARD 0.702 0.005
    RAB27A 0.736 0.008
    RAB30 0.761 0.011
    RARB 0.746 0.010
    RASSF1 0.805 0.043
    RHOB 0.755 0.029 0.672 0.001
    RLN1 0.742 0.036 0.740 0.036
    RND3 0.607 <.001 0.633 <.001
    RNF114 0.782 0.041 0.747 0.013
    SDC2 0.714 0.002
    SDHC 0.698 <.001 0.762 0.029
    SERPINA3 0.752 0.030
    SERPINB5 0.669 0.014
    SH3RF2 0.705 0.012 0.568 <.001 0.755 0.016
    SLC22A3 0.650 <.001 0.582 <.001
    SMAD4 0.636 <.001 0.684 0.002 0.741 0.007 0.738 0.007
    SMARCD1 0.757 0.001
    SMO 0.790 0.049 0.766 0.013
    SOD1 0.741 0.037 0.713 0.007
    SORBS1 0.684 0.003 0.732 0.008 0.788 0.049
    SPDEF 0.840 0.012
    SPINT1 0.837 0.048
    SRC 0.674 <.001 0.671 <.001
    SRD5A2 0.553 <.001 0.588 <.001 0.618 <.001 0.701 <.001
    ST5 0.747 0.012 0.761 0.010 0.780 0.016 0.832 0.041
    STAT3 0.735 0.020
    STAT5A 0.731 0.005 0.743 0.009 0.817 0.027
    STAT5B 0.708 <.001 0.696 0.001
    SUMO1 0.815 0.037
    SVIL 0.689 0.003 0.739 0.008 0.761 0.011
    TBP 0.792 0.037
    TFF3 0.719 0.007 0.664 0.001
    TGFB1I1 0.676 0.003 0.707 0.007 0.709 0.005 0.777 0.035
    TGFB2 0.741 0.010 0.785 0.017
    TGFBR2 0.759 0.022
    TIMP3 0.785 0.037
    TMPRSS2 0.780 0.012 0.742 <.001
    TNF 0.654 0.007 0.682 0.006
    TNFRSF10B 0.623 <.001 0.681 <.001 0.801 0.018 0.815 0.019
    TNFSF10 0.721 0.004
    TP53 0.759 0.011
    TP63 0.737 0.020 0.754 0.007
    TPM2 0.609 <.001 0.671 <.001 0.673 <.001 0.789 0.031
    TRAF3IP2 0.795 0.041 0.727 0.005
    TRO 0.793 0.033 0.768 0.027 0.814 0.023
    TUBB2A 0.626 <.001 0.590 <.001
    VCL 0.613 <.001 0.701 0.011
    VIM 0.716 0.005 0.792 0.025
    WFDC1 0.824 0.029
    YY1 0.668 <.001 0.787 0.014 0.716 0.001 0.819 0.011
    ZFHX3 0.732 <.001 0.709 <.001
    ZFP36 0.656 0.001 0.609 <.001 0.818 0.045
    ZNF827 0.750 0.022
  • Tables 6A and 6B provide genes that were significantly associated (p<0.05), positively or negatively, with recurrence (cRFI, bRFI) after adjusting for Gleason pattern in the primary and/or highest Gleason pattern. Increased expression of genes in Table 6A is negatively associated with good prognosis, while increased expression of gene in Table 6B is positively associated with good prognosis.
  • TABLE 6A
    Genes significantly (p < 0.05) associated with cRFI or bRFI after adjustment for
    Gleason pattern in the primary Gleason pattern or highest Gleason pattern with a hazard
    ratio (HR) >1.0 (increased expression is negatively associated with good prognosis)
    Table 6A cRFI cRFI bRFI bRFI
    Official Primary Pattern Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value HR p-value
    AKR1C3 1.258 0.039
    ANLN 1.292 0.023 1.449 <.001 1.420 0.001
    AQP2 1.178 0.008 1.287 <.001
    ASAP2 1.396 0.015
    ASPN 1.809 <.001 1.508 0.009 1.506 0.002 1.438 0.002
    BAG5 1.367 0.012
    BAX 1.234 0.044
    BGN 1.465 0.009 1.342 0.046
    BIRC5 1.338 0.008 1.364 0.004 1.279 0.006
    BMP6 1.369 0.015 1.518 0.002
    BUB1 1.239 0.024 1.227 0.001 1.236 0.004
    CACNA1D 1.337 0.025
    CADPS 1.280 0.029
    CCNE2 1.256 0.043 1.577 <.001 1.324 0.001
    CD276 1.320 0.029 1.396 0.007 1.279 0.033
    CDC20 1.298 0.016 1.334 0.002 1.257 0.032 1.279 0.003
    CDH7 1.258 0.047 1.338 0.013
    CDKN2B 1.342 0.032 1.488 0.009
    CDKN2C 1.344 0.010 1.450 <.001
    CDKN3 1.284 0.012
    CENPF 1.289 0.048 1.498 0.001 1.344 0.010
    COL1A1 1.481 0.003 1.506 0.002
    COL3A1 1.459 0.004 1.430 0.013
    COL4A1 1.396 0.015
    COL8A1 1.413 0.008
    CRISP3 1.346 0.012 1.310 0.025
    CTHRC1 1.588 0.002
    DDIT4 1.363 0.020 1.379 0.028
    DICER1 1.294 0.008
    ENY2 1.269 0.024
    FADD 1.307 0.010
    FAS 1.243 0.025
    FGF5 1.328 0.002
    GNPTAB 1.246 0.037
    GREM1 1.332 0.024 1.377 0.013 1.373 0.011
    HDAC1 1.301 0.018 1.237 0.021
    HSD17B4 1.277 0.011
    IFN-γ 1.219 0.048
    IMMT 1.230 0.049
    INHBA 1.866 <.001 1.944 <.001
    JAG1 1.298 0.030
    KCNN2 1.378 0.020 1.282 0.017
    KHDRBS3 1.353 0.029 1.305 0.014
    LAMA3 1.344 <.001 1.232 0.048
    LAMC1 1.396 0.015
    LIMS1 1.337 0.004
    LOX 1.355 0.001 1.341 0.002
    LTBP2 1.304 0.045
    MAGEA4 1.215 0.024
    MANF 1.460 <.001
    MCM6 1.287 0.042 1.214 0.046
    MELK 1.329 0.002
    MMP11 1.281 0.050
    MRPL13 1.266 0.021
    MYBL2 1.453 <.001 1.274 0.019
    MYC 1.265 0.037
    MY06 1.278 0.047
    NET02 1.322 0.022
    NFKB1 1.255 0.032
    NOX4 1.266 0.041
    OR51E1 1.566 <.001 1.428 0.003
    PATE1 1.242 <.001 1.347 <.001 1.177 0.011
    PCNA 1.251 0.025
    PEX10 1.302 0.028
    PGD 1.335 0.045 1.379 0.014 1.274 0.025
    PIM1 1.254 0.019
    PLA2G7 1.289 0.025 1.250 0.031
    PLAU 1.267 0.031
    PSMD13 1.333 0.005
    PTK6 1.432 <.001 1.577 <.001 1.223 0.040
    PTTG1 1.279 0.013 1.308 0.006
    RAGE 1.329 0.011
    RALA 1.363 0.044 1.471 0.003
    RGS7 1.120 0.040 1.173 0.031
    RRM1 1.490 0.004 1.527 <.001
    SESN3 1.353 0.017
    SFRP4 1.370 0.025
    SHMT2 1.460 0.008 1.410 0.006 1.407 0.008 1.345 <.001
    SKIL 1.307 0.025
    SLC25A21 1.414 0.002 1.330 0.004
    SMARCC2 1.219 0.049
    SPARC 1.431 0.005
    TFDP1 1.283 0.046 1.345 0.003
    THBS2 1.456 0.005 1.431 0.012
    TK1 1.214 0.015 1.222 0.006
    TOP2A 1.367 0.018 1.518 0.001 1.480 <.001
    TPX2 1.513 0.001 1.607 <.001 1.588 <.001 1.481 <.001
    UBE2T 1.409 0.002 1.285 0.018
    UGT2B15 1.216 0.009 1.182 0.021
    XIAP 1.336 0.037 1.194 0.043
  • TABLE 6B
    Genes significantly (p < 0.05) associated with cRFI or bRFI after adjustment for
    Gleason pattern in the primary Gleason pattern or highest Gleason pattern with hazard
    ration (HR) < 1.0 (increased expression is positively associated with good prognosis)
    Table 6B cRFI cRFI bRFI bRFI
    Official Primary Pattern Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value HR p-value
    AAMP 0.660 0.001 0.675 <.001 0.836 0.045
    ABCA5 0.807 0.014 0.737 <.001 0.845 0.030
    ABCC1 0.780 0.038 0.794 0.015
    ABCG2 0.807 0.035
    ABHD2 0.720 0.002
    ADH5 0.750 0.034
    AKAP1 0.721 <.001
    ALDH1A2 0.735 0.009 0.592 <.001 0.756 0.007 0.781 0.021
    ANGPT2 0.741 0.036
    ANPEP 0.637 <.001 0.536 <.001
    ANXA2 0.762 0.044
    APOE 0.707 0.013
    APRT 0.727 0.004 0.771 0.006
    ATXN1 0.725 0.013
    AURKA 0.784 0.037 0.735 0.003
    AXIN2 0.744 0.004 0.630 <.001
    AZGP1 0.672 <.001 0.720 <.001 0.764 0.001
    BAD 0.687 <.001
    BAK1 0.783 0.014
    BCL2 0.777 0.033 0.772 0.036
    BIK 0.768 0.040
    BIN1 0.691 <.001
    BTRC 0.776 0.029
    C7 0.707 0.004 0.791 0.024
    CADM1 0.587 <.001 0.593 <.001
    CASP1 0.773 0.023 0.820 0.025
    CAV1 0.753 0.014
    CAV2 0.627 0.009 0.682 0.003
    CCL2 0.740 0.019
    CCNH 0.736 0.003
    CCR1 0.755 0.022
    CD1A 0.740 0.025
    CD44 0.590 <.001 0.637 <.001
    CD68 0.757 0.026
    CD82 0.778 0.012 0.759 0.016
    CDC25B 0.760 0.021
    CDK3 0.762 0.024 0.774 0.007
    CDKN1A 0.714 0.015
    CDKN1C 0.738 0.014 0.768 0.021
    COL6A1 0.690 <.001 0.805 0.048
    CSF1 0.675 0.002 0.779 0.036
    CSK 0.825 0.004
    CTNNB1 0.884 0.045 0.888 0.027
    CTSB 0.740 0.017 0.676 0.003 0.755 0.010
    CTSD 0.673 0.031 0.722 0.009
    CTSK 0.804 0.034
    CTSL2 0.748 0.019
    CXCL12 0.731 0.017
    CYP3A5 0.523 <.001 0.518 <.001
    CYR61 0.744 0.041
    DAP 0.755 0.011
    DARC 0.763 0.029
    DDR2 0.813 0.041
    DES 0.743 0.020
    DHRS9 0.606 0.001
    DHX9 0.916 0.021
    DIAPH1 0.749 0.036 0.688 0.003
    DLGAP1 0.758 0.042 0.676 0.002
    DLL4 0.779 0.010
    DNIVI3 0.732 0.007
    DPP4 0.732 0.004 0.750 0.014
    DPT 0.704 0.014
    DUSP6 0.662 <.001 0.665 0.001
    EBNA1BP2 0.828 0.019
    EDNRA 0.782 0.048
    EGF 0.712 0.023
    EGR1 0.678 0.004 0.725 0.028
    EGR3 0.680 0.006 0.738 0.027
    EIF2C2 0.789 0.032
    EIF253 0.759 0.012
    ELK4 0.745 0.024
    EPHA2 0.661 0.007
    EPHA3 0.781 0.026 0.828 0.037
    ERBB2 0.791 0.022 0.760 0.014 0.789 0.006
    ERBB3 0.757 0.009
    ERCC1 0.760 0.008
    ESR1 0.742 0.014
    ESR2 0.711 0.038
    ETV4 0.714 0.035
    FAM107A 0.619 <.001 0.710 0.011 0.781 0.019
    FAM13C 0.664 <.001 0.686 <.001 0.813 0.014
    F AM49B 0.670 <.001 0.793 0.014 0.815 0.044 0.843 0.047
    FASLG 0.616 0.004 0.813 0.038
    FGF10 0.751 0.028 0.766 0.019
    FGF17 0.718 0.031 0.765 0.019
    FGFR2 0.740 0.009 0.738 0.002
    FKBP5 0.749 0.031
    FLNC 0.826 0.029
    FLT1 0.779 0.045 0.729 0.006
    FLT4 0.815 0.024
    FOS 0.657 0.003 0.656 0.004
    FSD1 0.763 0.017
    FYN 0.716 0.004 0.792 0.024
    GADD45B 0.692 0.009 0.697 0.010
    GDF15 0.767 0.016
    GHR 0.701 0.002 0.704 0.002 0.640 <.001
    GNRH1 0.778 0.039
    GPM6B 0.749 0.010 0.750 0.010 0.827 0.037
    GRB7 0.696 0.005
    GSK3B 0.726 0.005
    GSN 0.660 <.001 0.752 0.019
    GSTM1 0.710 0.004 0.676 <.001
    GSTM2 0.643 <.001 0.767 0.015
    HK1 0.798 0.035
    HLA-G 0.660 0.013
    HLF 0.644 <.001 0.727 0.011
    HNF1B 0.755 0.013
    HPS1 0.756 0.006 0.791 0.043
    HSD17B10 0.737 0.006
    HSD3B2 0.674 0.003
    HSP90AB1 0.763 0.015
    HSPB1 0.787 0.020 0.778 0.015
    HSPE1 0.794 0.039
    ICAM1 0.664 0.003
    IER3 0.699 0.003 0.693 0.010
    IFIT1 0.621 <.001 0.733 0.027
    IGF1 0.751 0.017 0.655 <.001
    IGFBP2 0.599 <.001 0.605 <.001
    IGFBP5 0.745 0.007 0.775 0.035
    IGFBP6 0.671 0.005
    IL1B 0.732 0.016 0.717 0.005
    IL6 0.763 0.040
    IL6R 0.764 0.022
    IL6ST 0.647 <.001 0.739 0.012
    IL8 0.711 0.015 0.694 0.006
    ING5 0.729 0.007 0.727 0.003
    ITGA4 0.755 0.009
    ITGA5 0.743 0.018 0.770 0.034
    ITGA6 0.816 0.044 0.772 0.006
    ITGA7 0.680 0.004
    ITGAD 0.590 0.009
    ITGB4 0.663 <.001 0.658 <.001 0.759 0.004
    JUN 0.656 0.004 0.639 0.003
    KIAA0196 0.737 0.011
    KIT 0.730 0.021 0.724 0.008
    KLC1 0.755 0.035
    KLK1 0.706 0.008
    KLK2 0.740 0.016 0.723 0.001
    KLK3 0.765 0.006 0.740 0.002
    KRT1 0.774 0.042
    KRT15 0.658 <.001 0.632 <.001 0.764 0.008
    KRT18 0.703 0.004 0.672 <.001 0.779 0.015 0.811 0.032
    KRT5 0.686 <.001 0.629 <.001 0.802 0.023
    KRT8 0.763 0.034 0.771 0.022
    L1CAM 0.748 0.041
    LAG3 0.693 0.008 0.724 0.020
    LAMA4 0.689 0.039
    LAMB3 0.667 <.001 0.645 <.001 0.773 0.006
    LGALS3 0.666 <.001 0.822 0.047
    LIG3 0.723 0.008
    LRP1 0.777 0.041 0.769 0.007
    MDM2 0.688 <.001
    MET 0.709 0.010 0.736 0.028 0.715 0.003
    MGMT 0.751 0.031
    MICA 0.705 0.002
    MPPED2 0.690 0.001 0.657 <.001 0.708 <.001
    MRC1 0.812 0.049
    MSH6 0.860 0.049
    MTSS1 0.686 0.001
    MVP 0.798 0.034 0.761 0.033
    MYBPC1 0.754 0.009 0.615 <.001
    NCAPD3 0.739 0.021 0.664 0.005
    NEXN 0.798 0.037
    NFAT5 0.596 <.001 0.732 0.005
    NFATC2 0.743 0.016 0.792 0.047
    NOS3 0.730 0.012 0.757 0.032
    OAZ1 0.732 0.020 0.705 0.002
    OCLN 0.746 0.043 0.784 0.025
    OLFML3 0.711 0.002 0.709 <.001 0.720 0.001
    OMD 0.729 0.011 0.762 0.033
    OSM 0.813 0.028
    PAGE4 0.668 0.003 0.725 0.004 0.688 <.001 0.766 0.005
    PCA3 0.736 0.001 0.691 <.001
    PCDHGB7 0.769 0.019 0.789 0.022
    PIK3CA 0.768 0.010
    PIK3CG 0.792 0.019 0.758 0.009
    PLG 0.682 0.009
    PPAP2B 0.688 0.005 0.815 0.046
    PPP1R12A 0.731 0.026 0.775 0.042
    PRIMA1 0.697 0.004 0.757 0.032
    PRKCA 0.743 0.019
    PRKCB 0.756 0.036 0.767 0.029
    PROM1 0.640 0.027 0.699 0.034 0.503 0.013
    PTCH1 0.730 0.018
    PTEN 0.779 0.015 0.789 0.007
    PTGS2 0.644 <.001 0.703 0.007
    PTHLH 0.655 0.012 0.706 0.038 0.634 0.001 0.665 0.003
    PTK2B 0.779 0.023 0.702 0.002 0.806 0.015 0.806 0.024
    PYCARD 0.659 0.001
    RAB30 0.779 0.033 0.754 0.014
    RARB 0.787 0.043 0.742 0.009
    RAS SF1 0.754 0.005
    RHOA 0.796 0.041 0.819 0.048
    RND3 0.721 0.011 0.743 0.028
    SDC1 0.707 0.011
    SDC2 0.745 0.002
    SDHC 0.750 0.013
    SERPINA3 0.730 0.016
    SERPINB5 0.715 0.041
    SH3RF2 0.698 0.025
    SIPA1L1 0.796 0.014 0.820 0.004
    SLC22A3 0.724 0.014 0.700 0.008
    SMAD4 0.668 0.002 0.771 0.016
    SMARCD1 0.726 <.001 0.700 0.001 0.812 0.028
    SMO 0.785 0.027
    SOD1 0.735 0.012
    SORBS1 0.785 0.039
    SPDEF 0.818 0.002
    SPINT1 0.761 0.024 0.773 0.006
    SRC 0.709 <.001 0.690 <.001
    SRD5A1 0.746 0.010 0.767 0.024 0.745 0.003
    SRD5A2 0.575 <.001 0.669 0.001 0.674 <.001 0.781 0.018
    ST5 0.774 0.027
    STAT1 0.694 0.004
    STAT5A 0.719 0.004 0.765 0.006 0.834 0.049
    STAT5B 0.704 0.001 0.744 0.012
    SUMO1 0.777 0.014
    SVIL 0.771 0.026
    TBP 0.774 0.031
    TFF3 0.742 0.015 0.719 0.024
    TGFB1I1 0.763 0.048
    TGFB2 0.729 0.011 0.758 0.002
    TMPRSS2 0.810 0.034 0.692 <.001
    TNF 0.727 0.022
    TNFRSF10A 0.805 0.025
    TNFRSF10B 0.581 <.001 0.738 0.014 0.809 0.034
    TNFSF10 0.751 0.015 0.700 <.001
    TP63 0.723 0.018 0.736 0.003
    TPM2 0.708 0.010 0.734 0.014
    TRAF3IP2 0.718 0.004
    TRO 0.742 0.012
    TSTA3 0.774 0.028
    TUBB2A 0.659 <.001 0.650 <.001
    TYMP 0.695 0.002
    VCL 0.683 0.008
    VIM 0.778 0.040
    WDR19 0.775 0.014
    XRC C 5 0.793 0.042
    YY1 0.751 0.025 0.810 0.008
    ZFHX3 0.760 0.005 0.726 0.001
    ZFP36 0.707 0.008 0.672 0.003
    ZNF827 0.667 0.002 0.792 0.039
  • Tables 7A and 7B provide genes significantly associated (p<0.05), positively or negatively, with clinical recurrence (cRFI) in negative TMPRSS fusion specimens in the primary or highest Gleason pattern specimen. Increased expression of genes in Table 7A is negatively associated with good prognosis, while increased expression of genes in Table 7B is positively associated with good prognosis.
  • TABLE 7A
    Genes significantly (p < 0.05) associated with cRFI for TMPRSS2-ERG
    fusion negative in the primary Gleason pattern or highest Gleason pattern
    with hazard ratio (HR) > 1.0 (increased expression is negatively
    associated with good prognosis)
    Primary Pattern Highest Pattern
    Official Symbol HR p-value HR p-value
    ANLN 1.42 0.012 1.36 0.004
    AQP2 1.25 0.033
    ASPN 2.48 <.001 1.65 <.001
    BGN 2.04 <.001 1.45 0.007
    BIRC5 1.59 <.001 1.37 0.005
    BMP6 1.95 <.001 1.43 0.012
    BMPR1B 1.93 0.002
    BUB1 1.51 <.001 1.35 <.001
    CCNE2 1.48 0.007
    CD276 1.93 <.001 1.79 <.001
    CDC20 1.49 0.004 1.47 <.001
    CDC6 1.52 0.009 1.34 0.022
    CDKN2B 1.54 0.008 1.55 0.003
    CDKN2C 1.55 0.003 1.57 <.001
    CDKN3 1.34 0.026
    CENPF 1.63 0.002 1.33 0.018
    CKS2 1.50 0.026 1.43 0.009
    CLTC 1.46 0.014
    COL1A1 1.98 <.001 1.50 0.002
    COL3A1 2.03 <.001 1.42 0.007
    COL4A1 1.81 0.002
    COL8A1 1.63 0.004 1.60 0.001
    CRISP3 1.31 0.016
    CTHRC1 1.67 0.006 1.48 0.005
    DDIT4 1.49 0.037
    ENY2 1.29 0.039
    EZH2 1.35 0.016
    F2R 1.46 0.034 1.46 0.007
    FAP 1.66 0.006 1.38 0.012
    FGF5 1.46 0.001
    GNPTAB 1.49 0.013
    HSD17B4 1.34 0.039 1.44 0.002
    INHBA 2.92 <.001 2.19 <.001
    JAG1 1.38 0.042
    KCNN2 1.71 0.002 1.73 <.001
    KHDRBS3 1.46 0.015
    KLK14 1.28 0.034
    KPNA2 1.63 0.016
    LAMC1 1.41 0.044
    LOX 1.29 0.036
    LTBP2 1.57 0.017
    MELK 1.38 0.029
    MMP11 1.69 0.002 1.42 0.004
    MYBL2 1.78 <.001 1.49 <.001
    NETO2 2.01 <.001 1.43 0.007
    NME1 1.38 0.017
    PATE1 1.43 <.001 1.24 0.005
    PEX10 1.46 0.030
    PGD 1.77 0.002
    POSTN 1.49 0.037 1.34 0.026
    PPFIA3 1.51 0.012
    PPP3CA 1.46 0.033 1.34 0.020
    PTK6 1.69 <.001 1.56 <.001
    PTTG1 1.35 0.028
    RAD51 1.32 0.048
    RALBP1 1.29 0.042
    RGS7 1.18 0.012 1.32 0.009
    RRM1 1.57 0.016 1.32 0.041
    RRM2 1.30 0.039
    SAT1 1.61 0.007
    SESN3 1.76 <.001 1.36 0.020
    SFRP4 1.55 0.016 1.48 0.002
    SHMT2 2.23 <.001 1.59 <.001
    SPARC 1.54 0.014
    SQLE 1.86 0.003
    STMN1 2.14 <.001
    THBS2 1.79 <.001 1.43 0.009
    TK1 1.30 0.026
    TOP2A 2.03 <.001 1.47 0.003
    TPD52 1.63 0.003
    TPX2 2.11 <.001 1.63 <.001
    TRAP1 1.46 0.023
    UBE2C 1.57 <.001 1.58 <.001
    UBE2G1 1.56 0.008
    UBE2T 1.75 <.001
    UGT2B15 1.31 0.036 1.33 0.004
    UHRF1 1.46 0.007
    UTP23 1.52 0.017
  • TABLE 7B
    Genes significantly (p < 0.05) associated with cRFI for TMPRSS2-ERG
    fusion negative in the primary Gleason pattern or highest Gleason pattern
    with hazard ratio (HR) < 1.0 (increased expression is positively associated
    with good prognosis)
    Primary Pattern Highest Pattern
    Official Symbol HR p-value HR p-value
    AAMP 0.56 <.001 0.65 0.001
    ABCA5 0.64 <.001 0.71 <.001
    ABCB1 0.62 0.004
    ABCC3 0.74 0.031
    ABCG2 0.78 0.050
    ABHD2 0.71 0.035
    ACOX2 0.54 <.001 0.71 0.007
    ADH5 0.49 <.001 0.61 <.001
    AKAP1 0.77 0.031 0.76 0.013
    AKR1C1 0.65 0.006 0.78 0.044
    AKT1 0.72 0.020
    AKT3 0.75 <.001
    ALDH1A2 0.53 <.001 0.60 <.001
    AMPD3 0.62 <.001 0.78 0.028
    ANPEP 0.54 <.001 0.61 <.001
    ANXA2 0.63 0.008 0.74 0.016
    ARHGAP29 0.67 0.005 0.77 0.016
    ARHGDIB 0.64 0.013
    ATP5J 0.57 0.050
    ATXN1 0.61 0.004 0.77 0.043
    AXIN2 0.51 <.001 0.62 <.001
    AZGP1 0.61 <.001 0.64 <.001
    BCL2 0.64 0.004 0.75 0.029
    BIN1 0.52 <.001 0.74 0.010
    BTG3 0.75 0.032 0.75 0.010
    BTRC 0.69 0.011
    C7 0.51 <.001 0.67 <.001
    CADM1 0.49 <.001 0.76 0.034
    CASP1 0.71 0.010 0.74 0.007
    CAV1 0.73 0.015
    CCL5 0.67 0.018 0.67 0.003
    CCNH 0.63 <.001 0.75 0.004
    CCR1 0.77 0.032
    CD164 0.52 <.001 0.63 <.001
    CD44 0.53 <.001 0.74 0.014
    CDH10 0.69 0.040
    CDH18 0.40 0.011
    CDK14 0.75 0.013
    CDK2 0.81 0.031
    CDK3 0.73 0.022
    CDKN1A 0.68 0.038
    CDKN1C 0.62 0.003 0.72 0.005
    COL6A1 0.54 <.001 0.70 0.004
    COL6A3 0.64 0.004
    CSF1 0.56 <.001 0.78 0.047
    CSRP1 0.40 <.001 0.66 0.002
    CTGF 0.66 0.015 0.74 0.027
    CTNNB1 0.69 0.043
    CTSB 0.60 0.002 0.71 0.011
    CTSS 0.67 0.013
    CXCL12 0.56 <.001 0.77 0.026
    CYP3A5 0.43 <.001 0.63 <.001
    CYR61 0.43 <.001 0.58 <.001
    DAG1 0.72 0.012
    DARC 0.66 0.016
    DDR2 0.65 0.007
    DES 0.52 <.001 0.74 0.018
    DHRS9 0.54 0.007
    DICER1 0.70 0.044
    DLC1 0.75 0.021
    DLGAP1 0.55 <.001 0.72 0.005
    DNIVI3 0.61 0.001
    DPP4 0.55 <.001 0.77 0.024
    DPT 0.48 <.001 0.61 <.001
    DUSP1 0.47 <.001 0.59 <.001
    DUSP6 0.65 0.009 0.65 0.002
    DYNLL1 0.74 0.045
    EDNRA 0.61 0.002 0.75 0.038
    EFNB2 0.71 0.043
    EGR1 0.43 <.001 0.58 <.001
    EGR3 0.47 <.001 0.66 <.001
    EIF5 0.77 0.028
    ELK4 0.49 <.001 0.72 0.012
    EPHA2 0.70 0.007
    EPHA3 0.62 <.001 0.72 0.009
    EPHB2 0.68 0.009
    ERBB2 0.64 <.001 0.63 <.001
    ERBB3 0.69 0.018
    ERCC1 0.69 0.019 0.77 0.021
    ESR2 0.61 0.020
    FAAH 0.57 <.001 0.77 0.035
    FABP5 0.67 0.035
    FAM107A 0.42 <.001 0.59 <.001
    FAM13C 0.53 <.001 0.59 <.001
    FAS 0.71 0.035
    FASLG 0.56 0.017 0.67 0.014
    FGF10 0.57 0.002
    FGF17 0.70 0.039 0.70 0.010
    FGF7 0.63 0.005 0.70 0.004
    FGFR2 0.63 0.003 0.71 0.003
    FKBP5 0.72 0.020
    FLNA 0.48 <.001 0.74 0.022
    FOS 0.45 <.001 0.56 <.001
    FOXO1 0.59 <.001
    FOXQ1 0.57 <.001 0.69 0.008
    FYN 0.62 0.001 0.74 0.013
    G6PD 0.77 0.014
    GADD45A 0.73 0.045
    GADD45B 0.45 <.001 0.64 0.001
    GDF15 0.58 <.001
    GHR 0.62 0.008 0.68 0.002
    GPM6B 0.60 <.001 0.70 0.003
    GSK3B 0.71 0.016 0.71 0.006
    GSN 0.46 <.001 0.66 <.001
    GSTM1 0.56 <.001 0.62 <.001
    GSTM2 0.47 <.001 0.67 <.001
    HGD 0.72 0.002
    HIRIP3 0.69 0.021 0.69 0.002
    HK1 0.68 0.005 0.73 0.005
    HLA-G 0.54 0.024 0.65 0.013
    HLF 0.41 <.001 0.68 0.001
    HNF1B 0.55 <.001 0.59 <.001
    HPS1 0.74 0.015 0.76 0.025
    HSD17B3 0.65 0.031
    HSPB2 0.62 0.004 0.76 0.027
    ICAM1 0.61 0.010
    IER3 0.55 <.001 0.67 0.003
    IFIT1 0.57 <.001 0.70 0.008
    IFNG 0.69 0.040
    IGF1 0.63 <.001 0.59 <.001
    IGF2 0.67 0.019 0.70 0.005
    IGFBP2 0.53 <.001 0.63 <.001
    IGFBP5 0.57 <.001 0.71 0.006
    IGFBP6 0.41 <.001 0.71 0.012
    IL10 0.59 0.020
    IL1B 0.53 <.001 0.70 0.005
    IL6 0.55 0.001
    IL6ST 0.45 <.001 0.68 <.001
    IL8 0.60 0.005 0.70 0.008
    ILK 0.68 0.029 0.76 0.036
    ING5 0.54 <.001 0.82 0.033
    ITGA1 0.66 0.017
    ITGA3 0.70 0.020
    ITGA5 0.64 0.011
    ITGA6 0.66 0.003 0.74 0.006
    ITGA7 0.50 <.001 0.71 0.010
    ITGB4 0.63 0.014 0.73 0.010
    ITPR1 0.55 <.001
    ITPR3 0.76 0.007
    JUN 0.37 <.001 0.54 <.001
    JUNB 0.58 0.002 0.71 0.016
    KCTD12 0.68 0.017
    KIT 0.49 0.002 0.76 0.043
    KLC1 0.61 0.005 0.77 0.045
    KLF 6 0.65 0.009
    KLK1 0.68 0.036
    KLK10 0.76 0.037
    KLK2 0.64 <.001 0.73 0.006
    KLK3 0.65 <.001 0.76 0.021
    KLRK1 0.63 0.005
    KRT15 0.52 <.001 0.58 <.001
    KRT18 0.46 <.001
    KRT5 0.51 <.001 0.58 <.001
    KRT8 0.53 <.001
    L1CAM 0.65 0.031
    LAG3 0.58 0.002 0.76 0.033
    LAMA4 0.52 0.018
    LAMB3 0.60 0.002 0.65 0.003
    LGALS3 0.52 <.001 0.71 0.002
    LIG3 0.65 0.011
    LRP1 0.61 0.001 0.75 0.040
    MGMT 0.66 0.003
    MICA 0.59 0.001 0.68 0.001
    MLXIP 0.70 0.020
    MMP2 0.68 0.022
    MMP9 0.67 0.036
    MPPED2 0.57 <.001 0.66 <.001
    MRC1 0.69 0.028
    MTSS1 0.63 0.005 0.79 0.037
    MVP 0.62 <.001
    MYBPC1 0.53 <.001 0.70 0.011
    NCAM1 0.70 0.039 0.77 0.042
    NCAPD3 0.52 <.001 0.59 <.001
    NDRG1 0.69 0.008
    NEXN 0.62 0.002
    NFAT5 0.45 <.001 0.59 <.001
    NFATC2 0.68 0.035 0.75 0.036
    NFKBIA 0.70 0.030
    NRG1 0.59 0.022 0.71 0.018
    OAZ1 0.69 0.018 0.62 <.001
    OLFML3 0.59 <.001 0.72 0.003
    OR51E2 0.73 0.013
    PAGE4 0.42 <.001 0.62 <.001
    PCA3 0.53 <.001
    PCDHGB7 0.70 0.032
    PGF 0.68 0.027 0.71 0.013
    PGR 0.76 0.041
    PIK3C2A 0.80 <.001
    PIK3CA 0.61 <.001 0.80 0.036
    PIK3CG 0.67 0.001 0.76 0.018
    PLP2 0.65 0.015 0.72 0.010
    PPAP2B 0.45 <.001 0.69 0.003
    PPP1R12A 0.61 0.007 0.73 0.017
    PRIMA1 0.51 <.001 0.68 0.004
    PRKCA 0.55 <.001 0.74 0.009
    PRKCB 0.55 <.001
    PROM1 0.67 0.042
    PROS1 0.73 0.036
    PTCH1 0.69 0.024 0.72 0.010
    PTEN 0.54 <.001 0.64 <.001
    PTGS2 0.48 <.001 0.55 <.001
    PTH1R 0.57 0.003 0.77 0.050
    PTHLH 0.55 0.010
    PTK2B 0.56 <.001 0.70 0.001
    PYCARD 0.73 0.009
    RAB27A 0.65 0.009 0.71 0.014
    RAB30 0.59 0.003 0.72 0.010
    RAGE 0.76 0.011
    RARB 0.59 <.001 0.63 <.001
    RASSF1 0.67 0.003
    RB1 0.67 0.006
    RFX1 0.71 0.040 0.70 0.003
    RHOA 0.71 0.038 0.65 <.001
    RHOB 0.58 0.001 0.71 0.006
    RND3 0.54 <.001 0.69 0.003
    RNF114 0.59 0.004 0.68 0.003
    SCUBE2 0.77 0.046
    SDHC 0.72 0.028 0.76 0.025
    SEC23A 0.75 0.029
    SEMA3A 0.61 0.004 0.72 0.011
    SEPT9 0.66 0.013 0.76 0.036
    SERPINB5 0.75 0.039
    SH3RF2 0.44 <.001 0.48 <.001
    SHH 0.74 0.049
    SLC22A3 0.42 <.001 0.61 <.001
    SMAD4 0.45 <.001 0.66 <.001
    SMARCD1 0.69 0.016
    SOD1 0.68 0.042
    SORBS1 0.51 <.001 0.73 0.012
    SPARCL1 0.58 <.001 0.77 0.040
    SPDEF 0.77 <.001
    SPINT1 0.65 0.004 0.79 0.038
    SRC 0.61 <.001 0.69 0.001
    SRD5A2 0.39 <.001 0.55 <.001
    STS 0.61 <.001 0.73 0.012
    STAT1 0.64 0.006
    STAT3 0.63 0.010
    STAT5A 0.62 0.001 0.70 0.003
    STAT5B 0.58 <.001 0.73 0.009
    SUMO1 0.66 <.001
    SVIL 0.57 0.001 0.74 0.022
    TBP 0.65 0.002
    TFF1 0.65 0.021
    TFF3 0.58 <.001
    TGFB1I1 0.51 <.001 0.75 0.026
    TGFB2 0.48 <.001 0.62 <.001
    TGFBR2 0.61 0.003
    TIAM1 0.68 0.019
    TIMP2 0.69 0.020
    TIMP3 0.58 0.002
    TNFRSF10A 0.73 0.047
    TNFRSF10B 0.47 <.001 0.70 0.003
    TNFSF10 0.56 0.001
    TP63 0.67 0.001
    TPM1 0.58 0.004 0.73 0.017
    TPM2 0.46 <.001 0.70 0.005
    TRA2A 0.68 0.013
    TRAF3IP2 0.73 0.041 0.71 0.004
    TRO 0.72 0.016 0.71 0.004
    TUBB2A 0.53 <.001 0.73 0.021
    TYMP 0.70 0.011
    VCAM1 0.69 0.041
    VCL 0.46 <.001
    VEGFA 0.77 0.039
    VEGFB 0.71 0.035
    VIM 0.60 0.001
    XRCC5 0.75 0.026
    YY1 0.62 0.008 0.77 0.039
    ZFHX3 0.53 <.001 0.58 <.001
    ZFP36 0.43 <.001 0.54 <.001
    ZNF827 0.55 0.001
  • Tables 8A and 8B provide genes that were significantly associated (p<0.05), positively or negatively, with clinical recurrence (cRFI) in positive TMPRSS fusion specimens in the primary or highest Gleason pattern specimen. Increased expression of genes in Table 8A is negatively associated with good prognosis, while increased expression of genes in Table 8B is positively associated with good prognosis.
  • TABLE 8A
    Genes significantly (p < 0.05) associated with cRFI for TMPRSS2-ERG
    fusion positive in the primary Gleason pattern or highest Gleason pattern
    with hazard ratio (HR) > 1.0 (increased expression is negatively associated
    with good prognosis)
    Primary Pattern Highest Pattern
    Official Symbol HR p-value HR p-value
    ACTR2 1.78 0.017
    AKR1C3 1.44 0.013
    ALCAM 1.44 0.022
    ANLN 1.37 0.046 1.81 <.001
    APOE 1.49 0.023 1.66 0.005
    AQP2 1.30 0.013
    ARHGMB 1.55 0.021
    ASPN 2.13 <.001 2.43 <.001
    ATP5E 1.69 0.013 1.58 0.014
    BGN 1.92 <.001 2.55 <.001
    BIRC5 1.48 0.006 1.89 <.001
    BMP6 1.51 0.010 1.96 <.001
    BRCA2 1.41 0.007
    BUB1 1.36 0.007 1.52 <.001
    CCNE2 1.55 0.004 1.59 <.001
    CD276 1.65 <.001
    CDC20 1.68 <.001 1.74 <.001
    CDH11 1.50 0.017
    CDH18 1.36 <.001
    CDH7 1.54 0.009 1.46 0.026
    CDKN2B 1.68 0.008 1.93 0.001
    CDKN2C 2.01 <.001 1.77 <.001
    CDKN3 1.51 0.002 1.33 0.049
    CENPF 1.51 0.007 2.04 <.001
    CKS2 1.43 0.034 1.56 0.007
    COL1A1 2.23 <.001 3.04 <.001
    COL1A2 1.79 0.001 2.22 <.001
    COL3A1 1.96 <.001 2.81 <.001
    COL4A1 1.52 0.020
    COL5A1 1.50 0.020
    COL5A2 1.64 0.017 1.55 0.010
    COL8A1 1.96 <.001 2.38 <.001
    CRISP3 1.68 0.002 1.67 0.002
    CTHRC1 2.06 <.001
    CTNND2 1.42 0.046 1.50 0.025
    CTSK 1.43 0.049
    CXCR4 1.82 0.001 1.64 0.007
    DDIT4 1.54 0.016 1.58 0.009
    DLL4 1.51 0.007
    DYNLL1 1.50 0.021 1.22 0.002
    F2R 2.27 <.001 2.02 <.001
    FAP 2.12 <.001
    FCGR3A 1.94 0.002
    FGF5 1.23 0.047
    FOXP3 1.52 0.006 1.48 0.018
    GNPTAB 1.44 0.042
    GPR68 1.51 0.011
    GREM1 1.91 <.001 2.38 <.001
    HDAC1 1.43 0.048
    HDAC9 1.65 <.001 1.67 0.004
    HRAS 1.65 0.005 1.58 0.021
    IGFBP3 1.94 <.001 1.85 <.001
    INHBA 2.03 <.001 2.64 <.001
    JAG1 1.41 0.027 1.50 0.008
    KCTD12 1.51 0.017
    KHDRBS3 1.48 0.029 1.54 0.014
    KPNA2 1.46 0.050
    LAMA3 1.35 0.040
    LAMC1 1.77 0.012
    LTBP2 1.82 <.001
    LUM 1.51 0.021 1.53 0.009
    MELK 1.38 0.020 1.49 0.001
    MKI67 1.37 0.014
    MMP11 1.73 <.001 1.69 <.001
    MRPL13 1.30 0.046
    MYBL2 1.56 <.001 1.72 <.001
    MYLK3 1.17 0.007
    NOX4 1.58 0.005 1.96 <.001
    NRIP3 1.30 0.040
    NRP1 1.53 0.021
    OLFML2B 1.54 0.024
    OSM 1.43 0.018
    PATE1 1.20 <.001 1.33 <.001
    PCNA 1.64 0.003
    PEX10 1.41 0.041 1.64 0.003
    PIK3CA 1.38 0.037
    PLK1 1.52 0.009 1.67 0.002
    PLOD2 1.65 0.002
    POSTN 1.79 <.001 2.06 <.001
    PTK6 1.67 0.002 2.38 <.001
    PTTG1 1.56 0.002 1.54 0.003
    RAD21 1.61 0.036 1.53 0.005
    RAD51 1.33 0.009
    RALA 1.95 0.004 1.60 0.007
    REG4 1.43 0.042
    ROBO2 1.46 0.024
    RRM1 1.44 0.033
    RRM2 1.50 0.003 1.48 <.001
    SAT1 1.42 0.009 1.43 0.012
    SEC14L1 1.64 0.002
    SFRP4 2.07 <.001 2.40 <.001
    SHMT2 1.52 0.030 1.60 0.001
    SLC44A1 1.42 0.039
    SPARC 1.93 <.001 2.21 <.001
    SULF1 1.63 0.006 2.04 <.001
    THBS2 1.95 <.001 2.26 <.001
    THY1 1.69 0.016 1.95 0.002
    TK1 1.43 0.003
    TOP2A 1.57 0.002 2.11 <.001
    TPX2 1.84 <.001 2.27 <.001
    UBE2C 1.41 0.011 1.44 0.006
    UBE2T 1.63 0.001
    UHRF1 1.51 0.007 1.69 <.001
    WISP1 1.47 0.045
    WNT5A 1.35 0.027 1.63 0.001
    ZWINT 1.36 0.045
  • TABLE 8B
    Genes significantly (p < 0.05) associated with cRFI for TMPRSS2-ERG
    fusion positive in the primary Gleason pattern or highest Gleason pattern
    with hazard ratio (HR) < 1.0 (increased expression is positively associated
    with good prognosis)
    Primary Pattern Highest Pattern
    Official Symbol HR p-value HR p-value
    AAMP 0.57 0.007 0.58 <.001
    ABCA5 0.80 0.044
    ACE 0.65 0.023 0.55 <.001
    ACOX2 0.55 <.001
    ADH5 0.68 0.022
    AKAP1 0.81 0.043
    ALDH1A2 0.72 0.036 0.43 <.001
    ANPEP 0.66 0.022 0.46 <.001
    APRT 0.73 0.040
    AXIN2 0.60 <.001
    AZGP1 0.57 <.001 0.65 <.001
    BCL2 0.69 0.035
    BIK 0.71 0.045
    BIN1 0.71 0.004 0.71 0.009
    BTRC 0.66 0.003 0.58 <.001
    C7 0.64 0.006
    CADM1 0.61 <.001 0.47 <.001
    CCL2 0.73 0.042
    CCNH 0.69 0.022
    CD44 0.56 <.001 0.58 <.001
    CD82 0.72 0.033
    CDC25B 0.74 0.028
    CDH1 0.75 0.030 0.72 0.010
    CDH19 0.56 0.015
    CDK3 0.78 0.045
    CDKN1C 0.74 0.045 0.70 0.014
    CSF1 0.72 0.037
    CTSB 0.69 0.048
    CTSL2 0.58 0.005
    CYP3A5 0.51 <.001 0.30 <.001
    DHX9 0.89 0.006 0.87 0.012
    DLC1 0.64 0.023
    DLGAP1 0.69 0.010 0.49 <.001
    DPP4 0.64 <.001 0.56 <.001
    DPT 0.63 0.003
    EGR1 0.69 0.035
    EGR3 0.68 0.025
    EIF2S3 0.70 0.021
    EIF5 0.71 0.030
    ELK4 0.71 0.041 0.60 0.003
    EPHA2 0.72 0.036 0.66 0.011
    EPHB 4 0.65 0.007
    ERCC1 0.68 0.023
    ESR2 0.64 0.027
    FAM107A 0.64 0.003 0.61 0.003
    FAM13C 0.68 0.006 0.55 <.001
    FGFR2 0.73 0.033 0.59 <.001
    FKBP5 0.60 0.006
    FLNC 0.68 0.024 0.65 0.012
    FLT1 0.71 0.027
    FOS 0.62 0.006
    FOXO1 0.75 0.010
    GADD45B 0.68 0.020
    GHR 0.62 0.006
    GPM6B 0.57 <.001
    GSTM1 0.68 0.015 0.58 <.001
    GSTM2 0.65 0.005 0.47 <.001
    HGD 0.63 0.001 0.71 0.020
    HK1 0.67 0.003 0.62 0.002
    HLF 0.59 <.001
    HNF1B 0.66 0.004 0.61 0.001
    IER3 0.70 0.026
    IGF1 0.63 0.005 0.55 <.001
    IGF1R 0.76 0.049
    IGFBP2 0.59 0.007 0.64 0.003
    IL6ST 0.65 0.005
    IL8 0.61 0.005 0.66 0.019
    ILK 0.64 0.015
    ING5 0.73 0.033 0.70 0.009
    ITGA7 0.72 0.045 0.69 0.019
    ITGB4 0.63 0.002
    KLC1 0.74 0.045
    KLK1 0.56 0.002 0.49 <.001
    KLK10 0.68 0.013
    KLK11 0.66 0.003
    KLK2 0.66 0.045 0.65 0.011
    KLK3 0.75 0.048 0.77 0.014
    KRT15 0.71 0.017 0.50 <.001
    KRT5 0.73 0.031 0.54 <.001
    LAMAS 0.70 0.044
    LAMB3 0.70 0.005 0.58 <.001
    LGALS3 0.69 0.025
    LIG3 0.68 0.022
    MDK 0.69 0.035
    MGMT 0.59 0.017 0.60 <.001
    MGST1 0.73 0.042
    MICA 0.70 0.009
    MPPED2 0.72 0.031 0.54 <.001
    MTSS1 0.62 0.003
    MYBPC1 0.50 <.001
    NCAPD3 0.62 0.007 0.38 <.001
    NCOR1 0.82 0.048
    NFAT5 0.60 0.001 0.62 <.001
    NRG1 0.66 0.040 0.61 0.029
    NUP62 0.75 0.037
    OMD 0.54 <.001
    PAGE4 0.64 0.005
    PCA3 0.66 0.012
    PCDHGB7 0.68 0.018
    PGR 0.60 0.012
    PPAP2B 0.62 0.010
    PPP1R12A 0.73 0.031 0.58 0.003
    PRIMA1 0.65 0.013
    PROM1 0.41 0.013
    PTCH1 0.64 0.006
    PTEN 0.75 0.047
    PTGS2 0.67 0.011
    PTK2B 0.66 0.005
    PTPN1 0.71 0.026
    RAGE 0.70 0.012
    RARB 0.68 0.016
    RGS10 0.84 0.034
    RHOB 0.66 0.016
    RND3 0.63 0.004
    SDHC 0.73 0.044 0.69 0.016
    SERPINA3 0.67 0.011 0.51 <.001
    SERPINB5 0.42 <.001
    SH3RF2 0.66 0.012 0.51 <.001
    SLC22A3 0.59 0.003 0.48 <.001
    SMAD4 0.64 0.004 0.49 <.001
    SMARCC2 0.73 0.042
    SMARCD1 0.73 <.001 0.76 0.035
    SMO 0.64 0.006
    SNAI1 0.53 0.008
    SOD1 0.60 0.003
    SRC 0.64 <.001 0.61 <.001
    SRD5A2 0.63 0.004 0.59 <.001
    STAT3 0.64 0.014
    STAT5A 0.70 0.032
    STAT5B 0.74 0.034 0.63 0.003
    SVIL 0.71 0.028
    TGFB1I1 0.68 0.036
    TMPRSS2 0.72 0.015 0.67 <.001
    TNFRSF10A 0.69 0.010
    TNFRSF10B 0.67 0.007 0.64 0.001
    TNFRSF18 0.38 0.003
    TNFSF10 0.71 0.025
    TP53 0.68 0.004 0.57 <.001
    TP63 0.75 0.049 0.52 <.001
    TPM2 0.62 0.007
    TRAF3IP2 0.71 0.017 0.68 0.005
    TRO 0.72 0.033
    TUBB2A 0.69 0.038
    VCL 0.62 <.001
    VEGFA 0.71 0.037
    WWOX 0.65 0.004
    ZFHX3 0.77 0.011 0.73 0.012
    ZFP36 0.69 0.018
    ZNF827 0.68 0.013 0.49 <.001
  • Tables 9A and 9B provide genes significantly associated (p<0.05), positively or negatively, with TMPRSS fusion status in the primary Gleason pattern. Increased expression of genes in Table 9A are positively associated with TMPRSS fusion positivity, while increased expression of genes in Table 10A are negatively associated with TMPRSS fusion positivity.
  • TABLE 9A
    Genes significantly (p < 0.05) associated with TMPRSS fusion status
    in the primary Gleason pattern with odds ratio (OR) > 1.0 (increased
    expression is positively associated with TMPRSS fusion positivity
    Official Symbol p-value Odds Ratio
    ABCC8 <.001 1.86
    ALDH18A1 0.005 1.49
    ALKBH3 0.043 1.30
    ALOX5 <.001 1.66
    AMPD3 <.001 3.92
    APEX1 <.001 2.00
    ARHGD113 <.001 1.87
    ASAP2 0.019 1.48
    ATXN1 0.013 1.41
    BMPR1B <.001 2.37
    CACNA1D <.001 9.01
    CADPS 0.015 1.39
    CD276 0.003 2.25
    CDH1 0.016 1.37
    CDH7 <.001 2.22
    CDK7 0.025 1.43
    COL9A2 <.001 2.58
    CRISP3 <.001 2.60
    CTNND1 0.033 1.48
    ECE1 <.001 2.22
    EIF5 0.023 1.34
    EPHB4 0.005 1.51
    ERG <.001 14.5
    FAM171B 0.047 1.32
    FAM73A 0.008 1.45
    FASN 0.004 1.50
    GNPTAB <.001 1.60
    GPS1 0.006 1.45
    GRB7 0.023 1.38
    HDAC1 <.001 4.95
    HGD <.001 1.64
    HIP1 <.001 1.90
    HNF1B <.001 3.55
    HSPA8 0.041 1.32
    IGF1R 0.001 1.73
    ILF3 <.001 1.91
    IMMT 0.025 1.36
    ITPR1 <.001 2.72
    ITPR3 <.001 5.91
    JAG1 0.007 1.42
    KCNN2 <.001 2.80
    KHDRBS3 <.001 2.63
    KIAA0247 0.019 1.38
    KLK11 <.001 1.98
    LAMC1 0.008 1.56
    LAMC2 <.001 3.30
    LOX 0.009 1.41
    LRP1 0.044 1.30
    MAP3K5 <.001 2.06
    MAP7 <.001 2.74
    MSH2 0.005 1.59
    MSH3 0.006 1.45
    MUC1 0.012 1.42
    MYO6 <.001 3.79
    NCOR2 0.001 1.62
    NDRG1 <.001 6.77
    NETO2 <.001 2.63
    ODC1 <.001 1.98
    OR51E1 <.001 2.24
    PDE9A <.001 2.21
    PEX10 <.001 3.41
    PGK1 0.022 1.33
    PLA2G7 <.001 5.51
    PPP3CA 0.047 1.38
    PSCA 0.013 1.43
    PSMD13 0.004 1.51
    PTCH1 0.022 1.38
    PTK2 0.014 1.38
    PTK6 <.001 2.29
    PTK7 <.001 2.45
    PTPRK <.001 1.80
    RAB30 0.001 1.60
    REG4 0.018 1.58
    RELA 0.001 1.62
    RFX1 0.020 1.43
    RGS10 <.001 1.71
    SCUBE2 0.009 1.48
    SEPT9 <.001 3.91
    SH3RF2 0.004 1.48
    SH3YL1 <.001 1.87
    SHH <.001 2.45
    SIM2 <.001 1.74
    SIPA1L1 0.021 1.35
    SLC22A3 <.001 1.63
    SLC44A1 <.001 1.65
    SPINT1 0.017 1.39
    TFDP1 0.005 1.75
    TMPRSS2ERGA 0.002 14E5
    TMPRSS2ERGB <.001 1.97
    TRIM14 <.001 1.65
    TSTA3 0.018 1.38
    UAP1 0.046 1.39
    UBE2G1 0.001 1.66
    UGDH <.001 2.22
    XRCCS <.001 1.66
    ZMYND8 <.001 2.19
  • TABLE 9B
    Genes significantly (p < 0.05) associated with TMPRSS fusion status
    in the primary Gleason pattern with odds ratio (OR) < 1.0 (increased
    expression is negatively associated with TMPRSS fusion positivity)
    Official Symbol p-value Odds Ratio
    ABCC4 0.045 0.77
    ABHD2 <.001 0.38
    ACTR2 0.027 0.73
    ADAMTS1 0.024 0.58
    ADH5 <.001 0.58
    AGTR2 0.016 0.64
    AKAP1 0.013 0.70
    AKT2 0.015 0.71
    ALCAM <.001 0.45
    ALDH1A2 0.004 0.70
    ANPEP <.001 0.43
    ANXA2 0.010 0.71
    APC 0.036 0.73
    APOC1 0.002 0.56
    APOE <.001 0.44
    ARF1 0.041 0.77
    ATM 0.036 0.74
    AURKB <.001 0.62
    AZGP1 <.001 0.54
    BBC3 0.030 0.74
    BCL2 0.012 0.70
    BIN1 0.021 0.74
    BTG1 0.004 0.67
    BTG3 0.003 0.63
    C7 0.023 0.74
    CADM1 0.007 0.69
    CASP1 0.011 0.70
    CAV1 0.011 0.71
    CCND1 0.019 0.72
    CCR1 0.022 0.73
    CD44 <.001 0.57
    CD68 <.001 0.54
    CD82 0.002 0.66
    CDH5 0.007 0.66
    CDKN1A <.001 0.60
    CDKN2B <.001 0.54
    CDKN2C 0.012 0.72
    CDKN3 0.037 0.77
    CHN1 0.038 0.75
    CKS2 <.001 0.48
    COL11A1 0.017 0.72
    COL1A1 <.001 0.59
    COL1A2 0.001 0.62
    COL3A1 0.027 0.73
    COL4A1 0.043 0.76
    COL5A1 0.039 0.74
    COL5A2 0.026 0.73
    COL6A1 0.008 0.66
    COL6A3 <.001 0.59
    COL8A1 0.022 0.74
    CSF1 0.011 0.70
    CTNNB1 0.021 0.69
    CTSB <.001 0.62
    CTSD 0.036 0.68
    CTSK 0.007 0.70
    CTSS 0.002 0.64
    CXCL12 <.001 0.48
    CXCR4 0.005 0.68
    CXCR7 0.046 0.76
    CYR61 0.004 0.65
    DAP 0.002 0.64
    DARC 0.021 0.73
    DDR2 0.021 0.73
    DHRS9 <.001 0.52
    DIAPH1 <.001 0.56
    DICER1 0.029 0.75
    DLC1 0.013 0.72
    DLGAP1 <.001 0.60
    DLL4 <.001 0.57
    DPT 0.006 0.68
    DUSP1 0.012 0.68
    DUSP6 0.001 0.62
    DVL1 0.037 0.75
    EFNB2 <.001 0.32
    EGR1 0.003 0.65
    ELK4 <.001 0.60
    ERBB2 <.001 0.61
    ERBB3 0.045 0.76
    ESR2 0.010 0.70
    ETV1 0.042 0.74
    FABP5 <.001 0.21
    FAM13C 0.006 0.67
    FCGR3A 0.018 0.72
    FGF17 0.009 0.71
    FGF6 0.011 0.70
    FGF7 0.003 0.63
    FN1 0.006 0.69
    FOS 0.035 0.74
    FOXP3 0.010 0.71
    GABRG2 0.029 0.74
    GADD45B 0.003 0.63
    GDF15 <.001 0.54
    GPM6B 0.004 0.67
    GPNMB 0.001 0.62
    GSN 0.009 0.69
    HLA-G 0.050 0.74
    HLF 0.018 0.74
    HPS1 <.001 0.48
    HSD17B3 0.003 0.60
    HSD17B4 <.001 0.56
    HSPB1 <.001 0.38
    HSPB2 0.002 0.62
    IFI30 0.049 0.75
    IFNG 0.006 0.64
    IGF1 0.016 0.73
    IGF2 0.001 0.57
    IGFBP2 <.001 0.51
    IGFBP3 <.001 0.59
    IGFBP6 <.001 0.57
    IL10 <.001 0.62
    IL17A 0.012 0.63
    IL1A 0.011 0.59
    IL2 0.001 0.63
    IL6ST <.001 0.52
    INSL4 0.014 0.71
    ITGA1 0.009 0.69
    ITGA4 0.007 0.68
    JUN <.001 0.59
    KIT <.001 0.64
    KRT76 0.016 0.70
    LAG3 0.002 0.63
    LAPTM5 <.001 0.58
    LGALS3 <.001 0.53
    LTBP2 0.011 0.71
    LUM 0.012 0.70
    MAOA 0.020 0.73
    MAP4K4 0.007 0.68
    MGST1 <.001 0.54
    MMP2 <.001 0.61
    MPPED2 <.001 0.45
    MRC1 0.005 0.67
    MTPN 0.002 0.56
    MTSS1 <.001 0.53
    MVP 0.009 0.72
    MYBPC1 <.001 0.51
    MYLK3 0.001 0.58
    NCAM1 <.001 0.59
    NCAPD3 <.001 0.40
    NCOR1 0.004 0.69
    NFKBIA <.001 0.63
    NNMT 0.006 0.66
    NPBWR1 0.027 0.67
    OAZ1 0.049 0.64
    OLFML3 <.001 0.56
    OSM <.001 0.64
    PAGE1 0.012 0.52
    PDGFRB 0.016 0.73
    PECAM1 <.001 0.55
    PGR 0.048 0.77
    PIK3CA <.001 0.55
    PIK3CG 0.008 0.71
    PLAU 0.044 0.76
    PLK1 0.006 0.68
    PLOD2 0.013 0.71
    PLP2 0.024 0.73
    PNLIPRP2 0.009 0.70
    PPAP2B <.001 0.62
    PRKAR2B <.001 0.61
    PRKCB 0.044 0.76
    PROS1 0.005 0.67
    PTEN <.001 0.47
    PTGER3 0.007 0.69
    PTH1R 0.011 0.70
    PTK2B <.001 0.61
    PTPN1 0.028 0.73
    RAB27A <.001 0.21
    RAD51 <.001 0.51
    RAD9A 0.030 0.75
    RARB <.001 0.62
    RASSF1 0.038 0.76
    RECK 0.009 0.62
    RHOB 0.004 0.64
    RHOC <.001 0.56
    RLN1 <.001 0.30
    RND3 0.014 0.72
    S100P 0.002 0.66
    SDC2 <.001 0.61
    SEMA3A 0.001 0.64
    SMAD4 <.001 0.64
    SPARC <.001 0.59
    SPARCL1 <.001 0.56
    SPINK1 <.001 0.26
    SRD5A1 0.039 0.76
    STAT1 0.026 0.74
    STS 0.006 0.64
    SULF1 <.001 0.53
    TFF3 <.001 0.19
    TGFA 0.002 0.65
    TGFB1I1 0.040 0.77
    TGFB2 0.003 0.66
    TGFB3 <.001 0.54
    TGFBR2 <.001 0.61
    THY1 <.001 0.63
    TIMP2 0.004 0.66
    TIMP3 <.001 0.60
    TMPRSS2 <.001 0.40
    TNFSF11 0.026 0.63
    TPD52 0.002 0.64
    TRAM1 <.001 0.45
    TRPC6 0.002 0.64
    TUBB2A <.001 0.49
    VCL <.001 0.57
    VEGFB 0.033 0.73
    VEGFC <.001 0.61
    VIM 0.012 0.69
    WISP1 0.030 0.75
    WNT5A <.001 0.50
  • A molecular field effect was investigated, and determined that the expression levels of histologically normal-appearing cells adjacent to the tumor exhibited a molecular signature of prostate cancer. Tables 10A and 10B provide genes significantly associated (p<0.05), positively or negatively, with cRFI or bRFI in non-tumor samples. Table 10A is negatively associated with good prognosis, while increased expression of genes in Table 10B is positively associated with good prognosis.
  • TABLE 10A
    Genes significantly (p < 0.05) associated with cRFI
    or bRFI in Non-Tumor Samples with hazard ratio
    (HR) > 1.0 (increased expression is negatively
    associated with good prognosis)
    Official cRFI bRFI
    Symbol HR p-value HR p-value
    ALCAM 1.278 0.036
    ASPN 1.309 0.032
    BAG5 1.458 0.004
    BRCA2 1.385 <.001
    CACNA1D 1.329 0.035
    CD164 1.339 0.020
    CDKN2B 1.398 0.014
    COL3A1 1.300 0.035
    COL4A1 1.358 0.019
    CTNND2 1.370 0.001
    DARC 1.451 0.003
    DICER1 1.345 <.001
    DPP4 1.358 0.008
    EFNB2 1.323 0.007
    FASN 1.327 0.035
    GHR 1.332 0.048
    HSPA5 1.260 0.048
    INHBA 1.558 <.001
    KCNN2 1.264 0.045
    KRT76 1.115 <.001
    LAMC1 1.390 0.014
    LAMC2 1.216 0.042
    LIG3 1.313 0.030
    MAOA 1.405 0.013
    MCM6 1.307 0.036
    MKI67 1.271 0.008
    NEK2 1.312 0.016
    NPBWR1 1.278 0.035
    ODC1 1.320 0.010
    PEX10 1.361 0.014
    PGK1 1.488 0.004
    PLA2G7 1.337 0.025
    POSTN 1.306 0.043
    PTK6 1.344 0.005
    REG4 1.348 0.009
    RGS7 1.144 0.047
    SFRP4 1.394 0.009
    TARP 1.412 0.011
    TFF1 1.346 0.010
    TGFBR2 1.310 0.035
    THY1 1.300 0.038
    TMPRSS2ERGA 1.333 <.001
    TPD52 1.374 0.015
    TRPC6 1.272 0.046
    UBE2C 1.323 0.007
    UHRF1 1.325 0.021
  • TABLE 10B
    Genes significantly (p < 0.05) associated with cRFI
    or bRFI in Non-Tumor Samples with hazard ratio
    (HR) < 1.0 (increased expression is positively
    associated with good prognosis)
    Official cRFI bRFI
    Symbol HR p-value HR p-value
    ABCA5 0.807 0.028
    ABCC3 0.760 0.019 0.750 0.003
    ABHD2 0.781 0.028
    ADAM15 0.718 0.005
    AKAP1 0.740 0.009
    AMPD3 0.793 0.013
    ANGPT2 0.752 0.027
    ANXA2 0.776 0.035
    APC 0.755 0.014
    APRT 0.762 0.025
    AR 0.752 0.015
    ARHGDIB 0.753 <.001
    BIN1 0.738 0.016
    CADM1 0.711 0.004
    CCNH 0.820 0.041
    CCR1 0.749 0.007
    CDK14 0.772 0.014
    CDK3 0.819 0.044
    CDKN1C 0.808 0.038
    CHAF1A 0.634 0.002 0.779 0.045
    CHN1 0.803 0.034
    CHRAC1 0.751 0.014 0.779 0.021
    COL5A1 0.736 0.012
    COL5A2 0.762 0.013
    COL6A1 0.757 0.032
    COL6A3 0.757 0.019
    CSK 0.663 <.001 0.698 <.001
    CTSK 0.782 0.029
    CXCL12 0.771 0.037
    CXCR7 0.753 0.008
    CYP3A5 0.790 0.035
    DDIT4 0.725 0.017
    DIAPH1 0.771 0.015
    DLC1 0.744 0.004 0.807 0.015
    DLGAP1 0.708 0.004
    DUSP1 0.740 0.034
    EDN1 0.742 0.010
    EGR1 0.731 0.028
    EIF3H 0.761 0.024
    EIF4E 0.786 0.041
    ERBB2 0.664 0.001
    ERBB4 0.764 0.036
    ERCC1 0.804 0.041
    ESR2 0.757 0.025
    EZH2 0.798 0.048
    FAAH 0.798 0.042
    FAM13C 0.764 0.012
    FAM171B 0.755 0.005
    FAM49B 0.811 0.043
    FAM73A 0.778 0.015
    FASLG 0.757 0.041
    FGFR2 0.735 0.016
    FOS 0.690 0.008
    FYN 0.788 0.035 0.777 0.011
    GPNMB 0.762 0.011
    GSK3B 0.792 0.038
    HGD 0.774 0.017
    HIRIP3 0.802 0.033
    HSP90AB1 0.753 0.013
    HSPB1 0.764 0.021
    HSPE1 0.668 0.001
    IFI30 0.732 0.002
    IGF2 0.747 0.006
    IGFBP5 0.691 0.006
    IL6ST 0.748 0.010
    IL8 0.785 0.028
    IMMT 0.708 <.001
    ITGA6 0.747 0.008
    ITGAV 0.792 0.016
    ITGB3 0.814 0.034
    ITPR3 0.769 0.009
    JUN 0.655 0.005
    KHDRBS3 0.764 0.012
    KLF6 0.714 <.001
    KLK2 0.813 0.048
    LAMA4 0.702 0.009
    LAMA5 0.744 0.011
    LAPTM5 0.740 0.009
    LGALS3 0.773 0.036 0.788 0.024
    LIMS1 0.807 0.012
    MAP3K5 0.815 0.034
    MAP3K7 0.809 0.032
    MAP4K4 0.735 0.018 0.761 0.010
    MAPKAPK3 0.754 0.014
    MICA 0.785 0.019
    MTA1 0.808 0.043
    MVP 0.691 0.001
    MYLK3 0.730 0.039
    MYO6 0.780 0.037
    NCOA1 0.787 0.040
    NCOR1 0.876 0.020
    NDRG1 0.761 <.001
    NFAT5 0.770 0.032
    NFKBIA 0.799 0.018
    NME2 0.753 0.005
    NUP62 0.842 0.032
    OAZ1 0.803 0.043
    OLFML2B 0.745 0.023
    OLFML3 0.743 0.009
    OSM 0.726 0.018
    PCA3 0.714 0.019
    PECAM1 0.774 0.023
    PIK3C2A 0.768 0.001
    PIM1 0.725 0.011
    PLOD2 0.713 0.008
    PPP3CA 0.768 0.040
    PROM1 0.482 <.001
    PTEN 0.807 0.012
    PTGS2 0.726 0.011
    PTTG1 0.729 0.006
    PYCARD 0.783 0.012
    RAB30 0.730 0.002
    RAGE 0.792 0.012
    RFX1 0.789 0.016 0.792 0.010
    RGS10 0.781 0.017
    RUNX1 0.747 0.007
    SDHC 0.827 0.036
    SEC23A 0.752 0.010
    SEPT9 0.889 0.006
    SERPINA3 0.738 0.013
    SLC25A21 0.788 0.045
    SMARCD1 0.788 0.010 0.733 0.007
    SMO 0.813 0.035
    SRC 0.758 0.026
    SRD5A2 0.738 0.005
    ST5 0.767 0.022
    STAT5A 0.784 0.039
    TGFB2 0.771 0.027
    TGFB3 0.752 0.036
    THBS2 0.751 0.015
    TNFRSF10B 0.739 0.010
    TPX2 0.754 0.023
    TRAF3IP2 0.774 0.015
    TRAM1 0.868 <.001 0.880 <.001
    TRIM14 0.785 0.047
    TUBB2A 0.705 0.010
    TYMP 0.778 0.024
    UAP1 0.721 0.013
    UTP23 0.763 0.007 0.826 0.018
    VCL 0.837 0.040
    VEGFA 0.755 0.009
    WDR19 0.724 0.005
    YBX1 0.786 0.027
    ZFP36 0.744 0.032
    ZNF827 0.770 0.043
  • Table 11 provides genes that are significantly associated (p<0.05) with cRFI or bRFI after adjustment for Gleason pattern or highest Gleason pattern.
  • TABLE 11
    Genes significantly (p < 0.05) associated with
    cRFI or bRFI after adjustment for Gleason
    pattern in the primary Gleason pattern or highest
    Gleason pattern Some HR <= 1.0 and some HR >1.0
    TABLE 11 cRFI bRFI bRFI
    Official Highest Pattern Primary Pattern Highest Pattern
    Symbol HR p-value HR p-value HR p-value
    HSPA5 0.710 0.009 1.288 0.030
    ODC1 0.741 0.026 1.343 0.004 1.261 0.046
  • Tables 12A and 12B provide genes that are significantly associated (p<0.05) with prostate cancer specific survival (PCSS) in the primary Gleason pattern. Increased expression of genes in Table 12A is negatively associated with good prognosis, while increased expression of genes in Table 12B is positively associated with good prognosis.
  • TABLE 12A
    Genes significantly (p < 0.05)
    associated with prostate cancer
    specific survival (PCSS) in the
    Primary Gleason Pattern HR > 1.0
    (Increased expression is negatively
    associated with good prognosis)
    Official
    Symbol HR p-value
    AKR1C3 1.476 0.016
    ANLN 1.517 0.006
    APOC1 1.285 0.016
    APOE 1.490 0.024
    ASPN 3.055 <.001
    ATP5E 1.788 0.012
    AURKB 1.439 0.008
    BGN 2.640 <.001
    BIRC5 1.611 <.001
    BMP6 1.490 0.021
    BRCA1 1.418 0.036
    CCNB1 1.497 0.021
    CD276 1.668 0.005
    CDC20 1.730 <.001
    CDH11 1.565 0.017
    CDH7 1.553 0.007
    CDKN2B 1.751 0.003
    CDKN2C 1.993 0.013
    CDKN3 1.404 0.008
    CENPF 2.031 <.001
    CHAF1A 1.376 0.011
    CKS2 1.499 0.031
    COL1A1 2.574 <.001
    COL1A2 1.607 0.011
    COL3A1 2.382 <.001
    COL4A1 1.970 <.001
    COL5A2 1.938 0.002
    COL8A1 2.245 <.001
    CTHRC1 2.085 <.001
    CXCR4 1.783 0.007
    DDIT4 1.535 0.030
    DYNLL1 1.719 0.001
    F2R 2.169 <.001
    FAM171B 1.430 0.044
    FAP 1.993 0.002
    FCGR3A 2.099 <.001
    FN1 1.537 0.024
    GPR68 1.520 0.018
    GREM1 1.942 <.001
    IFI30 1.482 0.048
    IGFBP3 1.513 0.027
    INHBA 3.060 <.001
    KIF4A 1.355 0.001
    KLK14 1.187 0.004
    LAPTM5 1.613 0.006
    LTBP2 2.018 <.001
    MMP11 1.869 <.001
    MYBL2 1.737 0.013
    NEK2 1.445 0.028
    NOX4 2.049 <.001
    OLFML2B 1.497 0.023
    PLK1 1.603 0.006
    POSTN 2.585 <.001
    PPFIA3 1.502 0.012
    PTK6 1.527 0.009
    PTTG1 1.382 0.029
    RAD51 1.304 0.031
    RGS7 1.251 <.001
    RRM2 1.515 <.001
    SAT1 1.607 0.004
    SDC1 1.710 0.007
    SESN3 1.399 0.045
    SFRP4 2.384 <.001
    SHMT2 1.949 0.003
    SPARC 2.249 <.001
    STMN1 1.748 0.021
    SULF1 1.803 0.004
    THBS2 2.576 <.001
    THY1 1.908 0.001
    TK1 1.394 0.004
    TOP2A 2.119 <.001
    TPX2 2.074 0.042
    UBE2C 1.598 <.001
    UGT2B15 1.363 0.016
    UHRF1 1.642 0.001
    ZWINT 1.570 0.010
  • TABLE 12B
    Genes significantly (p < 0.05)
    associated with prostate cancer
    specific survival (PCSS) in
    the Primary Gleason
    Pattern HR < 1.0 (Increased
    expression is positively
    associated with good prognosis)
    Official
    Symbol HR p-value
    AAMP 0.649 0.040
    ABCA5 0.777 0.015
    ABCG2 0.715 0.037
    ACOX2 0.673 0.016
    ADH5 0.522 <.001
    ALDH1A2 0.561 <.001
    AMACR 0.693 0.029
    AMPD3 0.750 0.049
    ANPEP 0.531 <.001
    ATXN1 0.640 0.011
    AXIN2 0.657 0.002
    AZGP1 0.617 <.001
    BDKRB1 0.553 0.032
    BIN1 0.658 <.001
    BTRC 0.716 0.011
    C7 0.531 <.001
    CADM1 0.646 0.015
    CASP7 0.538 0.029
    CCNH 0.674 0.001
    CD164 0.606 <.001
    CD44 0.687 0.016
    CDK3 0.733 0.039
    CHN1 0.653 0.014
    COL6A1 0.681 0.015
    CSF1 0.675 0.019
    CSRP1 0.711 0.007
    CXCL12 0.650 0.015
    CYP3A5 0.507 <.001
    CYR61 0.569 0.007
    DLGAP1 0.654 0.004
    DNM3 0.692 0.010
    DPP4 0.544 <.001
    DPT 0.543 <.001
    DUSP1 0.660 0.050
    DUSP6 0.699 0.033
    EGR1 0.490 <.001
    EGR3 0.561 <.001
    EIF5 0.720 0.035
    ERBB3 0.739 0.042
    FAAH 0.636 0.010
    FAM107A 0.541 <.001
    FAM13C 0.526 <.001
    FAS 0.689 0.030
    FGF10 0.657 0.024
    FKBP5 0.699 0.040
    FLNC 0.742 0.036
    FOS 0.556 0.005
    FOXQ1 0.666 0.007
    GADD45B 0.554 0.002
    GDF15 0.659 0.009
    GHR 0.683 0.027
    GPM6B 0.666 0.005
    GSN 0.646 0.006
    GSTM1 0.672 0.006
    GSTM2 0.514 <.001
    HGD 0.771 0.039
    HIRIP3 0.730 0.013
    HK1 0.778 0.048
    HLF 0.581 <.001
    HNF1B 0.643 0.013
    HSD17B10 0.742 0.029
    IER3 0.717 0.049
    IGF1 0.612 <.001
    IGFBP6 0.578 0.003
    IL2 0.528 0.010
    IL6ST 0.574 <.001
    IL8 0.540 0.001
    ING5 0.688 0.015
    ITGA6 0.710 0.005
    ITGA7 0.676 0.033
    JUN 0.506 0.001
    KIT 0.628 0.047
    KLK1 0.523 0.002
    KLK2 0.581 <.001
    KLK3 0.676 <.001
    KRT15 0.684 0.005
    KRT18 0.536 <.001
    KRT5 0.673 0.004
    KRT8 0.613 0.006
    LAMB3 0.740 0.027
    LGALS3 0.678 0.007
    MGST1 0.640 0.002
    MPPED2 0.629 <.001
    MTSS1 0.705 0.041
    MYBPC1 0.534 <.001
    NCAPD3 0.519 <.001
    NFAT5 0.536 <.001
    NRG1 0.467 0.007
    OLFML3 0.646 0.001
    OMD 0.630 0.006
    OR51E2 0.762 0.017
    PAGE4 0.518 <.001
    PCA3 0.581 <.001
    PGF 0.705 0.038
    PPAP2B 0.568 <.001
    PPP1R12A 0.694 0.017
    PRIMA1 0.678 0.014
    PRKCA 0.632 0.001
    PRKCB 0.692 0.028
    PROM1 0.393 0.017
    PTEN 0.689 0.002
    PTGS2 0.611 0.004
    PTH1R 0.629 0.031
    RAB27A 0.721 0.046
    RND3 0.678 0.029
    RNF114 0.714 0.035
    SDHC 0.590 <.001
    SERPINA3 0.710 0.050
    SH3RF2 0.570 0.005
    SLC22A3 0.517 <.001
    SMAD4 0.528 <.001
    SMO 0.751 0.026
    SRC 0.667 0.004
    SRD5A2 0.488 <.001
    STAT5B 0.700 0.040
    SVIL 0.694 0.024
    TFF3 0.701 0.045
    TGFB1I1 0.670 0.029
    TGFB2 0.646 0.010
    TNFRSF10B 0.685 0.014
    TNFSF10 0.532 <.001
    TPM2 0.623 0.005
    TRO 0.767 0.049
    TUBB2A 0.613 0.003
    VEGFB 0.780 0.034
    ZFP36 0.576 0.001
    ZNF827 0.644 0.014
  • Analysis of gene expression and upgrading/upstaging was based on univariate ordinal logistic regression models using weighted maximum likelihood estimators for each gene in the gene list (727 test genes and 5 reference genes). P-values were generated using a Wald test of the null hypothesis that the odds ratio (OR) is one. Both unadjusted p-values and the q-value (smallest FDR at which the hypothesis test in question is rejected) were reported. Un-adjusted p-values <0.05 were considered statistically significant. Since two tumor specimens were selected for each patient, this analysis was performed using the 2 specimens from each patient as follows: (1) analysis using the primary Gleason pattern specimen from each patient (Specimens A1 and B2 as described in Table 2); and (2) analysis using the highest Gleason pattern specimen from each patient (Specimens A1 and B1 as described in Table 2). 200 genes were found to be significantly associated (p<0.05) with upgrading/upstaging in the primary Gleason pattern sample (PGP) and 203 genes were found to be significantly associated (p<0.05) with upgrading/upstaging in the highest Gleason pattern sample (HGP).
  • Tables 13A and 13B provide genes significantly associated (p<0.05), positively or negatively, with upgrading/upstaging in the primary and/or highest Gleason pattern. Increased expression of genes in Table 13A is positively associated with higher risk of upgrading/upstaging (poor prognosis), while increased expression of genes in Table 13B is negatively associated with risk of upgrading/upstaging (good prognosis).
  • TABLE 13A
    Genes significantly (p < 0.05) associated with
    upgrading/upstaging in the Primary Gleason
    Pattern (PGP) and Highest Gleason Pattern
    (HGP) OR > 1.0 (Increased expression is
    positively associated with higher risk of
    upgrading/upstaging (poor prognosis))
    PGP HGP
    Gene OR p-value OR p-value
    ALCAM 1.52 0.0179 1.50 0.0184
    ANLN 1.36 0.0451  .  .
    APOE 1.42 0.0278 1.50 0.0140
    ASPN 1.60 0.0027 2.06 0.0001
    AURKA 1.47 0.0108  .  .
    AURKB  .  . 1.52 0.0070
    BAX  .  . 1.48 0.0095
    BGN 1.58 0.0095 1.73 0.0034
    BIRC5 1.38 0.0415  .  .
    BMP6 1.51 0.0091 1.59 0.0071
    BUB1 1.38 0.0471 1.59 0.0068
    CACNA1D 1.36 0.0474 1.52 0.0078
    CASP7  .  . 1.32 0.0450
    CCNE2 1.54 0.0042  .  .
    CD276  .  . 1.44 0.0265
    CDC20 1.35 0.0445 1.39 0.0225
    CDKN2B  .  . 1.36 0.0415
    CENPF 1.43 0.0172 1.48 0.0102
    CLTC 1.59 0.0031 1.57 0.0038
    COL1A1 1.58 0.0045 1.75 0.0008
    COL3A1 1.45 0.0143 1.47 0.0131
    COL8A1 1.40 0.0292 1.43 0.0258
    CRISP3  .  . 1.40 0.0256
    CTHRC1  .  . 1.56 0.0092
    DBN1 1.43 0.0323 1.45 0.0163
    DIAPH1 1.51 0.0088 1.58 0.0025
    DICER1  .  . 1.40 0.0293
    DIO2  .  . 1.49 0.0097
    DVL1  .  . 1.53 0.0160
    F2R 1.46 0.0346 1.63 0.0024
    FAP 1.47 0.0136 1.74 0.0005
    FCGR3A  .  . 1.42 0.0221
    HPN  .  . 1.36 0.0468
    HSD17B4  .  . 1.47 0.0151
    HSPA8 1.65 0.0060 1.58 0.0074
    IL11 1.50 0.0100 1.48 0.0113
    IL1B 1.41 0.0359  .  .
    INHBA 1.56 0.0064 1.71 0.0042
    KHDRBS3 1.43 0.0219 1.59 0.0045
    KIF4A  .  . 1.50 0.0209
    KPNA2 1.40 0.0366  .  .
    KRT2  .  . 1.37 0.0456
    KRT75  .  . 1.44 0.0389
    MANF  .  . 1.39 0.0429
    MELK 1.74 0.0016  .  .
    MKI67 1.35 0.0408  .  .
    MMP11  .  . 1.56 0.0057
    NOX4 1.49 0.0105 1.49 0.0138
    PLAUR 1.44 0.0185  .  .
    PLK1  .  . 1.41 0.0246
    PTK6  .  . 1.36 0.0391
    RAD51  .  . 1.39 0.0300
    RAF1  .  . 1.58 0.0036
    RRM2 1.57 0.0080  .  .
    SESN3 1.33 0.0465  .  .
    SFRP4 2.33 <0.0001 2.51 0.0015
    SKIL 1.44 0.0288 1.40 0.0368
    SOX4 1.50 0.0087 1.59 0.0022
    SPINK1 1.52 0.0058  .  .
    SPP1  .  . 1.42 0.0224
    THBS2  .  . 1.36 0.0461
    TK1  .  . 1.38 0.0283
    TOP2A 1.85 0.0001 1.66 0.0011
    TPD52 1.78 0.0003 1.64 0.0041
    TPX2 1.70 0.0010  .  .
    UBE2G1 1.38 0.0491  .  .
    UBE2T 1.37 0.0425 1.46 0.0162
    UHRF1  .  . 1.43 0.0164
    VCPIP1  .  . 1.37 0.0458
  • TABLE 13B
    Genes significantly (p < 0.05) associated with
    upgrading/upstaging in the Primary Gleason
    Pattern (PGP) and Highest Gleason Pattern
    (HGP) OR < 1.0 (Increased expression is
    negatively associated with higher risk of
    upgrading/upstaging (good prognosis))
    PGP HGP
    Gene OR p-value OR p-value
    ABCC3  .    . 0.70   0.0216
    ABCC8 0.66   0.0121  .    .
    ABCG2 0.67   0.0208 0.61   0.0071
    ACE  .    . 0.73   0.0442
    ACOX2 0.46   0.0000 0.49   0.0001
    ADH5 0.69   0.0284 0.59   0.0047
    AIG1  .    . 0.60   0.0045
    AKR1C1  .    . 0.66   0.0095
    ALDH1A2 0.36 <0.0001 0.36 <0.0001
    ALKBH3 0.70   0.0281 0.61   0.0056
    ANPEP  .    . 0.68   0.0109
    ANXA2 0.73   0.0411 0.66   0.0080
    APC  .    . 0.68   0.0223
    ATXN1  .    . 0.70   0.0188
    AXIN2 0.60   0.0072 0.68   0.0204
    AZGP1 0.66   0.0089 0.57   0.0028
    BCL2 .    . 0.71   0.0182
    BIN1 0.55   0.0005  .    .
    BTRC 0.69   0.0397 0.70   0.0251
    C7 0.53   0.0002 0.51 <0.0001
    CADM1 0.57   0.0012 0.60   0.0032
    CASP1 0.64   0.0035 0.72   0.0210
    CAV1 0.64   0.0097 0.59   0.0032
    CAV2  .    . 0.58   0.0107
    CD164  .    . 0.69   0.0260
    CD82 0.67   0.0157 0.69   0.0167
    CDH1 0.61   0.0012 0.70   0.0210
    CDK14 0.70   0.0354  .    .
    CDK3  .    . 0.72   0.0267
    CDKN1C 0.61   0.0036 0.56   0.0003
    CHN1 0.71   0.0214  .    .
    COL6A1 0.62   0.0125 0.60   0.0050
    COL6A3 0.65   0.0080 0.68   0.0181
    CSRP1 0.43   0.0001 0.40   0.0002
    CTSB 0.66   0.0042 0.67   0.0051
    CTSD 0.64   0.0355  .    .
    CTSK 0.69   0.0171  .    .
    CTSL1 0.72   0.0402  .    .
    CUL1 0.61   0.0024 0.70   0.0120
    CXCL12 0.69   0.0287 0.63   0.0053
    CYP3A5 0.68   0.0099 0.62   0.0026
    DDR2 0.68   0.0324 0.62   0.0050
    DES 0.54   0.0013 0.46   0.0002
    DHX9 0.67   0.0164  .    .
    DLGAP1  .    . 0.66   0.0086
    DPP4 0.69   0.0438 0.69   0.0132
    DPT 0.59   0.0034 0.51   0.0005
    DUSP1  .    . 0.67   0.0214
    EDN1  .    . 0.66   0.0073
    EDNRA 0.66   0.0148 0.54   0.0005
    EIF2C2  .    . 0.65   0.0087
    ELK4 0.55   0.0003 0.58   0.0013
    ENPP2 0.65   0.0128 0.59   0.0007
    EPHA3 0.71   0.0397 0.73   0.0455
    EPHB2 0.60   0.0014  .    .
    EPHB4 0.73   0.0418  .    .
    EPHX3  .    . 0.71   0.0419
    ERCC1 0.71   0.0325  .    .
    FAM107A 0.56   0.0008 0.55   0.0011
    FAM13C 0.68   0.0276 0.55   0.0001
    FAS 0.72   0.0404  .    .
    FBN1 0.72   0.0395  .    .
    FBXW7 0.69   0.0417  .    .
    FGF10 0.59   0.0024 0.51   0.0001
    FGF7 0.51   0.0002 0.56   0.0007
    FGFR2 0.54   0.0004 0.47 <0.0001
    FLNA 0.58   0.0036 0.50   0.0002
    FLNC 0.45   0.0001 0.40 <0.0001
    FLT4 0.61   0.0045  .    .
    FOXO1 0.55   0.0005 0.53   0.0005
    FOXP3 0.71   0.0275 0.72   0.0354
    GHR 0.59   0.0074 0.53   0.0001
    GNRH1 0.72   0.0386  .    .
    GPM6B 0.59   0.0024 0.52   0.0002
    GSN 0.65   0.0107 0.65   0.0098
    GSTM1 0.44 <0.0001 0.43 <0.0001
    GSTM2 0.42 <0.0001 0.39 <0.0001
    HLF 0.46 <0.0001 0.47   0.0001
    HPS1 0.64   0.0069 0.69   0.0134
    HSPA5 0.68   0.0113  .    .
    HSPB2 0.61   0.0061 0.55   0.0004
    HSPG2 0.70   0.0359  .    .
    ID3  .    . 0.70   0.0245
    IGF1 0.45 <0.0001 0.50   0.0005
    IGF2 0.67   0.0200 0.68   0.0152
    IGFBP2 0.59   0.0017 0.69   0.0250
    IGFBP6 0.49 <0.0001 0.64   0.0092
    IL6ST 0.56   0.0009 0.60   0.0012
    ILK 0.51   0.0010 0.49   0.0004
    ITGA1 0.58   0.0020 0.58   0.0016
    ITGA3 0.71   0.0286 0.70   0.0221
    ITGA5  .    . 0.69   0.0183
    ITGA7 0.56   0.0035 0.42 <0.0001
    ITGB1 0.63   0.0095 0.68   0.0267
    ITGB3 0.62   0.0043 0.62   0.0040
    ITPR1 0.62   0.0032  .    .
    JUN 0.73   0.0490 0.68   0.0152
    KIT 0.55   0.0003 0.57   0.0005
    KLC1  .    . 0.70   0.0248
    KLK1  .    . 0.60   0.0059
    KRT15 0.58   0.0009 0.45 <0.0001
    KRT5 0.70   0.0262 0.59   0.0008
    LAMA4 0.56   0.0359 0.68   0.0498
    LAMB3  .    . 0.60   0.0017
    LGALS3 0.58   0.0007 0.56   0.0012
    LRP1 0.69   0.0176  .    .
    MAP3K7 0.70   0.0233 0.73   0.0392
    MCM3 0.72   0.0320  .    .
    MMP2 0.66   0.0045 0.60   0.0009
    MMP7 0.61   0.0015 0.65   0.0032
    MMP9 0.64   0.0057 0.72   0.0399
    MPPED2 0.72   0.0392 0.63   0.0042
    MTA1  .    . 0.68   0.0095
    MTSS1 0.58   0.0007 0.71   0.0442
    MVP 0.57   0.0003 0.70   0.0152
    MYBPC1  .    . 0.70   0.0359
    NCAM1 0.63   0.0104 0.64   0.0080
    NCAPD3 0.67   0.0145 0.64   0.0128
    NEXN 0.54   0.0004 0.55   0.0003
    NFAT5 0.72   0.0320 0.70   0.0177
    NUDT6 0.66   0.0102  .    .
    OLFML3 0.56   0.0035 0.51   0.0011
    OMD 0.61   0.0011 0.73   0.0357
    PAGE4 0.42 <0.0001 0.36 <0.0001
    PAK6 0.72   0.0335  .    .
    PCDHGB7 0.70   0.0262 0.55   0.0004
    PGF 0.72   0.0358 0.71   0.0270
    PLP2 0.66   0.0088 0.63   0.0041
    PPAP2B 0.44 <0.0001 0.50   0.0001
    PPP1R12A 0.45   0.0001 0.40 <0.0001
    PRIMA1  .    . 0.63   0.0102
    PRKAR2B 0.71   0.0226  .    .
    PRKCA 0.34 <0.0001 0.42 <0.0001
    PRKCB 0.66   0.0120 0.49 <0.0001
    PROM1 0.61   0.0030  .    .
    PTEN 0.59   0.0008 0.55   0.0001
    PTGER3 0.67   0.0293  .    .
    PTH1R 0.69   0.0259 0.71   0.0327
    PTK2 0.75   0.0461  .    .
    PTK2B 0.70   0.0244 0.74   0.0388
    PYCARD 0.73   0.0339 0.67   0.0100
    RAD9A 0.64   0.0124  .    .
    RARB 0.67   0.0088 0.65   0.0116
    RGS10 0.70   0.0219  .    .
    RHOB  .    . 0.72   0.0475
    RND3  .    . 0.67   0.0231
    SDHC 0.72   0.0443  .    .
    SEC23A 0.66   0.0101 0.53   0.0003
    SEMA3A 0.51   0.0001 0.69   0.0222
    SH3RF2 0.55   0.0002 0.54   0.0002
    SLC22A3 0.48   0.0001 0.50   0.0058
    SMAD4 0.49   0.0001 0.50   0.0003
    SMARCC2 0.59   0.0028 0.65   0.0052
    SMO 0.60   0.0048 0.52 <0.0001
    SORBS1 0.56   0.0024 0.48   0.0002
    SPARCL1 0.43   0.0001 0.50   0.0001
    SRD5A2 0.26 <0.0001 0.31 <0.0001
    ST5 0.63   0.0103 0.52   0.0006
    STAT5A 0.60   0.0015 0.61   0.0037
    STAT5B 0.54   0.0005 0.57   0.0008
    SUMO1 0.65   0.0066 0.66   0.0320
    SVIL 0.52   0.0067 0.46   0.0003
    TGFB1I1 0.44   0.0001 0.43   0.0000
    TGFB2 0.55   0.0007 0.58   0.0016
    TGFB3 0.57   0.0010 0.53   0.0005
    TIMP1 0.72   0.0224  .    .
    TIMP2 0.68   0.0198 0.69   0.0206
    TIMP3 0.67   0.0105 0.64   0.0065
    TMPRSS2  .    . 0.72   0.0366
    TNFRSF10A 0.71   0.0181  .    .
    TNFSF10 0.71   0.0284  .    .
    TOP2B 0.73   0.0432  .    .
    TP63 0.62   0.0014 0.50 <0.0001
    TPM1 0.54   0.0007 0.52   0.0002
    TPM2 0.41 <0.0001 0.40 <0.0001
    TPP2 0.65   0.0122  .    .
    TRA2A 0.72   0.0318  .    .
    TRAF3IP2 0.62   0.0064 0.59   0.0053
    TRO 0.57   0.0003 0.51   0.0001
    VCL 0.52   0.0005 0.52   0.0004
    VIM 0.65   0.0072 0.65   0.0045
    WDR19 0.66   0.0097  .    .
    WFDC1 0.58   0.0023 0.60   0.0026
    ZFHX3 0.69   0.0144 0.62   0.0046
    ZNF827 0.62   0.0030 0.53   0.0001
    • Example 3: Identification of MicroRNAs Associated with Clinical Recurrence and Death Due to Prostate Cancer
  • MicroRNAs function by binding to portions of messenger RNA (mRNA) and changing how frequently the mRNA is translated into protein. They can also influence the turnover of mRNA and thus how long the mRNA remains intact in the cell. Since microRNAs function primarily as an adjunct to mRNA, this study evaluated the joint prognostic value of microRNA expression and gene (mRNA) expression. Since the expression of certain microRNAs may be a surrogate for expression of genes that are not in the assessed panel, we also evaluated the prognostic value of microRNA expression by itself.
  • Patients and Samples
  • Samples from the 127 patients with clinical recurrence and 374 patients without clinical recurrence after radical prostatectomy described in Example 2 were used in this study. The final analysis set comprised 416 samples from patients in which both gene expression and microRNA expression were successfully assayed. Of these, 106 patients exhibited clinical recurrence and 310 did not have clinical recurrence. Tissue samples were taken from each prostate sample representing (1) the primary Gleason pattern in the sample, and (2) the highest Gleason pattern in the sample. In addition, a sample of histologically normal-appearing tissue adjacent to the tumor (NAT) was taken. The number of patients in the analysis set for each tissue type and the number of them who experienced clinical recurrence or death due to prostate cancer are shown in Table 14.
  • TABLE 14
    Number of Patients and Events in Analysis Set
    Clinical Deaths Due to
    Patients Recurrences Prostate Cancer
    Primary Gleason 416 106 36
    Pattern Tumor Tissue
    Highest Gleason 405 102 36
    Pattern Tumor Tissue
    Normal Adjacent 364  81 29
    Tissue
  • Assay Method
  • Expression of 76 test microRNAs and 5 reference microRNAs were determined from RNA extracted from fixed paraffin-embedded (FPE) tissue. MicroRNA expression in all three tissue type was quantified by reverse transcriptase polymerase chain reaction (RT-PCR) using the crossing point (Cp) obtained from the Taqman® MicroRNA Assay kit (Applied Biosystems, Inc., Carlsbad, Calif.).
  • Statistical Analysis
  • Using univariate proportional hazards regression (Cox DR, Journal of the Royal Statistical Society, Series B 34:187-220, 1972), applying the sampling weights from the cohort sampling design, and using variance estimation based on the Lin and Wei method (Lin and Wei, Journal of the American Statistical Association 84:1074-1078, 1989), microRNA expression, normalized by the average expression for the 5 reference microRNAs hsa-miR-106a, hsa-miR-146b-5p, hsa-miR-191, hsa-miR-19b, and hsa-miR-92a, and reference-normalized gene expression of the 733 genes (including the reference genes) discussed above, were assessed for association with clinical recurrence and death due to prostate cancer. Standardized hazard ratios (the proportional change in the hazard associated with a change of one standard deviation in the covariate value) were calculated.
  • This analysis included the following classes of predictors:
  • 1. MicroRNAs alone
  • 2. MicroRNA-gene pairs Tier 1
  • 3. MicroRNA-gene pairs Tier 2
  • 4. MicroRNA-gene pairs Tier 3
  • 5. All other microRNA-gene pairs Tier 4
  • The four tiers were pre-determined based on the likelihood (Tier 1 representing the highest likelihood) that the gene-microRNA pair functionally interacted or that the microRNA was related to prostate cancer based on a review of the literature and existing microarray data sets.
  • False discovery rates (FDR) (Benjamini and Hochberg, Journal of the Royal Statistical Society, Series B 57:289-300, 1995) were assessed using Efron's separate class methodology (Efron, Annals of Applied Statistics 2:197-223, 2008). The false discovery rate is the expected proportion of the rejected null hypotheses that are rejected incorrectly (and thus are false discoveries). Efron's methodology allows separate FDR assessment (q-values) (Storey, Journal of the Royal Statistical Society, Series B 64:479-498, 2002) within each class while utilizing the data from all the classes to improve the accuracy of the calculation. In this analysis, the q-value for a microRNA or microRNA-gene pair can be interpreted as the empirical Bayes probability that the microRNA or microRNA-gene pair identified as being associated with clinical outcome is in fact a false discovery given the data. The separate class approach was applied to a true discovery rate degree of association (TDRDA) analysis (Crager, Statistics in Medicine 29:33-45, 2010) to determine sets of microRNAs or microRNA-gene pairs that have standardized hazard ratio for clinical recurrence or prostate cancer-specific death of at least a specified amount while controlling the FDR at 10%. For each microRNA or microRNA-gene pair, a maximum lower bound (MLB) standardized hazard ratio was computed, showing the highest lower bound for which the microRNA or microRNA-gene pair was included in a TDRDA set with 10% FDR. Also calculated was an estimate of the true standardized hazard ratio corrected for regression to the mean (RM) that occurs in subsequent studies when the best predictors are selected from a long list (Crager, 2010 above). The RM-corrected estimate of the standardized hazard ratio is a reasonable estimate of what could be expected if the selected microRNA or microRNA-gene pair were studied in a separate, subsequent study.
  • These analyses were repeated adjusting for clinical and pathology covariates available at the time of patient biopsy: biopsy Gleason score, baseline PSA level, and clinical T-stage (T1-T2A vs. T2B or T2C) to assess whether the microRNAs or microRNA-gene pairs have predictive value independent of these clinical and pathology covariates.
    • Results
  • The analysis identified 21 microRNAs assayed from primary Gleason pattern tumor tissue that were associated with clinical recurrence of prostate cancer after radical prostatectomy, allowing a false discovery rate of 10% (Table 15). Results were similar for microRNAs assessed from highest Gleason pattern tumor tissue (Table 16), suggesting that the association of microRNA expression with clinical recurrence does not change markedly depending on the location within a tumor tissue sample. No microRNA assayed from normal adjacent tissue was associated with the risk of clinical recurrence at a false discovery rate of 10%. The sequences of the microRNAs listed in Tables 15-21 are shown in Table B.
  • TABLE 15
    MicroRNAs Associated with Clinical Recurrence of Prostate Cancer
    Primary Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Direction Uncor- 95% Max. Lower RM-
    q-valuea of Asso- rected Confidence Bound Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval @10% FDR Estimatec
    hsa-miR-93 <0.0001 0.0% (+) 1.79 (1.38, 2.32) 1.19 1.51
    hsa-miR-106b <0.0001 0.1% (+) 1.80 (1.38,2.34) 1.19 1.51
    hsa-miR-30e-5p <0.0001 0.1% (−) 1.63 (1.30, 2.04) 1.18 1.46
    hsa-miR-21 <0.0001 0.1% (+) 1.66 (1.31,2.09) 1.18 1.46
    hsa-miR-133a <0.0001 0.1% (−) 1.72 (1.33, 2.21) 1.18 1.48
    hsa-miR-449a <0.0001 0.1% (+) 1.56 (1.26, 1.92) 1.17 1.42
    hsa-miR-30a 0.0001 0.1% (−) 1.56 (1.25, 1.94) 1.16 1.41
    hsa-miR-182 0.0001 0.2% (+) 1.74 (1.31, 2.31) 1.17 1.45
    hsa-miR-27a 0.0002 0.2% (+) 1.65 (1.27, 2.14) 1.16 1.43
    hsa-miR-222 0.0006 0.5% (−) 1.47 (1.18, 1.84) 1.12 1.35
    hsa-miR-103 0.0036 2.1% (+) 1.77 (1.21, 2.61) 1.12 1.36
    hsa-miR-1 0.0037 2.2% (−) 1.32 (1.10, 1.60) 1.07 1.26
    hsa-miR-145 0.0053 2.9% (−) 1.34 (1.09, 1.65) 1.07 1.27
    hsa-miR-141 0.0060 3.2% (+) 1.43 (1.11, 1.84) 1.07 1.29
    hsa-miR-92a 0.0104 4.8% (+) 1.32 (1.07, 1.64) 1.05 1.25
    hsa-miR-22 0.0204 7.7% (+) 1.31 (1.03, 1.64) 1.03 1.23
    hsa-miR-29b 0.0212 7.9% (+) 1.36 (1.03, 1.76) 1.03 1.24
    hsa-miR-210 0.0223 8.2% (+) 1.33 (1.03, 1.70) 1.00 1.23
    hsa-miR-486-5p 0.0267 9.4% (−) 1.25 (1.00, 1.53) 1.00 1.20
    hsa-miR-19b 0.0280 9.7% (−) 1.24 (1.00, 1.50) 1.00 1.19
    hsa-miR-205 0.0289 10.0% (−) 1.25 (1.00, 1.53) 1.00 1.20
    aThe q-value is the empirical Bayes probability that the microRNA's association with clinical recurrence is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of clinical recurrence.
    cRM: regression to the mean.
  • TABLE 16
    MicroRNAs Associated with Clinical Recurrence of Prostate Cancer
    Highest Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Direction Uncor- 95% Max. Lower RM-
    q-valuea of Asso- rected Confidence Bound Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval @10% FDR Estimatec
    hsa-miR-93 <0.0001 0.0% (+) 1.91 (1.48, 2.47) 1.24 1.59
    hsa-miR-449a <0.0001 0.0% (+) 1.75 (1.40, 2.18) 1.23 1.54
    hsa-miR-205 <0.0001 0.0% (−) 1.53 (1.29, 1.81) 1.20 1.43
    hsa-miR-19b <0.0001 0.0% (−) 1.37 (1.19, 1.57) 1.15 1.32
    hsa-miR-106b <0.0001 0.0% (+) 1.84 (1.39, 2.42) 1.22 1.51
    hsa-miR-21 <0.0001 0.0% (+) 1.68 (1.32, 2.15) 1.19 1.46
    hsa-miR-30a 0.0005 0.4% (−) 1.44 (1.17, 1.76) 1.13 1.33
    hsa-miR-30e-5p 0.0010 0.6% (−) 1.37 (1.14, 1.66) 1.11 1.30
    hsa-miR-133a 0.0015 0.8% (−) 1.57 (1.19, 2.07) 1.13 1.36
    hsa-miR-1 0.0016 0.8% (−) 1.42 (1.14, 1.77) 1.11 1.31
    hsa-miR-103 0.0021 1.1% (+) 1.69 (1.21, 2.37) 1.13 1.37
    hsa-miR-210 0.0024 1.2% (+) 1.43 (1.13, 1.79) 1.11 1.31
    hsa-miR-182 0.0040 1.7% (+) 1.48 (1.13, 1.93) 1.11 1.31
    hsa-miR-27a 0.0055 2.1% (+) 1.46 (1.12, 1.91) 1.09 1.30
    hsa-miR-222 0.0093 3.2% (−) 1.38 (1.08, 1.77) 1.08 1.27
    hsa-miR-331 0.0126 3.9% (+) 1.38 (1.07, 1.77) 1.07 1.26
    hsa-miR-191* 0.0143 4.3% (+) 1.38 (1.06, 1.78) 1.07 1.26
    hsa-miR-425 0.0151 4.5% (+) 1.40 (1.06, 1.83) 1.07 1.26
    hsa-miR-31 0.0176 5.1% (−) 1.29 (1.04, 1.60) 1.05 1.22
    hsa-miR-92a 0.0202 5.6% (+) 1.31 (1.03, 1.65) 1.05 1.23
    hsa-miR-155 0.0302 7.6% (−) 1.32 (1.00, 1.69) 1.03 1.22
    hsa-miR-22 0.0437 9.9% (+) 1.30 (1.00, 1.67) 1.00 1.21
    aThe q-value is the empirical Bayes probability that the microRNA's association with death due to prostate cancer is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of clinical recurrence.
    cRM: regression to the mean.
  • Table 17 shows microRNAs assayed from primary Gleason pattern tissue that were identified as being associated with the risk of prostate-cancer-specific death, with a false discovery rate of 10%. Table 18 shows the corresponding analysis for microRNAs assayed from highest Gleason pattern tissue. No microRNA assayed from normal adjacent tissue was associated with the risk of prostate-cancer-specific death at a false discovery rate of 10%.
  • TABLE 17
    MicroRNAs Associated with Death Due to Prostate Cancer
    Primary Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Max.
    Lower
    Direction Uncor- 95% Bound RM-
    q-valuea of Asso- rected Confidence @10% Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval FDR Estimatec
    hsa-miR-30e-5p 0.0001 0.6% (−) 1.88 (1.37, 2.58) 1.15 1.46
    hsa-miR-30a 0.0001 0.7% (−) 1.78 (1.33, 2.40) 1.14 1.44
    hsa-miR-133a 0.0005 1.2% (−) 1.85 (1.31, 2.62) 1.13 1.41
    hsa-miR-222 0.0006 1.4% (−) 1.65 (1.24, 2.20) 1.12 1.38
    hsa-miR-106b 0.0024 2.7% (+) 1.85 (1.24, 2.75) 1.11 1.35
    hsa-miR-1 0.0028 3.0% (−) 1.43 (1.13, 1.81) 1.08 1.30
    hsa-miR-21 0.0034 3.3% (+) 1.63 (1.17, 2.25) 1.09 1.33
    hsa-miR-93 0.0044 3.9% (+) 1.87 (1.21, 2.87) 1.09 1.32
    hsa-miR-26a 0.0072 5.3% (−) 1.47 (1.11, 1.94) 1.07 1.29
    hsa-miR-152 0.0090 6.0% (−) 1.46 (1.10, 1.95) 1.06 1.28
    hsa-miR-331 0.0105 6.5% (+) 1.46 (1.09, 1.96) 1.05 1.27
    hsa-miR-150 0.0159 8.3% (+) 1.51 (1.07, 2.10) 1.03 1.27
    hsa-miR-27b 0.0160 8.3% (+) 1.97 (1.12, 3.42) 1.05 1.25
    aThe q-value is the empirical Bayes probability that the microRNA's association with death due to prostate cancer endpoint is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of death due to prostate cancer.
    cRM: regression to the mean.
  • TABLE 18
    MicroRNAs Associated with Death Due to Prostate Cancer
    Highest Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Max.
    Lower
    Direction Uncor- 95% Bound RM-
    q-valuea of Asso- rected Confidence @10% Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval FDR Estimatec
    hsa-miR-27b 0.0016 6.1% (+) 2.66 (1.45, 4.88) 1.07 1.32
    hsa-miR-21 0.0020 6.4% (+) 1.66 (1.21, 2.30) 1.05 1.34
    hsa-miR-10a 0.0024 6.7% (+) 1.78 (1.23, 2.59) 1.05 1.34
    hsa-miR-93 0.0024 6.7% (+) 1.83 (1.24, 2.71) 1.05 1.34
    hsa-miR-106b 0.0028 6.8% (+) 1.79 (1.22, 2.63) 1.05 1.33
    hsa-miR-150 0.0035 7.1% (+) 1.61 (1.17, 2.22) 1.05 1.32
    hsa-miR-1 0.0104 9.0% (−) 1.52 (1.10, 2.09) 1.00 1.28
    aThe q-value is the empirical Bayes probability that the microRNA's association with clinical endpoint is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of death due to prostate cancer.
    cRM: regression to the mean.
  • Table 19 and Table 20 shows the microRNAs that can be identified as being associated with the risk of clinical recurrence while adjusting for the clinical and pathology covariates of biopsy Gleason score, baseline PSA level, and clinical T-stage. The distributions of these covariates are shown in FIG. 1. Fifteen (15) of the microRNAs identified in Table 15 are also present in Table 19, indicating that these microRNAs have predictive value for clinical recurrence that is independent of the Gleason score, baseline PSA, and clinical T-stage.
  • Two microRNAs assayed from primary Gleason pattern tumor tissue were found that had predictive value for death due to prostate cancer independent of Gleason score, baseline PSA, and clinical T-stage (Table 21).
  • TABLE 19
    MicroRNAs Associated with Clinical Recurrence of Prostate Cancer
    Adjusting for Biopsy Gleason Score, Baseline PSA Level, and Clinical
    T-Stage Primary Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Max.
    Lower
    Direction Uncor- 95% Bound RM-
    q-valuea of Asso- rected Confidence @10% Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval FDR Estimatec
    hsa-miR-30e-5p <0.0001 0.0% (−) 1.80 (1.42, 2.27) 1.23 1.53
    hsa-miR-30a <0.0001 0.0% (−) 1.75 (1.40, 2.19) 1.22 1.51
    hsa-miR-93 <0.0001 0.1% (+) 1.70 (1.32, 2.20) 1.19 1.44
    hsa-miR-449a 0.0001 0.1% (+) 1.54 (1.25, 1.91) 1.17 1.39
    hsa-miR-133a 0.0001 0.1% (−) 1.58 (1.25, 2.00) 1.17 1.39
    hsa-miR-27a 0.0002 0.1% (+) 1.66 (1.28, 2.16) 1.17 1.41
    hsa-miR-21 0.0003 0.2% (+) 1.58 (1.23, 2.02) 1.16 1.38
    hsa-miR-182 0.0005 0.3% (+) 1.56 (1.22, 1.99) 1.15 1.37
    hsa-miR-106b 0.0008 0.5% (+) 1.57 (1.21, 2.05) 1.15 1.36
    hsa-miR-222 0.0028 1.1% (−) 1.39 (1.12, 1.73) 1.11 1.28
    hsa-miR-103 0.0048 1.7% (+) 1.69 (1.17, 2.43) 1.13 1.32
    hsa-miR-486-5p 0.0059 2.0% (−) 1.34 (1.09, 1.65) 1.09 1.25
    hsa-miR-1 0.0083 2.7% (−) 1.29 (1.07, 1.57) 1.07 1.23
    hsa-miR-141 0.0088 2.8% (+) 1.43 (1.09, 1.87) 1.09 1.27
    hsa-miR-200c 0.0116 3.4% (+) 1.39 (1.07, 1.79) 1.07 1.25
    hsa-miR-145 0.0201 5.1% (−) 1.27 (1.03, 1.55) 1.05 1.20
    hsa-miR-206 0.0329 7.2% (−) 1.40 (1.00, 1.91) 1.05 1.23
    hsa-miR-29b 0.0476 9.4% (+) 1.30 (1.00, 1.69) 1.00 1.20
    aThe q-value is the empirical Bayes probability that the microRNA's association with clinical recurrence is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of clinical recurrence.
    cRM: regression to the mean.
  • TABLE 20
    MicroRNAs Associated with Clinical Recurrence of Prostate Cancer
    Adjusting for Biopsy Gleason Score, Baseline PSA Level, and Clinical T-Stage
    Highest Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Max.
    Lower
    Direction Uncor- 95% Bound RM-
    q-valuea of Asso- rected Confidence @10% Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval FDR Estimatec
    hsa-miR-30a <0.0001 0.0% (−) 1.62 (1.32, 1.99) 1.20 1.43
    hsa-miR-30e-5p <0.0001 0.0% (−) 1.53 (1.27, 1.85) 1.19 1.39
    hsa-miR-93 <0.0001 0.0% (+) 1.76 (1.37, 2.26) 1.20 1.45
    hsa-miR-205 <0.0001 0.0% (−) 1.47 (1.23, 1.74) 1.18 1.36
    hsa-miR-449a 0.0001 0.1% (+) 1.62 (1.27, 2.07) 1.18 1.38
    hsa-miR-106b 0.0003 0.2% (+) 1.65 (1.26, 2.16) 1.17 1.36
    hsa-miR-133a 0.0005 0.2% (−) 1.51 (1.20, 1.90) 1.16 1.33
    hsa-miR-1 0.0007 0.3% (−) 1.38 (1.15, 1.67) 1.13 1.28
    hsa-miR-210 0.0045 1.2% (+) 1.35 (1.10, 1.67) 1.11 1.25
    hsa-miR-182 0.0052 1.3% (+) 1.40 (1.10, 1.77) 1.11 1.26
    hsa-miR-425 0.0066 1.6% (+) 1.48 (1.12, 1.96) 1.12 1.26
    hsa-miR-155 0.0073 1.8% (−) 1.36 (1.09, 1.70) 1.10 1.24
    hsa-miR-21 0.0091 2.1% (+) 1.42 (1.09, 1.84) 1.10 1.25
    hsa-miR-222 0.0125 2.7% (−) 1.34 (1.06, 1.69) 1.09 1.23
    hsa-miR-27a 0.0132 2.8% (+) 1.40 (1.07, 1.84) 1.09 1.23
    hsa-miR-191* 0.0150 3.0% (+) 1.37 (1.06, 1.76) 1.09 1.23
    hsa-miR-103 0.0180 3.4% (+) 1.45 (1.06, 1.98) 1.09 1.23
    hsa-miR-31 0.0252 4.3% (−) 1.27 (1.00, 1.57) 1.07 1.19
    hsa-miR-19b 0.0266 4.5% (−) 1.29 (1.00, 1.63) 1.07 1.20
    hsa-miR-99a 0.0310 5.0% (−) 1.26 (1.00, 1.56) 1.06 1.18
    hsa-miR-92a 0.0348 5.4% (+) 1.31 (1.00, 1.69) 1.06 1.19
    hsa-miR-146b-5p 0.0386 5.8% (−) 1.29 (1.00, 1.65) 1.06 1.19
    hsa-miR-145 0.0787 9.7% (−) 1.23 (1.00, 1.55) 1.00 1.15
    aThe q-value is the empirical Bayes probability that the microRNA's association with clinical clinical recurrence is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of clinical recurrence.
    cRM: regression to the mean.
  • TABLE 21
    MicroRNAs Associated with Death Due to Prostate Cancer
    Adjusting for Biopsy Gleason Score, Baseline PSA Level, and Clinical
    T-Stage Primary Gleason Pattern Tumor Tissue
    Absolute Standardized Hazard Ratio
    Max.
    Lower
    Direction Uncor- 95% Bound RM-
    q-valuea of Asso- rected Confidence @10% Corrected
    MicroRNA p-value (FDR) ciationb Estimate Interval FDR Estimatec
    hsa-miR-30e-5p 0.0001 2.9% (−) 1.97 (1.40, 2.78) 1.09 1.39
    hsa-miR-30a 0.0002 3.3% (−) 1.90 (1.36, 2.65) 1.08 1.38
    aThe q-value is the empirical Bayes probability that the microRNA's association with clinical recurrence is a false discovery, given the data.
    bDirection of association indicates where higher microRNA expression is associated with higher (+) or lower (−) risk of clinical recurrence.
    cRM: regression to the mean.
  • Accordingly, the normalized expression levels of hsa-miR-93; hsa-miR-106b; hsa-miR-21; hsa-miR-449a; hsa-miR-182; hsa-miR-27a; hsa-miR-103; hsa-miR-141; hsa-miR-92a; hsa-miR-22; hsa-miR-29b; hsa-miR-210; hsa-miR-331; hsa-miR-191; hsa-miR-425; and hsa-miR-200c are positively associated with an increased risk of recurrence; and hsa-miR-30e-5p; hsa-miR-133a; hsa-miR-30a; hsa-miR-222; hsa-miR-1; hsa-miR-145; hsa-miR-486-5p; hsa-miR-19b; hsa-miR-205; hsa-miR-31; hsa-miR-155; hsa-miR-206; hsa-miR-99a; and hsa-miR-146b-5p are negatively associated with an increased risk of recurrence.
  • Furthermore, the normalized expression levels of hsa-miR-106b; hsa-miR-21; hsa-miR-93; hsa-miR-331; hsa-miR-150; hsa-miR-27b; and hsa-miR-10a are positively associated with an increased risk of prostate cancer specific death; and the normalized expression levels of hsa-miR-30e-5p; hsa-miR-30a; hsa-miR-133a; hsa-miR-222; hsa-miR-1; hsa-miR-26a; and hsa-miR-152 are negatively associated with an increased risk of prostate cancer specific death.
  • Table 22 shows the number of microRNA-gene pairs that were grouped in each tier (Tiers 1-4) and the number and percentage of those that were predictive of clinical recurrence at a false discovery rate of 10%.
  • TABLE 22
    Number of Pairs
    Total Predictive of Clinical
    Number of Recurrence at False
    MicroRNA- Discovery Rate 10%
    Tier Gene Pairs (%)
    Tier 1    80    46 (57.5%)
    Tier 2   719   591 (82.2%)
    Tier 3  3,850  2,792 (72.5%)
    Tier 4 54,724 38,264 (69.9%)
  • TABLE A
    SEQ SEQ
    Official Accession ID ID
    Symbol: Number: NO Forward Primer Sequence: NO Reverse Primer Sequence:
    AAMP NM_001087 1 GTGTGGCAGGTGGACACTAA 2 CTCCATCCACTCCAGGTCTC
    ABCA5 NM_172232 5 GGTATGGATCCCAAAGCCA 6 CAGCCCGCTTTCTGTTTTTA
    ABCB1 NM_000927 9 AAACACCACTGGAGCATTGA 10 CAAGCCTGGAACCTATAGCC
    ABCC1 NM_004996 13 TCATGGTGCCCGTCAATG 14 CGATTGTCTTTGCTCTTCATGTG
    ABCC3 NM_003786 17 TCATCCTGGCGATCTACTTCCT 18 CCGTTGAGTGGAATCAGCAA
    ABCC4 NM_005845 21 AGCGCCTGGAATCTACAACT 22 AGAGCCCCTGGAGAGAAGAT
    ABCC8 NM_000352 25 CGTCTGTCACTGTGGAGTGG 26 TGATCCGGTTTAGCAGGC
    ABCG2 NM_004827 29 GGTCTCAACGCCATCCTG 30 CTTGGATCTTTCCTTGCAGC
    ABHD2 NM_007011 33 GTAGTGGGTCTGCATGGATGT 34 TGAGGGTTGGCACTCAGG
    ACE NM_000789 37 CCGCTGTACGAGGATTTCA 38 CCGTGTCTGTGAAGCCGT
    ACOX2 NM_003500 41 ATGGAGGTGCCCAGAACAC 42 ACTCCGGGTAACTGTGGATG
    ACTR2 NM_005722 45 ATCCGCATTGAAGACCCA 46 ATCCGCTAGAACTGCACCAC
    ADAM15 NM_003815 49 GGCGGGATGTGGTAACAG 50 ATTTCTGGGCCTCCGAGT
    ADAMTS1 NM_006988 53 GGACAGGTGCAAGCTCATCTG 54 ATCTACAACCTTGGGCTGCAA
    ADH5 NM_000671 57 ATGCTGTCATCATTGTCACG 58 CTGCTTCCTTTCCCTTTCC
    AFAP1 NM_198595 61 GATGTCCATCCTTGAAACAGC 62 CAACCCTGATGCCTGGAG
    AGTR1 NM_000685 65 AGCATTGATCGATACCTGGC 66 CTACAAGCATTGTGCGTCG
    AGTR2 NM_000686 69 ACTGGCATAGGAAATGGTATCC 70 ATTGACTGGGTCTCTTTGCC
    AIG1 NM_016108 73 CGACGGTTCTGCCCTTTAT 74 TGCTCCTGCTGGGATACTG
    AKAP1 NM_003488 77 TGTGGTTGGAGATGAAGTGG 78 GTCTACCCACTGGGCAAGG
    AKR1C1 BC040210 81 GTGTGTGAAGCTGAATGATGG 82 CTCTGCAGGCGCATAGGT
    AKR1C3 NM_003739 85 GCTTTGCCTGATGTCTACCAGAA 86 GTCCAGTCACCGGCATAGAGA
    AKT1 NM_005163 89 CGCTTCTATGGCGCTGAGAT 90 TCCCGGTACACCACGTTCTT
    AKT2 NM_001626 93 TCCTGCCACCCTTCAAACC 94 GGCGGTAAATTCATCATCGAA
    AKT3 NM_005465 97 TTGTCTCTGCCTTGGACTATCTACA 98 CCAGCATTAGATTCTCCAACTTGA
    ALCAM NM_001627 101 GAGGAATATGGAATCCAAGGG 102 GTGGCGGAGATCAAGAGG
    ALDH18A1 NM_002860 105 GATGCAGCTGGAACCCAA 106 CTCCAGCTCAGTGGGGAA
    ALDH1A2 NM_170696 109 CACGTCTGTCCCTCTCTGCT 110 GACCGTGGCTCAACTTTGTAT
    ALKBH3 NM_139178 113 TCGCTTAGTCTGCACCTCAAC 114 TCTGAGCCCCAGTTTTTCC
    ALOX12 NM_000697 117 AGTTCCTCAATGGTGCCAAC 118 AGCACTAGCCTGGAGGGC
    ALOX5 NM_000698 121 GAGCTGCAGGACTTCGTGA 122 GAAGCCTGAGGACTTGCG
    AMACR NM_203382 125 GTCTCTGGGCTGTCAGCTTT 126 TGGGTATAAGATCCAGAACTTGC
    AMPD3 NM_000480 129 TGGTTCATCCAGCACAAGG 130 CATAAATCCGGGGCACCT
    ANGPT2 NM_001147 133 CCGTGAAAGCTGCTCTGTAA 134 TTGCAGTGGGAAGAACAGTC
    ANLN NM_018685 137 TGAAAGTCCAAAACCAGGAA 138 CAGAACCAAGGCTATCACCA
    ANPEP NM_001150 141 CCACCTTGGACCAAAGTAAAGC 142 TCTCAGCGTCACCTGGTAGGA
    ANXA2 NM_004039 145 CAAGACACTAAGGGCGACTACCA 146 CGTGTCGGGCTTCAGTCAT
    APC NM_000038 149 GGACAGCAGGAATGTGTTTC 150 ACCCACTCGATTTGTTTCTG
    APEX1 NM_001641 153 GATGAAGCCTTTCGCAAGTT 154 AGGTCTCCACACAGCACAAG
    APOC1 NM_001645 157 CCAGCCTGATAAAGGTCCTG 158 CACTCTGAATCCTTGCTGGA
    APOE NM_000041 161 GCCTCAAGAGCTGGTTCG 162 CCTGCACCTTCTCCACCA
    APRT NM_000485 165 GAGGTCCTGGAGTGCGTG 166 AGGTGCCAGCTTCTCCCT
    AQP2 NM_000486 169 GTGTGGGTGCCAGTCCTC 170 CCCTTCAGCCCTCTCAAAG
    AR NM_000044 173 CGACTTCACCGCACCTGAT 174 TGACACAAGTGGGACTGGGATA
    ARF1 NM_001658 177 CAGTAGAGATCCCCGCAACT 178 ACAAGCACATGGCTATGGAA
    ARHGAP29 NM_004815 181 CACGGTCTCGTGGTGAAGT 182 CAGTTGCTTGCCCAGGAC
    ARHGDIB NM_001175 185 TGGTCCCTAGAACAAGAGGC 186 TGATGGAGGATCAGAGGGAG
    ASAP2 NM_003887 189 CGGCCCATCAGCTTCTAC 190 CTCTGGCCAAAGATACAGCG
    ASPN NM_017680 193 TGGACTAATCTGTGGGAGCA 194 AAACACCCTTCAACACAGTCC
    ATM NM_000051 197 TGCTTTCTACACATGTTCAGGG 198 GTTGTGGATCGGCTCGTT
    ATP5E NM_006886 201 CCGCTTTCGCTACAGCAT 202 TGGGAGTATCGGATGTAGCTG
    ATP5J NM_ 205 GTCGACCGACTGAAACGG 206 CTCTACTTCCGGCCCTGG
    001003703
    ATXN1 NM_000332 209 GATCGACTCCAGCACCGTAG 210 GAACTGTATCACGGCCACG
    AURKA NM_003600 213 CATCTTCCAGGAGGACCACT 214 TCCGACCTTCAATCATTTCA
    AURKB NM_004217 217 AGCTGCAGAAGAGCTGCACAT 218 GCATCTGCCAACTCCTCCAT
    AXIN2 NM_004655 221 GGCTATGTCTTTGCACCAGC 222 ATCCGTCAGCGCATCACT
    AZGP1 NM_001185 225 GAGGCCAGCTAGGAAGCAA 226 CAGGAAGGGCAGCTACTGG
    BAD NM_032989 229 GGGTCAGGGGCCTCGAGAT 230 CTGCTCACTCGGCTCAAACTC
    BAG5 NM_ 233 ACTCCTGCAATGAACCCTGT 234 ACAAACAGCTCCCCACGA
    001015049
    BAK1 NM_001188 237 CCATTCCCACCATTCTACCT 238 GGGAACATAGACCCACCAAT
    BAX NM_004324 241 CCGCCGTGGACACAGACT 242 TTGCCGTCAGAAAACATGTCA
    BBC3 NM_014417 245 CCTGGAGGGTCCTGTACAAT 246 CTAATTGGGCTCCATCTCG
    BCL2 NM_000633 249 CAGATGGACCTAGTACCCACTGAGA 250 CCTATGATTTAAGGGCATTTTTCC
    BDKRB1 NM_000710 253 GTGGCAGAAATCTACCTGGC 254 GAAGGGCAAGCCCAAGAC
    BGN NM_001711 257 GAGCTCCGCAAGGATGAC 258 CTTGTTGTTCACCAGGACGA
    BIK NM_001197 261 ATTCCTATGGCTCTGCAATTGTC 262 GGCAGGAGTGAATGGCTCTTC
    BIN1 NM_004305 265 CCTGCAAAAGGGAACAAGAG 266 CGTGGTTGACTCTGATCTCG
    BIRC5 NM_ 269 TTCAGGTGGATGAGGAGACA 270 CACACAGCAGTGGCAAAAG
    001012271
    BMP6 NM_001718 273 GTGCAGACCTTGGTTCACCT 274 CTTAGTTGGCGCACAGCAC
    BMPR1B NM_001203 277 ACCACTTTGGCCATCCCT 278 GCGGTGTTTGTACCCAGTG
    BRCA1 NM_007294 281 TCAGGGGGCTAGAAATCTGT 282 CCATTCCAGTTGATCTGTGG
    BRCA2 NM_000059 285 AGTTCGTGCTTTGCAAGATG 286 AAGGTAAGCTGGGTCTGCTG
    BTG1 NM_001731 289 GAGGTCCGAGCGATGTGA 290 AGTTATTTTCGAGACAGGAGGC
    BTG3 NM_006806 293 CCATATCGCCCAATTCCA 294 CCAGTGATTCCGGTCACAA
    BTRC NM_033637 297 GTTGGGACACAGTTGGTCTG 298 TGAAGCAGTCAGTTGTGCTG
    BUB1 NM_004336 301 CCGAGGTTAATCCAGCACGTA 302 AAGACATGGCGCTCTCAGTTC
    C7 NM_000587 305 ATGTCTGAGTGTGAGGCGG 306 AGGCCTTATGCTGGTGACAG
    CACNA1D NM_000720 309 AGGACCCAGCTCCATGTG 310 CCTACATTCCGTGCCATTG
    CADM1 NM_014333 313 CCACCACCATCCTTACCATC 314 GATCCACTGCCCTGATCG
    CADPS NM_003716 317 CAGCAAGGAGACTGTGCTGA 318 GGTCCTCTTCTCCACGGTAGAT
    CASP3 NM_032991 325 TGAGCCTGAGCAGAGACATGA 326 CCTTCCTGCGTGGTCCAT
    CASP7 NM_033338 329 GCAGCGCCGAGACTTTTA 330 AGTCTCTCTCCGTCGCTCC
    CAV1 NM_001753 333 GTGGCTCAACATTGTGTTCC 334 CAATGGCCTCCATTTTACAG
    CAV2 NM_198212 337 CTTCCCTGGGACGACTTG 338 CTCCTGGTCACCCTTCTGG
    CCL2 NM_002982 341 CGCTCAGCCAGATGCAATC 342 GCACTGAGATCTTCCTATTGGTGAA
    CCL5 NM_002985 345 AGGTTCTGAGCTCTGGCTTT 346 ATGCTGACTTCCTTCCTGGT
    CCNB1 NM_031966 349 TTCAGGTTGTTGCAGGAGAC 350 CATCTTCTTGGGCACACAAT
    CCND1 NM_001758 353 GCATGTTCGTGGCCTCTAAGA 354 CGGTGTAGATGCACAGCTTCTC
    CCNE2 NM_057749 357 ATGCTGTGGCTCCTTCCTAACT 358 ACCCAAATTGTGATATACAAAAAGGTT
    CCNH NM_001239 361 GAGATCTTCGGTGGGGGTA 362 CTGCAGACGAGAACCCAAAC
    CCR1 NM_001295 365 TCCAAGACCCAATGGGAA 366 TCGTAGGCTTTCGTGAGGA
    CD164 NM_006016 369 CAACCTGTGCGAAAGTCTACC 370 ACACCCAAGACCAGGACAAT
    CD1A NM_001763 373 GGAGTGGAAGGAACTGGAAA 374 TCATGGGCGTATCTACGAAT
    CD276 NM_ 377 CCAAAGGATGCGATACACAG 378 GGATGACTTGGGAATCATGTC
    001024736
    CD44 NM_000610 381 GGCACCACTGCTTATGAAGG 382 GATGCTCATGGTGAATGAGG
    CD68 NM_001251 385 TGGTTCCCAGCCCTGTGT 386 CTCCTCCACCCTGGGTTGT
    CD82 NM_002231 389 GTGCAGGCTCAGGTGAAGTG 390 GACCTCAGGGCGATTCATGA
    CDC20 NM_001255 393 TGGATTGGAGTTCTGGGAATG 394 GCTTGCACTCCACAGGTACACA
    CDC25B NM_021873 397 GCTGCAGGACCAGTGAGG 398 TAGGGCAGCTGGCTTCAG
    CDC6 NM_001254 401 GCAACACTCCCCATTTACCTC 402 TGAGGGGGACCATTCTCTTT
    CDH1 NM_004360 405 TGAGTGTCCCCCGGTATCTTC 406 CAGCCGCTTTCAGATTTTCAT
    CDH10 NM_006727 409 TGTGGTGCAAGTCACAGCTAC 410 TGTAAATGACTCTGGCGCTG
    CDH11 NM_001797 413 GTCGGCAGAAGCAGGACT 414 CTACTCATGGGCGGGATG
    CDH19 NM_021153 417 AGTACCATAATGCGGGAACG 418 AGACTGCCTGTATAGGCTCCTG
    CDH5 NM_001795 421 ACAGGAGACGTGTTCGCC 422 CAGCAGTGAGGTGGTACTCTGA
    CDH7 NM_033646 425 GTTTGACATGGCTGCACTGA 426 AGTCACATCCCTCCGGGT
    CDK14 NM_012395 429 GCAAGGTAAATGGGAAGTTGG 430 GATAGCTGTGAAAGGTGTCCCT
    CDK2 NM_001798 433 AATGCTGCACTACGACCCTA 434 TTGGTCACATCCTGGAAGAA
    CDK3 NM_001258 437 CCAGGAAGGGACTGGAAGA 438 GTTGCATGAGCAGGTCCC
    CDK7 NM_001799 441 GTCTCGGGCAAAGCGTTAT 442 CTCTGGCCTTGTAAACGGTG
    CDKN1A NM_000389 445 TGGAGACTCTCAGGGTCGAAA 446 GGCGTTTGGAGTGGTAGAAATC
    CDKN1C NM_000076 449 CGGCGATCAAGAAGCTGT 450 CAGGCGCTGATCTCTTGC
    CDKN2B NM_004936 453 GACGCTGCAGAGCACCTT 454 GCGGGAATCTCTCCTCAGT
    CDKN2C NM_001262 457 GAGCACTGGGCAATCGTTAC 458 CAAAGGCGAACGGGAGTAG
    CDKN3 NM_005192 461 TGGATCTCTACCAGCAATGTG 462 ATGTCAGGAGTCCCTCCATC
    CDS2 NM_003818 465 GGGCTTCTTTGCTACTGTGG 466 ACAGGGCAGACAAAGCATCT
    CENPF NM_016343 469 CTCCCGTCAACAGCGTTC 470 GGGTGAGTCTGGCCTTCA
    CHAF1A NM_005483 473 GAACTCAGTGTATGAGAAGCGG 474 GCTCTGTAGCACCTGCGG
    CHN1 NM_001822 477 TTACGACGCTCGTGAAAGC 478 TCTCCCTGATGCACATGTCT
    CHRAC1 NM_017444 481 TCTCGCTGCCTCTATCCC 482 CCTGGTTGATGCTGGACA
    CKS2 NM_001827 485 GGCTGGACGTGGTTTTGTCT 486 CGCTGCAGAAAATGAAACGA
    CLDN3 NM_001306 489 ACCAACTGCGTGCAGGAC 490 GGCGAGAAGGAACAGCAC
    CLTC NM_004859 493 ACCGTATGGACAGCCACAG 494 TGACTACAGGATCAGCGCTTC
    COL11A1 NM_001854 497 GCCCAAGAGGGGAAGATG 498 GGACCTGGGTCTCCAGTTG
    COL1A1 NM_000088 501 GTGGCCATCCAGCTGACC 502 CAGTGGTAGGTGATGTTCTGGGA
    COL1A2 NM_000089 505 CAGCCAAGAACTGGTATAGGAGCT 506 AAACTGGCTGCCAGCATTG
    COL3A1 NM_000090 509 GGAGGTTCTGGACCTGCTG 510 ACCAGGACTGCCACGTTC
    COL4A1 NM_001845 513 ACAAAGGCCTCCCAGGAT 514 GAGTCCCAGGAAGACCTGCT
    COL5A1 NM_000093 517 CTCCCTGGGAAAGATGGC 518 CTGGACCAGGAAGCCCTC
    COL5A2 NM_000393 521 GGTCGAGGAACCCAAGGT 522 GCCTGGAGGTCCAACTCTG
    COL6A1 NM_001848 525 GGAGACCCTGGTGAAGCTG 526 TCTCCAGGGACACCAACG
    COL6A3 NM_004369 529 GAGAGCAAGCGAGACATTCTG 530 AACAGGGAACTGGCCCAC
    COL8A1 NM_001850 533 TGGTGTTCCAGGGCTTCT 534 CCCTGTAAACCCTGATCCC
    COL9A2 NM_001852 537 GGGAACCATCCAGGGTCT 538 ATTCCGGGTGGACAGTTG
    CRISP3 NM_006061 541 TCCCTTATGAACAAGGAGCAC 542 AACCATTGGTGCATAGTCCAT
    CSF1 NM_000757 545 TGCAGCGGCTGATTGACA 546 CAACTGTTCCTGGTCTACAAACTCA
    CSK NM_004383 549 CCTGAACATGAAGGAGCTGA 550 CATCACGTCTCCGAACTCC
    CSRP1 NM_004078 553 ACCCAAGACCCTGCCTCT 554 GCAGGGGTGGAGTGATGT
    CTGF NM_001901 557 GAGTTCAAGTGCCCTGACG 558 AGTTGTAATGGCAGGCACAG
    CTHRC1 NM_138455 561 TGGCTCACTTCGGCTAAAAT 562 TCAGCTCCATTGAATGTGAAA
    CTNNA1 NM_001903 565 CGTTCCGATCCTCTATACTGCAT 566 AGGTCCCTGTTGGCCTTATAGG
    CTNNB1 NM_001904 569 GGCTCTTGTGCGTACTGTCCTT 570 TCAGATGACGAAGAGCACAGATG
    CTNND1 NM_001331 573 CGGAAACTTCGGGAATGTGA 574 CTGAATCCTTCTGCCCAATCTC
    CTNND2 NM_001332 577 GCCCGTCCCTACAGTGAAC 578 CTCACACCCAGGAGTCGG
    CTSB NM_001908 581 GGCCGAGATCTACAAAAACG 582 GCAGGAAGTCCGAATACACA
    CTSD NM_001909 585 GTACATGATCCCCTGTGAGAAGGT 586 GGGACAGCTTGTAGCCTTTGC
    CTSK NM_000396 589 AGGCTTCTCTTGGTGTCCATAC 590 CCACCTCTTCACTGGTCATGT
    CTSL2 NM_001333 593 TGTCTCACTGAGCGAGCAGAA 594 ACCATTGCAGCCCTGATTG
    CTSS NM_004079 597 TGACAACGGCTTTCCAGTACAT 598 TCCATGGCTTTGTAGGGATAGG
    CUL1 NM_003592 601 ATGCCCTGGTAATGTCTGCAT 602 GCGACCACAAGCCTTATCAAG
    CXCL12 NM_000609 605 GAGCTACAGATGCCCATGC 606 TTTGAGATGCTTGACGTTGG
    CXCR4 NM_003467 609 TGACCGCTTCTACCCCAATG 610 AGGATAAGGCCAACCATGATGT
    CXCR7 NM_020311 613 CGCCTCAGAACGATGGAT 614 GTTGCATGGCCAGCTGAT
    CYP3A5 NM_000777 617 TCATTGCCCAGTATGGAGATG 618 GACAGGCTTGCCTTTCTCTG
    CYR61 NM_001554 621 TGCTCATTCTTGAGGAGCAT 622 GTGGCTGCATTAGTGTCCAT
    DAG1 NM_004393 625 GTGACTGGGCTCATGCCT 626 ATCCCACTTGTGCTCCTGTC
    DAP NM_004394 629 CCAGCCTTTCTGGTGCTG 630 GACCAGGTCTGCCTCTGC
    DAPK1 NM_004938 633 CGCTGACATCATGAATGTTCCT 634 TCTCTTTCAGCAACGATGTGTCTT
    DARC NM_002036 637 GCCCTCATTAGTCCTTGGCT 638 CAGACAGAAGGGCTGGGAC
    DDIT4 NM_019058 641 CCTGGCGTCTGTCCTCAC 642 CGAAGAGGAGGTGGACGA
    DDR2 NM_ 645 CTATTACCGGATCCAGGGC 646 CCCAGCAAGATACTCTCCCA
    001014796
    DES NM_001927 649 ACTTCTCACTGGCCGACG 650 GCTCCACCTTCTCGTTGGT
    DHRS9 NM_005771 653 GGAGAAAGGTCTCTGGGGTC 654 CAGTCAGTGGGAGCCAGC
    DHX9 NM_001357 657 GTTCGAACCATCTCAGCGAC 658 TCCAGTTGGATTGTGGAGGT
    DIAPH1 NM_005219 661 CAAGCAGTCAAGGAGAACCA 662 AGTTTTGCTCGCCTCATCTT
    DICER1 NM_177438 665 TCCAATTCCAGCATCACTGT 666 GGCAGTGAAGGCGATAAAGT
    DIO2 NM_013989 669 CTCCTTTCACGAGCCAGC 670 AGGAAGTCAGCCACTGAGGA
    DLC1 NM_006094 673 GATTCAGACGAGGATGAGCC 674 CACCTCTTGCTGTCCCTTTG
    DLGAP1 NM_004746 677 CTGCTGAGCCCAGTGGAG 678 AGCCTGGAAGGAGTTCCG
    DLL4 NM_019074 681 CACGGAGGTATAAGGCAGGAG 682 AGAAGGAAGGTCCAGCCG
    DNM3 NM_015569 685 CTTTCCCACCCGGCTTAC 686 AAGGACCTTCTGCAGGTGTG
    DPP4 NM_001935 689 GTCCTGGGATCGGGAAGT 690 GTACTCCCACCGGGATACAG
    DPT NM_001937 693 CACCTAGAAGCCTGCCCAC 694 CAGTAGCTCCCCAGGGTTC
    DUSP1 NM_004417 697 AGACATCAGCTCCTGGTTCA 698 GACAAACACCCTTCCTCCAG
    DUSP6 NM_001946 701 CATGCAGGGACTGGGATT 702 TGCTCCTACCCTATCATTTGG
    DVL1 NM_004421 705 TCTGTCCCACCTGCTGCT 706 TCAGACTGTTGCCGGATG
    DYNLL1 NM_ 709 GCCGCCTACCTCACAGAC 710 GCCTGACTCCAGCTCTCCT
    001037494
    EBNA1BP2 NM_006824 713 TGCGGCGAGATGGACACT 714 GTGACAAGGGATTCATCGGATT
    ECE1 NM_001397 717 ACCTTGGGATCTGCCTCC 718 GGACCAGGACCTCCATCTG
    EDN1 NM_001955 721 TGCCACCTGGACATCATTTG 722 TGGACCTAGGGCTTCCAAGTC
    EDNRA NM_001957 725 TTTCCTCAAATTTGCCTCAAG 726 TTACACATCCAACCAGTGCC
    EFNB2 NM_004093 729 TGACATTATCATCCCGCTAAGGA 730 GTAGTCCCCGCTGACCTTCTC
    EGF NM_001963 733 CTTTGCCTTGCTCTGTCACAGT 734 AAATACCTGACACCCTTATGACAAATT
    EGR1 NM_001964 737 GTCCCCGCTGCAGATCTCT 738 CTCCAGCTTAGGGTAGTTGTCCAT
    EGR3 NM_004430 741 CCATGTGGATGAATGAGGTG 742 TGCCTGAGAAGAGGTGAGGT
    EIF2C2 NM_012154 745 GCACTGTGGGCAGATGAA 746 ATGTTTGGTGACTGGCGG
    EIF2S3 NM_001415 749 CTGCCTCCCTGATTCAAGTG 750 GGTGGCAAGTGCCTGTAATATC
    EIF3H NM_003756 753 CTCATTGCAGGCCAGATAAA 754 GCCATGAAGAGCTTGCCTA
    EIF4E NM_001968 757 GATCTAAGATGGCGACTGTCGAA 758 TTAGATTCCGTTTTCTCCTCTTCTG
    EIF5 NM_001969 761 GAATTGGTCTCCAGCTGCC 762 TCCAGGTATATGGCTCCTGC
    ELK4 NM_001973 765 GATGTGGAGAATGGAGGGAA 766 AGTCATTGCGGCTAGAGGTC
    ENPP2 NM_006209 769 CTCCTGCGCACTAATACCTTC 770 TCCCTGGATAATTGGGTCTG
    ENY2 NM_020189 773 CCTCAAAGAGTTGCTGAGAGC 774 CCTCTTTACAGTGTGCCTTCA
    EPHA2 NM_004431 777 CGCCTGTTCACCAAGATTGAC 778 GTGGCGTGCCTCGAAGTC
    EPHA3 NM_005233 781 CAGTAGCCTCAAGCCTGACA 782 TTCGTCCCATATCCAGCG
    EPHB2 NM_004442 785 CAACCAGGCAGCTCCATC 786 GTAATGCTGTCCACGGTGC
    EPHB4 NM_004444 789 TGAACGGGGTATCCTCCTTA 790 AGGTACCTCTCGGTCAGTGG
    ERBB2 NM_004448 793 CGGTGTGAGAAGTGCAGCAA 794 CCTCTCGCAAGTGCTCCAT
    ERBB3 NM_001982 797 CGGTTATGTCATGCCAGATACAC 798 GAACTGAGACCCACTGAAGAAAGG
    ERBB4 NM_005235 801 TGGCTCTTAATCAGTTTCGTTACCT 802 CAAGGCATATCGATCCTCATAAAGT
    ERCC1 NM_001983 805 GTCCAGGTGGATGTGAAAGA 806 CGGCCAGGATACACATCTTA
    EREG NM_001432 809 TGCTAGGGTAAACGAAGGCA 810 TGGAGACAAGTCCTGGCAC
    ERG NM_004449 813 CCAACACTAGGCTCCCCA 814 CCTCCGCCAGGTCTTTAGT
    ESR1 NM_000125 817 CGTGGTGCCCCTCTATGAC 818 GGCTAGTGGGCGCATGTAG
    ESR2 NM_001437 821 TGGTCCATCGCCAGTTATCA 822 TGTTCTAGCGATCTTGCTTCACA
    ETV1 NM_004956 825 TCAAACAAGAGCCAGGAATG 826 AACTGCCAGAGCTGAAGTGA
    ETV4 NM_001986 829 TCCAGTGCCTATGACCCC 830 ACTGTCCAAGGGCACCAG
    EZH2 NM_004456 833 TGGAAACAGCGAAGGATACA 834 CACCGAACACTCCCTAGTCC
    F2R NM_001992 837 AAGGAGCAAACCATCCAGG 838 GCAGGGTTTCATTGAGCAC
     
    FAH NM_001441 841 GACAGCGTAGTGGTGCATGT 842 AGCTGAACATGGACTGTGGA
    FABP5 NM_001444 845 GCTGATGGCAGAAAAACTCA 846 CTTTCCTTCCCATCCCACT
    FADD NM_003824 849 GTTTTCGCGAGATAACGGTC 850 CTCCGGTGCCTGATTCAC
    FAM107A NM_007177 853 AAGTCAGGGAAAACCTGCG 854 GCTGGCCCTACAGCTCTCT
    FAM13C NM_198215 857 ATCTTCAAAGCGGAGAGCG 858 GCTGGATACCACATGCTCTG
    FAM171B NM_177454 861 CCAGGAAGGAAAAGCACTGT 862 GTGGTCTGCCCCTTCTTTTA
    FAM49B NM_016623 865 AGATGCAGAAGGCATCTTGG 866 GCTGGATTGCCTCTCGTATT
    FAM73A NM_198549 869 TGAGAAGGTGCGCTATTCAA 870 GGCCATTAAAAGCTCAGTGC
    FAP NM_004460 873 GTTGGCTCACGTGGGTTAC 874 GACAGGACCGAAACATTCTG
    FAS NM_000043 877 GGATTGCTCAACAACCATGCT 878 GGCATTAACACTTTTGGACGATAA
    FASLG NM_000639 881 GCACTTTGGGATTCTTTCCATTAT 882 GCATGTAAGAAGACCCTCACTGAA
    FASN NM_004104 885 GCCTCTTCCTGTTCGACG 886 GCTTTGCCCGGTAGCTCT
    FCGR3A NM_000569 889 GTCTCCAGTGGAAGGGAAAA 890 AGGAATGCAGCTACTCACTGG
    FGF10 NM_004465 893 TCTTCCGTCCCTGTCACCT 894 AGAGTTGGTGGCCTCTGGT
    FGF17 NM_003867 897 GGTGGCTGTCCTCAAAATCT 898 TCTAGCCAGGAGGAGTTTGG
    FGF5 NM_004464 901 GCATCGGTTTCCATCTGC 902 AACATATTGGCTTCGTGGGA
    FGF6 NM_020996 905 GGGCCATTAATTCTGACCAC 906 CCCGGGACATAGTGATGAA
    FGF7 NM_002009 909 CCAGAGCAAATGGCTACAAA 910 TCCCCTCCTTCCATGTAATC
    FGFR2 NM_000141 913 GAGGGACTGTTGGCATGCA 914 GAGTGAGAATTCGATCCAAGTCTTC
    FGFR4 NM_002011 917 CTGGCTTAAGGATGGACAGG 918 ACGAGACTCCAGTGCTGATG
    FKBP5 NM_004117 921 CCCACAGTAGAGGGGTCTCA 922 GGTTCTGGCTTTCACGTCTG
    FLNA NM_001456 925 GAACCTGCGGTGGACACT 926 GAAGACACCCTGGCCCTC
    FLNC NM_001458 929 CAGGACAATGGTGATGGCT 930 TGATGGTGTACTCGCCAGG
    FLT1 NM_002019 933 GGCTCCTGAATCTATCTTTG 934 TCCCACAGCAATACTCCGTA
    FLT4 NM_002020 937 ACCAAGAAGCTGAGGACCTG 938 CCTGGAAGCTGTAGCAGACA
    FN1 NM_002026 941 GGAAGTGACAGACGTGAAGGT 942 ACACGGTAGCCGGTCACT
    FOS NM_005252 945 CGAGCCCTTTGATGACTTCCT 946 GGAGCGGGCTGTCTCAGA
    FOXO1 NM_002015 949 GTAAGCACCATGCCCCAC 950 GGGGCAGAGGCACTTGTA
    FOXP3 NM_014009 953 CTGTTTGCTGTCCGGAGG 954 GTGGAGGAACTCTGGGAATG
    FOXQ1 NM_033260 957 TGTTTTTGTCGCAACTTCCA 958 TGGAAAGGTTCCCTGATGTACT
    FSD1 NM_024333 961 AGGCCTCCTGTCCTTCTACA 962 TGTGTGAACCTGGTCTTGAAA
    FYN NM_002037 965 GAAGCGCAGATCATGAAGAA 966 CTCCTCAGACACCACTGCAT
    G6PD NM_000402 969 AATCTGCCTGTGGCCTTG 970 CGAGATGTTGCTGGTGACA
    GABRG2 NM_198904 973 CCACTGTCCTGACAATGACC 974 GAGATCCATCGCTGTGACAT
    GADD45A NM_001924 977 GTGCTGGTGACGAATCCA 978 CCCGGCAAAAACAAATAAGT
    GADD45B NM_015675 981 ACCCTCGACAAGACCACACT 982 TGGGAGTTCATGGGTACAGA
    GDF15 NM_004864 985 CGCTCCAGACCTATGATGACT 986 ACAGTGGAAGGACCAGGACT
    GHR NM_000163 989 CCACCTCCCACAGGTTCA 990 GGTGCGTGCCTGTAGTCC
    GNPTAB NM_024312 993 GGATTCACATCGCGGAAA 994 GTTCTTGCATAACAATCCGGTC
    GNRH1 NM_000825 997 AAGGGCTAAATCCAGGTGTG 998 CTGGATCTCTGTGGCTGGT
    GPM6B NM_ 1001 ATGTGCTTGGAGTGGCCT 1002 TGTAGAACATAAACACGGGCA
    001001994
    GPNMB NM_ 1005 CAGCCTCGCCTTTAAGGAT 1006 TGACAAATATGGCCAAGCAG
    001005340
    GPR68 NM_003485 1009 CAAGGACCAGATCCAGCG 1010 GGTAGGGCAGGAAGCAGG
    GPS1 NM_004127 1013 AGTACAAGCAGGCTGCCAAG 1014 GCAGCTCAGGGAAGTCACA
    GRB7 NM_005310 1017 CCATCTGCATCCATCTTGTT 1018 GGCCACCAGGGTATTATCTG
    GREM1 NM_013372 1021 GTGTGGGCAAGGACAAGC 1022 GACCTGATTTGGCCTCACC
    GSK3B NM_002093 1025 GACAAGGACGGCAGCAAG 1026 TTGTGGCCTGTCTGGACC
    GSN NM_000177 1029 CTTCTGCTAAGCGGTACATCGA 1030 GGCTCAAAGCCTTGCTTCAC
    GSTM1 NM_000561 1033 AAGCTATGAGGAAAAGAAGTACACGA 1034 GGCCCAGCTTGAATTTTTCA
    T
    GSTM2 NM_000848 1037 CTGCAGGCACTCCCTGAAAT 1038 CCAAGAAACCATGGCTGCTT
    HDAC1 NM_004964 1041 CAAGTACCACAGCGATGACTACATTA 1042 GCTTGCTGTACTCCGACATGTT
    A
    HDAC9 NM_178423 1045 AACCAGGCAGTCACCTTGAG 1046 CTCTGTCTTCCTGCATCGC
    HGD NM_000187 1049 CTCAGGTCTGCCCCTACAAT 1050 TTATTGGTGCTCCGTGGAC
    HIP1 NM_005338 1053 CTCAGAGCCCCACCTGAG 1054 GGGTTTCCCTGCCATACTG
    HIRIP3 NM_003609 1057 GGATGAGGAAAAGGGGGAT 1058 TCCCTAGCTGACTTTCTCCG
    HK1 NM_000188 1061 TACGCACAGAGGCAAGCA 1062 GAGAGAAGTGCTGGAGAGGC
    HLA-G NM_002127 1065 CCATCCCCATCATGGGTATC 1066 CCGCAGCTCCAGTGACTACA
    HLF NM_002126 1069 CACCCTGCAGGTGTCTGAG 1070 GGTACCTAGGAGCAGAAGGTGA
    HNF1B NM_000458 1073 TCCCAGCATCTCAACAAGG 1074 CGTACCAGGTGTACAGAGCG
    HPS1 NM_000195 1077 GCGGAAGCTGTATGTGCTC 1078 TTCGGATAAGATGACCGTCC
    HRAS NM_005343 1081 GGACGAATACGACCCCACT 1082 GCACGTCTCCCCATCAAT
    HSD17B10 NM_004493 1085 CCAGCGAGTTCTTGATGTGA 1086 ATCTCACCAGCCACCAGG
    HSD17B2 NM_002153 1089 GCTTTCCAAGTGGGGAATTA 1090 TGCCTGCGATATTTGTTAGG
    HSD17B3 NM_000197 1093 GGGACGTCCTGGAACAGT 1094 TGGAGAATCTCACGCACTTC
    HSD17B4 NM_000414 1097 CGGGAAGCTTCAGAGTACCTT 1098 ACCTCAGGCCCAATATCCTT
    HSD3B2 NM_000198 1101 GCCTTCCTTTAACCCTGATG 1102 GGAGTAAATTGGGCTGAGTAGG
    HSP90AB1 NM_007355 1105 GCATTGTGACCAGCACCTAC 1106 GAAGTGCCTGGGCTTTCAT
    HSPA5 NM_005347 1109 GGCTAGTAGAACTGGATCCCAACA 1110 GGTCTGCCCAAATGCTTTTC
    HSPA8 NM_006597 1113 CCTCCCTCTGGTGGTGCTT 1114 GCTACATCTACACTTGGTTGGCTTAA
    HSPB1 NM_001540 1117 CCGACTGGAGGAGCATAAA 1118 ATGCTGGCTGACTCTGCTC
    HSPB2 NM_001541 1121 CACCACTCCAGAGGTAGCAG 1122 TGGGACCAAACCATACATTG
    HSPE1 NM_002157 1125 GCAAGCAACAGTAGTCGCTG 1126 CCAACTTTCACGCTAACTGGT
    HSPG2 NM_005529 1129 GAGTACGTGTGCCGAGTGTT 1130 CTCAATGGTGACCAGGACA
    ICAM1 NM_000201 1133 GCAGACAGTGACCATCTACAGCTT 1134 CTTCTGAGACCTCTGGCTTCGT
    IER3 NM_003897 1137 GTACCTGGTGCGCGAGAG 1138 GCGTCTCCGCTGTAGTGTT
    IFI30 NM_006332 1141 ATCCCATGAAGCCCAGATAC 1142 GCACCATTCTTAGTGGAGCA
    IFIT1 NM_001548 1145 TGACAACCAAGCAAATGTGA 1146 CAGTCTGCCCATGTGGTAAT
    IFNG NM_000619 1149 GCTAAAACAGGGAAGCGAAA 1150 CAACCATTACTGGGATGCTC
    IGF1 NM_000618 1153 TCCGGAGCTGTGATCTAAGGA 1154 CGGACAGAGCGAGCTGACTT
    IGF1R NM_000875 1157 GCATGGTAGCCGAAGATTTCA 1158 TTTCCGGTAATAGTCTGTCTCATAGATA
    TC
    IGF2 NM_000612 1161 CCGTGCTTCCGGACAACTT 1162 TGGACTGCTTCCAGGTGTCA
    IGFBP2 NM_000597 1165 GTGGACAGCACCATGAACA 1166 CCTTCATACCCGACTTGAGG
    IGFBP3 NM_000598 1169 ACATCCCAACGCATGCTC 1170 CCACGCCCTTGTTTCAGA
    IGFBP5 NM_000599 1173 TGGACAAGTACGGGATGAAGCT 1174 CGAAGGTGTGGCACTGAAAGT
    IGKBP6 NM_002178 1177 TGAACCGCAGAGACCAACAG 1178 GTCTTGGACACCCGCAGAAT
    IL10 NM_000572 1181 CTGACCACGCTTTCTAGCTG 1182 CCAAGCCCAGAGACAAGATAA
    IL11 NM_000641 1185 TGGAAGGTTCCACAAGTCAC 1186 TCTTGACCTTGCAGCTTTGT
    IL17A NM_002190 1189 TCAAGCAACACTCCTAGGGC 1190 CAGCTCCTTTCTGGGTTGTG
    IL1A NM_000575 1193 GGTCCTTGGTAGAGGGCTACTT 1194 GGATGGAGCTTCAGGAGAGA
    IL1B NM_000576 1197 AGCTGAGGAAGATGCTGGTT 1198 GGAAAGAAGGTGCTCAGGTC
    IL2 NM_000586 1201 ACCTCAACTCCTGCCACAAT 1202 CACTGTTTGTGACAAGTGCAAG
    IL6 NM_000600 1205 CCTGAACCTTCCAAAGATGG 1206 ACCAGGCAAGTCTCCTCATT
    IL6R NM_000565 1209 CCAGCTTATCTCAGGGGTGT 1210 CTGGCGTAGAACCTTCCG
    IL6ST NM_002184 1213 GGCCTAATGTTCCAGATCCT 1214 AAAATTGTGCCTTGGAGGAG
    IL8 NM_000584 1217 AAGGAACCATCTCACTGTGTGTAAAC 1218 ATCAGGAAGGCTGCCAAGAG
    ILF3 NM_004516 1221 GACACGCCAAGTGGTTCC 1222 CTCAAGACCCGGATCACAA
    ILK NM_ 1225 CTCAGGATTTTCTCGCATCC 1226 AGGAGCAGGTGGAGACTGG
    001014794
    IMMT NM_006839 1229 CTGCCTATGCCAGACTCAGA 1230 GCTTTTCTGGCTTCCTCTTC
    ING5 NM_032329 1233 CCTACAGCAAGTGCAAGGAA 1234 CATCTCGTAGGTCTGCATGG
    INHBA NM_002192 1237 GTGCCCGAGCCATATAGCA 1238 CGGTAGTGGTTGATGACTGTTGA
    INSL4 NM_002195 1241 CTGTCATATTGCCCCATGC 1242 CAGATTCCAGCAGCCACC
    ITGA1 NM_181501 1245 GCTTCTTCTGGAGATGTGCTCT 1246 CCTGTAGATAATGACCTGGCCT
    ITGA3 NM_002204 1249 CCATGATCCTCACTCTGCTG 1250 GAAGCTTTGTAGCCGGTGAT
    ITGA4 NM_000885 1253 CAACGCTTCAGTGATCAATCC 1254 GTCTGGCCGGGATTCTTT
    ITGA5 NM_002205 1257 AGGCCAGCCCTACATTATCA 1258 GTCTTCTCCACAGTCCAGCA
    ITGA6 NM_000210 1261 CAGTGACAAACAGCCCTTCC 1262 GTTTAGCCTCATGGGCGTC
    ITGA7 NM_002206 1265 GATATGATTGGTCGCTGCTTTG 1266 AGAACTTCCATTCCCCACCAT
    ITGAD NM_005353 1269 GAGCCTGGTGGATCCCAT 1270 ACTGTCAGGATGCCCGTG
    ITGB3 NM_000212 1273 ACCGGGAGCCCTACATGAC 1274 CCTTAAGCTCTTTCACTGACTCAATCT
    ITGB4 NM_000213 1277 CAAGGTGCCCTCAGTGGA 1278 GCGCACACCTTCATCTCAT
    ITGB5 NM_002213 1281 TCGTGAAAGATGACCAGGAG 1282 GGTGAACATCATGACGCAGT
    ITPR1 NM_002222 1285 GAGGAGGTGTGGGTGTTCC 1286 GTAATCCCATGTCCGCGA
    ITPR3 NM_002224 1289 TTGCCATCGTGTCAGTGC 1290 ATGGAGCTGGCGTCATTG
    ITSN1 NM_003024 1293 TAACTGGGATGCATGGGC 1294 CTCTGCCTTAACTGGCCG
    JAG1 NM_000214 1297 TGGCTTACACTGGCAATGG 1298 GCATAGCTGTGAGATGCGG
    JUN NM_002228 1301 GACTGCAAAGATGGAAACGA 1302 TAGCCATAAGGTCCGCTCTC
    JUNB NM_002229 1305 CTGTCAGCTGCTGCTTGG 1306 AGGGGGTGTCCGTAAAGG
    KCNN2 NM_021614 1309 TGTGCTATTCATCCCATACCTG 1310 GGGCATAGGAGAAGGCAAG
    KCTD12 NM_138444 1313 AGCAGTTACTGGCAAGAGGG 1314 TGGAGACCTGAGCAGCCT
    KNDRBS3 NM_006558 1317 CGGGCAAGAAGAGTGGAC 1318 CTGTAGACGCCCTTTGCTGT
    KIAA0196 NM_014846 1321 CAGACACCAGCTCTGAGGC 1322 AACATTGTGAGGCGGACC
    KIAA0247 NM_014734 1325 CCGTGGGACATGGAGTGT 1326 GAAGCAAGTCCGTCTCCAAG
    KF4A NM_012310 1329 AGAGCTGGTCTCCTCCAAAA 1330 GCTGGTCTTGCTCTGTTTCA
    KIT NM_000222 1333 GAGGCAACTGCTTATGGCTTAATTA 1334 GGCACTCGGCTTGAGCAT
    KLC1 NM_182923 1337 AGTGGCTACGGGATGAACTG 1338 TGAGCCACAGACTGCTCACT
    KLF6 NM_001300 1341 CACGAGACCGGCTACTTCTC 1342 GCTCTAGGCAGGTCTGTTGC
    KLK1 NM_002257 1345 AACACAGCCCAGTTTGTTCA 1346 CCAGGAGGCTCATGTTGAAG
    KLK10 NM_002776 1349 GCCCAGAGGCTCCATCGT 1350 CAGAGGTTTGAACAGTGCAGACA
    KLK11 NM_006853 1353 CACCCCGGCTTCAACAAC 1354 CATCTTCACCAGCATGATGTCA
    KLK14 NM_022046 1357 CCCCTAAAATGTTCCTCCTG 1358 CTCATCCTCTTGGCTCTGTG
    KLK2 NM_005551 1361 AGTCTCGGATTGTGGGAGG 1362 TGTACACAGCCACCTGCC
    KLK3 NM_001648 1365 CCAAGCTTACCACCTGCAC 1366 AGGGTGAGGAAGACAACCG
    KLRK1 NM_007360 1369 TGAGAGCCAGGCTTCTTGTA 1370 ATCCTGGTCCTCTTTGCTGT
    KPNA2 NM_002266 1373 TGATGGTCCAAATGAACGAA 1374 AAGCTTCACAAGTTGGGGC
    KRT1 NM_006121 1377 TGGACAACAACCGCAGTC 1378 TATCCTCGTACTGGGCCTTG
    KRT15 NM_002275 1381 GCCTGGTTCTTCAGCAAGAC 1382 CTTGCTGGTCTGGATCATTTC
    KRT18 NM_000224 1385 AGAGATCGAGGCTCTCAAGG 1386 GGCCTTTTACTTCCTCTTCG
    KRT2 NM_000423 1389 CCAGTGACGCCTCTGTGTT 1390 GGGCATGGCTAGAAGCAC
    KRT5 NM_000424 1393 TCAGTGGAGAAGGAGTTGGA 1394 TGCCATATCCAGAGGAAACA
    KRT75 NM_004693 1397 TCAAAGTCAGGTACGAAGATGAAATT 1398 ACGTCCTTTTTCAGGGCTACAA
    KRT76 NM_015848 1401 ATCTCCAGACTGCTGGTTCC 1402 TCAGGGAATTAGGGGACAGA
    KRT8 NM_002273 1405 GGATGAAGCTTACATGAACAAGGTAG 1406 CATATAGCTGCCTGAGGAAGTTGAT
    A
    L1CAM NM_000425 1409 CTTGCTGGCCAATGCCTA 1410 TGATTGTCCGCAGTCAGG
    LAG3 NM_002286 1413 GCCTTAGAGCAAGGGATTCA 1414 CGGTTCTTGCTCCAGCTC
    LAMA3 NM_000227 1417 CCTGTCACTGAAGCCTTGG 1418 TGGGTTACTGGTCAGGACAAC
    LAMA4 NM_002290 1421 GATGCACTGCGGTTAGCAG 1422 CAGAGGATACGCTCAGCACC
    LAMA5 NM_005560 1425 CTCCTGGCCAACAGCACT 1426 ACACAAGGCCCAGCCTCT
    LAMB1 NM_002291 1429 CAAGGAGACTGGGAGGTGTC 1430 CGGCAGAACTGACAGTGTTC
    LAMB3 NM_000228 1433 ACTGACCAAGCCTGAGACCT 1434 GTCACACTTGCAGCATTTCA
    LAMC1 NM_002293 1437 GCCGTGATCTCAGACAGCTAC 1438 ACCTGCTTGCCCAAGAACT
    LAMC2 NM_005562 1441 ACTCAAGCGGAAATTGAAGCA 1442 ACTCCCTGAAGCCGAGACACT
    LAPTM5 NM_006762 1445 TGCTGGACTTCTGCCTGAG 1446 TGAGATAGGTGGGCACTTCC
    LGALS3 NM_002306 1449 AGCGGAAAATGGCAGACAAT 1450 CTTGAGGGTTTGGGTTTCCA
    LIG3 NM_002311 1453 GGAGGTGGAGAAGGAGCC 1454 ACAGGTGTCATCAGCGAGG
    LIMS1 NM_004987 1457 TGAACAGTAATGGGGAGCTG 1458 TTCTGGGAACTGCTGGAAG
    LOX NM_002317 1461 CCAATGGGAGAACAACGG 1462 CGCTGAGGCTGGTACTGTG
    LRP1 NM_002332 1465 TTTGGCCCAATGGGCTAAG 1466 GTCTCGATGCGGTCGTAGAAG
    LTBP2 NM_000428 1469 GCACACCCATCCTTGAGTCT 1470 GATGGCTGGCCACGTAGT
    LUM NM_002345 1473 GGCTCTTTTGAAGGATTGGTAA 1474 AAAAGCAGCTGAAACAGCATC
    MAGEA4 NM_002362 1477 GCATCTAACAGCCCTGTGC 1478 CAGAGTGAAGAATGGGCCTC
    MANF NM_006010 1481 CAGATGTGAAGCCTGGAGC 1482 AAGGGAATCCCCTCATGG
    MAOA NM_000240 1485 GTGTCAGCCAAAGCATGGA 1486 CGACTACGTCGAACATGTGG
    MAP3K5 NM_005923 1489 AGGACCAAGAGGCTACGGA 1490 CCTGTGGCCATTTCAATGAT
    MAP3K7 NM_145333 1493 CAGGCAAGAACTAGTTGCAGAA 1494 CCTGTACCAGGCGAGATGTAT
    MAP4K4 NM_004834 1497 TCGCCGAGATTTCCTGAG 1498 CTGTTGTCTCCGAAGAGCCT
    MAP7 NM_003980 1501 GAGGAACAGAGGTGTCTGCAC 1502 CTGCCAACTGGCTTTCCA
    MAPKAPK3 NM_004635 1505 AAGCTGCAGAGATAATGCGG 1506 GTGGGCAATGTTATGGCTG
    MCM2 NM_004526 1509 GACTTTTGCCCGCTACCTTTC 1510 GCCACTAACTGCTTCAGTATGAAGAG
    MCM3 NM_002388 1513 GGAGAACAATCCCCTTGAGA 1514 ATCTCCTGGATGGTGATGGT
    MCM6 NM_005915 1517 TGATGGTCCTATGTGTCACATTCA 1518 TGGGACAGGAAACACACCAA
    MDK NM_002391 1521 GGAGCCGACTGCAAGTACA 1522 GACTTTGGTGCCTGTGCC
    MDM2 NM_002392 1525 CTACAGGGACGCCATCGAA 1526 ATCCAACCAATCACCTGAATGTT
    MELK NM_014791 1529 AGGATCGCCTGTCAGAAGAG 1530 TGCACATAAGCAACAGCAGA
    MET NM_000245 1533 GACATTTCCAGTCCTGCAGTCA 1534 CTCCGATCGCACACATTTGT
    MGMT NM_002412 1537 GTGAAATGAAACGCACCACA 1538 GACCCTGCTCACAACCAGAC
    MGST1 NM_020300 1541 ACGGATCTACCACACCATTGC 1542 TCCATATCCAACAAAAAAACTCAAAG
    MICA NM_000247 1545 ATGGTGAATGTCACCCGC 1546 AAGCCAGAAGCCCTGCAT
    MKI67 NM_002417 1549 GATTGCACCAGGGCAGAA 1550 TCCAAAGTGCCTCTGCTAAGA
    MLXIP NM_014938 1553 TGCTTAGCTGGCATGTGG 1554 CAGCCTACTCTCCATGGGC
    MMP11 NM_005940 1557 CCTGGAGGCTGCAACATACC 1558 TACAATGGCTTTGGAGGATAGCA
    MMP2 NM_004530 1561 CAGCCAGAAGCGGAAACTTA 1562 AGACACCATCACCTGTGCC
    MMP7 NM_002423 1565 GGATGGTAGCAGTCTAGGGATTAACT 1566 GGAATGTCCCATACCCAAAGAA
    MMP9 NM_004994 1569 GAGAACCAATCTCACCGACA 1570 CACCCGAGTGTAACCATAGC
    MPPED2 NM_001584 1573 CCGACCAACCCTCCAATTA 1574 AGGGCATTTAGAGCTTCAGGA
    MRC1 NM_002438 1577 CTTGACCTCAGGACTCTGGATT 1578 GGACTGCGGTCACTCCAC
    MRPL13 NM_014078 1581 TCCGGTTCCCTTCGTTTAG 1582 GTGGAAAAACTGCGGAAAAC
    MSH2 NM_000251 1585 GATGCAGAATTGAGGCAGAC 1586 TCTTGGCAAGTCGGTTAAGA
    MSH3 NM_002439 1589 TGATTACCATCATGGCTCAGA 1590 CTTGTGAAAATGCCATCCAC
    MSH6 NM_000179 1593 TCTATTGGGGGATTGGTAGG 1594 CAAATTGCGAGTGGTGAAAT
    MTA1 NM_004689 1597 CCGCCCTCACCTGAAGAGA 1598 GGAATAAGTTAGCCGCGCTTCT
    MTPN NM_145808 1601 GGTGGAAGGAAACCTCTTCA 1602 CAGCAGCAGAAATTCCAGG
    MTSS1 NM_014751 1605 TTCGACAAGTCCTCCACCAT 1606 CTTGGAACATCCGTCGGTAG
    MUC1 NM_002456 1609 GGCCAGGATCTGTGGTGGTA 1610 CTCCACGTCGTGGACATTGA
    MVP NM_017458 1613 ACGAGAACGAGGGCATCTATGT 1614 GCATGTAGGTGCTTCCAATCAC
    MYBL2 NM_002466 1617 GCCGAGATCGCCAAGATG 1618 CTTTTGATGGTAGAGTTCCAGTGATTC
    MYBPC1 NM_002465 1621 CAGCAACCAGGGAGTCTGTA 1622 CAGCAGTAAGTGCCTCCATC
    MYC NM_002467 1625 TCCCTCCACTCGGAAGGACTA 1626 CGGTTGTTGCTGATCTGTCTCA
    MYLK3 NM_182493 1629 CACCTGACTGAGCTGGATGT 1630 GATGTAGTGCTGGTGCAGGT
    MYO6 NM_004999 1633 AAGCAGTTCTGGAGCAGGAG 1634 GATGAGCTCGGCTTCACTCT
    NCAM1 NM_000615 1637 TAGTTCCCAGCTGACCATCA 1638 CAGCCTTGTTCTCAGCAATG
    NCAPD3 NM_015261 1641 TCGTTGCTTAGACAAGGCG 1642 CTCCAGACAGTGTGCAAAGC
    NCOR1 NM_006311 1645 AACCGTTACAGCCCAGAATC 1646 TCTGGAGAGACCCTTGAACC
    NCOR2 NM_006312 1649 CGTCATCTACGAAGGCAAGA 1650 GAGCACTGGGTCACAGACAT
    NDRG1 NM_006096 1653 AGGGCAACATTCCACAGC 1654 CAGTGCTCCTACTCCGGC
    NDUFS5 NM_004552 1657 AGAAGAGTCAAGGGCACGAG 1658 AGGCCGAACCTTTTCTGG
    NEK2 NM_002497 1661 GTGAGGCAGCGCGACTCT 1662 TGCCAATGGTGTACAACACTTCA
    NETO2 NM_018092 1665 CCAGGGCACCATACTGTTTC 1666 AACGGTAAATCAAGGTCTTCGT
    NEXN NM_144573 1669 AGGAGGAGGAAGAAGGTAGCA 1670 GAGCTCCTGATCTGGTTTGC
    NFAT5 NM_006599 1673 CTGAACCCCTCTCCTGGTC 1674 AGGAAACGATGGCGAGGT
    NFATC2 NM_173091 1677 CAGTCAAGGTCAGAGGCTGAG 1678 CTTTGGCTCGTGGCATTC
    NFKB1 NM_003998 1681 CAGACCAAGGAGATGGACCT 1682 AGCTGCCAGTGCTATCCG
    NFKBIA NM_020529 1685 CTACTGGACGACCGCCAC 1686 CCTTGACCATCTGCTCGTACT
    NME1 NM_000269 1689 CCAACCCTGCAGACTCCAA 1690 ATGTATAATGTTCCTGCCAACTTGTATG
    NNMT NM_006169 1693 CCTAGGGCAGGGATGGAG 1694 CTAGTCCAGCCAAACATCCC
    NOS3 NM_000603 1697 ATCTCCGCCTCGCTCATG 1698 TCGGAGCCATACAGGATTGTC
    NOX4 NM_016931 1701 CCTCAACTGCAGCCTTATCC 1702 TGCTTGGAACCTTCTGTGAT
    NPBWR1 NM_005285 1705 TCACCAACCTGTTCATCCTC 1706 GATGTTGATGGGCAGCAC
    NPM1 NM_002520 1709 AATGTTGTCCAGGTTCTATTGC 1710 CAAGCAAAGGGTGGAGTTC
    NRG1 NM_013957 1713 CGAGACTCTCCTCATAGTGAAAGGTA 1714 CTTGGCGTGTGGAAATCTACAG
    T
    NRIP3 NM_020645 1717 CCCACAAGCATGAAGGAGA 1718 TGCTCAATCTGGCCCACTA
    NRP1 NM_003873 1721 CAGCTCTCTCCACGCGATTC 1722 CCCAGCAGCTCCATTCTGA
    NUP62 NM_153719 1725 AGCCTCTTTGCGTCAATAGC 1726 CTGTGGTCACAGGGGTACAG
    OAZ1 NM_004152 1729 AGCAAGGACAGCTTTGCAGT 1730 GAAGACATGGTCGGCTCG
    OCLN NM_002538 1733 CCCTCCCATCCGAGTTTC 1734 GACGCGGGAGTGTAGGTG
    ODC1 NM_002539 1737 AGAGATCACCGGCGTAATCAA 1738 CGGGCTCAGCTATGATTCTCA
    OLFML2B NM_015441 1741 CATGTTGGAAGGAGCGTTCT 1742 CACCAGTTTGGTGGTGACTG
    OLFML3 NM_020190 1745 TCAGAACTGAGGCCGACAC 1746 CCAGATAGTCTACCTCCCGCT
    OMD NM_005014 1749 CGCAAACTCAAGACTATCCCA 1750 CAGTCACAGCCTCAATTTCATT
    OR51E1 NM_152430 1753 GCATGCTTTCAGGCATTGA 1754 AGAAGATGGCCAGCATTTTG
    OR51E2 NM_030774 1757 TATGGTGCCAAAACCAAACA 1758 GTCCTTGTCACAGCTGATCTTG
    OSM NM_020530 1761 GTTTCTGAAGGGGAGGTCAC 1762 AGGTGTCTGGTTTGGGACA
    PAGE1 NM_003785 1765 CAACCTGACGAAGTGGAATC 1766 CAGATGCTCCCTCATCCTCT
    PAGE4 NM_007003 1769 GAATCTCAGCAAGAGGAACCA 1770 GTTCTTCGATCGGAGGTGTT
    PAK6 NM_020168 1773 CCTCCAGGTCACCCACAG 1774 GTCCCTTCAGGCCAGAACTT
    PATE1 NM_138294 1777 TGGTAATCCCTGGTTAACCTTC 1778 TCCACCTTATGCCTTTCACA
    PCA3 NR_015342 1781 CGTGATTGTCAGGAGCAAGA 1782 AGAAAGGGGAGATGCAGAGG
    PCDHGB7 NM_018927 1785 CCCAGCGTTGAAGCAGAT 1786 GAAACGCCAGTCCGTGTT
    PCNA NM_002592 1789 GAAGGTGTTGGAGGCACTCAAG 1790 GGTTTACACCGCTGGAGCTAA
    PDE9A NM_ 1793 TTCCACAACTTCCGGCAC 1794 AGACTGCAGAGCCAGACCA
    001001570
    PDGFRB NM_002609 1797 CCAGCTCTCCTTCCAGCTAC 1798 GGGTGGCTCTCACTTAGCTC
    PECAM1 NM_000442 1801 TGTATTTCAAGACCTCTGTGCACTT 1802 TTAGCCTGAGGAATTGCTGTGTT
    PEX10 NM_153818 1805 GGAGAAGTTCCCTCCCCAG 1806 ATCTGTGTCCAGGCCCAC
    PGD NM_002631 1809 ATTCCCATGCCCTGTTTTAC 1810 CTGGCTGGAAGCATCTCAT
    PGF NM_002632 1813 GTGGTTTTCCCTCGGAGC 1814 AGCAAGGGAACAGCCTCAT
    PGK1 NM_000291 1817 AGAGCCAGTTGCTGTAGAACTCAA 1818 CTGGGCCTACACAGTCCTTCA
    PGR NM_000926 1821 GATAAAGGAGCCGCGTGTCA 1822 TCACAAGTCCGGCACTTGAG
    PHTF2 NM_020432 1825 GATATGGCTGATGCTGCTCC 1826 GGTTTGGGTGTTCTTGTGGA
    PIK3C2A NM_002645 1829 ATACCAATCACCGCACAAACC 1830 CACACTAGCATTTTCTCCGCATA
    PIK3CA NM_006218 1833 GTGATTGAAGAGCATGCCAA 1834 GTCCTGCGTGGGAATAGC
    PIK3CG NM_002649 1837 GGAGAACTCAATGTCCATCTCC 1838 TGATGCTTAGGCAGGGCT
    PIM1 NM_002648 1841 CTGCTCAAGGACACCGTCTA 1842 GGATCCACTCTGGAGGGC
    PLA2G7 NM_005084 1845 CCTGGCTGTGGTTTATCCTT 1846 TGACCCATGCTGATGATTTC
    PLAU NM_002658 1849 GTGGATGTGCCCTGAAGGA 1850 CTGCGGATCCAGGGTAAGAA
    PLAUR NM_002659 1853 CCCATGGATGCTCCTCTGAA 1854 CCGGTGGCTACCAGACATTG
    PLG NM_000301 1857 GGCAAAATTTCCAAGACCAT 1858 ATGTATCCATGAGCGTGTGG
    PLK1 NM_005030 1861 AATGAATACAGTATTCCCAAGCACAT 1862 TGTCTGAAGCATCTTCTGGATGA
    PLOD2 NM_000935 1865 CAGGGAGGTGGTTGCAAAT 1866 TCTCCCAGGATGCATGAAG
    PLP2 NM_002668 1869 CCTGATCTGCTTCAGTGCC 1870 GCAGCAAGGATCATCTCAATC
    PNLIPRP2 NM_005396 1873 TGGAGAAGGTGAACTGCATC 1874 CACGGCTTGGGTGTACATT
    POSTN NM_006475 1877 GTGGCCCAATTAGGCTTG 1878 TCACAGGTGCCAGCAAAG
    PPAP2B NM_003713 1881 ACAAGCACCATCCCAGTGA 1882 CACGAAGAAAACTATGCAGCAG
    PPFIA3 NM_003660 1885 CCTGGAGCTCCGTTACTCTC 1886 AGCCACATAGGGATCCAGG
    PPP1R12A NM_002480 1889 CGGCAAGGGGTTGATATAGA 1890 TGCCTGGCATCTCTAAGCA
    PPP3CA NM_000944 1893 ATACTCCGAGCCCACGAA 1894 GGAAGCCTGTTGTTTGGC
    PRIMA1 NM_178013 1897 ATCCTCTTCCCTGAGCCG 1898 CCCAGCTGAGAGGGAATTTA
    PRKAR1B NM_002735 1901 ACAAAACCATGACTGCGCT 1902 TGTCATCCAGGTGAGCGA
    PRKAR2B NM_002736 1905 TGATAATCGTGGGAGTTTCG 1906 GCACCAGGAGAGGTAGCAGT
    PRKCA NM_002737 1909 CAAGCAATGCGTCATCAATGT 1910 GTAAATCCGCCCCCTCTTCT
    PRKCB NM_002738 1913 GACCCAGCTCCACTCCTG 1914 CCCATTCACGTACTCCATCA
    PROM1 NM_006017 1917 CTATGACAGGCATGCCACC 1918 CTCCAACCATGAGGAAGACG
    PROS1 NM_000313 1921 GCAGCACAGGAATCTTCTTCTT 1922 CCCACCTATCCAACCTAATCTG
    PSCA NM_005672 1925 ACCGTCATCAGCAAAGGCT 1926 CGTGATGTTCTTCTTGCCC
    PSMD13 NM_002817 1929 GGAGGAGCTCTACACGAAGAAG 1930 CGGATCCTGCACAAAATCA
    PTCH1 NM_000264 1933 CCACGACAAAGCCGACTAC 1934 TACTCGATGGGCTCTGCTG
    PTEN NM_000314 1937 TGGCTAAGTGAAGATGACAATCATG 1938 TGCACATATCATTACACCAGTTCGT
    PTGER3 NM_000957 1941 TAACTGGGGCAACCTTTTCT 1942 TTGCAGGAAAAGGTGACTGT
    PTGS2 NM_000963 1945 GAATCATTCACCAGGCAAATTG 1946 CTGTACTGCGGGTGGAACAT
    PTH1R NM_000316 1949 CGAGGTACAAGCTGAGATCAAGAA 1950 GCGTGCCTTTCGCTTGAA
    PTHLH NM_002820 1953 AGTGACTGGGAGTGGGCTAGAA 1954 AAGCCTGTTACCGTGAATCGA
    PTK2 NM_005607 1957 GACCGGTCGAATGATAAGGT 1958 CTGGACATCTCGATGACAGC
    PTK2B NM_004103 1961 CAAGCCCAGCCGACCTAAG 1962 GAACCTGGAACTGCAGCTTTG
    PTK6 NM_005975 1965 GTGCAGGAAAGGTTCACAAA 1966 GCACACACGATGGAGTAAGG
    PTK7 NM_002821 1969 TCAGAGGACTCACGGTTCG 1970 CATACACCTCCACGCTGTTG
    PTPN1 NM_002827 1973 AATGAGGAAGTTTCGGATGG 1974 CTTCGATCACAGCCAGGTAG
    PTPRK NM_002844 1977 TCAAACCCTCCCAGTGCT 1978 AGCAGCCAGTTCGTCCAG
    PTTG1 NM_004219 1981 GGCTACTCTGATCTATGTTGATAAGG 1982 GCTTCAGCCCATCCTTAGCA
    AA
    PYCARD NM_013258 1985 CTTTATAGACCAGCACCGGG 1986 AGCATCCAGCAGCCACTC
    RAB27A NM_004580 1989 TGAGAGATTAATGGGCATTGTG 1990 CCGGATGCTTTATTCGTAGG
    RAB30 NM_014488 1993 TAAAGGCTGAGGCACGGA 1994 CTCCCCAGCATCTCATGG
    RAB31 NM_006868 1997 CTGAAGGACCCTACGCTCG 1998 ATGCAAAGCCAGTGTGCTC
    RAD21 NM_006265 2001 TAGGGATGGTATCTGAAACAACA 2002 TCGCGTACACCTCTGCTC
    RAD51 NM_002875 2005 AGACTACTCGGGTCGAGGTG 2006 AGCATCCGCAGAAACCTG
    RAD9A NM_004584 2009 GCCATCTTCACCATCAAGG 2010 CGGTGTCTGAGAGTGTGGC
    RAF1 NM_002880 2013 CGTCGTATGCGAGAGTCTGT 2014 TGAAGGCGTGAGGTGTAGAA
    RAGE NM_014226 2017 ATTAGGGGACTTTGGCTCCT 2018 GGGTGGAGATGTATTCCGTG
    RALA NM_005402 2021 TGGTCCTGAATGTAGCGTGT 2022 CCCCATTTCACCTCTTCAAT
    RALBP1 NM_006788 2025 GGTGTCAGATATAAATGTGCAAATGC 2026 TTCGATATTGCCAGCAGCTATAAA
    RAP1B NM_ 2029 TGACAGCGTGAGAGGTACTAGG 2030 CTGAGCCAAGAACGACTAGCTT
    001010942
    RARB NM_000965 2033 ATGAACCCTTGACCCCAAGT 2034 GAGCTGGGTGAGATGCTAGG
    RASSF1 NM_007182 2037 AGGGCACGTGAAGTCATTG 2038 AAAGAGTGCAAACTTGCGG
    RB1 NM_000321 2041 CGAAGCCCTTACAAGTTTCC 2042 GGACTCTTCAGGGGTGAAAT
    RECK NM_021111 2045 GTCGCCGAGTGTGCTTCT 2046 GTGGGATGATGGGTTTGC
    REG4 NM_032044 2049 TGCTAACTCCTGCACAGCC 2050 TGCTAGGTTTCCCCTCTGAA
    RELA NM_021975 2053 CTGCCGGGATGGCTTCTAT 2054 CCAGGTTCTGGAAACTGTGGAT
    RFX1 NM_002918 2057 TCCTCTCCAAGTTCGAGCC 2058 CAGGCCCTGGTACAGCAC
    RGS10 NM_ 2061 AGACATCCACGACAGCGAT 2062 CCATTTGGCTGTGCTCTTG
    001005339
    RGS7 NM_002924 2065 CAGGCTGCAGAGAGCATTT 2066 TTTGCTTGTGCTTCTGCTTG
    RHOA NM_001664 2069 TGGCATAGCTCTGGGGTG 2070 TGCCACAGCTGCATGAAC
    RHOB NM_004040 2073 AAGCATGAACAGGACTTGACC 2074 CCTCCCCAAGTCAGTTGC
    RHOC NM_175744 2077 CCCGTTCGGTCTGAGGAA 2078 GAGCACTCAAGGTAGCCAAAGG
    RLN1 NM_006911 2081 AGCTGAAGGCAGCCCTATC 2082 TTGGAATCCTTTAATGCAGGT
    RND3 NM_005168 2085 TCGGAATTGGACTTGGGAG 2086 CTGGTTACTCCCCTCCAACA
    RNF114 NM_018683 2089 TGACAGGGGAAGTGGGTC 2090 GGAAGACAGCTTTGGCAAGA
    ROBO2 NM_002942 2093 CTACAAGGCCCAGCCAAC 2094 CACCAGTGGCTTTACATTTCAG
    RRM1 NM_001033 2097 GGGCTACTGGCAGCTACATT 2098 CTCTCAGCATCGGTACAAGG
    RRM2 NM_001034 2101 CAGCGGGATTAAACAGTCCT 2102 ATCTGCGTTGAAGCAGTGAG
    S100P NM_005980 2105 AGACAAGGATGCCGTGGATAA 2106 GAAGTCCACCTGGGCATCTC
    SAT1 NM_002970 2109 CCTTTTACCACTGCCTGGTT 2110 ACAATGCTGTGTCCTTCCG
    SCUBE2 NM_020974 2113 TGACAATCAGCACACCTGCAT 2114 TGTGACTACAGCCGTGATCCTTA
    SDC1 NM_002997 2117 GAAATTGACGAGGGGTGTCT 2118 AGGAGCTAACGGAGAACCTG
    SDC2 NM_002998 2121 GGATTGAAGTGGCTGGAAAG 2122 ACCAGCCACAGTACCCTCA
    SDHC NM_003001 2125 CTTCCCTCGGGTCTCAGG 2126 TTCCCTCCTGGTAAAGGTCA
    SEC14L1 NM_ 2129 AGGGTTCCCATGTGACCAG 2130 GCAGGCATGCTGTGGAAT
    001039573
    SEC23A NM_006364 2133 CGTGTGCATTAGATCAGACAGG 2134 CCCATTACCATGTATCCTCCAG
    SEMA3A NM_006080 2137 TTGGAATGCAGTCCGAAGT 2138 CTCTTCATTTCGCCTCTGGA
    SEPT9 NM_006640 2141 CAGTGACCACGAGTACCAGG 2142 CTTCGATGGTACCCCACTTG
    SERPINA3 NM_001085 2145 GTGTGGCCCTGTCTGCTTA 2146 CCCTGTGCATGTGAGAGCTAC
    SERPINB5 NM_002639 2149 CAGATGGCCACTTTGAGAACATT 2150 GGCAGCATTAACCACAAGGATT
    SESN3 NM_144665 2153 GACCCTGGTTTTGGGTATGA 2154 GAGCTCGGAATGTTGGCA
    SFRP4 NM_003014 2157 TACAGGATGAGGCTGGGC 2158 GTTGTTAGGGCAAGGGGC
    SH3RF2 NM_152550 2161 CCATCACAACAGCCTTGAAC 2162 CACTGGGGTGCTGATCTCTA
    SH3YL1 NM_015677 2165 CCTCCAAAGCCATTGTCAAG 2166 CTTTGAGAGCCAGAGTTCAGC
    SHH NM_000193 2169 GTCCAAGGCACATATCCACTG 2170 GAAGCAGCCTCCCGATTT
    SHMT2 NM_005412 2173 AGCGGGTGCTAGAGCTTGTA 2174 ATGGCACTTCGGTCTCCA
    SIM2 NM_005069 2177 GATGGTAGGAAGGGATGTGC 2178 CACAAGGAGCTGTGAATGAGG
    SIPA1L1 NM_015556 2181 CTAGGACAGCTTGGCTTCCA 2182 CATAACCGTAGGGCTCCACA
    SKIL NM_005414 2185 AGAGGCTGAATATGCAGGACA 2186 CTATCGGCCTCAGCATGG
    SLC22A3 NM_021977 2189 ATCGTCAGCGAGTTTGACCT 2190 CAGGATGGCTTGGGTGAG
    SLC25A21 NM_030631 2193 AAGTGTTTTTCCCCCTTGAGAT 2194 GGCCGATCGATAGTCTCTCTT
    SLC44A1 NM_080546 2197 AGGACCGTAGCTGCACAGAC 2198 ATCCCATCCCAATGCAGA
    SMAD4 NM_005359 2201 GGACATTACTGGCCTGTTCACA 2202 ACCAATACTCAGGAGCAGGATGA
    SMARCC2 NM_003075 2205 TACCGACTGAACCCCCAA 2206 GACATCACCCGCTAGGTTTC
    SMARCD1 NM_003076 2209 CCGAGTTAGCATATCCCAGG 2210 CCTTTGTGCCCAGCTGTC
    SMO NM_005631 2213 GGCATCCAGTGCCAGAAC 2214 CGCGATGTAGCTGTGCAT
    SNAI1 NM_005985 2217 CCCAATCGGAAGCCTAACTA 2218 GTAGGGCTGCTGGAAGGTAA
    SNRPB2 NM_003092 2221 CGTTTCCTGCTTTTGGTTCT 2222 AGGTAGAAGGCGCACGAA
    SOD1 NM_000454 2225 TGAAGAGAGGCATGTTGGAG 2226 AATAGACACATCGGCCACAC
    SORBS1 NM_015385 2229 GCAGATGAGTGGAGGCTTTC 2230 AGCGAGTGAAGAGGGCTG
    SOX4 NM_003107 2233 AGATGATCTCGGGAGACTGG 2234 GCGCCCTTCAGTAGGTGA
    SPARC NM_003118 2237 TCTTCCCTGTACACTGGCAGTTC 2238 AGCTCGGTGTGGGAGAGGTA
    SPARCL1 NM_004684 2241 GGCACAGTGCAAGTGATGA 2242 GATTGAGCTCTCTCGGCCT
    SPDEF NM_012391 2245 CCATCCGCCAGTATTACAAG 2246 GGGTGCACGAACTGGTAGA
    SPINK1 NM_003122 2249 CTGCCATATGACCCTTCCAG 2250 GTTGAAAACTGCACCGCAC
    SPINT1 NM_003710 2253 ATTCCCAGCACAGGCTCTGT 2254 AGATGGCTACCACCACCACAA
    SPP1 NM_ 2257 TCACACATGGAAAGCGAGG 2258 GTTCAGGTCCTGGGCAAC
    001040058
    SQLE NM_003129 2261 ATTTTCGAGGCCAAAAAATC 2262 CCTGAGCAAGGATATTCACG
    SRC NM_005417 2265 TGAGGAGTGGTATTTTGGCAAGA 2266 CTCTCGGGTTCTCTGCATTGA
    SRD5A1 NM_001047 2269 GGGCTGGAATCTGTCTAGGA 2270 CCATGACTGCACAATGGCT
    SRD5A2 NM_000348 2273 GTAGGTCTCCTGGCGTTCTG 2274 TCCCTGGAAGGGTAGGAGTAA
    STS NM_005418 2277 CCTGTCCTGCCAGAGCAT 2278 CAGCTGCACAAAACTGGC
    STAT1 NM_007315 2281 GGGCTCAGCTTTCAGAAGTG 2282 ACATGTTCAGCTGGTCCACA
    STAT3 NM_003150 2285 TCACATGCCACTTTGGTGTT 2286 CTTGCAGGAAGCGGCTATAC
    STAT5A NM_003152 2289 GAGGCGCTCAACATGAAATTC 2290 GCCAGGAACACGAGGTTCTC
    STAT5B NM_012448 2293 CCAGTGGTGGTGATCGTTCA 2294 GCAAAAGCATTGTCCCAGAGA
    STMN1 NM_005563 2297 AATACCCAACGCACAAATGA 2298 GGAGACAATGCAAACCACAC
    STS NM_000351 2301 GAAGATCCCTTTCCTCCTACTGTTC 2302 GGATGATGTTCGGCCTTGAT
    SULF1 NM_015170 2305 TGCAGTTGTAGGGAGTCTGG 2306 TCTCAAGAATTGCCGTTGAC
    SUMO1 NM_003352 2309 GTGAAGCCACCGTCATCATG 2310 CCTTCCTTCTTATCCCCCAAGT
    SVIL NM_003174 2313 ACTTGCCCAGCACAAGGA 2314 GACACCATCCGTGTCACATC
    TAF2 NM_003184 2317 GCGCTCCACTCTCAGTCTTT 2318 CTTGTGCTCATGGTGATGGT
    TARP NM_ 2321 GAGCAACACGATTCTGGGA 2322 GGCACCGTTAACCAGCTAAAT
    001003799
    TBP NM_003194 2325 GCCCGAAACGCCGAATATA 2326 CGTGGCTCTCTTATCCTCATGAT
    TFDP1 NM_007111 2329 TGCGAAGTGCTTTTGTTTGT 2330 GCCTTCCAGACAGTCTCCAT
    TFF1 NM_003225 2333 GCCCTCCCAGTGTGCAAAT 2334 CGTCGATGGTATTAGGATAGAAGCA
    TFF3 NM_003226 2337 AGGCACTGTTCATCTCAGTTTTTCT 2338 CATCAGGCTCCAGATATGAACTTTC
    TGFA NM_003236 2341 GGTGTGCCACAGACCTTCCT 2342 ACGGAGTTCTTGACAGAGTTTTGA
    TGFB1I1 NM_ 2345 GCTACTTTGAGCGCTTCTCG 2346 GGTCACCATCTTGTGTCGG
    001042454
    TGFB2 NM_003238 2349 ACCAGTCCCCCAGAAGACTA 2350 CCTGGTGCTGTTGTAGATGG
    TGFB3 NM_003239 2353 GGATCGAGCTCTTCCAGATCCT 2354 GCCACCGATATAGCGCTGTT
    TGFBR2 NM_003242 2357 AACACCAATGGGTTCCATCT 2358 CCTCTTCATCAGGCCAAACT
    THBS2 NM_003247 2361 CAAGACTGGCTACATCAGAGTCTTAG 2362 CAGCGTAGGTTTGGTCATAGATAGG
    TG
    THY1 NM_006288 2365 GGACAAGACCCTCTCAGGCT 2366 TTGGAGGCTGTGGGTCAG
    TIAM1 NM_003253 2369 GTCCCTGGCTGAAAATGG 2370 GGGCTCCCGAAGTCTTCTA
    TIMP2 NM_003255 2373 TCACCCTCTGTGACTTCATCGT 2374 TGTGGTTCAGGCTCTTCTTCTG
    TIMP3 NM_000362 2377 CTACCTGCCTTGCTTTGTGA 2378 ACCGAAATTGGAGAGCATGT
    TK1 NM_003258 2381 GCCGGGAAGACCGTAATTGT 2382 CAGCGGCACCAGGTTCAG
    TMPRSS2 NM_005656 2385 GGACAGTGTGCACCTCAAAG 2386 CTCCCACGAGGAAGGTCC
    TMPRSS2 0Q204772 2389 GAGGCGGAGGGCGAG 2390 ACTGGTCCTCACTCACAACT
    ERGA
    TMPRSS2 0Q204773 2393 GAGGCGGAGGGCGAG 2394 TTCCTCGGGTCTCCAAAGAT
    ERGB
    TNF NM_000594 2397 GGAGAAGGGTGACCGACTCA 2398 TGCCCAGACTCGGCAAAG
    TNFRSF10A NM_003844 2401 TGCACAGAGGGTGTGGGTTAC 2402 TCTTCATCTGATTTACAAGCTGTACATG
    TNFRSF10B NM_003842 2405 CTCTGAGACAGTGCTTCGATGACT 2406 CCATGAGGCCCAACTTCCT
    TNFRSF18 NM_148901 2409 CAGAAGCTGCCAGTTCCC 2410 CACCCACAGGTCTCCCAG
    TNFSF10 NM_003810 2413 CTTCACAGTGCTCCTGCAGTCT 2414 CATCTGCTTCAGCTCGTTGGT
    TNFSF11 NM_003701 2417 AACTGCATGTGGGCTATGG 2418 TGACACCCTCTCCACTTCAG
    TOP2A NM_001067 2421 AATCCAAGGGGGAGAGTGAT 2422 GTACAGATTTTGCCCGAGGA
    TP53 NM_000546 2425 CTTTGAACCCTTGCTTGCAA 2426 CCCGGGACAAAGCAAATG
    TP63 NM_003722 2429 CCCCAAGCAGTGCCTCTACA 2430 GAATCGCACAGCATCAATAACAC
    TPD52 NM_005079 2433 GCCTGTGAGATTCCTACCTTTG 2434 ATGTGCTTGGACCTCGCTT
    TPM1 NM_ 2437 TCTCTGAGCTCTGCATTTGTC 2438 GGCTCTAAGGCAGGATGCTA
    001018005
    TPM2 NM_213674 2441 AGGAGATGCAGCTGAAGGAG 2442 CCACCTCTTCATATTTGCGG
    TPP2 NM_003291 2445 TAACCGTGGCATCTACCTCC 2446 ATGCCAACGCCATGATCT
    TPX2 NM_012112 2449 TCAGCTGTGAGCTGCGGATA 2450 ACGGTCCTAGGTTTGAGGTTAAGA
    TRA2A NM_013293 2453 GCAAATCCAGATCCCAACAC 2454 CTTCACGAAGATCCCTCTCTG
    TRAF3IP2 NM_147200 2457 CCTCACAGGAACCGAGCA 2458 CTGGGGCTGGGAATCATA
    TRAM1 NM_014294 2461 CAAGAAAAGCACCAAGAGCC 2462 ATGTCCGCGTGATTCTGC
    TRAP1 NM_016292 2465 TTACCAGTGGCTTTCAGATGG 2466 TGTCCCGGTTCTAACTCCC
    TRIM14 NM_033220 2469 CATTCGCCTTAAGGAAAGCA 2470 CAAGGTACCTGGCTTGGTG
    TRO NM_177556 2473 GCAACTGCCACCCATACAG 2474 TGGTGTGGATACTGGCTGTC
    TRPC6 NM_004621 2477 CGAGAGCCAGGACTATCTGC 2478 TAGCCGTAGCAAGGCAGC
    TRPV6 NM_018646 2481 CCGTAGTCCCTGCAACCTC 2482 TCCTCACTGTTCACACAGGC
    TSTA3 NM_003313 2485 CAATTTGGACTTCTGGAGGAA 2486 CACCTCAAAGGCCGAGTG
    TUBB2A NM_001069 2489 CGAGGACGAGGCTTAAAAAC 2490 ACCATGCTTGAGGACAACAG
    TYMP NM_001953 2493 CTATATGCAGCCAGAGATGTGACA 2494 CCACGAGTTTCTTACTGAGAATGG
    TYMS NM_001071 2497 GCCTCGGTGTGCCTTTCA 2498 CGTGATGTGCGCAATCATG
    UAP1 NM_003115 2501 CTGGAGACGGTCGTAGCTG 2502 GCCAAGCTTTGTAGAAATAGGG
    UBE2C NM_007019 2505 TGTCTGGCGATAAAGGGATT 2506 ATGGTCCCTACCCATTTGAA
    UBE2G1 NM_003342 2509 TGACACTGAACGAGGTGGC 2510 AAGCAGAGAGGAATCGCCT
    UBE2T NM_014176 2513 TGTTCTCAAATTGCCACCAA 2514 AGAGGTCAACACAGTTGCGA
    UGDH NM_003359 2517 GAAACTCCAGAGGGCCAGA 2518 CTCTGGGAACCCAGTGCTC
    UGT2B15 NM_001076 2521 AAGCCTGAAGTGGAATGACTG 2522 CCTCCATTTAAAACCCTCCA
    UGT2B17 NM_001077 2525 TTGAGTTTGTCATGCGCC 2526 TCCAGGTGAGGTTGTGGG
    UHRF1 NM_013282 2529 CTACAGGGGCAAACAGATGG 2530 GGTGTCATTCAGGCGGAC
    UTP23 NM_032334 2533 GATTGCACAAAAATGCCAAG 2534 GGAAAGCAGACATTCTGATCC
    VCAM1 NM_001078 2537 TGGCTTCAGGAGCTGAATACC 2538 TGCTGTCGTGATGAGAAAATAGTG
    VCL NM_003373 2541 GATACCACAACTCCCATCAAGCT 2542 TCCCTGTTAGGCGCATCAG
    VCPIP1 NM_025054 2545 TTTCTCCCAGTACCATTCGTG 2546 TGAATAGGGAGCCTTGGTAGG
    VDR NM_000376 2549 CCTCTCCTTCCAGCCTGAGT 2550 TCATTGCCAAACACTTCGAG
    VEGFA NM_003376 2553 CTGCTGTCTTGGGTGCATTG 2554 GCAGCCTGGGACCACTTG
    VEGFB NM_003377 2557 TGACGATGGCCTGGAGTGT 2558 GGTACCGGATCATGAGGATCTG
    VEGFC NM_005429 2561 CCTCAGCAAGACGTTATTTGAAATT 2562 AAGTGTGATTGGCAAAACTGATTG
    VIM NM_003380 2565 TGCCCTTAAAGGAACCAATGA 2566 GCTTCAACGGCAAAGTTCTCTT
    VTI1B NM_006370 2569 ACGTTATGCACCCCTGTCTT 2570 CCGATGGAGTTTAGCAAGGT
    WDR19 NM_025132 2573 GAGTGGCCCAGATGTCCATA 2574 GATGCTTGAGGGCTTGGTT
    WFDC1 NM_021197 2577 ACCCCTGCTCTGTCCCTC 2578 ATACCTTCGGCCACGTCAC
    WISP1 NM_003882 2581 AGAGGCATCCATGAACTTCACA 2582 CAAACTCCACAGTACTTGGGTTGA
    WNT5A NM_003392 2585 GTATCAGGACCACATGCAGTACATC 2586 TGTCGGAATTGATACTGGCATT
    WWOX NM_016373 2589 ATCGCAGCTGGTGGGTGTAC 2590 AGCTCCCTGTTGCATGGACTT
    XIAP NM_001167 2593 GCAGTTGGAAGACACAGGAAAGT 2594 TGCGTGGCACTATTTTCAAGA
    XRCC5 NM_021141 2597 AGCCCACTTCAGCGTCTC 2598 AGCAGGATTCACACTTCCAAC
    YY1 NM_003403 2601 ACCCGGGCAACAAGAAGT 2602 GACCGAGAACTCGCCCTC
    ZFHX3 NM_006885 2605 CTGTGGAGCCTCTGCCTG 2606 GGAGCAGGGTTGGATTGAG
    ZFP36 NM_003407 2609 CATTAACCCACTCCCCTGA 2610 CCCCCACCATCATGAATACT
    ZMYND8 NM_183047 2613 GGTCTGGGCCAAACTGAAG 2614 TGCCCGTCTTTATCCCTTAG
    ZNF3 NM_017715 2617 CGAAGGGACTCTGCTCCA 2618 GCAGGAGGTCCTCAGAAGG
    ZNF827 NM_178835 2621 TGCCTGAGGACCCTCTACC 2622 GAGGTGGCGGAGTGACTTT
    ZWINT NM_007057 2625 TAGAGGCCATCAAAATTGGC 2626 TCCGTTTCCTCTGGGCTT
    SEQ SEQ
    Official ID ID
    Symbol: NO Probe Sequence: NO Amplicon Sequence:
    AAMP 3 CGCTTCAAAGGACCAGACCTCCTC 4 GTGTGGCAGGTGGACACTAAGGAGGAGGTCTGGTCCTTTGAA
    GCGGGAGACCTGGAGTGGATGGAG
    ABCA5 7 CACATGTGGCGAGCAATTCGAACT 5 GGTATGGATCCCAAAGCCAAACAGCACATGTGGCGAGCAATT
    CGAACTGCATTTAAAAACAGAAAGCGGGCTG
    ABCB1 11 CAAGCCTGGAACCTATAGCC 12 AAACACCACTGGAGCATTGACTACCAGGCTCGCCAATGATGCT
    GCTCAAGTTAAAGGGGCTATAGGTTCCAGGCTTG
    ABCC1 15 ACCTGATACGTCTTGGTCTTCATCGCC 16 TCATGGTGCCCGTCAATGCTGTGATGGCGATGAAGACCAAGA
    AT CGTATCAGGTGGCCCACATGAAGAGCAAAGACAATCG
    ABCC3 19 TCTGTCCTGGCTGGAGTCGCTTTCAT 20 TCATCCTGGCGATCTACTTCCTCTGGCAGAACCTAGGTCCCTC
    TGTCCTGGCTGGAGTCGCTTTCATGGTCTTGCTGATTCCACTC
    AACGG
    ABCC4 23 CGGAGTCCAGTGTTTTCCCACTTA 24 AGCGCCTGGAATCTACAACTCGGAGTCCAGTGTTTTCCCACTT
    ATCATCTTCTCTCCAGGGGCTCT
    ABCC8 27 AGTCTCTTGGCCACCTTCAGCCCT 28 CGTCTGTCACTGTGGAGTGGACAGGGCTGAAGGTGGCCAAGA
    GACTGCACCGCAGCCTGCTAAACCGGATCA
    ABCG2 31 ACGAAGATTTGCCTCCACCTGTGG 32 GGTCTCAACGCCATCCTGGGACCCACAGGTGGAGGCAAATCT
    TCGTTATTAGATGTCTTAGCTGCAAGGAAAGATCCAAG
    ABHD2 35 CAGGTGGCTCCTTTGATCCCTGA 36 GTAGTGGGTCTGCATGGATGTTTCAGGGATCAAAGGAGCCAC
    CTGGGCGCCTGAGTGCCAACCCTCA
    ACE 39 TGCCCTCAGCAATGAAGCCTACAA 40 CCGCTGTACGAGGATTTCACTGCCCTCAGCAATGAAGCCTACA
    AGCAGGACGGCTTCACAGACACGG
    ACOX2 43 TGCTCTCAACTTTCCTGCGGAGTG 44 ATGGAGGTGCCCAGAACACTGCACTCCGCAGGAAAGTTGAGA
    GCATCATCCACAGTTACCCGGAGT
    ACTR2 47 CCCGCAGAAAGCACATGGTATTCC 48 ATCCGCATTGAAGACCCACCCCGCAGAAAGCACATGGTATTCC
    TGGGTGGTGCAGTTCTAGCGGAT
    ADAM15 51 TCAGCCACAATCACCAACTCCACA 52 GGCGGGATGTGGTAACAGAGACCAAGACTGTGGAGTTGGTGA
    TTGTGGCTGATCACTCGGAGGCCCAGAAAT
    ADAMTS1 55 CAAGCCAAAGGCATTGGCTACTTCTTCG 56 GGACAGGTGCAAGCTCATCTGCCAAGCCAAAGGCATTGGCTA
    CTTCTTCGTTTTGCAGCCCAAGGTTGTAGAT
    ADH5 59 TGTCTGCCCATTATCTTCATTCTGCAA 60 ATGCTGTCATCATTGTCACGGTTTGTCTGCCCATTATCTTCATT
    CTGCAAGGGAAAGGGAAAGGAAGCAG
    AFAP1 63 CCTCCAGTGCTGTGTTCCCAGAAG 64 GATGTCCATCCTTGAAACAGCCTCTTCTGGGAACACAGCACTG
    GAGGTCTCCAGGCATCAGGGTTG
    AGTR1 67 ATTGTTCACCCAATGAAGTCCCGC 68 AGCATTGATCGATACCTGGCTATTGTTCACCCAATGAAGTCCC
    GCCTTCGACGCACAATGCTTGTAG
    AGTR2 71 CCACCCAGACCCCATGTAGCAAAA 72 ACTGGCATAGGAAATGGTATCCAGAATGGAATTTTGCTACATG
    GGGTCTGGGTGGGGGCAAAGAGACCCAGTCAAT
    AIG1 75 AATCGAGATGAGGACATCGCACCA 76 CGACGGTTCTGCCCTTTATATTAATCGAGATGAGGACATCGCA
    CCATCAGTATCCCAGCAGGAGCA
    AKAP1 79 CTCCACCAGGGACCGGTTTATCAA 80 TGTGGTTGGAGATGAAGTGGTGTTGATAAACCGGTCCCTGGTG
    GAGCGAGGCCTTGCCCAGTGGGTAGAC
    AKR1C1 83 CCAAATCCCAGGACAGGCATGAAG 84 GTGTGTGAAGCTGAATGATGGTCACTTCATGCCTGTCCTGGGA
    TTTGGCACCTATGCGCCTGCAGAG
    AKR1C3 87 TGCGTCACCATCCACACACAGGG 88 GCTTTGCCTGATGTCTACCAGAAGCCCTGTGTGTGGATGGTGA
    CGCAGAGGACGTCTCTATGCCGGTGACTGGAC
    AKT1 91 CAGCCCTGGACTACCTGCACTCGG 92 CGCTTCTATGGCGCTGAGATTGTGTCAGCCCTGGACTACCTGC
    ACTCGGAGAAGAACGTGGTGTACCGGGA
    AKT2 95 CAGGTCACGTCCGAGGTCGACACA 96 TCCTGCCACCCTTCAAACCTCAGGTCACGTCCGAGGTCGACA
    CAAGGTACTTCGATGATGAATTTACCGCC
    AKT3 99 TCACGGTACACAATCTTTCCGGA 100 TTGTCTCTGCCTTGGACTATCTACATTCCGGAAAGATTGTGTAC
    CGTGATCTCAAGTTGGAGAATCTAATGCTGG
    ALCAM 103 CCAGTTCCTGCCGTCTGCTCTTCT 104 GAGGAATATGGAATCCAAGGGGGCCAGTTCCTGCCGTCTGCT
    CTTCTGCCTCTTGATCTCCGCCAC
    ALDH18A1 107 CCTGAAACTTGCATCTCCTGCTGC 108 GATGCAGCTGGAACCCAAGCTGCAGCAGGAGATGCAAGTTTC
    AGGATGTTCCCCACTGAGCTGGAG
    ALDH1A2 111 TCTCTGTAGGGCCCAGCTCTCAGG 112 CACGTCTGTCCCTCTCTGCTTTCTCTGTAGGGCCCAGCTCTCA
    GGAATACAAAGTTGAGCCACGGTC
    ALKBH3 115 TAAACAGGGCAGTCACTTTCCGCA 116 TCGCTTAGTCTGCACCTCAACCGTGCGGAAAGTGACTGCCCTG
    TTTACTGAGGAAAAACTGGGGCTCAGA
    ALOX12 119 CATGCTGTTGAGACGCTCGACCTC 120 AGTTCCTCAATGGTGCCAACCCCATGCTGTTGAGACGCTCGAC
    CTCTCTGCCCTCCAGGCTAGTGCT
    ALOX5 123 CCGCATGCCGTACACGTAGACATC 124 GAGCTGCAGGACTTCGTGAACGATGTCTACGTGTACGGCATG
    CGGGGCCGCAAGTCCTCAGGCTTC
    AMACR 127 TCCATGTGTTTGATTTCTCCTCAGGC 128 GTCTCTGGGCTGTCAGCTTTCCTTTCTCCATGTGTTTGATTTCT
    CCTCAGGCTGGTAGCAAGTTCTGGATCTTATACCCA
    AMPD3 131 TACTCTCCCAACATGCGCTGGATC 132 TGGTTCATCCAGCACAAGGTCTACTCTCCCAACATGCGCTGGA
    TCATCCAGGTGCCCCGGATTTATG
    ANGPT2 135 AAGCTGACACAGCCCTCCCAAGTG 136 CCGTGAAAGCTGCTCTGTAAAAGCTGACACAGCCCTCCCAAGT
    GAGCAGGACTGTTCTTCCCACTGCAA
    ANLN 139 CCAAAGAACTCGTGTCCCTCGAGC 140 TGAAAGTCCAAAACCAGGAAAATTCCAAAGAACTCGTGTCCCT
    CGAGCTGAATCTGGTGATAGCCTTGGTTCTG
    ANPEP 143 CTCCCCAACACGCTGAAACCCG 144 CCACCTTGGACCAAAGTAAAGCGTGGAATCGTTACCGCCTCCC
    CAACACGCTGAAACCCGATTCCTACCGGGTGACGCTGAGA
    ANXA2 147 CCACCACACAGGTACAGCAGCGCT 148 CAAGACACTAAGGGCGACTACCAGAAAGCGCTGCTGTACCTG
    TGTGGTGGAGATGACTGAAGCCCGACACG
    APC 151 CATTGGCTCCCCGTGACCTGTA 152 GGACAGCAGGAATGTGTTTCTCCATACAGGTCACGGGGAGCC
    AATGGTTCAGAAACAAATCGAGTGGGT
    APEX1 155 CTTTCGGGAAGCCAGGCCCTT 156 GATGAAGCCTTTCGCAAGTTCCTGAAGGGCCTGGCTTCCCGAA
    AGCCCCTTGTGCTGTGTGGAGACCT
    APOC1 159 AGGACAGGACCTCCCAACCAAGC 160 CCAGCCTGATAAAGGTCCTGCGGGCAGGACAGGACCTCCCAA
    CCAAGCCCTCCAGCAAGGATTCAGAGTG
    APOE 163 ACTGGCGCTGCATGTCTTCCAC 164 GCCTCAAGAGCTGGTTCGAGCCCCTGGTGGAAGACATGCAGC
    GCCAGTGGGCCGGGCTGGTGGAGAAGGTGCAGG
    APRT 167 CCTTAAGCGAGGTCAGCTCCACCA 168 GAGGTCCTGGAGTGCGTGAGCCTGGTGGAGCTGACCTCGCTT
    AAGGGCAGGGAGAAGCTGGCACCT
    AQP2 171 CTCCTTCCCTTCCCCTTCTCCTGA 172 GTGTGGGTGCCAGTCCTCCTCAGGAGAAGGGGAAGGGAAGG
    AGGCCACTTTGAGAGGGCTGAAGGG
    AR 175 ACCATGCCGCCAGGGTACCACA 176 CGACTTCACCGCACCTGATGTGTGGTACCCTGGCGGCATGGT
    GAGCAGAGTGCCCTATCCCAGTCCCACTTGTGTCA
    ARF1 179 CTTGTCCTTGGGTCACCCTGCA 180 CAGTAGAGATCCCCGCAACTCGCTTGTCCTTGGGTCACCCTGC
    ATTCCATAGCCATGTGCTTGT
    ARHGAP29 183 ATGCCAGACCCAGACAAAGCATCA 184 CACGGTCTCGTGGTGAAGTCAATGCCAGACCCAGACAAAGCA
    TCAGCTTGTCCTGGGCAAGCAACTG
    ARHGDIB 187 TAAAACCGGGCTTTCACCCAACCT 188 TGGTCCCTAGAACAAGAGGCTTAAAACCGGGCTTTCACCCAAC
    CTGCTCCCTCTGATCCTCCATCA
    ASAP2 191 CTGGGCTCCAACCAGCTTCAGTCT 192 CGGCCCATCAGCTTCTACCAGCTGGGCTCCAACCAGCTTCAG
    TCTAACGCTGTATCTTTGGCCAGAG
    ASPN 195 AGTATCACCCAGGGTGCAGCCAC 196 TGGACTAATCTGTGGGAGCAGTTTATTCCAGTATCACCCAGGG
    TGCAGCCACACCAGGACTGTGTTGAAGGGTGTTT
    ATM 199 CCAGCTGTCTTCGACACTTCTCGC 200 TGCTTTCTACACATGTTCAGGGATTTTTCACCAGCTGTCTTCGA
    CACTTCTCGCAAACGAGCCGATCCACAAC
    ATP5E 203 TCCAGCCTGTCTCCAGTAGGCCAC 204 CCGCTTTCGCTACAGCATGGTGGCCTACTGGAGACAGGCTGG
    ACTCAGCTACATCCGATACTCCCA
    ATP5J 207 CTACCCGCCATCGCAATGCATTAT 208 GTCGACCGACTGAAACGGCGGCCCATAATGCATTGCGATGGC
    GGGTAGGCGTGTGGGGGCGGAGCCAGGGCCGGAAGTAGAG
    ATXN1 211 CGGGCTATGGCTGTCTTCAATCCT 212 GATCGACTCCAGCACCGTAGAGAGGATTGAAGACAGCCATAG
    CCCGGGCGTGGCCGTGATACAGTTC
    AURKA 215 CTCTGTGGCACCCTGGACTACCTG 216 CATCTTCCAGGAGGACCACTCTCTGTGGCACCCTGGACTACCT
    GCCCCCTGAAATGATTGAAGGTCGGA
    AURKB 219 TGACGAGCAGCGAACAGCCACG 220 AGCTGCAGAAGAGCTGCACATTTGACGAGCAGCGAACAGCCA
    CGATCATGGAGGAGTTGGCAGATGC
    AXIN2 223 ACCAGCGCCAACGACAGTGAGATA 224 GGCTATGTCTTTGCACCAGCCACCAGCGCCAACGACAGTGAG
    ATATCCAGTGATGCGCTGACGGAT
    AZGP1 227 TCTGAGATCCCACATTGCCTCCAA 228 GAGGCCAGCTAGGAAGCAAGGGTTGGAGGCAATGTGGGATCT
    CAGACCCAGTAGCTGCCCTTCCTG
    BAD 231 TGGGCCCAGAGCATGTTCCAGATC 232 GGGTCAGGGGCCTCGAGATCGGGCTTGGGCCCAGAGCATGTT
    CCAGATCCCAGAGTTTGAGCCGAGTGAGCAG
    BAG5 235 ACACCGGATTTAGCTCTTGTCGGC 236 ACTCCTGCAATGAACCCTGTTGACACCGGATTTAGCTCTTGTC
    GGCCTTCGTGGGGAGCTGTTTGT
    BAK1 239 ACACCCCAGACGTCCTGGCCT 240 CCATTCCCACCATTCTACCTGAGGCCAGGACGTCTGGGGTGT
    GGGGATTGGTGGGTCTATGTTCCC
    BAX 243 TGCCACTCGGAAAAAGACCTCTCGG 244 CCGCCGTGGACACAGACTCCCCCCGAGAGGTCTTTTTCCGAG
    TGGCAGCTGACATGTTTTCTGACGGCAA
    BBC3 247 CATCATGGGACTCCTGCCCTTACC 248 CCTGGAGGGTCCTGTACAATCTCATCATGGGACTCCTGCCCTT
    ACCCAGGGGCCACAGAGCCCCCGAGATGGAGCCCAATTAG
    BCL2 251 TTCCACGCCGAAGGACAGCGAT 252 CAGATGGACCTAGTACCCACTGAGATTTCCACGCCGAAGGAC
    AGCGATGGGAAAAATGCCCTTAAATCATAGG
    BDKRB1 255 ACCTGGCAGCCTCTGATCTGGTGT 256 GTGGCAGAAATCTACCTGGCCAACCTGGCAGCCTCTGATCTG
    GTGTTTGTCTTGGGCTTGCCCTTC
    BGN 259 CAAGGGTCTCCAGCACCTCTACGC 260 GAGCTCCGCAAGGATGACTTCAAGGGTCTCCAGCACCTCTAC
    GCCCTCGTCCTGGTGAACAACAAG
    BIK 263 CCGGTTAACTGTGGCCTGTGCCC 264 ATTCCTATGGCTCTGCAATTGTCACCGGTTAACTGTGGCCTGT
    GCCCAGGAAGAGCCATTCACTCCTGCC
    BIN1 267 CTTCGCCTCCAGATGGCTCCC 268 CCTGCAAAAGGGAACAAGAGCCCTTCGCCTCCAGATGGCTCC
    CCTGCCGCCACCCCCGAGATCAGAGTCAACCACG
    BIRC5 271 TCTGCCAGACGCTTCCTATCACTCTATTC 272 TTCAGGTGGATGAGGAGACAGAATAGAGTGATAGGAAGCGTC
    TGGCAGATACTCCTTTTGCCACTGCTGTGTG
    BMP6 275 TGAACCCCGAGTATGTCCCCAAAC 276 GTGCAGACCTTGGTTCACCTTATGAACCCCGAGTATGTCCCCA
    AACCGTGCTGTGCGCCAACTAAG
    BMPR1B 279 ATTCACATTACCATAGCGGCCCCA 280 ACCACTTTGGCCATCCCTGCATTTGGGGCCGCTATGGTAATGT
    GAATGCACTGGGTACAAACACCGC
    BRCA1 283 CTATGGGCCCTTCACCAACATGC 284 TCAGGGGGCTAGAAATCTGTTGCTATGGGCCCTTCACCAACAT
    GCCCACAGATCAACTGGAATGG
    BRCA2 287 CATTCTTCACTGCTTCATAAAGCTCTGCA 288 AGTTCGTGCTTTGCAAGATGGTGCAGAGCTTTATGAAGCAGTG
    AAGAATGCAGCAGACCCAGCTTACCTT
    BTG1 291 CGCTCGTCTCTTCCTCTCTCCTGC 292 GAGGTCCGAGCGATGTGACCAGGCCGCCATCGCTCGTCTCTT
    CCTCTCTCCTGCCGCCTCCTGTCTCGAAAATAACT
    BTG3 295 CATGGGTACCTCCTCCTGGAATGC 296 CCATATCGCCCAATTCCAGTGACATGGGTACCTCCTCCTGGAA
    TGCATTGTGACCGGAATCACTGG
    BTRC 299 CAGTCGGCCCAGGACGGTCTACT 300 GTTGGGACACAGTTGGTCTGCAGTCGGCCCAGGACGGTCTAC
    TCAGCACAACTGACTGCTTCA
    BUB1 303 TGCTGGGAGCCTACACTTGGCCC 304 CCGAGGTTAATCCAGCACGTATGGGGCCAAGTGTAGGCTCCC
    AGCAGGAACTGAGAGCGCCATGTCTT
    C7 307 ATGCTCTGCCCTCTGCATCTCAGA 308 ATGTCTGAGTGTGAGGCGGGCGCTCTGAGATGCAGAGGGCAG
    AGCATCTCTGTCACCAGCATAAGGCCT
    CACNA1D 311 CAGTACACTGGCGTCCATTCCCTG 312 AGGACCCAGCTCCATGTGCGTTCTCAGGGAATGGACGCCAGT
    GTACTGCCAATGGCACGGAATGTAGG
    CADM1 315 TCTTCACCTGCTCGGGAATCTGTG 316 CCACCACCATCCTTACCATCATCACAGATTCCCGAGCAGGTGA
    AGAAGGCTCGATCAGGGCAGTGGATC
    CADPS 319 CTCCTGGATGGCCAAATTTGATGC 320 CAGCAAGGAGACTGTGCTGAGCTCCTGGATGGCCAAATTTGAT
    GCCATCTACCGTGGAGAAGAGGACC
    CASP1 323 TCACAGGCATGACAATGCTGCTACA 324 AACTGGAGCTGAGGTTGACATCACAGGCATGACAATGCTGCTA
    CAAAATCTGGGGTACAGCGTAGATG
    CASP3 327 TCAGCCTGTTCCATGAAGGCAGAGC 328 TGAGCCTGAGCAGAGACATGACTCAGCCTGTTCCATGAAGGC
    AGAGCCATGGACCACGCAGGAAGG
    CASP7 331 CTTTCGCTAAAGGGGCCCCAGAC 332 GCAGCGCCGAGACTTTTAGTTTCGCTTTCGCTAAAGGGGCCCC
    AGACCCTTGCTGCGGAGCGACGGAGAGAGACT
    CAV1 335 ATTTCAGCTGATCAGTGGGCCTCC 336 GTGGCTCAACATTGTGTTCCCATTTCAGCTGATCAGTGGGCCT
    CCAAGGAGGGGCTGTAAAATGGAGGCCATTG
    CAV2 339 CCCGTACTGTCATGCCTCAGAGCT 340 CTTCCCTGGGACGACTTGCCAGCTCTGAGGCATGACAGTACG
    GGCCCCCAGAAGGGTGACCAGGAG
    CCL2 343 TGCCCCAGTCACCTGCTGTTA 344 CGCTCAGCCAGATGCAATCAATGCCCCAGTCACCTGCTGTTAT
    AACTTCACCAATAGGAAGATCTCAGTGC
    CCL5 347 ACAGAGCCCTGGCAAAGCCAAG 348 AGGTTCTGAGCTCTGGCTTTGCCTTGGCTTTGCCAGGGCTCTG
    TGACCAGGAAGGAAGTCAGCAT
    CCNB1 351 TGTCTCCATTATTGATCGGTTCATGCA 352 TTCAGGTTGTTGCAGGAGACCATGTACATGACTGTCTCCATTAT
    TGATCGGTTCATGCAGAATAATTGTGTGCCCAAGAAGATG
    CCND1 355 AAGGAGACCATCCCCCTGACGGC 356 GCATGTTCGTGGCCTCTAAGATGAAGGAGACCATCCCCCTGA
    CGGCCGAGAAGCTGTGCATCTACACCG
    CCNE2 359 TACCAAGCAACCTACATGTCAAGAAAGC 360 ATGCTGTGGCTCCTTCCTAACTGGGGCTTTCTTGACATGTAGG
    CC TTGCTTGGTAATAACCTTTTTGTATATCACAATTTGGGT
    CCNH 363 CATCAGCGTCCTGGCGTAAAACAC 364 GAGATCTTCGGTGGGGGTACGGGTGTTTTACGCCAGGACGCT
    GATGCGTTTGGGTTCTCGTCTGCAG
    CCR1 367 ACTCACCACACCTGCAGCCTTCAC 368 TCCAAGACCCAATGGGAATTCACTCACCACACCTGCAGCCTTC
    ACTTTCCTCACGAAAGCCTACGA
    CD164 371 CCTCCAATGAAACTGGCTGCATCA 372 CAACCTGTGCGAAAGTCTACCTTTGATGCAGCCAGTTTCATTG
    GAGGAATTGTCCTGGTCTTGGGTGT
    CD1A 375 CGCACCATTCGGTCATTTGAGG 376 GGAGTGGAAGGAACTGGAAACATTATTCCGTATACGCACCATT
    CGGTCATTTGAGGGAATTCGTAGATACGCCCATGA
    CD276 379 CCACTGTGCAGCCTTATTTCTCCAATG 380 CCAAAGGATGCGATACACAGACCACTGTGCAGCCTTATTTCTC
    CAATGGACATGATTCCCAAGTCATCC
    CD44 383 ACTGGAACCCAGAAGCACACCCTC 384 GGCACCACTGCTTATGAAGGAAACTGGAACCCAGAAGCACAC
    CCTCCCCTCATTCACCATGAGCATC
    CD68 387 CTCCAAGCCCAGATTCAGATTCGAGTCA 388 TGGTTCCCAGCCCTGTGTCCACCTCCAAGCCCAGATTCAGATT
    CGAGTCATGTACACAACCCAGGGTGGAGGAG
    CD82 391 TCAGCTTCTACAACTGGACAGACAACGC 392 GTGCAGGCTCAGGTGAAGTGCTGCGGCTGGGTCAGCTTCTAC
    TG AACTGGACAGACAACGCTGAGCTCATGAATCGCCCTGAGGTC
    CDC20 395 ACTGGCCGTGGCACTGGACAACA 396 TGGATTGGAGTTCTGGGAATGTACTGGCCGTGGCACTGGACA
    ACAGTGTGTACCTGTGGAGTGCAAGC
    CDC25B 399 CTGCTACCTCCCTTGCCTTTCGAG 400 GCTGCAGGACCAGTGAGGGGCCTGCGCCAGTCCTGCTACCTC
    CCTTGCCTTTCGAGGCCTGAAGCCAGCTGCCCTA
    CDC6 403 TTGTTCTCCACCAAAGCAAGGCAA 404 GCAACACTCCCCATTTACCTCCTTGTTCTCCACCAAAGCAAGG
    CAAGAAAGAGAATGGTCCCCCTCA
    CDH1 407 TGCCAATCCCGATGAAATTGGAAATTT 408 TGAGTGTCCCCCGGTATCTTCCCCGCCCTGCCAATCCCGATGA
    AATTGGAAATTTTATTGATGAAAATCTGAAAGCGGCTG
    CDH10 411 ATGCCGATGACCCTTCATATGGGA 412 TGTGGTGCAAGTCACAGCTACAGATGCCGATGACCCTTCATAT
    GGGAACAGCGCCAGAGTCATTTACA
    CDH11 415 CCTTCTGCCCATAGTGATCAGCGA 416 GTCGGCAGAAGCAGGACTTGTACCTTCTGCCCATAGTGATCAG
    CGATGGCGGCATCCCGCCCATGAGTAG
    CDH19 419 ACTCGGAAAACCACAAGCGCTGAG 420 AGTACCATAATGCGGGAACGCAAGACTCGGAAAACCACAAGC
    GCTGAGATCAGGAGCCTATACAGGCAGTCT
    CDH5 423 TATTCTCCCGGTCCAGCCTCTCAA 424 ACAGGAGACGTGTTCGCCATTGAGAGGCTGGACCGGGAGAAT
    ATCTCAGAGTACCACCTCACTGCTG
    CDH7 427 ACCTCAACGTCATCCGAGACACCA 428 GTTTGACATGGCTGCACTGAGAAACCTCAACGTCATCCGAGAC
    ACCAAGACCCGGAGGGATGTGACT
    CDK14 431 CTTCCTGCAGCCTGATCACCTTCA 432 GCAAGGTAAATGGGAAGTTGGTAGCTCTGAAGGTGATCAGGC
    TGCAGGAAGAAGAAGGGACACCTTTCACAGCTATC
    CDK2 435 CCTTGGCCGAAATCCGCTTGT 436 AATGCTGCACTACGACCCTAACAAGCGGATTTCGGCCAAGGC
    AGCCCTGGCTCACCCTTTCTTCCAGGATGTGACCAA
    CDK3 439 CTCTGGCTCCAGATTGGGCACAAT 440 CCAGGAAGGGACTGGAAGAGATTGTGCCCAATCTGGAGCCAG
    AGGGCAGGGACCTGCTCATGCAAC
    CDK7 443 CCTCCCCAAGGAAGTCCAGCTTCT 444 GTCTCGGGCAAAGCGTTATGAGAAGCTGGACTTCCTTGGGGA
    GGGACAGTTTGCCACCGTTTACAAGGCCAGAG
    CDKN1A 447 CGGCGGCAGACCAGCATGAC 448 TGGAGACTCTCAGGGTCGAAAACGGCGGCAGACCAGCATGAC
    AGATTTCTACCACTCCAAACGCC
    CDKN1C 451 CGGGCCTCTGATCTCCGATTTCTT 452 CGGCGATCAAGAAGCTGTCCGGGCCTCTGATCTCCGATTTCTT
    CGCCAAGCGCAAGAGATCAGCGCCTG
    CDKN2B 455 CACAGGATGCTGGCCTTTGCTCTT 456 GACGCTGCAGAGCACCTTTGCACAGGATGCTGGCCTTTGCTCT
    TACTACACTGAGGAGAGATTCCCGC
    CDKN2C 459 CCTGTAACTTGAGGGCCACCGAAC 460 GAGCACTGGGCAATCGTTACGACCTGTAACTTGAGGGCCACC
    GAACTGCTACTCCCGTTCGCCTTTG
    CDKN3 463 ATCACCCATCATCATCCAATCGCA 464 TGGATCTCTACCAGCAATGTGGAATTATCACCCATCATCATCC
    AATCGCAGATGGAGGGACTCCTGACAT
    CDS2 467 CCCGGACATCACATAGGACAGCAG 468 GGGCTTCTTTGCTACTGTGGTGTTTGGCCTTCTGCTGTCCTAT
    GTGATGTCCGGGTACAGATGCTTTGTCTGCCCTGT
    CENPF 471 ACACTGGACCAGGAGTGCATCCAG 472 CTCCCGTCAACAGCGTTCTTTCCAAACACTGGACCAGGAGTGC
    ATCCAGATGAAGGCCAGACTCACCC
    CHAF1A 475 TGCACGTACCAGCACATCCTGAAG 476 GAACTCAGTGTATGAGAAGCGGCCTGACTTCAGGATGTGCTG
    GTACGTGCACCCGCAGGTGCTACAGAGC
    CHN1 479 CCACCATTGGCCGCTTAGTGGTAT 480 TTACGACGCTCGTGAAAGCACATACCACTAAGCGGCCAATGGT
    GGTAGACATGTGCATCAGGGAGA
    CHRAC1 483 ATCCGGGTCATCATGAAGAGCTCC 484 TCTCGCTGCCTCTATCCCGCATCCGGGTCATCATGAAGAGCTC
    CCCCGAGGTGTCCAGCATCAACCAGG
    CKS2 487 CTGCGCCCGCTCTTCGCG 488 GGCTGGACGTGGTTTTGTCTGCTGCGCCCGCTCTTCGCGCTCT
    CGTTTCATTTTCTGCAGCG
    CLDN3 491 CAAGGCCAAGATCACCATCGTGG 492 ACCAACTGCGTGCAGGACGACACGGCCAAGGCCAAGATCACC
    ATCGTGGCAGGCGTGCTGTTCCTTCTCGCC
    CLTC 495 TCTCACATGCTGTACCCAAAGCCA 496 ACCGTATGGACAGCCACAGCCTGGCTTTGGGTACAGCATGTG
    AGATGAAGCGCTGATCCTGTAGTCA
    COL11A1 499 CTGCTCGACCTTTGGGTCCTTCAG 500 GCCCAAGAGGGGAAGATGGCCCTGAAGGACCCAAAGGTCGA
    GCAGGCCCAACTGGAGACCCAGGTCC
    COL1A1 503 TCCTGCGCCTGATGTCCACCG 504 GTGGCCATCCAGCTGACCTTCCTGCGCCTGATGTCCACCGAG
    GCCTCCCAGAACATCACCTACCACTG
    COL1A2 507 TCTCCTAGCCAGACGTGTTTCTTGTCCT 508 CAGCCAAGAACTGGTATAGGAGCTCCAAGGACAAGAAACACG
    TG TCTGGCTAGGAGAAACTATCAATGCTGGCAGCCAGTTT
    COL3A1 511 CTCCTGGTCCCCAAGGTGTCAAAG 512 GGAGGTTCTGGACCTGCTGGTCCTCCTGGTCCCCAAGGTGTC
    AAAGGTGAACGTGGCAGTCCTGGT
    COL4A1 515 CTCCTTTGACACCAGGGATGCCAT 516 ACAAAGGCCTCCCAGGATTGGATGGCATCCCTGGTGTCAAAG
    GAGAAGCAGGTCTTCCTGGGACTC
    COL5A1 519 CCAGGGAAACCACGTAATCCTGGA 520 CTCCCTGGGAAAGATGGCCCTCCAGGATTACGTGGTTTCCCTG
    GGGACCGAGGGCTTCCTGGTCCAG
    COL5A2 523 CCAGGAAATCCTGTAGCACCAGGC 524 GGTCGAGGAACCCAAGGTCCGCCTGGTGCTACAGGATTTCCT
    GGTTCTGCGGGCAGAGTTGGACCTCCAGGC
    COL6A1 527 CTTCTCTTCCCTGATCACCCTGCG 528 GGAGACCCTGGTGAAGCTGGCCCGCAGGGTGATCAGGGAAG
    AGAAGGCCCCGTTGGTGTCCCTGGAGA
    COL6A3 531 CCTCTTTGACGGCTCAGCCAATCT 532 GAGAGCAAGCGAGACATTCTGTTCCTCTTTGACGGCTCAGCCA
    ATCTTGTGGGCCAGTTCCCTGTT
    COL8A1 535 CCTAAGGGAGAGCCAGGAATCCCA 536 TGGTGTTCCAGGGCTTCTCGGACCTAAGGGAGAGCCAGGAAT
    CCCAGGGGATCAGGGTTTACAGGG
    COL9A2 539 ACACAGGAAATCCGCACTGCCTTC 540 GGGAACCATCCAGGGTCTGGAAGGCAGTGCGGATTTCCTGTG
    TCCAACCAACTGTCCACCCGGAAT
    CRISP3 543 TGCCAGTTGCCCAGATAACTGTGA 544 TCCCTTATGAACAAGGAGCACCTTGTGCCAGTTGCCCAGATAA
    CTGTGACGATGGACTATGCACCAATGGTT
    CSF1 547 TCAGATGGAGACCTCGTGCCAAATTACA 548 TGCAGCGGCTGATTGACAGTCAGATGGAGACCTCGTGCCAAA
    TTACATTTGAGTTTGTAGACCAGGAACAGTTG
    CSK 551 TCCCGATGGTCTGCAGCAGCT 552 CCTGAACATGAAGGAGCTGAAGCTGCTGCAGACCATCGGGAA
    GGGGGAGTTCGGAGACGTGATG
    CSRP1 555 CCACCCTTCTCCAGGGACCCTTAG 556 ACCCAAGACCCTGCCTCTTCCACTCCACCCTTCTCCAGGGACC
    CTTAGATCACATCACTCCACCCCTGC
    CTGF 559 AACATCATGTTCTTCTTCATGACCTCGC 560 GAGTTCAAGTGCCCTGACGGCGAGGTCATGAAGAAGAACATG
    ATGTTCATCAAGACCTGTGCCTGCCATTACAACT
    CTHRC1 563 CAACGCTGACAGCATGCATTTCTG 564 TGGCTCACTTCGGCTAAAATGCAGAAATGCATGCTGTCAGCGT
    TGGTATTTCACATTCAATGGAGCTGA
    CTNNA1 567 ATGCCTACAGCACCCTGATGTCGCA 568 CGTTCCGATCCTCTATACTGCATCCCAGGCATGCCTACAGCAC
    CCTGATGTCGCAGCCTATAAGGCCAACAGGGACCT
    CTNNB1 571 AGGCTCAGTGATGTCTTCCCTGTCACCAG 572 GGCTCTTGTGCGTACTGTCCTTCGGGCTGGTGACAGGGAAGA
    CATCACTGAGCCTGCCATCTGTGCTCTTCGTCATCTGA
    CTNND1 575 TTGATGCCCTCATTTTCATTGTTCAGGC 576 CGGAAACTTCGGGAATGTGATGGTTTAGTTGATGCCCTCATTT
    TCATTGTTCAGGCTGAGATTGGGCAGAAGGATTCAG
    CTNND2 579 CTATGAAACGAGCCACTACCCGGC 580 GCCCGTCCCTACAGTGAACTGAACTATGAAACGAGCCACTACC
    CGGCCTCCCCCGACTCCTGGGTGTGAG
    CTSB 583 CCCCGTGGAGGGAGCTTTCTC 584 GGCCGAGATCTACAAAAACGGCCCCGTGGAGGGAGCTTTCTC
    TGTGTATTCGGACTTCCTGC
    CTSD 587 ACCCTGCCCGCGATCACACTGA 588 GTACATGATCCCCTGTGAGAAGGTGTCCACCCTGCCCGCGAT
    CACACTGAAGCTGGGAGGCAAAGGCTACAAGCTGTCCC
    CTSK 591 CCCCAGGTGGTTCATAGCCAGTTC 592 AGGCTTCTCTTGGTGTCCATACATATGAACTGGCTATGAACCA
    CCTGGGGGACATGACCAGTGAAGAGGTGG
    CTSL2 595 CTTGAGGACGCGAACAGTCCACCA 596 TGTCTCACTGAGCGAGCAGAATCTGGTGGACTGTTCGCGTCCT
    CAAGGCAATCAGGGCTGCAATGGT
    CTSS 599 TGATAACAAGGGCATCGACTCAGACGCT 600 TGACAACGGCTTTCCAGTACATCATTGATAACAAGGGCATCGA
    CTCAGACGCTTCCTATCCCTACAAAGCCATGGA
    CUL1 603 CAGCCACAAAGCCAGCGTCATTGT 604 ATGCCCTGGTAATGTCTGCATTCAACAATGACGCTGGCTTTGT
    GGCTGCTCTTGATAAGGCTTGTGGTCGC
    CXCL12 607 TTCTTCGAAAGCCATGTTGCCAGA 608 GAGCTACAGATGCCCATGCCGATTCTTCGAAAGCCATGTTGCC
    AGAGCCAACGTCAAGCATCTCAAA
    CXCR4 611 CTGAAACTGGAACACAACCACCCACAAG 612 TGACCGCTTCTACCCCAATGACTTGTGGGTGGTTGTGTTCCAG
    TTTCAGCACATCATGGTTGGCCTTATCCT
    CXCR7 615 CTCAGAGCCAGGGAACTTCTCGGA 616 CGCCTCAGAACGATGGATCTGCATCTCTTCGACTACTCAGAGC
    CAGGGAACTTCTCGGACATCAGCTGGCCATGCAAC
    CYP3A5 619 TCCCGCCTCAAGTTTCTCACCAAT 620 TCATTGCCCAGTATGGAGATGTATTGGTGAGAAACTTGAGGCG
    GGAAGCAGAGAAAGGCAAGCCTGTC
    CYR61 623 CAGCACCCTTGGCAGTTTCGAAAT 624 TGCTCATTCTTGAGGAGCATTAAGGTATTTCGAAACTGCCAAG
    GGTGCTGGTGCGGATGGACACTAATGCAGCCAC
    DAG1 627 CAAGTCAGAGTTTCCCTGGTGCCC 628 GTGACTGGGCTCATGCCTCCAAGTCAGAGTTTCCCTGGTGCC
    CCAGAGACAGGAGCACAAGTGGGAT
    DAP 631 CTCACCAGCTGGCAGACGTGAACT 632 CCAGCCTTTCTGGTGCTGTTCTCCAGTTCACGTCTGCCAGCTG
    GTGAGGGCAGAGGCAGACCTGGTC
    DAPK1 635 TCATATCCAAACTCGCCTCCAGCCG 636 CGCTGACATCATGAATGTTCCTCGACCGGCTGGAGGCGAGTTT
    GGATATGACAAAGACACATCGTTGCTGAAAGAGA
    DARC 639 TCAGCGCCTGTGCTTCCAAGATAA 640 GCCCTCATTAGTCCTTGGCTCTTATCTTGGAAGCACAGGCGCT
    GACAGCCGTCCCAGCCCTTCTGTCTG
    DDIT4 643 CTAGCCTTTGGGACCGCTTCTCGT 644 CCTGGCGTCTGTCCTCACCATGCCTAGCCTTTGGGACCGCTTC
    TCGTCGTCGTCCACCTCCTCTTCG
    DDR2 647 AGTGCTCCCTATCCGCTGGATGTC 648 CTATTACCGGATCCAGGGCCGGGCAGTGCTCCCTATCCGCTG
    GATGTCTTGGGAGAGTATCTTGCTGGG
    DES 651 TGAACCAGGAGTTTCTGACCACGC 652 ACTTCTCACTGGCCGACGCGGTGAACCAGGAGTTTCTGACCA
    CGCGCACCAACGAGAAGGTGGAGC
    DHRS9 655 ATCAATAATGCTGGTGTTCCCGGC 656 GGAGAAAGGTCTCTGGGGTCTGATCAATAATGCTGGTGTTCCC
    GGCGTGCTGGCTCCCACTGACTG
    DHX9 659 CCAAGGAACCACACCCACTTGGTT 660 GTTCGAACCATCTCAGCGACAAAACCAAGTGGGTGTGGTTCCT
    TGGTCACCTCCACAATCCAACTGGA
    DIAPH1 663 TTCTTCTGTCTCCCGCCGCTTC 664 CAAGCAGTCAAGGAGAACCAGAAGCGGCGGGAGACAGAAGA
    AAAGATGAGGCGAGCAAAACT
    DICER1 667 AGAAAAGCTGTTTGTCTCCCCAGCA 668 TCCAATTCCAGCATCACTGTGGAGAAAAGCTGTTTGTCTCCCC
    AGCATACTTTATCGCCTTCACTGCC
    DIO2 671 ACTCTTCCACCAGTTTGCGGAAGG 672 CTCCTTTCACGAGCCAGCTGCCAGCCTTCCGCAAACTGGTGG
    AAGAGTTCTCCTCAGTGGCTGACTTCCT
    DLC1 675 AAAGTCCATTTGCCACTGATGGCA 676 GATTCAGACGAGGATGAGCCTTGTGCCATCAGTGGCAAATGG
    ACTTTCCAAAGGGACAGCAAGAGGTG
    DLGAP1 679 CGCAGACCACCCATACTACACCCA 680 CTGCTGAGCCCAGTGGAGCACCACCCCGCAGACCACCCATAC
    TACACCCAGCGGAACTCCTTCCAGGCT
    DLL4 683 CTACCTGGACATCCCTGCTCAGCC 684 CACGGAGGTATAAGGCAGGAGCCTACCTGGACATCCCTGCTC
    AGCCCCGCGGCTGGACCTTCCTTCT
    DNM3 687 CATATCGCTGACCGAATGGGAACC 688 CTTTCCCACCCGGCTTACAGACATATCGCTGACCGAATGGGAA
    CCCCACACCTGCAGAAGGTCCTT
    DPP4 691 CGGCTATTCCACACTTGAACACGC 692 GTCCTGGGATCGGGAAGTGGCGTGTTCAAGTGTGGAATAGCC
    GTGGCGCCTGTATCCCGGTGGGAGTAC
    DPT 695 TTCCTAGGAAGGCTGGCAGACACC 696 CACCTAGAAGCCTGCCCACGATTCCTAGGAAGGCTGGCAGAC
    ACCCTGGAACCCTGGGGAGCTACTG
    DUSP1 699 CGAGGCCATTGACTTCATAGACTCCA 700 AGACATCAGCTCCTGGTTCAACGAGGCCATTGACTTCATAGAC
    TCCATCAAGAATGCTGGAGGAAGGGTGTTTGTC
    DUSP6 703 TCTACCCTATGCGCCTGGAAGTCC 704 CATGCAGGGACTGGGATTCGAGGACTTCCAGGCGCATAGGGT
    AGAACCAAATGATAGGGTAGGAGCA
    DVL1 707 CTTGGAGCAGCCTGCACCTTCTCT 708 TCTGTCCCACCTGCTGCTGCCCCTTGGAGCAGCCTGCACCTTC
    TCTCCTCCCATCCGGCAACAGTCTGA
    DYNLL1 711 ACCCACGTCAGTGAGTGCTCACAA 712 GCCGCCTACCTCACAGACTTGTGAGCACTCACTGACGTGGGT
    AGCGCCCAGGGCCTGCGGGGCGCAGGAGAGCTGGAGTCAGG
    C
    EBNA1BP2 715 CCCGCTCTCGGATTCGGAGTCG 716 TGCGGCGAGATGGACACTCCCCCGCTCTCGGATTCGGAGTCG
    GAATCCGATGAATCCCTTGTCAC
    ECE1 719 TCCACTCTCGATACCCTGCACCAG 720 ACCTTGGGATCTGCCTCCAAGCTGGTGCAGGGTATCGAGAGT
    GGATTCCAGATGGAGGTCCTGGTCC
    EDN1 723 CACTCCCGAGCACGTTGTTCCGT 724 TGCCACCTGGACATCATTTGGGTCAACACTCCCGAGCACGTTG
    TTCCGTATGGACTTGGAAGCCCTAGGTCCA
    EDNRA 727 CCTTTGCCTCAGGGCATCCTTTT 728 TTTCCTCAAATTTGCCTCAAGATGGAAACCCTTTGCCTCAGGG
    CATCCTTTTGGCTGGCACTGGTTGGATGTGTAA
    EFNB2 731 CGGACAGCGTCTTCTGCCCTCACT 732 TGACATTATCATCCCGCTAAGGACTGCGGACAGCGTCTTCTGC
    CCTCACTACGAGAAGGTCAGCGGGGACTAC
    EGF 735 AGAGTTTAACAGCCCTGCTCTGGCTGAC 736 CTTTGCCTTGCTCTGTCACAGTGAAGTCAGCCAGAGCAGGGCT
    TT GTTAAACTCTGTGAAATTTGTCATAAGGGTGTCAGGTATTT
    EGR1 739 CGGATCCTTTCCTCACTCGCCCA 740 GTCCCCGCTGCAGATCTCTGACCCGTTCGGATCCTTTCCTCAC
    TCGCCCACCATGGACAACTACCCTAAGCTGGAG
    EGR3 743 ACCCAGTCTCACCTTCTCCCCACC 744 CCATGTGGATGAATGAGGTGTCTCCTTTCCATACCCAGTCTCA
    CCTTCTCCCCACCCTACCTCACCTCTTCTCAGGCA
    EIF2C2 747 CGGGTCACATTGCAGACACGGTAC 748 GCACTGTGGGCAGATGAAGAGGAAGTACCGCGTCTGCAATGT
    GACCCGGCGGCCCGCCAGTCACCAAACAT
    EIF2S3 751 TCTCGTGCTTCAGCCTCCCATGTA 752 CTGCCTCCCTGATTCAAGTGATTCTCGTGCTTCAGCCTCCCAT
    GTAGCTGATATTACAGGCACTTGCCACC
    EIF3H 755 CAGAACATCAAGGAGTTCACTGCCCA 756 CTCATTGCAGGCCAGATAAACACTTACTGCCAGAACATCAAGG
    AGTTCACTGCCCAAAACTTAGGCAAGCTCTTCATGGC
    EIF4E 759 ACCACCCCTACTCCTAATCCCCCGACT 760 GATCTAAGATGGCGACTGTCGAACCGGAAACCACCCCTACTC
    CTAATCCCCCGACTACAGAAGAGGAGAAAACGGAATCTAA
    EIF5 763 CCACTTGCACCCGAATCTTGATCA 764 GAATTGGTCTCCAGCTGCCTTTGATCAAGATTCGGGTGCAAGT
    GGAGCAGGAGCCATATACCTGGA
    ELK4 767 ATAAACCACCTCAGCCTGGTGCCA 768 GATGTGGAGAATGGAGGGAAAGATAAACCACCTCAGCCTGGT
    GCCAAGACCTCTAGCCGCAATGACT
    ENPP2 771 TAACTTCCTCTGGCATGGTTGGCC 772 CTCCTGCGCACTAATACCTTCAGGCCAACCATGCCAGAGGAA
    GTTACCAGACCCAATTATCCAGGGA
    ENY2 775 CTGATCCTTCCAGCCACATTCAATTAAT 776 CCTCAAAGAGTTGCTGAGAGCTAAATTAATTGAATGTGGCTGG
    TT AAGGATCAGTTGAAGGCACACTGTAAAGAGG
    EPHA2 779 TGCGCCCGATGAGATCACCG 780 CGCCTGTTCACCAAGATTGACACCATTGCGCCCGATGAGATCA
    CCGTCAGCAGCGACTTCGAGGCACGCCAC
    EPHA3 783 TATTCCAAATCCGAGCCCGAACAG 784 CAGTAGCCTCAAGCCTGACACTATATACGTATTCCAAATCCGA
    GCCCGAACAGCCGCTGGATATGGGACGAA
    EPHB2 787 CACCTGATGCATGATGGACACTGC 788 CAACCAGGCAGCTCCATCGGCAGTGTCCATCATGCATCAGGT
    GAGCCGCACCGTGGACAGCATTAC
    EPHB4 791 CGTCCCATTTGAGCCTGTCAATGT 792 TGAACGGGGTATCCTCCTTAGCCACGGGGCCCGTCCCATTTG
    AGCCTGTCAATGTCACCACTGACCGAGAGGTACCT
    ERBB2 795 CCAGACCATAGCACACTCGGGCAC 796 CGGTGTGAGAAGTGCAGCAAGCCCTGTGCCCGAGTGTGCTAT
    GGTCTGGGCATGGAGCACTTGCGAGAGG
    ERBB3 799 CCTCAAAGGTACTCCCTCCTCCCGG 800 CGGTTATGTCATGCCAGATACACACCTCAAAGGTACTCCCTCC
    TCCCGGGAAGGCACCCTTTCTTCAGTGGGTCTCAGTTC
    ERBB4 803 TGTCCCACGAATAATGCGTAAATTCTCC 804 TGGCTCTTAATCAGTTTCGTTACCTGCCTCTGGAGAATTTACGC
    AG ATTATTCGTGGGACAAAACTTTATGAGGATCGATATGCCTTG
    ERCC1 807 CAGCAGGCCCTCAAGGAGCTG 808 GTCCAGGTGGATGTGAAAGATCCCCAGCAGGCCCTCAAGGAG
    CTGGCTAAGATGTGTATCCTGGCCG
    EREG 811 TAAGCCATGGCTGACCTCTGGAGC 812 TGCTAGGGTAAACGAAGGCATAATAAGCCATGGCTGACCTCTG
    GAGCACCAGGTGCCAGGACTTGTCTCCA
    ERG 815 AGCCATATGCCTTCTCATCTGGGC 816 CCAACACTAGGCTCCCCACCAGCCATATGCCTTCTCATCTGGG
    CACTTACTACTAAAGACCTGGCGGAGG
    ESR1 819 CTGGAGATGCTGGACGCCC 820 CGTGGTGCCCCTCTATGACCTGCTGCTGGAGATGCTGGACGC
    CCACCGCCTACATGCGCCCACTAGCC
    ESR2 823 ATCTGTATGCGGAACCTCAAAAGAGTCC 824 TGGTCCATCGCCAGTTATCACATCTGTATGCGGAACCTCAAAA
    CT GAGTCCCTGGTGTGAAGCAAGATCGCTAGAACA
    ETV1 827 ATCGGGAAGGACCCACATACCAAC 828 TCAAACAAGAGCCAGGAATGTATCGGGAAGGACCCACATACC
    AACGGCGAGGATCACTTCAGCTCTGGCAGTT
    ETV4 831 CAGACAAATCGCCATCAAGTCCCC 832 TCCAGTGCCTATGACCCCCCCAGACAAATCGCCATCAAGTCCC
    CTGCCCCTGGTGCCCTTGGACAGT
    EZH2 835 TCCTGACTTCTGTGAGCTCATTGCG 836 TGGAAACAGCGAAGGATACAGCCTGTGCACATCCTGACTTCTG
    TGAGCTCATTGCGCGGGACTAGGGAGTGTTCGGTG
    F2R 839 CCCGGGCTCAACATCACTACCTGT 840 AAGGAGCAAACCATCCAGGTGCCCGGGCTCAACATCACTACC
    TGTCATGATGTGCTCAATGAAACCCTGC
    FAH 843 TGCCCTTCGTGCACACCAATG 844 GACAGCGTAGTGGTGCATGTGCTGAAGCTGCAGGGTGCCGTG
    CCCTTCGTGCACACCAATGTTCCACAGTCCATGTTCAGCT
    FABP5 847 CCTGATGCTGAACCAATGCACCAT 848 GCTGATGGCAGAAAAACTCAGACTGTCTGCAACTTTACAGATG
    GTGCATTGGTTCAGCATCAGGAGTGGGATGGGAAGGAAAG
    FADD 851 AACGCGCTCTTGTCGATTTCCTGT 852 GrITTCGCGAGATAACGGTCGAAAACGCGCTCTTGTCGATTTC
    CTGTAGTGAATCAGGCACCGGAG
    FAM107A 855 AATTGCCACACTGACCAGCGAAGA 856 AAGTCAGGGAAAACCTGCGGAGAATTGCCACACTGACCAGCG
    AAGAGAGAGAGCTGTAGGGCCAGC
    FAM13C 859 TCCTGACTTTCTCCGTGGCTCCTC 860 ATCTTCAAAGCGGAGAGCGGGAGGAGCCACGGAGAAAGTCAG
    GAGACAGAGCATGTGGTATCCAGC
    FAM171B 863 TGAAGATTTTGAAGCTAATACATCCCCC 864 CCAGGAAGGAAAAGCACTGTTGAAGATTTTGAAGCTAATACAT
    AC CCCCCACTAAAAGAAGGGGCAGACCAC
    FAM49B 867 TGGCCAGCTCCTCTGTATGACTGC 868 AGATGCAGAAGGCATCTTGGAGGACTTGCAGTCATACAGAGG
    AGCTGGCCACGAAATACGAGAGGCAATCCAGC
    FAM73A 871 AAGACCTCATGCAGTTACTCATTCGCC 872 TGAGAAGGTGCGCTATTCAAGTACAGAGACTTTAGCTGAAGAC
    CTCATGCAGTTACTCATTCGCCGCACTGAGCTTTTAATGGCC
    FAP 875 AGCCACTGCAAACATACTCGTTCATCA 876 GTTGGCTCACGTGGGTTACTGATGAACGAGTATGTTTGCAGTG
    GCTAAAAAGAGTCCAGAATGTTTCGGTCCTGTC
    FAS 879 TCTGGACCCTCCTACCTCTGGTTCTTAC 880 GGATTGCTCAACAACCATGCTGGGCATCTGGACCCTCCTACCT
    GT CTGGTTCTTACGTCTGTTGCTAGATTATCGTCCAAAAGTGTTAA
    TGCC
    FASLG 883 ACAACATTCTCGGTGCCTGTAACAAAGAA 884 GCACTTTGGGATTCTTTCCATTATGATTCTTTGTTACAGGCACC
    GAGAATGTTGTATTCAGTGAGGGTCTTCTTACATGC
    FASN 887 TCGCCCACCTACGTACTGGCCTAC 888 GCCTCTTCCTGTTCGACGGCTCGCCCACCTACGTACTGGCCTA
    CACCCAGAGCTACCGGGCAAAGC
    FCGR3A 891 CCCATGATCTTCAAGCAGGGAAGC 892 GTCTCCAGTGGAAGGGAAAAGCCCATGATCTTCAAGCAGGGA
    AGCCCCAGTGAGTAGCTGCATTCCT
    FGF10 895 ACACCATGTCCTGACCAAGGGCTT 896 TCTTCCGTCCCTGTCACCTGCCAAGCCCTTGGTCAGGACATGG
    TGTCACCAGAGGCCACCAACTCT
    FGF17 899 TTCTCGGATCTCCCTCAGTCTGCC 900 GGTGGCTGTCCTCAAAATCTGCTTCTCGGATCTCCCTCAGTCT
    GCCCCCAGCCCCCAAACTCCTCCTGGCTAGA
    FGF5 903 CCATTGACTTTGCCATCCGGGTAG 904 GCATCGGTTTCCATCTGCAGATCTACCCGGATGGCAAAGTCAA
    TGGATCCCACGAAGCCAATATGTT
    FGF6 907 CATCCACCTTGCCTCTCAGGCAC 908 GGGCCATTAATTCTGACCACGTGCCTGAGAGGCAAGGTGGAT
    GGCCCTGGGACAGAAACTGTTCATCACTATGTCCCGGG
    FGF7 911 CAGCCCTGAGCGACACACAAGAAG 912 CCAGAGCAAATGGCTACAAATGTGAACTGTTCCAGCCCTGAGC
    GACACACAAGAAGTTATGATTACATGGAAGGAGGGGA
    FGFR2 915 TCCCAGAGACCAACGTTCAAGCAGTTG 916 GAGGGACTGTTGGCATGCAGTGCCCTCCCAGAGACCAACGTT
    CAAGCAGTTGGTAGAAGACTTGGATCGAATTCTCACTC
    FGFR4 919 CCTTTCATGGGGAGAACCGCATT 920 CTGGCTTAAGGATGGACAGGCCTTTCATGGGGAGAACCGCAT
    TGGAGGCATTCGGCTGCGCCATCAGCACTGGAGTCTCGT
    FKBP5 923 TCTCCCCAGTTCCACAGCAGTGTC 924 CCCACAGTAGAGGGGTCTCATGTCTCCCCAGTTCCACAGCAG
    TGTCACAGACGTGAAAGCCAGAACC
    FLNA 927 TACCAGGCCCATAGCACTGGACAC 928 GAACCTGCGGTGGACACTTCCGGTGTCCAGTGCTATGGGCCT
    GGTATTGAGGGCCAGGGTGTCTTC
    FLNC 931 ATGTGCTGTCAGCTACCTGCCCAC 932 CAGGACAATGGTGATGGCTCATGTGCTGTCAGCTACCTGCCCA
    CGGAGCCTGGCGAGTACACCATCA
    FLT1 935 CTACAGCACCAAGAGCGACGTGTG 936 GGCTCCTGAATCTATCTTTGACAAAATCTACAGCACCAAGAGC
    GACGTGTGGTCTTACGGAGTATTGCTGTGGGA
    FLT4 939 AGCCCGCTGACCATGGAAGATCT 940 ACCAAGAAGCTGAGGACCTGTGGCTGAGCCCGCTGACCATGG
    AAGATCTTGTCTGCTACAGCTTCCAGG
    FN1 943 ACTCTCAGGCGGTGTCCACATGAT 944 GGAAGTGACAGACGTGAAGGTCACCATCATGTGGACACCGCC
    TGAGAGTGCAGTGACCGGCTACCGTGT
    FOS 947 TCCCAGCATCATCCAGGCCCAG 948 CGAGCCCTTTGATGACTTCCTGTTCCCAGCATCATCCAGGCCC
    AGTGGCTCTGAGACAGCCCGCTCC
    FOXO1 951 TATGAACCGCCTGACCCAAGTGAA 952 GTAAGCACCATGCCCCACACCTCGGGTATGAACCGCCTGACC
    CAAGTGAAGACACCTGTACAAGTGCCTCTGCCCC
    FOXP3 955 TGTTTCCATGGCTACCCCACAGGT 956 CTGTTTGCTGTCCGGAGGCACCTGTGGGGTAGCCATGGAAAC
    AGCACATTCCCAGAGTTCCTCCAC
    FOXQ1 959 TGATTTATGTCCCTTCCCTCCCCC 960 TGTTTTTGTCGCAACTTCCATTGATTTATGTCCCTTCCCTCCCC
    CCTAAGTACATCAGGGAACCTTTCCA
    FSD1 963 CGCACCAAACAAGTGCTGCACA 964 AGGCCTCCTGTCCTTCTACAATGCCCGCACCAAACAAGTGCTG
    CACACTTTCAAGACCAGGTTCACACA
    FYN 967 CTGAAGCACGACAAGCTGGTCCAG 968 GAAGCGCAGATCATGAAGAAGCTGAAGCACGACAAGCTGGTC
    CAGCTCTATGCAGTGGTGTCTGAGGAG
    G6PD 971 CCAGCCTCAGTGCCACTTGACATT 972 AATCTGCCTGTGGCCTTGCCCGCCAGCCTCAGTGCCACTTGA
    CATTCCTTGTCACCAGCAACATCTCG
    GABRG2 975 CTCAGCACCATTGCCCGGAAAT 976 CCACTGTCCTGACAATGACCACCCTCAGCACCATTGCCCGGA
    AATCGCTCCCCAAGGTCTCCTATGTCACAGCGATGGATCTC
    GADD45A 979 TTCATCTCAATGGAAGGATCCTGCC 980 GTGCTGGTGACGAATCCACATTCATCTCAATGGAAGGATCCTG
    CCTTAAGTCAACTTATTTGTTTTTGCCGGG
    GADD45B 983 TGGGAGTTCATGGGTACAGA 984 ACCCTCGACAAGACCACACTTTGGGACTTGGGAGCTGGGGCT
    GAAGTTGCTCTGTACCCATGAACTCCCA
    GDF15 987 TGTTAGCCAAAGACTGCCACTGCA 988 CGCTCCAGACCTATGATGACTTGTTAGCCAAAGACTGCCACTG
    CATATGAGCAGTCCTGGTCCTTCCACTGT
    GHR 991 CGTGCCTCAGCCTCCTGAGTAGCT 992 CCACCTCCCACAGGTTCAGGCGATTCCCGTGCCTCAGCCTCC
    TGAGTAGCTGGGACTACAGGCACGCACC
    GNPTAB 995 CCCTGCTCACATGCCTCACATGAT 996 GGATTCACATCGCGGAAAGTCCCTGCTCACATGCCTCACATGA
    TTGACCGGATTGTTATGCAAGAAC
    GNRH1 999 TCCTGTCCTTCACTGTCCTTGCCA 1000 AAGGGCTAAATCCAGGTGTGACGGTATCTAATGATGTCCTGTC
    CTTCACTGTCCTTGCCATCACCAGCCACAGAGATCCAG
    GPM6B 1003 CGCTGAGAAACCAAACACACCCAG 1004 ATGTGCTTGGAGTGGCCTGGCTGGGTGTGTTTGGTTTCTCAGC
    GGTGCCCGTGTTTATGTTCTACA
    GPNMB 1007 CAAACAGTGCCCTGATCTCCGTTG 1008 CAGCCTCGCCTTTAAGGATGGCAAACAGTGCCCTGATCTCCGT
    TGGCTGCTTGGCCATATTTGTCA
    GPR68 1011 CTCAGCACCGTGGTCATCTTCCTG 1012 CAAGGACCAGATCCAGCGGCTGGTGCTCAGCACCGTGGTCAT
    CTTCCTGGCCTGCTTCCTGCCCTACC
    GPS1 1015 CCTCCTGCTGGCTTCCTTTGATCA 1016 AGTACAAGCAGGCTGCCAAGTGCCTCCTGCTGGCTTCCTTTGA
    TCACTGTGACTTCCCTGAGCTGC
    GRB7 1019 CTCCCCACCCTTGAGAAGTGCCT 1020 CCATCTGCATCCATCTTGTTTGGGCTCCCCACCCTTGAGAAGT
    GCCTCAGATAATACCCTGGTGGCC
    GREM1 1023 TCCACCCTCCCTTTCTCACTCCAC 1024 GTGTGGGCAAGGACAAGCAGGATAGTGGAGTGAGAAAGGGAG
    GGTGGAGGGTGAGGCCAAATCAGGTC
    GSK3B 1027 CCAGGAGTTGCCACCACTGTTGTC 1028 GACAAGGACGGCAGCAAGGTGACAACAGTGGTGGCAACTCCT
    GGGCAGGGTCCAGACAGGCCACAA
    GSN 1031 ACCCAGCCAATCGGGATCGGC 1032 CTTCTGCTAAGCGGTACATCGAGACGGACCCAGCCAATCGGG
    ATCGGCGGACGCCCATCACCGTGGTGAAGCAAGGCTTTGAGC
    C
    GSTM1 1035 TCAGCCACTGGCTTCTGTCATAATCAGG 1036 AAGCTATGAGGAAAAGAAGTACACGATGGGGGACGCTCCTGA
    AG TTATGACAGAAGCCAGTGGCTGAATGAAAAATTCAAGCTGGGC
    C
    GSTM2 1039 CTGAAGCTCTACTCACAGTTTCTGGG 1040 CTGCAGGCACTCCCTGAAATGCTGAAGCTCTACTCACAGTTTC
    TGGGGAAGCAGCCATGGTTTCTTGG
    HDAC1 1043 TTCTTGCGCTCCATCCGTCCAGA 1044 CAAGTACCACAGCGATGACTACATTAAATTCTTGCGCTCCATC
    CGTCCAGATAACATGTCGGAGTACAGCAAGC
    HDAC9 1047 CCCCCTGAAGCTCTTCCTCTGCTT 1048 AACCAGGCAGTCACCTTGAGGAAGCAGAGGAAGAGCTTCAGG
    GGGACCAGGCGATGCAGGAAGACAGAG
    HGD 1051 CTGAGCAGCTCTCAGGATCGGCTT 1052 CTCAGGTCTGCCCCTACAATCTCTATGCTGAGCAGCTCTCAGG
    ATCGGCTTTCACTTGTCCACGGAGCACCAATAA
    HIP1 1055 CGACTCACTGACCGAGGCCTGTAA 1056 CTCAGAGCCCCACCTGAGCCTGCCGACTCACTGACCGAGGCC
    TGTAAGCAGTATGGCAGGGAAACCC
    HIRIP3 1059 CCATTGCTCCTGGTTCTGGGTTTC 1060 GGATGAGGAAAAGGGGGATTGGAAACCCAGAACCAGGAGCAA
    TGGCCGGAGAAAGTCAGCTAGGGA
    HK1 1063 TAAGAGTCCGGGATCCCCAGCCTA 1064 TACGCACAGAGGCAAGCAGCTAAGAGTCCGGGATCCCCAGCC
    TACTGCCTCTCCAGCACTTCTCTC
    HLA-G 1067 CTGCAAGGACAACCAGGCCAGCAA 1068 CCTGCGCGGCTACTACAACCAGAGCGAGGCCAGTTCTCACAC
    CCTCCAGTGGATGATTGGCTGCGACCTG
    HLF 1071 TAAGTGATCTGCCCTCCAGGTGGC 1072 CACCCTGCAGGTGTCTGAGACTAAGTGATCTGCCCTCCAGGT
    GGCGATCACCTTCTGCTCCTAGGTACC
    HNF1B 1075 CCCCTATGAAGACCCAGAAGCGTG 1076 TCCCAGCATCTCAACAAGGGCACCCCTATGAAGACCCAGAAG
    CGTGCCGCTCTGTACACCTGGTACG
    HPS1 1079 CAGTCACCAGCCCAAAGTGCACTT 1080 GCGGAAGCTGTATGTGCTCAAGTACCTGTTTGAAGTGCACTTT
    GGGCTGGTGACTGTGGACGGTCATCTTATCCGAA
    HRAS 1083 ACCACCTGCTTCCGGTAGGAATCC 1084 GGACGAATACGACCCCACTATAGAGGATTCCTACCGGAAGCA
    GGTGGTCATTGATGGGGAGACGTGC
    HSD17B10 1087 TCATGGGCACCTTCAATGTGATCC 1088 CCACCAGACAAGACCGATTCGCTGGCCTCCATTTCTTCAACCC
    AGTGCCTGTCATGAAACTTGTGG
    HSD17B2 1091 AGTTGCTTCCATCCAACCTGGAGG 1092 GCTTTCCAAGTGGGGAATTAAAGTTGCTTCCATCCAACCTGGA
    GGCTTCCTAACAAATATCGCAGGCA
    HSD17B3 1095 CTTCATCCTCACAGGGCTGCTGGT 1096 GGGACGTCCTGGAACAGTTCTTCATCCTCACAGGGCTGCTGG
    TGTGCCTGGCCTGCCTGGCGAAGTGCGTGAGATTCTCCA
    HSD17B4 1099 AGGCGGCGTCCTATTTCCTCAAAT 1100 CGGGAAGCTTCAGAGTACCTTTGTATTTGAGGAAATAGGACGC
    CGCCTAAAGGATATTGGGCCTGAGGT
    HSD3B2 1103 ACTTCCAGCAGGAAGCCAATCCAG 1104 GCCTTCCTTTAACCCTGATGTACTGGATTGGCTTCCTGCTGGA
    AGTAGTGAGCTTCCTACTCAGCCCAATTTACTCC
    HSP90AB1 1107 ATCCGCTCCATATTGGCTGTCCAG 1108 GCATTGTGACCAGCACCTACGGCTGGACAGCCAATATGGAGC
    GGATCATGAAAGCCCAGGCACTTC
    HSPA5 1111 TAATTAGACCTAGGCCTCAGCTGCACTG 1112 GGCTAGTAGAACTGGATCCCAACACCAAACTCTTAATTAGACC
    CC TAGGCCTCAGCTGCACTGCCCGAAAAGCATTTGGGCAGACC
    HSPA8 1115 CTCAGGGCCCACCATTGAAGAGGTTG 1116 CCTCCCTCTGGTGGTGCTTCCTCAGGGCCCACCATTGAAGAG
    GTTGATTAAGCCAACCAAGTGTAGATGTAGC
    HSPB1 1119 CGCACTTTTCTGAGCAGACGTCCA 1120 CCGACTGGAGGAGCATAAAAGCGCAGCCGAGCCCAGCGCCC
    CGCACTTTTCTGAGCAGACGTCCAGAGCAGAGTCAGCCAGCA
    T
    HSPB2 1123 CACCTTTCCCTTCCCCCAAGGAT 1124 CACCACTCCAGAGGTAGCAGCATCCTTGGGGGAAGGGAAAGG
    TGCATGGTCCACAATGTATGGTTTGGTCCCA
    HSPE1 1127 TCTCCACCCTTTCCTTTAGAACCCG 1128 GCAAGCAACAGTAGTCGCTGTTGGATCGGGTTCTAAAGGAAA
    GGGTGGAGAGATTCAACCAGTTAGCGTGAAAGTTGG
    HSPG2 1131 CAGCTCCGTGCCTCTAGAGGCCT 1132 GAGTACGTGTGCCGAGTGTTGGGCAGCTCCGTGCCTCTAGAG
    GCCTCTGTCCTGGTCACCATTGAG
    ICAM1 1135 CCGGCGCCCAACGTGATTCT 1136 GCAGACAGTGACCATCTACAGCTTTCCGGCGCCCAACGTGATT
    CTGACGAAGCCAGAGGTCTCAGAAG
    IER3 1139 TCAAGTTGCCTCGGAAGTCCCAGT 1140 GTACCTGGTGCGCGAGAGCGTATCCCCAACTGGGACTTCCGA
    GGCAACTTGAACTCAGAACACTACAGCGGAGACGC
    IFI30 1143 AAAATTCCACCCCATGATCAAGAATCC 1144 ATCCCATGAAGCCCAGATACACAAAATTCCACCCCATGATCAA
    GAATCCTGCTCCACTAAGAATGGTGC
    IFIT1 1147 AAGTTGCCCCAGGTCACCAGACTC 1148 TGACAACCAAGCAAATGTGAGGAGTCTGGTGACCTGGGGCAA
    CTTTGCCTGGATGTATTACCACATGGGCAGACTG
    IFNG 1151 TCGACCTCGAAACAGCATCTGACTCC 1152 GCTAAAACAGGGAAGCGAAAAAGGAGTCAGATGCTGTTTCGA
    GGTCGAAGAGCATCCCAGTAATGGTTG
    IGF1 1155 TGTATTGCGCACCCCTCAAGCCTG 1156 TCCGGAGCTGTGATCTAAGGAGGCTGGAGATGTATTGCGCAC
    CCCTCAAGCCTGCCAAGTCAGCTCGCTCTGTCCG
    IGF1R 1159 CGCGTCATACCAAAATCTCCGATTTTGA 1160 GCATGGTAGCCGAAGATTTCACAGTCAAAATCGGAGATTTTGG
    TATGACGCGAGATATCTATGAGACAGACTATTACCGGAAA
    IGF2 1163 TACCCCGTGGGCAAGTTCTTCCAA 1164 CCGTGCTTCCGGACAACTTCCCCAGATACCCCGTGGGCAAGT
    TCTTCCAATATGACACCTGGAAGCAGTCCA
    IGFBP2 1167 CTTCCGGCCAGCACTGCCTC 1168 GTGGACAGCACCATGAACATGTTGGGCGGGGGAGGCAGTGCT
    GGCCGGAAGCCCCTCAAGTCGGGTATGAAGG
    IGFBP3 1171 ACACCACAGAAGGCTGTGAGCTCC 1172 ACATCCCAACGCATGCTCCTGGAGCTCACAGCCTTCTGTGGTG
    TCATTTCTGAAACAAGGGCGTGG
    IGFBP5 1175 CCCGTCAACGTACTCCATGCCTGG 1176 TGGACAAGTACGGGATGAAGCTGCCAGGCATGGAGTACGTTG
    ACGGGGACTTTCAGTGCCACACCTTCG
    IGKBP6 1179 ATCCAGGCACCTCTACCACGCCCTC 1180 TGAACCGCAGAGACCAACAGAGGAATCCAGGCACCTCTACCA
    CGCCCTCCCAGCCCAATTCTGCGGGTGTCCAAGAC
    IL10 1183 TTGAGCTGTTTTCCCTGACCTCCC 1184 CTGACCACGCTTTCTAGCTGTTGAGCTGTTTTCCCTGACCTCC
    CTCTAATTTATCTTGTCTCTGGGCTTGG
    IL11 1187 CCTGTGATCAACAGTACCCGTATGGG 1188 TGGAAGGTTCCACAAGTCACCCTGTGATCAACAGTACCCGTAT
    GGGACAAAGCTGCAAGGTCAAGA
    IL17A 1191 TGGCTTCTGTCTGATCAAGGCACC 1192 TCAAGCAACACTCCTAGGGCCTGGCTTCTGTCTGATCAAGGCA
    CCACACAACCCAGAAAGGAGCTG
    IL1A 1195 TCTCCACCCTGGCCCTGTTACAGT 1196 GGTCCTTGGTAGAGGGCTACTTTACTGTAACAGGGCCAGGGT
    GGAGAGTTCTCTCCTGAAGCTCCATCC
    IL1B 1199 TGCCCACAGACCTTCCAGGAGAAT 1200 AGCTGAGGAAGATGCTGGTTCCCTGCCCACAGACCTTCCAGG
    AGAATGACCTGAGCACCTTCTTTCC
    IL2 1203 TGCAACTCCTGTCTTGCATTGCAC 1204 ACCTCAACTCCTGCCACAATGTACAGGATGCAACTCCTGTCTT
    GCATTGCACTAAGTCTTGCACTTGTCACAAACAGTG
    IL6 1207 CCAGATTGGAAGCATCCATCTTTTTCA 1208 CCTGAACCTTCCAAAGATGGCTGAAAAAGATGGATGCTTCCAA
    TCTGGATTCAATGAGGAGACTTGCCTGGT
    IL6R 1211 CCTTTGGCTTCACGGAAGAGCCTT 1212 CCAGCTTATCTCAGGGGTGTGCGGCCTTTGGCTTCACGGAAG
    AGCCTTGCGGAAGGTTCTACGCCAG
    IL6ST 1215 CATATTGCCCAGTGGTCACCTCACA 1216 GGCCTAATGTTCCAGATCCTTCAAAGAGTCATATTGCCCAGTG
    GTCACCTCACACTCCTCCAAGGCACAATTTT
    IL8 1219 TGACTTCCAAGCTGGCCGTGGC 1220 AAGGAACCATCTCACTGTGTGTAAACATGACTTCCAAGCTGGC
    CGTGGCTCTCTTGGCAGCCTTCCTGAT
    ILF3 1223 ACACAAGACTTCAGCCCGTTGGCT 1224 GACACGCCAAGTGGTTCCAGGCCAGAGCCAACGGGCTGAAGT
    CTTGTGTCATTGTGATCCGGGTCTTGAG
    ILK 1227 ATGTGCTCCCAGTGCTAGGTGCCT 1228 CTCAGGATTTTCTCGCATCCAAATGTGCTCCCAGTGCTAGGTG
    CCTGCCAGTCTCCACCTGCTCCT
    IMMT 1231 CAACTGCATGGCTCTGAACAGCCT 1232 CTGCCTATGCCAGACTCAGAGGAATCGAACAGGCTGTTCAGA
    GCCATGCAGTTGCTGAAGAGGAAGCCAGAAAAGC
    ING5 1235 CCAGCTGCACTTTGTCGTCACTGT 1236 CCTACAGCAAGTGCAAGGAATACAGTGACGACAAAGTGCAGC
    TGGCCATGCAGACCTACGAGATG
    INHBA 1239 ACGTCCGGGTCCTCACTGTCCTTCC 1240 GTGCCCGAGCCATATAGCAGGCACGTCCGGGTCCTCACTGTC
    CTTCCACTCAACAGTCATCAACCACTACCG
    INSL4 1243 TGAGAAGACATTCACCACCACCCC 1244 CTGTCATATTGCCCCATGCCTGAGAAGACATTCACCACCACCC
    CAGGAGGGTGGCTGCTGGAATCTG
    ITGA1 1247 TTGCTGGACAGCCTCGGTACAATC 1248 GCTTCTTCTGGAGATGTGCTCTATATTGCTGGACAGCCTCGGT
    ACAATCATACAGGCCAGGTCATTATCTACAGG
    ITGA3 1251 CACTCCAGACCTCGCTTAGCATGG 1252 CCATGATCCTCACTCTGCTGGTGGACTATACACTCCAGACCTC
    GCTTAGCATGGTAAATCACCGGCTACAAAGCTTC
    ITGA4 1255 CGATCCTGCATCTGTAAATCGCCC 1256 CAACGCTTCAGTGATCAATCCCGGGGCGATTTACAGATGCAG
    GATCGGAAAGAATCCCGGCCAGAC
    ITGA5 1259 TCTGAGCCTTGTCCTCTATCCGGC 1260 AGGCCAGCCCTACATTATCAGAGCAAGAGCCGGATAGAGGAC
    AAGGCTCAGATCTTGCTGGACTGTGGAGAAGAC
    ITGA6 1263 TCGCCATCTTTTGTGGGATTCCTT 1264 CAGTGACAAACAGCCCTTCCAACCCAAGGAATCCCACAAAAGA
    TGGCGATGACGCCCATGAGGCTAAAC
    ITGA7 1267 CAGCCAGGACCTGGCCATCCG 1268 GATATGATTGGTCGCTGCTTTGTGCTCAGCCAGGACCTGGCCA
    TCCGGGATGAGTTGGATGGTGGGGAATGGAAGTTCT
    ITGAD 1271 CAACTGAAAGGCCTGACGTTCACG 1272 GAGCCTGGTGGATCCCATCGTCCAACTGAAAGGCCTGACGTT
    CACGGCCACGGGCATCCTGACAGT
    ITGB3 1275 AAATACCTGCAACCGTTACTGCCGTGAC 1276 ACCGGGGAGCCCTACATGACGAAAATACCTGCAACCGTTACT
    GCCGTGACGAGATTGAGTCAGTGAAAGAGCTTAAGG
    ITGB4 1279 CACCAACCTGTACCCGTATTGCGA 1280 CAAGGTGCCCTCAGTGGAGCTCACCAACCTGTACCCGTATTG
    CGACTATGAGATGAAGGTGTGCGC
    ITGB5 1283 TGCTATGTTTCTACAAAACCGCCAAGG 1284 TCGTGAAAGATGACCAGGAGGCTGTGCTATGTTTCTACAAAAC
    CGCCAAGGACTGCGTCATGATGTTCACC
    ITPR1 1287 CCATCCTAACGGAACGAGCTCCCT 1288 GAGGAGGTGTGGGTGTTCCGCTTCCATCCTAACGGAACGAGC
    TCCCTCTTCGCGGACATGGGATTAC
    ITPR3 1291 TCCAGGTCTCGGATCTCAGACACG 1292 TTGCCATCGTGTCAGTGCCCGTGTCTGAGATCCGAGACCTGG
    ACTTTGCCAATGACGCCAGCTCCAT
    ITSN1 1295 AGCCCTCTCTCACCGTTCCAAGTG 1296 TAACTGGGATGCATGGGCAGCCCAGCCCTCTCTCACCGTTCC
    AAGTGCCGGCCAGTTAAGGCAGAG
    JAG1 1299 ACTCGATTTCCCAGCCAACCACAG 1300 TGGCTTACACTGGCAATGGTAGTTTCTGTGGTTGGCTGGGAAA
    TCGAGTGCCGCATCTCACAGCTATGC
    JUN 1303 CTATGACGATGCCCTCAACGCCTC 1304 GACTGCAAAGATGGAAACGACCTTCTATGACGATGCCCTCAAC
    GCCTCGTTCCTCCCGTCCGAGAGCGGACCTTATGGCTA
    JUNB 1307 CAAGGGACACGCCTTCTGAACGT 1308 CTGTCAGCTGCTGCTTGGGGTCAAGGGACACGCCTTCTGAAC
    GTCCCCTGCCCCTTTACGGACACCCCCT
    KCNN2 1311 TTATACATTCACATGGACGGCCCG 1312 TGTGCTATTCATCCCATACCTGGGAATTATACATTCACATGGAC
    GGCCCGGCTTGCCTTCTCCTATGCCC
    KCTD12 1315 ACTCTTAGGCGGCAGCGTCCTTTC 1316 AGCAGTTACTGGCAAGAGGGAGAAAGGACGCTGCCGCCTAAG
    AGTGCAAGGCTGCTCAGGTCTCCA
    KNDRBS3 1319 CAAGACACAAGGCACCTTCAGCGA 1320 CGGGCAAGAAGAGTGGACTAACTCAAGACACAAGGCACCTTC
    AGCGAGGACAGCAAAGGGCGTCTACAG
    KIAA0196 1323 TCCCCAGTGTCCAGGCACAGAGTA 1324 CAGACACCAGCTCTGAGGCCAGTTAATCATCCCCAGTGTCCAG
    GCACAGAGTAGTCGGTCCGCCTCACAATGTT
    KIAA0247 1327 TCCGCTAGTGATCCTTTGCACCCT 1328 CCGTGGGACATGGAGTGTTCCTTCCGCTAGTGATCCTTTGCAC
    CCTGCTTGGAGACGGACTTGCTTC
    KF4A 1331 CAGGTCAGCAAACTTGAAAGCAGCC 1332 AGAGCTGGTCTCCTCCAAAATACAGGTCAGCAAACTTGAAAGC
    AGCCTGAAACAGAGCAAGACCAGC
    KIT 1335 TTACAGCGACAGTCATGGCCGCAT 1336 GAGGCAACTGCTTATGGCTTAATTAAGTCAGATGCGGCCATGA
    CTGTCGCTGTAAAGATGCTCAAGCCGAGTGCC
    KLC1 1339 CAACACGCAGCAGAAACTGCAGAA 1340 AGTGGCTACGGGATGAACTGGCCAACACGCAGCAGAAACTGC
    AGAAGAGTGAGCAGTCTGTGGCTCA
    KLF6 1343 AGTACTCCTCCAGAGACGGCAGCG 1344 CACGAGACCGGCTACTTCTCGGCGCTGCCGTCTCTGGAGGAG
    TACTGGCAACAGACCTGCCTAGAGC
    KLK1 1347 TCAGTGAGAGCTTCCCACACCCTG 1348 AACACAGCCCAGTTTGTTCATGTCAGTGAGAGCTTCCCACACC
    CTGGCTTCAACATGAGCCTCCTGG
    KLK10 1351 CCTCTTCCTCCCCAGTCGGCTGA 1352 GCCCAGAGGCTCCATCGTCCATCCTCTTCCTCCCCAGTCGGCT
    GAACTCTCCCCTTGTCTGCACTGTTCAAACCTCTG
    KLK11 1355 CCTCCCCAACAAAGACCACCGCA 1356 CACCCCGGCTTCAACAACAGCCTCCCCAACAAAGACCACCGC
    AATGACATCATGCTGGTGAAGATG
    KLK14 1359 CAGCACTTCAAGTCCTGGCTATAGCCA 1360 CCCCTAAAATGTTCCTCCTGCTGACAGCACTTCAAGTCCTGGC
    TATAGCCATGACACAGAGCCAAGAGGATGAG
    KLK2 1363 TTGGGAATGCTTCTCACACTCCCA 1364 AGTCTCGGATTGTGGGAGGCTGGGAGTGTGAGAAGCATTCCC
    AACCCTGGCAGGTGGCTGTGTACA
    KLK3 1367 ACCCACATGGTGACACAGCTCTCC 1368 CCAAGCTTACCACCTGCACCCGGAGAGCTGTGTCACCATGTG
    GGTCCCGGTTGTCTTCCTCACCCT
    KLRK1 1371 TGTCTCAAAATGCCAGCCTTCTGAA 1372 TGAGAGCCAGGCTTCTTGTATGTCTCAAAATGCCAGCCTTCTG
    AAAGTATACAGCAAAGAGGACCAGGAT
    KPNA2 1375 ACTCCTGTTTTCACCACCATGCCA 1376 TGATGGTCCAAATGAACGAATTGGCATGGTGGTGAAAACAGGA
    GTTGTGCCCCAACTTGTGAAGCTT
    KRT1 1379 CCTCAGCAATGATGCTGTCCAGGT 1380 TGGACAACAACCGCAGTCTCGACCTGGACAGCATCATTGCTGA
    GGTCAAGGCCCAGTACGAGGATA
    KRT15 1383 TGAACAAAGAGGTGGCCTCCAACA 1384 GCCTGGTTCTTCAGCAAGACTGAGGAGCTGAACAAAGAGGTG
    GCCTCCAACACAGAAATGATCCAGACCAGCAAG
    KRT18 1387 TGGTTCTTCTTCATGAAGAGCAGCTCC 1388 AGAGATCGAGGCTCTCAAGGAGGAGCTGCTCTTCATGAAGAA
    GAACCACGAAGAGGAAGTAAAAGGCC
    KRT2 1391 ACCTAGACAGCACAGATTCCGCCC 1392 CCAGTGACGCCTCTGTGTTCTGGGGCGGAATCTGTGCTGTCTA
    GGTTTGTGCTTCTAGCCATGCCC
    KRT5 1395 CCAGTCAACATCTCTGTTGTCACAAGCA 1396 TCAGTGGAGAAGGAGTTGGACCAGTCAACATCTCTGTTGTCAC
    AAGCAGTGTTTCCTCTGGATATGGCA
    KRT75 1399 TTCATTCTCAGCAGCTGTGCGCTTGT 1400 TCAAAGTCAGGTACGAAGATGAAATTAACAAGCGCACAGCTGC
    TGAGAATGAATTTGTAGCCCTGAAAAAGGACGT
    KRT76 1403 TCTGGGCTTCAGATCCTGACTCCC 1404 ATCTCCAGACTGCTGGTTCCCAGGGAACCCTCCCTACATCTGG
    GCTTCAGATCCTGACTCCCTTCTGTCCCCTAATTCCCTGA
    KRT8 1407 CGTCGGTCAGCCCTTCCAGGC 1408 GGATGAAGCTTACATGAACAAGGTAGAGCTGGAGTCTCGCCT
    GGAAGGGCTGACCGACGAGATCAACTTCCTCAGGCAGCTATA
    TG
    L1CAM 1411 ATCTACGTTGTCCAGCTGCCAGCC 1412 CTTGCTGGCCAATGCCTACATCTACGTTGTCCAGCTGCCAGCC
    AAGATCCTGACTGCGGACAATCA
    LAG3 1415 TCTATCTTGCTCTGAGCCTGCGGA 1416 GCCTTAGAGCAAGGGATTCACCCTCCGCAGGCTCAGAGCAAG
    ATAGAGGAGCTGGAGCAAGAACCG
    LAMA3 1419 ATTCAGACTGACAGGCCCCTGGAC 1420 CCTGTCACTGAAGCCTTGGAAGTCCAGGGGCCTGTCAGTCTG
    AATGGTTGTCCTGACCAGTAACCCA
    LAMA4 1423 CTCTCCATCGAGGAAGGCAAATCC 1424 GATGCACTGCGGTTAGCAGCGCTCTCCATCGAGGAAGGCAAA
    TCCGGGGTGCTGAGCGTATCCTCTG
    LAMA5 1427 CTGTTCCTGGAGCATGGCCTCTTC 1428 CTCCTGGCCAACAGCACTGCACTAGAAGAGGCCATGCTCCAG
    GAACAGCAGAGGCTGGGCCTTGTGT
    LAMB1 1431 CAAGTGCCTGTACCACACGGAAGG 1432 CAAGGAGACTGGGAGGTGTCTCAAGTGCCTGTACCACACGGA
    AGGGGAACACTGTCAGTTCTGCCG
    LAMB3 1435 CCACTCGCCATACTGGGTGCAGT 1436 ACTGACCAAGCCTGAGACCTACTGCACCCAGTATGGCGAGTG
    GCAGATGAAATGCTGCAAGTGTGAC
    LAMC1 1439 CCTCGGTACTTCATTGCTCCTGCA 1440 GCCGTGATCTCAGACAGCTACTTTCCTCGGTACTTCATTGCTC
    CTGCAAAGTTCTTGGGCAAGCAGGT
    LAMC2 1443 AGGTCTTATCAGCACAGTCTCCGCCTCC 1444 ACTCAAGCGGAAATTGAAGCAGATAGGTCTTATCAGCACAGTC
    TCCGCCTCCTGGATTCAGTGTCTCGGCTTCAGGGAGT
    LAPTM5 1447 TCCTGACCCTCTGCAGCTCCTACA 1448 TGCTGGACTTCTGCCTGAGCATCCTGACCCTCTGCAGCTCCTA
    CATGGAAGTGCCCACCTATCTCA
    LGALS3 1451 ACCCAGATAACGCATCATGGAGCGA 1452 AGCGGAAAATGGCAGACAATTTTTCGCTCCATGATGCGTTATC
    TGGGTCTGGAAACCCAAACCCTCAAG
    LIG3 1455 CTGGACGCTCAGAGCTCGTCTCTG 1456 GGAGGTGGAGAAGGAGCCGGGCCAGAGACGAGCTCTGAGCG
    TCCAGGCCTCGCTGATGACACCTGT
    LIMS1 1459 ACTGAGCGCACACGAAACACTGCT 1460 TGAACAGTAATGGGGAGCTGTACCATGAGCAGTGTTTCGTGTG
    CGCTCAGTGCTTCCAGCAGTTCCCAGAA
    LOX 1463 CAGGCTCAGCAAGCTGAACACCTG 1464 CCAATGGGAGAACAACGGGCAGGTGTTCAGCTTGCTGAGCCT
    GGGCTCACAGTACCAGCCTCAGCG
    LRP1 1467 TCCCGGCTGGGCGCCTCTACT 1468 TTTGGCCCAATGGGCTAAGCCTGGACATCCCGGCTGGGCGCC
    TCTACTGGGTGGATGCCTTCTACGACCGCATCGAGAC
    LTBP2 1471 CTTTGCAGCCCTCAGAACTCCAGC 1472 GCACACCCATCCTTGAGTCTCCTTTGCAGCCCTCAGAACTCCA
    GCCCCACTACGTGGCCAGCCATC
    LUM 1475 CCTGACCTTCATCCATCTCCAGCA 1476 GGCTCTTTTGAAGGATTGGTAAACCTGACCTTCATCCATCTCC
    AGCACAATCGGCTGAAAGAGGATGCTGTTTCAGCTGCTTTT
    MAGEA4 1479 CAGCTTCCCTTGCCTCGTGTAACA 1480 GCATCTAACAGCCCTGTGCAGCAGCTTCCCTTGCCTCGTGTAA
    CATGAGGCCCATTCTTCACTCTG
    MANF 1483 TTCCTGATGATGCTGGCCCTACAG 1484 CAGATGTGAAGCCTGGAGCTTTCCTGATGATGCTGGCCCTACA
    GTACCCCCATGAGGGGATTCCCTT
    MAOA 1487 CCGCGATACTCGCCTTCTCTTGAT 1488 GTGTCAGCCAAAGCATGGAGAATCAAGAGAAGGCGAGTATCG
    CGGGCCACATGTTCGACGTAGTCG
    MAP3K5 1491 CAGCCCAGAGACCAGATGTCTGCT 1492 AGGACCAAGAGGCTACGGAAAAGCAGCAGACATCTGGTCTCT
    GGGCTGTACAATCATTGAAATGGCCACAGG
    MAP3K7 1495 TGCTGGTCCTTTTCATCCTGGTCC 1496 CAGGCAAGAACTAGTTGCAGAACTGGACCAGGATGAAAAGGA
    CCAGCAAAATACATCTCGCCTGGTACAGG
    MAP4K4 1499 AACGTTCCTTGTTCTCCTGCTGCA 1500 TCGCCGAGATTTCCTGAGACTGCAGCAGGAGAACAAGGAACG
    TTCCGAGGCTCTTCGGAGACAACAG
    MAP7 1503 CATGTACAACAAACGCTCCGGGAA 1504 GAGGAACAGAGGTGTCTGCACTTCCATGTACAACAAACGCTCC
    GGGAAATGGAAAGCCAGTTGGCAG
    MAPKAPK3 1507 ATTGGCACTGCCATCCAGTTTCTG 1508 AAGCTGCAGAGATAATGCGGGATATTGGCACTGCCATCCAGTT
    TCTGCACAGCCATAACATTGCCCAC
    MCM2 1511 ACAGCTCATTGTTGTCACGCCGGA 1512 GACTTTTGCCCGCTACCTTTCATTCCGGCGTGACAACAATGAG
    CTGTTGCTCTTCATACTGAAGCAGTTAGTGGC
    MCM3 1515 TGGCCTTTCTGTCTACAAGGATCACCA 1516 GGAGAACAATCCCCTTGAGACAGAATATGGCCTTTCTGTCTAC
    AAGGATCACCAGACCATCACCATCCAGGAGAT
    MCM6 1519 CAGGTTTCATACCAACACAGGCTTCAGC 1520 TGATGGTCCTATGTGTCACATTCATCACAGGTTTCATACCAACA
    AC CAGGCTTCAGCACTTCCTTTGGTGTGTTTCCTGTCCCA
    MDK 1523 ATCACACGCACCCCAGTTCTCAAA 1524 GGAGCCGACTGCAAGTACAAGTTTGAGAACTGGGGTGCGTGT
    GATGGGGGCACAGGCACCAAAGTC
    MDM2 1527 CTTACACCAGCATCAAGATCCGG 1528 CTACAGGGACGCCATCGAATCCGGATCTTGATGCTGGTGTAAG
    TGAACATTCAGGTGATTGGTTGGAT
    MELK 1531 CCCGGGTTGTCTTCCGTCAGATAG 1532 AGGATCGCCTGTCAGAAGAGGAGACCCGGGTTGTCTTCCGTC
    AGATAGTATCTGCTGTTGCTTATGTGCA
    MET 1535 TGCCTCTCTGCCCCACCCTTTGT 1536 GACATTTCCAGTCCTGCAGTCAATGCCTCTCTGCCCCACCCTT
    TGTTCAGTGTGGCTGGTGCCACGACAAATGTGTGCGATCGGA
    G
    MGMT 1539 CAGCCCTTTGGGGAAGCTGG 1540 GTGAAATGAAACGCACCACACTGGACAGCCCTTTGGGGAAGC
    TGGAGCTGTCTGGTTGTGAGCAGGGTC
    MGST1 1543 TTTGACACCCCTTCCCCAGCCA 1544 ACGGATCTACCACACCATTGCATATTTGACACCCCTTCCCCAG
    CCAAATAGAGCTTTGAGTTTTTTTGTTGGATATGGA
    MICA 1547 CGAGGCCTCAGAGGGCAACATTAC 1548 ATGGTGAATGTCACCCGCAGCGAGGCCTCAGAGGGCAACATT
    ACCGTGACATGCAGGGCTTCTGGCTT
    MKI67 1551 CCACTCTTCCTTGAACACCCTCCC 1552 GATTGCACCAGGGCAGAACAGGGGAGGGTGTTCAAGGAAGAG
    TGGCTCTTAGCAGAGGCACTTTGGA
    MLXIP 1555 CATGAGATGCCAGGAGACCCTTCC 1556 TGCTTAGCTGGCATGTGGCCGCATGAGATGCCAGGAGACCCT
    TCCCTGCCCATGGAGAGTAGGCTG
    MMP11 1559 ATCCTCCTGAAGCCCTTTTCGCAGC 1560 CCTGGAGGCTGCAACATACCTCAATCCTGTCCCAGGCCGGAT
    CCTCCTGAAGCCCTTTTCGCAGCACTGCTATCCTCCAAAGCCA
    TTGTA
    MMP2 1563 AAGTCCGAATCTCTGCTCCCTGCA 1564 CAGCCAGAAGCGGAAACTTAAAAAGTCCGAATCTCTGCTCCCT
    GCAGGGCACAGGTGATGGTGTCT
    MMP7 1567 CCTGTATGCTGCAACTCATGAACTTGGC 1568 GGATGGTAGCAGTCTAGGGATTAACTTCCTGTATGCTGCAACT
    CATGAACTTGGCCATTCTTTGGGTATGGGACATTCC
    MMP9 1571 ACAGGTATTCCTCTGCCAGCTGCC 1572 GAGAACCAATCTCACCGACAGGCAGCTGGCAGAGGAATACCT
    GTACCGCTATGGTTACACTCGGGTG
    MPPED2 1575 ATTTGACCTTCCAAACCCACAGGG 1576 CCGACCAACCCTCCAATTATATTTGACCTTCCAAACCCACAGG
    GTTCCTGAAGCTCTAAATGCCCT
    MRC1 1579 CCAACCGCTGTTGAAGCTCAGACT 1580 CTTGACCTCAGGACTCTGGATTGGACTTAACAGTCTGAGCTTC
    AACAGCGGTTGGCAGTGGAGTGACCGCAGTCC
    MRPL13 1583 CGGCTGGAAATTATGTCCTCCGTC 1584 TCCGGTTCCCTTCGTTTAGGTCGGCTGGAAATTATGTCCTCCG
    TCGGTTTTCCGCAGTTTTTCCAC
    MSH2 1587 CAAGAAGATTTACTTCGTCGATTCCCAGA 1588 GATGCAGAATTGAGGCAGACTTTACAAGAAGATTTACTTCGTC
    GATTCCCAGATCTTAACCGACTTGCCAAGA
    MSH3 1591 TCCCAATTGTCGCTTCTTCTGCAG 1592 TGATTACCATCATGGCTCAGATTGGCTCCTATGTTCCTGCAGA
    AGAAGCGACAATTGGGATTGTGGATGGCATTTTCACAAG
    MSH6 1595 CCGTTACCAGCTGGAAATTCCTGAGA 1596 TCTATTGGGGGATTGGTAGGAACCGTTACCAGCTGGAAATTCC
    TGAGAATTTCACCACTCGCAATTTG
    MTA1 1599 CCCAGTGTCCGCCAAGGAGCG 1600 CCGCCCTCACCTGCAGAGAAACGCGCTCCTTGGCGGACACTG
    GGGGAGGAGAGGAAGAAGCGCGGCTAACTTATTCC
    MTPN 1603 AAGCTGCCCACAATCTGCTGCATA 1604 GGTGGAAGGAAACCTCTTCATTATGCAGCAGATTGTGGGCAGC
    TTGAAATCCTGGAATTTCTGCTGCTG
    MTSS1 1607 CCAAGAAACAGCGACATCAGCCAG 1608 TTCGACAAGTCCTCCACCATTCCAAGAAACAGCGACATCAGCC
    AGTCCTACCGACGGATGTTCCAAG
    MUC1 1611 CTCTGGCCTTCCGAGAAGGTACC 1612 GGCCAGGATCTGTGGTGGTACAATTGACTCTGGCCTTCCGAG
    AAGGTACCATCAATGTCCACGACGTGGAG
    MVP 1615 CGCACCTTTCCGGTCTTGACATCCT 1616 ACGAGAACGAGGGCATCTATGTGCAGGATGTCAAGACCGGAA
    AGGTGCGCGCTGTGATTGGAAGCACCTACATGC
    MYBL2 1619 CAGCATTGTCTGTCCTCCCTGGCA 1620 GCCGAGATCGCCAAGATGTTGCCAGGGAGGACAGACAATGCT
    GTGAAGAATCACTGGAACTCTACCATCAAAAG
    MYBPC1 1623 AAATTCGCAAGCCCAGCCCCTAT 1624 CAGCAACCAGGGAGTCTGTACCCTGGAAATTCGCAAGCCCAG
    CCCCTATGATGGAGGCACTTACTGCTG
    MYC 1627 TCTGACACTGTCCAACTTGACCCTCTT 1628 TCCCTCCACTCGGAAGGACTATCCTGCTGCCAAGAGGGTCAA
    GTTGGACAGTGTCAGAGTCCTGAGACAGATCAGCAACAACCG
    MYLK3 1631 CACACCCTCACAGATCTGCCTGGT 1632 CACCTGACTGAGCTGGATGTGGTCCTGTTCACCAGGCAGATCT
    GTGAGGGTGTGCATTACCTGCACCAGCACTACATC
    MYO6 1635 CAATCCTCAGGGCCAGCTCCC 1636 AAGCAGTTCTGGAGCAGGAGCGCAGGGACCGGGAGCTGGCC
    CTGAGGATTGCCCAGAGTGAAGCCGAGCTCATC
    NCAM1 1639 CTCAGCCTCGTCGTTCTTATCCACC 1640 TAGTTCCCAGCTGACCATCAAAAAGGTGGATAAGAACGACGAG
    GCTGAGTACATCTGCATTGCTGAGAACAAGGCTG
    NCAPD3 1643 CTACTGTCCGCAGCAAGGCACTGT 1644 TCGTTGCTTAGACAAGGCGCCTACTGTCCGCAGCAAGGCACT
    GTCCAGCTTTGCACACTGTCTGGAG
    NCOR1 1647 CCAGGCTCAGTCTGTCCATCATCA 1648 AACCGTTACAGCCCAGAATCCCAGGCTCAGTCTGTCCATCATC
    AAAGACCAGGTTCAAGGGTCTCTCCAGA
    NCOR2 1651 CCTCATAGGACAAGACGTGGCCCT 1652 CGTCATCTACGAAGGCAAGAAGGGCCACGTCTTGTCCTATGA
    GGGTGGCATGTCTGTGACCCAGTGCTC
    NDRG1 1655 CTGCAAGGACACTCATCACAGCCA 1656 AGGGCAACATTCCACAGCTGCCCTGGCTGTGATGAGTGTCCTT
    GCAGGGGCCGGAGTAGGAGCACTG
    NDUFS5 1659 TGTCCAAGAAAGGCATGGCTACCC 1660 AGAAGAGTCAAGGGCACGAGCATCGGGTAGCCATGCCTTTCT
    TGGACATCCAGAAAAGGTTCGGCCT
    NEK2 1663 TGCCTTCCCGGGCTGAGGACT 1664 GTGAGGCAGCGCGACTCTGGCGACTGGCCGGCCATGCCTTCC
    CGGGCTGAGGACTATGAAGTGTTGTACACCATTGGCA
    NETO2 1667 AGCCAACCCTTTTCTCCCATCACA 1668 CCAGGGCACCATACTGTTTCCAGCAGCCAACCCTTTTCTCCCA
    TCACAACTACGAAGACCTTGATTTACCGTT
    NEXN 1671 TCATCTTCAGCAGTGGAGCCATTCA 1672 AGGAGGAGGAAGAAGGTAGCATCATGAATGGCTCCACTGCTG
    AAGATGAAGAGCAAACCAGATCAGGAGCTC
    NFAT5 1675 CGAGAATCAGTCCCCGTGGAGTTC 1676 CTGAACCCCTCTCCTGGTCACCGAGAATCAGTCCCCGTGGAG
    TTCCCCCTCCACCTCGCCATCGTTTCCT
    NFATC2 1679 CGGGTTCCTACCCCACAGTCATTC 1680 CAGTCAAGGTCAGAGGCTGAGCCCGGGTTCCTACCCCACAGT
    CATTCAGCAGCAGAATGCCACGAGCCAAAG
    NFKB1 1683 AAGCTGTAAACATGAGCCGCACCA 1684 CAGACCAAGGAGATGGACCTCAGCGTGGTGCGGCTCATGTTT
    ACAGCTTTTCTTCCGGATAGCACTGGCAGCT
    NFKBIA 1687 CTCGTCTTTCATGGAGTCCAGGCC 1688 CTACTGGACGACCGCCACGACAGCGGCCTGGACTCCATGAAA
    GACGAGGAGTACGAGCAGATGGTCAAGG
    NME1 1691 CCTGGGACCATCCGTGGAGACTTCT 1692 CCAACCCTGCAGACTCCAAGCCTGGGACCATCCGTGGAGACT
    TCTGCATACAAGTTGGCAGGAACATTATACAT
    NNMT 1695 CCCTCTCCTCATGCCCAGACTCTC 1696 CCTAGGGCAGGGATGGAGAGAGAGTCTGGGCATGAGGAGAG
    GGTCTCGGGATGTTTGGCTGGACTAG
    NOS3 1699 TTCACTCGCTTCGCCATCACCG 1700 ATCTCCGCCTCGCTCATGGGCACGGTGATGGCGAAGCGAGTG
    AAGGCGACAATCCTGTATGGCTCCGA
    NOX4 1703 CCGAACACTCTTGGCTTACCTCCG 1704 CCTCAACTGCAGCCTTATCCTTTTACCCATGTGCCGAACACTC
    TTGGCTTACCTCCGAGGATCACAGAAGGTTCCAAGCA
    NPBWR1 1707 ATCGCCGACGAGCTCTTCACG 1708 TCACCAACCTGTTCATCCTCAACCTGGCCATCGCCGACGAGCT
    CTTCACGCTGGTGCTGCCCATCAACATC
    NPM1 1711 AACAGGCATTTTGGACAACACATTCTTG 1712 AATGTTGTCCAGGTTCTATTGCCAAGAATGTGTTGTCCAAAATG
    CCTGTTTAGTTTTTAAAGATGGAACTCCACCCTTTGCTTG
    NRG1 1715 ATGACCACCCCGGCTCGTATGTCA 1716 CGAGACTCTCCTCATAGTGAAAGGTATGTGTCAGCCATGACCA
    CCCCGGCTCGTATGTCACCTGTAGATTTCCACACGCCAAG
    NRIP3 1719 AGCTTTCTCTACCCCGGCATCTCA 1720 CCCACAAGCATGAAGGAGAAAAGCTTTCTCTACCCCGGCATCT
    CAAAGTAGTGGGCCAGATTGAGCA
    NRP1 1723 CAGGATCTACCCCGAGAGAGCCACTCAT 1724 CAGCTCTCTCCACGCGATTCATCAGGATCTACCCCGAGAGAG
    CCACTCATGGCGGACTGGGGCTCAGAATGGAGCTGCTGGG
    NUP62 1727 TCATCTGCCACCACTGGACTCTCC 1728 AGCCTCTTTGCGTCAATAGCAACTGCTCCAACCTCATCTGCCA
    CCACTGGACTCTCCCTCTGTACCCCTGTGACCACAG
    OAZ1 1731 CTGCTCCTCAGCGAACTCCAGGAG 1732 AGCAAGGACAGCTTTGCAGTTCTCCTGGAGTTCGCTGAGGAG
    CAGCTGCGAGCCGACCATGTCTTC
    OCLN 1735 CTCCTCCCTCGGTGACCAATTCAC 1736 CCCTCCCATCCGAGTTTCAGGTGAATTGGTCACCGAGGGAGG
    AGGCCGACACACCACACCTACACTCCCGCGTC
    ODC1 1739 CCAGCGTTGGACAAATACTTTCCGTCA 1740 AGAGATCACCGGCGTAATCAACCCAGCGTTGGACAAATACTTT
    CCGTCAGACTCTGGAGTGAGAATCATAGCTGAGCCCG
    OLFML2B 1743 TGGCCTGGATCTCCTGAAGCTACA 1744 CATGTTGGAAGGAGCGTTCTATGGCCTGGATCTCCTGAAGCTA
    CATTCAGTCACCACCAAACTGGTG
    OLFML3 1747 CAGACGATCCACTCTCCCGGAGAT 1748 TCAGAACTGAGGCCGACACCATCTCCGGGAGAGTGGATCGTC
    TGGAGCGGGAGGTAGACTATCTGG
    OMD 1751 TCCGATGCACATTCAGCAACTCTACC 1752 CGCAAACTCAAGACTATCCCAAATATTCCGATGCACATTCAGC
    AACTCTACCTTCAGTTCAATGAAATTGAGGCTGTGACTG
    OR51E1 1755 TCCTCATCTCCACCTCATCCATGC 1756 GCATGCTTTCAGGCATTGACATCCTCATCTCCACCTCATCCAT
    GCCCAAAATGCTGGCCATCTTCT
    OR51E2 1759 ACATAGCCAGCACCCGTGTTCTGA 1760 TATGGTGCCAAAACCAAACAGATCAGAACACGGGTGCTGGCT
    ATGTTCAAGATCAGCTGTGACAAGGAC
    OSM 1763 CTGAGCTGGCCTCCTATGCCTCAT 1764 GTTTCTGAAGGGGAGGTCACAGCCTGAGCTGGCCTCCTATGC
    CTCATCATGTCCCAAACCAGACACCT
    PAGE1 1767 CCAACTCAAAGTCAGGATTCTACACCTGC 1768 CAACCTGACGAAGTGGAATCACCAACTCAAAGTCAGGATTCTA
    CACCTGCTGAAGAGAGAGAGGATGAGGGAGCATCTG
    PAGE4 1771 CCAACTGACAATCAGGATATTGAACCTGG 1772 GAATCTCAGCAAGAGGAACCACCAACTGACAATCAGGATATTG
    AACCTGGACAAGAGAGAGAAGGAACACCTCCGATCGAAGAAC
    PAK6 1775 AGTTTCAGGAAGGCTGCCCCTCTC 1776 CCTCCAGGTCACCCACAGCCAGTTTCAGGAAGGCTGCCCCTC
    TCTCCCACTAAGTTCTGGCCTGAAGGGAC
    PATE1 1779 CAGCACAGTTCTTTAGGCAGCCCA 1780 TGGTAATCCCTGGTTAACCTTCATGGGCTGCCTAAAGAACTGT
    GCTGATGTGAAAGGCATAAGGTGGA
    PCA3 1783 CTGAGATGCTCCCTGCCTTCAGTG 1784 CGTGATTGTCAGGAGCAAGACCTGAGATGCTCCCTGCCTTCAG
    TGTCCTCTGCATCTCCCCTTTCT
    PCDHGB7 1787 ATTCTTAAACAGCAAGCCCCGCC 1788 CCCAGCGTTGAAGCAGATAAGAAGATTCTTAAACAGCAAGCCC
    CGCCCAACACGGACTGGCGTTTC
    PCNA 1791 ATCCCAGCAGGCCTCGTTGATGAG 1792 GAAGGTGTTGGAGGCACTCAAGGACCTCATCAACGAGGCCTG
    CTGGGATATTAGCTCCAGCGGTGTAAACC
    PDE9A 1795 TACATCATCTGGGCCACGCAGAAG 1796 TTCCACAACTTCCGGCACTGCTTCTGCGTGGCCCAGATGATGT
    ACAGCATGGTCTGGCTCTGCAGTCT
    PDGFRB 1799 ATCAATGTCCCTGTCCGAGTGCTG 1800 CCAGCTCTCCTTCCAGCTACAGATCAATGTCCCTGTCCGAGTG
    CTGGAGCTAAGTGAGAGCCACCC
    PECAM1 1803 TTTATGAACCTGCCCTGCTCCCACA 1804 TGTATTTCAAGACCTCTGTGCACTTATTTATGAACCTGCCCTGC
    TCCCACAGAACACAGCAATTCCTCAGGCTAA
    PEX10 1807 CTACCTTCGGCACTACCGCTGAGC 1808 GGAGAAGTTCCCTCCCCAGAAGCTCATCTACCTTCGGCACTAC
    CGCTGAGCCGGCGCCCGGGTGGGCCTGGACACAGAT
    PGD 1811 ACTGCCCTCTCCTTCTATGACGGGT 1812 ATTCCCATGCCCTGTTTTACCACTGCCCTCTCCTTCTATGACGG
    GTACAGACATGAGATGCTTCCAGCCAG
    PGF 1815 ATCTTCTCAGACGTCCCGAGCCAG 1816 GTGGTTTTCCCTCGGAGCCCCCTGGCTCGGGACGTCTGAGAA
    GATGCCGGTCATGAGGCTGTTCCCTTGCT
    PGK1 1819 TCTCTGCTGGGCAAGGATGTTCTGTTC 1820 AGAGCCAGTTGCTGTAGAACTCAAATCTCTGCTGGGCAAGGAT
    GTTCTGTTCTTGAAGGACTGTGTAGGCCCAG
    PGR 1823 TAAATTGCCGTCGCAGCCGCA 1824 GATAAAGGAGCCGCGTGTCACTAAATTGCCGTCGCAGCCGCA
    GCCACTCAAGTGCCGGACTTGTGA
    PHTF2 1827 ACAATCTGGCAATGCACAGTTCCC 1828 GATATGGCTGATGCTGCTCCTGGGAACTGTGCATTGCCAGATT
    GTTTCCACAAGAACACCCAAACC
    PIK3C2A 1831 TGTGCTGTGACTGGACTTAACAAATAGC 1832 ATACCAATCACCGCACAAACCCAGGCTATTTGTTAAGTCCAGT
    CT CACAGCACAAAGAAACATATGCGGAGAAAATGCTAGTGTG
    PIK3CA 1835 TCCTGCTTCTCGGGATACAGACCA 1836 GTGATTGAAGAGCATGCCAATTGGTCTGTATCCCGAGAAGCAG
    GATTTAGCTATTCCCACGCAGGAC
    PIK3CG 1839 TTCTGGACAATTACTGCCACCCGA 1840 GGAGAACTCAATGTCCATCTCCATTCTTCTGGACAATTACTGC
    CACCCGATAGCCCTGCCTAAGCATCA
    PIM1 1843 TACACTCGGGTCCCATCGAAGTCC 1844 CTGCTCAAGGACACCGTCTACACGGACTTCGATGGGACCCGA
    GTGTATAGCCCTCCAGAGTGGATCC
    PLA2G7 1847 TGGCAATACATAAATCCTGTTGCCCA 1848 CCTGGCTGTGGTTTATCCTTTTGACTGGCAATACATAAATCCTG
    TTGCCCATATGAAATCATCAGCATGGGTCA
    PLAU 1851 AAGCCAGGCGTCTACACGAGAGTCTCAC 1852 GTGGATGTGCCCTGAAGGACAAGCCAGGCGTCTACACGAGAG
    TCTCACACTTCTTACCCTGGATCCGCAG
    PLAUR 1855 CATTGACTGCCGAGGCCCCATG 1856 CCCATGGATGCTCCTCTGAAGAGACTTTCCTCATTGACTGCCG
    AGGCCCCATGAATCAATGTCTGGTAGCCACCGG
    PLG 1859 TGCCAGGCCTGGGACTCTCA 1860 GGCAAAATTTCCAAGACCATGTCTGGACTGGAATGCCAGGCCT
    GGGACTCTCAGAGCCCACACGCTCATGGATACAT
    PLK1 1863 AACCCCGTGGCCGCCTCC 1864 AATGAATACAGTATTCCCAAGCACATCAACCCCGTGGCCGCCT
    CCCTCATCCAGAAGATGCTTCAGACA
    PLOD2 1867 TCCAGCCTTTTCGTGGTGACTCAA 1868 CAGGGAGGTGGTTGCAAATTTCTAAGGTACAATTGCTCTATTG
    AGTCACCACGAAAAGGCTGGAGCTTCATGCATCCTGGGAGA
    PLP2 1871 ACACCAGGCTACTCCTCCCTGTCG 1872 CCTGATCTGCTTCAGTGCCTCCACACCAGGCTACTCCTCCCTG
    TCGGTGATTGAGATGATCCTTGCTGC
    PNLIPRP2 1875 ACCCGTGCCTCCAGTCCACAC 1876 TGGAGAAGGTGAACTGCATCTGTGTGGACTGGAGGCACGGGT
    CCCGGGCAATGTACACCCAAGCCGTG
    POSTN 1879 TTCTCCATCTGGCCTCAGAGCAGA 1880 GTGGCCCAATTAGGCTTGGCATCTGCTCTGAGGCCAGATGGA
    GAATACACTTTGCTGGCACCTGTGA
    PPAP2B 1883 ACCAGGGCTCCTTGAGCAAATCCT 1884 ACAAGCACCATCCCAGTGATGTTCTGGCAGGATTTGCTCAAGG
    AGCCCTGGTGGCCTGCTGCATAGTTTTCTTCGTG
    PPFIA3 1887 CACCCACTTTACCTTCTGGTGCCC 1888 CCTGGAGCTCCGTTACTCTCAGGCACCCACTTTACCTTCTGGT
    GCCCACCTGGATCCCTATGTGGCT
    PPP1R12A 1891 CCGTTCTTCTTCCTTTCGAGCTGC 1892 CGGCAAGGGGTTGATATAGAAGCAGCTCGAAAGGAAGAAGAA
    CGGATCATGCTTAGAGATGCCAGGCA
    PPP3CA 1895 TACATGCGGTACCCTGCATCTTGG 1896 ATACTCCGAGCCCACGAAGCCCAAGATGCAGGGTACCGCATG
    TACAGGAAAAGCCAAACAACAGGCTTCC
    PRIMA1 1899 TGACGCATCCAGGGCTCTAGTCTG 1900 ATCCTCTTCCCTGAGCCGCTGACGCATCCAGGGCTCTAGTCTG
    CACATAAATTCCCTCTCAGCTGGG
    PRKAR1B 1903 AAGGCCATCTCCAAGAACGTGCTC 1904 ACAAAACCATGACTGCGCTGGCCAAGGCCATCTCCAAGAACG
    TGCTCTTCGCTCACCTGGATGACA
    PRKAR2B 1907 CGAACTGGCCTTAATGTACAATACACCCA 1908 TGATAATCGTGGGAGTTTCGGCGAACTGGCCTTAATGTACAAT
    ACACCCAGAGCAGCTACAATCACTGCTACCTCTCCTGGTGC
    PRKCA 1911 CAGCCTCTGCGGAATGGATCACACT 1912 CAAGCAATGCGTCATCAATGTCCCCAGCCTCTGCGGAATGGAT
    CACACTGAGAAGAGGGGGCGGATTTAC
    PRKCB 1915 CCAGACCATGGACCGCCTGTACTT 1916 GACCCAGCTCCACTCCTGCTTCCAGACCATGGACCGCCTGTA
    CTTTGTGATGGAGTACGTGAATGGG
    PROM1 1919 ACCCGAGGCTGTGTCTCCAACAC 1920 CTATGACAGGCATGCCACCCCGACCACCCGAGGCTGTGTCTC
    CAACACCGGAGGCGTCTTCCTCATGGTTGGAG
    PROS1 1923 CTCATCCTGACAGACTGCAGCTGC 1924 GCAGCACAGGAATCTTCTTCTTGGCAGCTGCAGTCTGTCAGGA
    TGAGATATCAGATTAGGTTGGATAGGTGGG
    PSCA 1927 CCTGTGAGTCATCCACGCAGTTCA 1928 ACCGTCATCAGCAAAGGCTGCAGCTTGAACTGCGTGGATGAC
    TCACAGGACTACTACGTGGGCAAGAAGAACATCACG
    PSMD13 1931 CCTGAAGTGTCAGCTGATGCCACA 1932 GGAGGAGCTCTACACGAAGAAGTTGTGGCATCAGCTGACACT
    TCAGGTGCTTGATTTTGTGCAGGATCCG
    PTCH1 1935 CCTGAAACAAGGCTGAGAATCCCG 1936 CCACGACAAAGCCGACTACATGCCTGAAACAAGGCTGAGAAT
    CCCGGCAGCAGAGCCCATCGAGTA
    PTEN 1939 CCTTTCCAGCTTTACAGTGAATTGCTGCA 1940 TGGCTAAGTGAAGATGACAATCATGTTGCAGCAATTCACTGTA
    AAGCTGGAAAGGGACGAACTGGTGTAATGATATGTGCA
    PTGER3 1943 CCTTTGCCTTCCTGGGGCTCTT 1944 TAACTGGGGCAACCTTTTCTTCGCCTCTGCCTTTGCCTTCCTG
    GGGCTCTTGGCGCTGACAGTCACCTTTTCCTGCAA
    PTGS2 1947 CCTACCACCAGCAACCCTGCCA 1948 GAATCATTCACCAGGCAAATTGCTGGCAGGGTTGCTGGTGGTA
    GGAATGTTCCACCCGCAGTACAG
    PTH1R 1951 CCAGTGCCAGTGTCCAGCGGCT 1952 CGAGGTACAAGCTGAGATCAAGAAATCTTGGAGCCGCTGGAC
    ACTGGCACTGGACTTCAAGCGAAAGGCACGC
    PTHLH 1955 TGACACCTCCACAACGTCGCTGGA 1956 AGTGACTGGGAGTGGGCTAGAAGGGGACCACCTGTCTGACAC
    CTCCACAACGTCGCTGGAGCTCGATTCACGGTAACAGGCTT
    PTK2 1959 ACCAGGCCCGTCACATTCTCGTAC 1960 GACCGGTCGAATGATAAGGTGTACGAGAATGTGACGGGCCTG
    GTGAAAGCTGTCATCGAGATGTCCAG
    PTK2B 1963 CTCCGCAAACCAACCTCCTGGCT 1964 CAAGCCCAGCCGACCTAAGTACAGACCCCCTCCGCAAACCAA
    CCTCCTGGCTCCAAAGCTGCAGTTCCAGGTTC
    PTK6 1967 AGTGTCTGCGTCCAATACACGCGT 1968 GTGCAGGAAAGGTTCACAAATGTGGAGTGTCTGCGTCCAATAC
    ACGCGTGTGCTCCTCTCCTTACTCCATCGTGTGTGC
    PTK7 1971 CGCAAGGTCCCATTCTTGAAGACC 1972 TCAGAGGACTCACGGTTCGAGGTCTTCAAGAATGGGACCTTGC
    GCATCAACAGCGTGGAGGTGTATG
    PTPN1 1975 CTGATCCAGACAGCCGACCAGCT 1976 AATGAGGAAGTTTCGGATGGGGCTGATCCAGACAGCCGACCA
    GCTGCGCTTCTCCTACCTGGCTGTGATCGAAG
    PTPRK 1979 CCCCATCGTTGTACATTGCAGTGC 1980 TCAAACCCTCCCAGTGCTGGCCCCATCGTTGTACATTGCAGTG
    CTGGTGCTGGACGAACTGGCTGCT
    PTTG1 1983 CACACGGGTGCCTGGTTCTCCA 1984 GGCTACTCTGATCTATGTTGATAAGGAAAATGGAGAACCAGGC
    ACCCGTGTGGTTGCTAAGGATGGGCTGAAGC
    PYCARD 1987 ACGTTTGTGACCCTCGCGATAAGC 1988 CTTTATAGACCAGCACCGGGCTGCGCTTATCGCGAGGGTCAC
    AAACGTTGAGTGGCTGCTGGATGCT
    RAB27A 1991 ACAAATTGCTTCTCACCATCCCCATT 1992 TGAGAGATTAATGGGCATTGTGTACAAATTGCTTCTCACCATCC
    CCATTAGACCTACGAATAAAGCATCCGG
    RAB30 1995 CCATCAGGGCAGTTGCTGATTCCT 1996 TAAAGGCTGAGGCACGGAGAAGAAAAGGAATCAGCAACTGCC
    CTGATGGGCCATGAGATGCTGGGGAG
    RAB31 1999 CTTCTCAAAGTGAGGTGCCAGGCC 2000 CTGAAGGACCCTACGCTCGGTGGCCTGGCACCTCACTTTGAG
    AAGAGTGAGCACACTGGCTTTGCAT
    RAD21 2003 CACTTAAAACGAATCTCAAGAGGGTGAC 2004 TAGGGATGGTATCTGAAACAACAATGGTCACCCTCTTGAGATT
    CA CGTTTTAAGTGTAATTCCATAATGAGCAGAGGTGTACGCGA
    RAD51 2007 CTTTCAGCCAGGCAGATGCACTTG 2008 AGACTACTCGGGTCGAGGTGAGCTTTCAGCCAGGCAGATGCA
    CTTGGCCAGGTTTCTGCGGATGCT
    RAD9A 2011 CTTTGCTGGACGGCCACTTTGTCT 2012 GCCATCTTCACCATCAAGGACTCTTTGCTGGACGGCCACTTTG
    TCTTGGCCACACTCTCAGACACCG
    RAF1 2015 TCCAGGATGCCTGTTAGTTCTCAGCA 2016 CGTCGTATGCGAGAGTCTGTTTCCAGGATGCCTGTTAGTTCTC
    AGCACAGATATTCTACACCTCACGCCTTCA
    RAGE 2019 CCGGAGTGTCTATTCCAAGCAGCC 2020 ATTAGGGGACTTTGGCTCCTGCCGGAGTGTCTATTCCAAGCAG
    CCGTACACGGAATACATCTCCACCC
    RALA 2023 TTGTGTTTCTTGGGCAGTCTTTCTTGAA 2024 TGGTCCTGAATGTAGCGTGTAAGCTTGTGTTTCTTGGGCAGTC
    TTTCTTGAAATTGAAGAGGTGAAATGGGG
    RALBP1 2027 TGCTGTCCTGTCGGTCTCAGTACGTTCA 2028 GGTGTCAGATATAAATGTGCAAATGCCTTCTTGCTGTCCTGTC
    GGTCTCAGTACGTTCACTTTATAGCTGCTGGCAATATCGAA
    RAP1B 2031 CACGCATGATGCAAGCTTGTCAAA 2032 TGACAGCGTGAGAGGTACTAGGTTTTGACAAGCTTGCATCATG
    CGTGAGTATAAGCTAGTCGTTCTTGGCTCAG
    RARB 2035 TGTGCTCTGCTGTGTTCCCACTTG 2036 ATGAACCCTTGACCCCAAGTTCAAGTGGGAACACAGCAGAGC
    ACAGTCCTAGCATCTCACCCAGCTC
    RASSF1 2039 CACCACCAAGAACTTTCGCAGCAG 2040 AGGGCACGTGAAGTCATTGAGGCCCTGCTGCGAAAGTTCTTG
    GTGGTGGATGACCCCCGCAAGTTTGCACTCTTT
    RB1 2043 CCCTTACGGATTCCTGGAGGGAAC 2044 CGAAGCCCTTACAAGTTTCCTAGTTCACCCTTACGGATTCCTG
    GAGGGAACATCTATATTTCACCCCTGAAGAGTCC
    RECK 2047 TCAAGTGTCCTTCGCTCTTGGCAG 2048 GTCGCCGAGTGTGCTTCTGTCAAGTGTCCTTCGCTCTTGGCAG
    CTGGATGCAAACCCATCATCCCAC
    REG4 2051 TCCTCTTCCTTTCTGCTAGCCTGGC 2052 TGCTAACTCCTGCACAGCCCCGTCCTCTTCCTTTCTGCTAGCC
    TGGCTAAATCTGCTCATTATTTCAGAGGGGAAACCTAGCA
    RELA 2055 CTGAGCTCTGCCCGGACCGCT 2056 CTGCCGGGATGGCTTCTATGAGGCTGAGCTCTGCCCGGACCG
    CTGCATCCACAGTTTCCAGAACCTGG
    RFX1 2059 TCCAATGGACCAAGCACTGTGACA 2060 TCCTCTCCAAGTTCGAGCCCGTGCTCCAATGGACCAAGCACTG
    TGACAACGTGCTGTACCAGGGCCTG
    RGS10 2063 AGTTCCAGCAGCAGCCACCAGAG 2064 AGACATCCACGACAGCGATGGCAGTTCCAGCAGCAGCCACCA
    GAGCCTCAAGAGCACAGCCAAATGG
    RGS7 2067 TGAAAATGAACTCCCACTTCCGGG 2068 CAGGCTGCAGAGAGCATTTGCCCGGAAGTGGGAGTTCATTTTC
    ATGCAAGCAGAAGCACAAGCAAA
    RHOA 2071 AAATGGGCTCAACCAGAAAAGCCC 2072 TGGCATAGCTCTGGGGTGGGCAGTTTTTTGAAAATGGGCTCAA
    CCAGAAAAGCCCAAGTTCATGCAGCTGTGGCA
    RHOB 2075 CTTTCCAACCCCTGGGGAAGACAT 2076 AAGCATGAACAGGACTTGACCATCTTTCCAACCCCTGGGGAAG
    ACATTTGCAACTGACTTGGGGAGG
    RHOC 2079 TCCGGTTCGCCATGTCCCG 2080 CCCGTTCGGTCTGAGGAAGGCCGGGACATGGCGAACCGGATC
    AGTGCCTTTGGCTACCTTGAGTGCTC
    RLN1 2083 TGAGAGGCAACCATCATTACCAGAGC 2084 AGCTGAAGGCAGCCCTATCTGAGAGGCAACCATCATTACCAG
    AGCTACAGCAGTATGTACCTGCATTAAAGGATTCCAA
    RND3 2087 TTTTAAGCCTGACTCCTCACCGCG 2088 TCGGAATTGGACTTGGGAGGCGCGGTGAGGAGTCAGGCTTAA
    AACTTGTTGGAGGGGAGTAACCAG
    RNF114 2091 CCAGGTCAGCCCTTCTCTTCCCTT 2092 TGACAGGGGAAGTGGGTCCCCAGGTCAGCCCTTCTCTTCCCT
    TTGGGCTCTTGCCAAAGCTGTCTTCC
    ROBO2 2095 CTGTACCATCCACTGCCAGCGTTT 2096 CTACAAGGCCCAGCCAACCAAACGCTGGCAGTGGATGGTACA
    GCGTTACTGAAATGTAAAGCCACTGGTG
    RRM1 2099 CATTGGAATTGCCATTAGTCCCAGC 2100 GGGCTACTGGCAGCTACATTGCTGGGACTAATGGCAATTCCAA
    TGGCCTTGTACCGATGCTGAGAG
    RRM2 2103 CCAGCACAGCCAGTTAAAAGATGCA 2104 CAGCGGGATTAAACAGTCCTTTAACCAGCACAGCCAGTTAAAA
    GATGCAGCCTCACTGCTTCAACGCAGAT
    S100P 2107 TTGCTCAAGGACCTGGACGCCAA 2108 AGACAAGGATGCCGTGGATAAATTGCTCAAGGACCTGGACGC
    CAATGGAGATGCCCAGGTGGACTTC
    SAT1 2111 TCCAGTGCTCTTTCGGCACTTCTG 2112 CCTTTTACCACTGCCTGGTTGCAGAAGTGCCGAAAGAGCACTG
    GACTCCGGAAGGACACAGCATTGT
    SCUBE2 2115 CAGGCCCTCTTCCGAGCGGT 2116 TGACAATCAGCACACCTGCATTCACCGCTCGGAAGAGGGCCT
    GAGCTGCATGAATAAGGATCACGGCTGTAGTCACA
    SDC1 2119 CTCTGAGCGCCTCCATCCAAGG 2120 GAAATTGACGAGGGGTGTCTTGGGCAGAGCTGGCTCTGAGCG
    CCTCCATCCAAGGCCAGGTTCTCCGTTAGCTCCT
    SDC2 2123 AACTCCATCTCCTTCCCCAGGCAT 2124 GGATTGAAGTGGCTGGAAAGAGTGATGCCTGGGGAAGGAGAT
    GGAGTTATGAGGGTACTGTGGCTGGT
    SDHC 2127 TTACATCCTCCCTCTCCCCGCAAT 2128 CTTCCCTCGGGTCTCAGGCATTTACATCCTCCCTCTCCCCGCA
    ATCTGACCTTTACCAGGAGGGAA
    SEC14L1 2131 CGGGCTTCTACATCCTGCAGTGG 2132 AGGGTTCCCATGTGACCAGGTGGCCGGGCTTCTACATCCTGC
    AGTGGAAATTCCACAGCATGCCTGC
    SEC23A 2135 TCCTGGAGATGAAATGCTGTCCCA 2136 CGTGTGCATTAGATCAGACAGGTCTCCTGGAGATGAAATGCTG
    TCCCAACCTTACTGGAGGATACATGGTAATGGG
    SEMA3A 2139 TTGCCAATAGACCAGCGCTCTCTG 2140 TTGGAATGCAGTCCGAAGTCGCAGAGAGCGCTGGTCTATTGG
    CAATTCCAGAGGCGAAATGAAGAG
    SEPT9 2143 TTGCCAATAGACCAGCGCTCTCTG 2144 CAGTGACCACGAGTACCAGGTCAACGGCAAGAGGATCCTTGG
    GAGGAAGACCAAGTGGGGTACCATCGAAG
    SERPINA3 2147 AGGGAATCGCTGTCACCTTCCAAG 2148 GTGTGGCCCTGTCTGCTTATCCTTGGAAGGTGACAGCGATTCC
    CTGTGTAGCTCTCACATGCACAGGG
    SERPINB5 2151 AGCTGACAACAGTGTGAACGACCAGACC 2152 CAGATGGCCACTTTGAGAACATTTTAGCTGACAACAGTGTGAA
    CGACCAGACCAAAATCCTTGTGGTTAATGCTGCC
    SESN3 2155 TGCTCTTCTCCTCGTCTGGCAAAG 2156 GACCCTGGTTTTGGGTATGAAGACTTTGCCAGACGAGGAGAA
    GAGCATTTGCCAACATTCCGAGCTC
    SFRP4 2159 CCTGGGACAGCCTATGTAAGGCCA 2160 TACAGGATGAGGCTGGGCATTGCCTGGGACAGCCTATGTAAG
    GCCATGTGCCCCTTGCCCTAACAAC
    SH3RF2 2163 AACCGGATGGTCCATTCTCCTTCA 2164 CCATCACAACAGCCTTGAACACTCTCAACCGGATGGTCCATTC
    TCCTTCAGGGCGCCATATGGTAGAGATCAGCACCCCAGTG
    SH3YL1 2167 CACAGCAGTCATCTGCACCAGTCC 2168 CCTCCAAAGCCATTGTCAAGACCACAGCAGTCATCTGCACCAG
    TCCAGCTGAACTCTGGCTCTCAAAG
    SHH 2171 CACCGAGTTCTCTGCTTTCACCGA 2172 GTCCAAGGCACATATCCACTGCTCGGTGAAAGCAGAGAACTC
    GGTGGCGGCCAAATCGGGAGGCTGCTTC
    SHMT2 2175 CCATCACTGCCAACAAGAACACCTG 2176 AGCGGGTGCTAGAGCTTGTATCCATCACTGCCAACAAGAACAC
    CTGTCCTGGAGACCGAAGTGCCAT
    SIM2 2179 CGCCTCTCCACGCACTCAGCTAT 2180 GATGGTAGGAAGGGATGTGCCCGCCTCTCCACGCACTCAGCT
    ATACCTCATTCACAGCTCCTTGTG
    SIPA1L1 2183 CGCCACAATGCCCTCATAGTTGAC 2184 CTAGGACAGCTTGGCTTCCATGTCAACTATGAGGGCATTGTGG
    CGGATGTGGAGCCCTACGGTTATG
    SKIL 2187 CCAATCTCTGCCTCAGTTCTGCCA 2188 AGAGGCTGAATATGCAGGACAGTTGGCAGAACTGAGGCAGAG
    ATTGGACCATGCTGAGGCCGATAG
    SLC22A3 2191 CAGCATCCACGCATTGACACAGAC 2192 ATCGTCAGCGAGTTTGACCTTGTCTGTGTCAATGCGTGGATGC
    TGGACCTCACCCAAGCCATCCTG
    SLC25A21 2195 TCATGGTGCTGCATAGCAAATATCCA 2196 AAGTGTTTTTCCCCCTTGAGATAATGGATATTTGCTATGCAGCA
    CCATGAAGAAGAGAGACTATCGATCGGCC
    SLC44A1 2199 TACCATGGCTGCTGCTCTTCATCC 2200 AGGACCGTAGCTGCACAGACATACCATGGCTGCTGCTCTTCAT
    CCTCTTCTGCATTGGGATGGGAT
    SMAD4 2203 TGCATTCCAGCCTCCCATTTCCA 2204 GGACATTACTGGCCTGTTCACAATGAGCTTGCATTCCAGCCTC
    CCATTTCCAATCATCCTGCTCCTGAGTATTGGT
    SMARCC2 2207 TATCTTACCTCTACCGCCTGCCGC 2208 TACCGACTGAACCCCCAAGAGTATCTTACCTCTACCGCCTGCC
    GCCGAAACCTAGCGGGTGATGTC
    SMARCD1 2211 CCCACCCTTGCTGTGTTGAGTCTG 2212 CCGAGTTAGCATATCCCAGGCTCGCAGACTCAACACAGCAAG
    GGTGGGAGACAGCTGGGCACAAAGG
    SMO 2215 CTTCACAGAGGCTGAGCACCAGGA 2216 GGCATCCAGTGCCAGAACCCGCTCTTCACAGAGGCTGAGCAC
    CAGGACATGCACAGCTACATCGCG
    SNAI1 2219 TCTGGATTAGAGTCCTGCAGCTCGC 2220 CCCAATCGGAAGCCTAACTACAGCGAGCTGCAGGACTCTAAT
    CCAGAGTTTACCTTCCAGCAGCCCTAC
    SNRPB2 2223 CCCACCTAAGGCCTACGCCGACTA 2224 CGTTTCCTGCTTTTGGTTCTTACAGTAGTCGGCGTAGGCCTTA
    GGTGGGTTCGTGCGCCTTCTACCT
    SOD1 2227 TTTGTCAGCAGTCACATTGCCCAA 2228 TGAAGAGAGGCATGTTGGAGACTTGGGCAATGTGACTGCTGA
    CAAAGATGGTGTGGCCGATGTGTCTATT
    SORBS1 2231 ATTTCCATTGGCATCAGCACTGGA 2232 GCAGATGAGTGGAGGCTTTCTTCCAGTGCTGATGCCAATGGAA
    ATGCCCAGCCCTCTTCACTCGCT
    SOX4 2235 CGAGTCCAGCATCTCCAACCTGGT 2236 AGATGATCTCGGGAGACTGGCTCGAGTCCAGCATCTCCAACC
    TGGTTTTCACCTACTGAAGGGCGC
    SPARC 2239 TGGACCAGCACCCCATTGACGG 2240 TCTTCCCTGTACACTGGCAGTTCGGCCAGCTGGACCAGCACC
    CCATTGACGGGTACCTCTCCCACACCGAGCT
    SPARCL1 2243 ACTTCATCCCAAGCCAGGCCTTTC 2244 GGCACAGTGCAAGTGATGACTACTTCATCCCAAGCCAGGCCTT
    TCTGGAGGCCGAGAGAGCTCAATC
    SPDEF 2247 ATCATCCGGAAGCCAGACATCTCC 2248 CCATCCGCCAGTATTACAAGAAGGGCATCATCCGGAAGCCAG
    ACATCTCCCAGCGCCTCGTCTACCAGTTCGTGCACCC
    SPINK1 2251 ACCACGTCTCTTCAGAAGCCTGGG 2252 CTGCCATATGACCCTTCCAGTCCCAGGCTTCTGAAGAGACGTG
    GTAAGTGCGGTGCAGTTTTCAAC
    SPINT1 2255 CTGTCGCAGTGTTCCTGGTCATCTGC 2256 ATTCCCAGCACAGGCTCTGTGGAGATGGCTGTCGCAGTGTTC
    CTGGTCATCTGCATTGTGGTGGTGGTAGCCATCT
    SPP1 2259 TGAATGGTGCATACAAGGCCATCC 2260 TCACACATGGAAAGCGAGGAGTTGAATGGTGCATACAAGGCC
    ATCCCCGTTGCCCAGGACCTGAAC
    SQLE 2263 TGGGCAAGAAAAACATCTCATTCCTTTG 2264 ATTTTCGAGGCCAAAAAATCATTTTACTGGGCAAGAAAAACATC
    TCATTCCTTTGTCGTGAATATCCTTGCTCAGG
    SRC 2267 AACCGCTCTGACTCCCGTCTGGTG 2268 TGAGGAGTGGTATTTTGGCAAGATCACCAGACGGGAGTCAGA
    GCGGTTACTGCTCAATGCAGAGAACCCGAGAG
    SRD5A1 2271 CCTCTCTCGGAGGCCACAGAGGCT 2272 GGGCTGGAATCTGTCTAGGAGCCCTCTCTCGGAGGCCACAGA
    GGCTGGGGGTAGCCATTGTGCAGTCATGG
    SRD5A2 2275 AGACACCACTCAGAATCCCCAGGC 2276 GTAGGTCTCCTGGCGTTCTGCCAGCTGGCCTGGGGATTCTGA
    GTGGTGTCTGCTTAGAGTTTACTCCTACCCTTCCAGGGA
    STS 2279 AGTCACGAGCACCCAGCGAAACTT 2280 CCTGTCCTGCCAGAGCATGGATGAAGTTTCGCTGGGTGCTCGT
    GACTGGCCAGTTTTGTGCAGCTG
    STAT1 2283 TGGCAGTTTTCTTCTGTCACCAAAA 2284 GGGCTCAGCTTTCAGAAGTGCTGAGTTGGCAGTTTTCTTCTGT
    CACCAAAAGAGGTCTCAATGTGGACCAGCTGAACATGT
    STAT3 2287 TCCTGGGAGAGATTGACCAGCA 2288 TCACATGCCACTTTGGTGTTTCATAATCTCCTGGGAGAGATTGA
    CCAGCAGTATAGCCGCTTCCTGCAAG
    STAT5A 2291 CGGTTGCTCTGCACTTCGGCCT 2292 GAGGCGCTCAACATGAAATTCAAGGCCGAAGTGCAGAGCAAC
    CGGGGCCTGACCAAGGAGAACCTCGTGTTCCTGGC
    STAT5B 2295 CAGCCAGGACAACAATGCGACGG 2296 CCAGTGGTGGTGATCGTTCATGGCAGCCAGGACAACAATGCG
    ACGGCCACTGTTCTCTGGGACAATGCTTTTGC
    STMN1 2299 CACGTTCTCTGCCCCGTTTCTTG 2300 AATACCCAACGCACAAATGACCGCACGTTCTCTGCCCCGTTTC
    TTGCCCCAGTGTGGTTTGCATTGTCTCC
    STS 2303 CTGCGTGGCTCTCGGCTTCCCA 2304 GAAGATCCCTTTCCTCCTACTGTTCTTTCTGTGGGAAGCCGAG
    AGCCACGCAGCATCAAGGCCGAACATCATCC
    SULF1 2307 TACCGTGCCAGCAGAAGCCAAAG 2308 TGCAGTTGTAGGGAGTCTGGTTACCGTGCCAGCAGAAGCCAA
    AGAAAGAGTCAACGGCAATTCTTGAGA
    SUMO1 2311 CTGACCAGGAGGCAAAACCTTCAACTGA 2312 GTGAAGCCACCGTCATCATGTCTGACCAGGAGGCAAAACCTTC
    AACTGAGGACTTGGGGGATAAGAAGGAAGG
    SVIL 2315 ACCCCAGGACTGATGTCAAGGCAT 2316 ACTTGCCCAGCACAAGGAAGACCCCAGGACTGATGTCAAGGC
    ATACGATGTGACACGGATGGTGTC
    TAF2 2319 AGCCTCCAAACACAGTGACCACCA 2320 GCGCTCCACTCTCAGTCTTTACTAAGGAATCTACAGCCTCCAA
    ACACAGTGACCACCATCACCACCATCACCATGAGCACAAG
    TARP 2323 TCTTCATGGTGTTCCCCTCCTGG 2324 GAGCAACACGATTCTGGGATCCCAGGAGGGGAACACCATGAA
    GACTAACGACACATACATGAAATTTAGCTGGTTAACGGTGCC
    TBP 2327 TACCGCAGCAAACCGCTTGGG 2328 GCCCGAAACGCCGAATATAATCCCAAGCGGTTTGCTGCGGTA
    ATCATGAGGATAAGAGAGCCACG
    TFDP1 2331 CGCACCAGCATGGCAATAAGCTTT 2332 TGCGAAGTGCTTTTGTTTGTTTGTTTTCGTTTGGTTAAAGCTTAT
    TGCCATGCTGGTGCGGCTATGGAGACTGTCTGGAAGGC
    TFF1 2335 TGCTGTTTCGACGACACCGTTCG 2336 GCCCTCCCAGTGTGCAAATAAGGGCTGCTGTTTCGACGACAC
    CGTTCGTGGGGTCCCCTGGTGCTTCTATCCTAATACCATCGAC
    G
    TFF3 2339 CAGAAGCGCTTGCCGGGAGCAAAGG 2340 AGGCACTGTTCATCTCAGCTTTTCTGTCCCTTTGCTCCCGGCA
    AGCGCTTCTGCTGAAAGTTCATATCTGGAGCCTGATG
    TGFA 2343 TTGGCCTGTAATCACCTGTGCAGCCTT 2344 GGTGTGCCACAGACCTTCCTACTTGGCCTGTAATCACCTGTGC
    AGCCTTTTGTGGGCCTTCAAAACTCTGTCAAGAACTCCGT
    TGFB1I1 2347 CAAGATGTGGCTTCTGCAACCAGC 2348 GCTACTTTGAGCGCTTCTCGCCAAGATGTGGCTTCTGCAACCA
    GCCCATCCGACACAAGATGGTGACC
    TGFB2 2351 TCCTGAGCCCGAGGAAGTCCC 2352 ACCAGTCCCCCAGAAGACTATCCTGAGCCCGAGGAAGTCCCC
    CCGGAGGTGATTTCCATCTACAACAGCACCAGG
    TGFB3 2355 CGGCCAGATGAGCACATTGCC 2356 GGATCGAGCTCTTCCAGATCCTTCGGCCAGATGAGCACATTGC
    CAAACAGCGCTATATCGGTGGC
    TGFBR2 2359 TTCTGGGCTCCTGATTGCTCAAGC 2360 AACACCAATGGGTTCCATCTTTCTGGGCTCCTGATTGCTCAAG
    CACAGTTTGGCCTGATGAAGAGG
    THBS2 2363 TGAGTCTGCCATGACCTGTTTTCCTTCAT 2364 CAAGACTGGCTACATCAGAGTCTTAGTGCATGAAGGAAAACAG
    GTCATGGCAGACTCAGGACCTATCTATGACCAAACCTACGCTG
    THY1 2367 CAAGCTCCCAAGAGCTTCCAGAGC 2368 GGACAAGACCCTCTCAGGCTGTCCCAAGCTCCCAAGAGCTTC
    CAGAGCTCTGACCCACAGCCTCCAA
    TIAM1 2371 TGGAGCCCTTCTCCCAAGATGGTA 2372 GTCCCTGGCTGAAAATGGCCTGGAGCCCTTCTCCCAAGATGG
    TACCCTAGAAGACTTCGGGAGCCC
    TIMP2 2375 CCCTGGGACACCCTGAGCACCA 2376 TCACCCTCTGTGACTTCATCGTGCCCTGGGACACCCTGAGCAC
    CACCCAGAAGAAGAGCCTGAACCACA
    TIMP3 2379 CCAAGAACGAGTGTCTCTGGACCG 2380 CTACCTGCCTTGCTTTGTGACTTCCAAGAACGAGTGTCTCTGG
    ACCGACATGCTCTCCAATTTCGGT
    TK1 2383 CAAATGGCTTCCTCTGGAAGGTCCCA 2384 GCCGGGAAGACCGTAATTGTGGCTGCACTGGATGGGACCTTC
    CAGAGGAAGCCATTTGGGGCCATCCTGAACCTGGTGCCGCTG
    TMPRSS2 2387 AAGCACTGTGCATCACCTTGACCC 2388 GGACAGTGTGCACCTCAAAGACTAAGAAAGCACTGTGCATCAC
    CTTGACCCTGGGGACCTTCCTCGTGGGAG
    TMPRSS2 2391 TAAGGCTTCCTGCCGCGCTCCA 2392 GAGGCGGAGGCGGAGGGCGAGGGGCGGGGAGCGCCGCCTG
    ERGA GAGCGCGGCAGGAAGCCTTATCAGTTGTGAGTGAGGACCAGT
    TMPRSS2 2395 CCTGGAATAACCTGCCGCGC 2396 GAGGCGGAGGGCGAGGGGCGGGGAGCGCCGCCTGGAGCGC
    ERGB GGCAGGTTATTCCAGGATCTTTGGAGACCCGAGGAA
    TNF 2399 CGCTGAGATCAATCGGCCCGACTA 2400 GGAGAAGGGTGACCGACTCAGCGCTGAGATCAATCGGCCCGA
    CTATCTCGACTTTGCCGAGTCTGGGCA
    TNFRSF10A 2403 CAATGCTTCCAACAATTTGTTTGCTTGCC 2404 TGCACAGAGGGTGTGGGTTACACCAATGCTTCCAACAATTTGT
    TTGCTTGCCTCCCATGTACAGCTTGTAAATCAGATGAAGA
    TNFRSF10B 2407 CAGACTTGGTGCCCTTTGACTCC 2408 CTCTGAGACAGTGCTTCGATGACTTTGCAGACTTGGTGCCCTT
    TGACTCCTGGGAGCCGCTCATGAGGAAGTTGGGCCTCATGG
    TNFRSF18 2411 CCTTCTCCTCTGCCGATCGCTC 2412 CAGAAGCTGCCAGTTCCCCGAGGAAGAGCGGGGCGAGCGAT
    CGGCAGAGGAGAAGGGGCGGCTGGGAGACCTGTGGGTG
    TNFSF10 2415 AAGTACACGTAAGTTACAGCCACACA 2416 CTTCACAGTGCTCCTGCAGTCTCTCTGTGTGGCTGTAACTTAC
    GTGTACTTTACCAACGAGCTGAAGCAGATG
    TNFSF11 2419 ACATGACCAGGGACCAACCCCTC 2420 AACTGCATGTGGGCTATGGGAGGGGTTGGTCCCTGGTCATGT
    GCCCCTTCGCAGCTGAAGTGGAGAGGGTGTCA
    TOP2A 2423 CATATGGACTTTGACTCAGCTGTGGC 2424 AATCCAAGGGGGAGAGTGATGACTTCCATATGGACTTTGACTC
    AGCTGTGGCTCCTCGGGCAAAATCTGTAC
    TP53 2427 AAGTCCTGGGTGCTTCTGACGCACA 2428 CTTTGAACCCTTGCTTGCAATAGGTGTGCGTCAGAAGCACCCA
    GGACTTCCATTTGCTTTGTCCCGGG
    TP63 2431 CCCGGGTCTCACTGGAGCCCA 2432 CCCCAAGCAGTGCCTCTACAGTCAGTGTGGGCTCCAGTGAGA
    CCCGGGGTGAGCGTGTTATTGATGCTGTGCGATTC
    TPD52 2435 TCTGCTACCCACTGCCAGATGCTG 2436 GCCTGTGAGATTCCTACCTTTGTTCTGCTACCCACTGCCAGAT
    GCTGCAAGCGAGGTCCAAGCACAT
    TPM1 2439 TTCTCCAGCTGACCCTGGTTCTCTC 2440 TCTCTGAGCTCTGCATTTGTCTATTCTCCAGCTGACCCTGGTTC
    TCTCTCTTAGCATCCTGCCTTAGAGCC
    TPM2 2443 CCAAGCACATCGCTGAGGATTCAG 2444 AGGAGATGCAGCTGAAGGAGGCCAAGCACATCGCTGAGGATT
    CAGACCGCAAATATGAAGAGGTGG
    TPP2 2447 ATCCTGTTCAGGTGGCTGCACCTT 2448 TAACCGTGGCATCTACCTCCGAGATCCTGTTCAGGTGGCTGCA
    CCTTCAGATCATGGCGTTGGCAT
    TPX2 2451 CAGGTCCCATTGCCGGGCG 2452 TCAGCTGTGAGCTGCGGATACCGCCCGGCAATGGGACCTGCT
    CTTAACCTCAAACCTAGGACCGT
    TRA2A 2455 AACTGAGGCCAAACACTCCAAGGC 2456 GCAAATCCAGATCCCAACACTTGCCTTGGAGTGTTTGGCCTCA
    GTTTGTACACAACAGAGAGGGATCTTCGTGAAG
    TRAF3IP2 2459 TGGATCTGCCAACCATAGACACGG 2460 CCTCACAGGAACCGAGCAGGCCTGGATCTGCCAACCATAGAC
    ACGGGATATGATTCCCAGCCCCAG
    TRAM1 2463 AGTGCTGAGCCACGAATTCGTCC 2464 CAAGAAAAGCACCAAGAGCCCCCCAGTGCTGAGCCACGAATT
    CGTCCTGCAGAATCACGCGGACAT
    TRAP1 2467 TTCGGCGATTTCAAACACTCCAGA 2468 TTACCAGTGGCTTTCAGATGGTTCTGGAGTGTTTGAAATCGCC
    GAAGCTTCGGGAGTTAGAACCGGGACA
    TRIM14 2471 AACTGCCAGCTCTCAGACCCTTCC 2472 CATTCGCCTTAAGGAAAGCATAAACTGCCAGCTCTCAGACCCT
    TCCAGCACCAAGCCAGGTACCTTG
    TRO 2475 CCACCCAAGGCCAAATTACCAATG 2476 GCAACTGCCACCCATACAGCTACCACCCAAGGCCAAATTACCA
    ATGAGACAGCCAGTATCCACACCA
    TRPC6 2479 CTTCTCCCAGCTCCGAGTCCATG 2480 CGAGAGCCAGGACTATCTGCTCATGGACTCGGAGCTGGGAGA
    AGACGGCTGCCCGCAAGCCCCGCTGCCTTGCTACGGCTA
    TRPV6 2483 ACTTTGGGGAGCACCCTTTGTCCT 2484 CCGTAGTCCCTGCAACCTCATCTACTTTGGGGAGCACCCTTTG
    TCCTTTGCTGCCTGTGTGAACAGTGAGGA
    TSTA3 2487 AACGTGCACATGAACGACAACGTC 2488 CAATTTGGACTTCTGGAGGAAAAACGTGCACATGAACGACAAC
    GTCCTGCACTCGGCCTTTGAGGTG
    TUBB2A 2491 TCTCAGATCAATCGTGCATCCTTAGTGAA 2492 CGAGGACGAGGCTTAAAAACTTCTCAGATCAATCGTGCATCCT
    TAGTGAACTTCTGTTGTCCTCAAGCATGGT
    TYMP 2495 ACAGCCTGCCACTCATCACAGCC 2496 CTATATGCAGCCAGAGATGTGACAGCCACCGTGGACAGCCTG
    CCACTCATCACAGCCTCCATTCTCAGTAAGAAACTCGTGG
    TYMS 2499 CATCGCCAGCTACGCCCTGCTC 2500 GCCTCGGTGTGCCTTTCAACATCGCCAGCTACGCCCTGCTCAC
    GTACATGATTGCGCACATCACG
    UAP1 2503 TACCTGTAAACCTTTCTCGGCGCG 2504 CTGGAGACGGTCGTAGCTGCGGTCGCGCCGAGAAAGGTTTAC
    AGGTACATACATTACACCCCTATTTCTACAAAGCTTGGC
    UBE2C 2507 TCTGCCTTCCCTGAATCAGACAACC 2508 TGTCTGGCGATAAAGGGATTTCTGCCTTCCCTGAATCAGACAA
    CCTTTTCAAATGGGTAGGGACCAT
    UBE2G1 2511 TTGTCCCACCAGTGCCTCATCAGT 2512 TGACACTGAACGAGGTGGCTTTTGTCCCACCAGTGCCTCATCA
    GTGTGAGGCGATTCCTCTCTGCTT
    UBE2T 2515 AGGTGCTTGGAGACCATCCCTCAA 2516 TGTTCTCAAATTGCCACCAAAAGGTGCTTGGAGACCATCCCTC
    AACATCGCAACTGTGTTGACCTCT
    UGDH 2519 TATACAGCACACAGGGCCTGCACA 2520 GAAACTCCAGAGGGCCAGAGAGCTGTGCAGGCCCTGTGTGCT
    GTATATGAGCACTGGGTTCCCAGAG
    UGT2B15 2523 AAAGATGGGACTCCTCCTTTATTTCAGCA 2524 AAGCCTGAAGTGGAATGACTGAAAGATGGGACTCCTCCTTTAT
    TTCAGCATGGAGGGTTTTAAATGGAGG
    UGT2B17 2527 ACCCGAAGGTGCTTGGCTCCTTTA 2528 TTGAGTTTGTCATGCGCCATAAAGGAGCCAAGCACCTTCGGGT
    CGCAGCCCACAACCTCACCTGGA
    UHRF1 2531 CGGCCATACCCTCTTCGACTACGA 2532 CTACAGGGGCAAACAGATGGAGGACGGCCATACCCTCTTCGA
    CTACGAGGTCCGCCTGAATGACACC
    UTP23 2535 TCGAAATTGTCCTCATTTCAAGAATGCA 2536 GATTGCACAAAAATGCCAAGTTCGAAATTGTCCTCATTTCAAGA
    ATGCAGTGAGTGGATCAGAATGTCTGCTTTCC
    VCAM1 2539 CAGGCACACACAGGTGGGACACAAAT 2540 TGGCTTCAGGAGCTGAATACCCTCCCAGGCACACACAGGTGG
    GACACAAATAAGGGTTTTGGAACCACTATTTTCTCATCACGACA
    GCA
    VCL 2543 AGTGGCAGCCACGGCGCC 2544 GATACCACAACTCCCATCAAGCTGTTGGCAGTGGCAGCCACG
    GCGCCTCCTGATGCGCCTAACAGGGA
    VCPIP1 2547 TGGTCCATCCTCTGCACCTGCTAC 2548 TTTCTCCCAGTACCATTCGTGATGGTCCATCCTCTGCACCTGC
    TACACCTACCAAGGCTCCCTATTCA
    VDR 2551 CAGCATGAAGCTAACGCCCCTTGT 2552 CCTCTCCTTCCAGCCTGAGTGCAGCATGAAGCTAACGCCCCTT
    GTGCTCGAAGTGTTTGGCAATGA
    VEGFA 2555 TTGCCTTGCTGCTCTACCTCCACCA 2556 CTGCTGTCTTGGGTGCATTGGAGCCTTGCCTTGCTGCTCTACC
    TCCACCATGCCAAGTGGTCCCAGGCTGC
    VEGFB 2559 CTGGGCAGCACCAAGTCCGGA 2560 TGACGATGGCCTGGAGTGTGTGCCCACTGGGCAGCACCAAGT
    CCGGATGCAGATCCTCATGATCCGGTACC
    VEGFC 2563 CCTCTCTCTCAAGGCCCCAAACCAGT 2564 CCTCAGCAAGACGTTATTTGAAATTACAGTGCCTCTCTCTCAAG
    GCCCCAAACCAGTAACAATCAGTTTTGCCAATCACACTT
    VIM 2567 ATTTCACGCATCTGGCGTTCCA 2568 TGCCCTTAAAGGAACCAATGAGTCCCTGGAACGCCAGATGCG
    TGAAATGGAAGAGAACTTTGCCGTTGAAGC
    VTI1B 2571 CGAAACCCCATGATGTCTAAGCTTCG 2572 ACGTTATGCACCCCTGTCTTTCCGAAACCCCATGATGTCTAAG
    CTTCGAAACTACCGGAAGGACCTTGCTAAACTCCATCGG
    WDR19 2575 CCCCTCGACGTATGTCTCCCATTC 2576 GAGTGGCCCAGATGTCCATAAGAATGGGAGACATACGTCGAG
    GGGTTAACCAAGCCCTCAAGCATC
    WFDC1 2579 CTATGAGTGCCACATCCTGAGCCC 2580 ACCCCTGCTCTGTCCCTCGGGCTATGAGTGCCACATCCTGAG
    CCCAGGTGACGTGGCCGAAGGTAT
    WISP1 2583 CGGGCTGCATCAGCACACGC 2584 AGAGGCATCCATGAACTTCACACTTGCGGGCTGCATCAGCACA
    CGCTCCTATCAACCCAAGTACTGTGGAGTTTG
    WNT5A 2587 TTGATGCCTGTCTTCGCGCCTTCT 2588 GTATCAGGACCACATGCAGTACATCGGAGAAGGCGCGAAGAC
    AGGCATCAAAGAATGCCAGTATCAATTCCGACA
    WWOX 2591 CTGCTGTTTACCTTGGCGAGGCCTTTC 2592 ATCGCAGCTGGTGGGTGTACACACTGCTGTTTACCTTGGCGAG
    GCCTTTCACCAAGTCCATGCAACAGGGAGCT
    XIAP 2595 TCCCCAAATTGCAGATTTATCAACGGC 2596 GCAGTTGGAAGACACAGGAAAGTATCCCCAAATTGCAGATTTA
    TCAACGGCTTTTATCTTGAAAATAGTGCCACGCA
    XRCC5 2599 TCTGGCTGAAGGCAGTGTCACCTC 2600 AGCCCACTTCAGCGTCTCCAGTCTGGCTGAAGGCAGTGTCAC
    CTCTGTTGGAAGTGTGAATCCTGCT
    YY1 2603 TTGATCTGCACCTGCTTCTGCTCC 2604 ACCCGGGCAACAAGAAGTGGGAGCAGAAGCAGGTGCAGATCA
    AGACCCTGGAGGGCGAGTTCTCGGTC
    ZFHX3 2607 ACCTGGCCCAACTCTACCAGCATC 2608 CTGTGGAGCCTCTGCCTGCGGACCTGGCCCAACTCTACCAGC
    ATCAGCTCAATCCAACCCTGCTCC
    ZFP36 2611 CAGGTCCCCAAGTGTGCAAGCTC 2612 CATTAACCCACTCCCCTGACCTCACGCTGGGGCAGGTCCCCA
    AGTGTGCAAGCTCAGTATTCATGATGGTGGGGG
    ZMYND8 2615 CTTTTGCAGGCCAGAATGGAAACC 2616 GGTCTGGGCCAAACTGAAGGGGTTTCCATTCTGGCCTGCAAAA
    GCTCTAAGGGATAAAGACGGGCA
    ZNF3 2619 AGGAGGTTCCACACTCGCCAGTTC 2620 CGAAGGGACTCTGCTCCAGTGAACTGGCGAGTGTGGAACCTC
    CTGACACCTTCTGAGGACCTCCTGC
    ZNF827 2623 CCCGCCTTCAGAGAAGAAACCAGA 2624 TGCCTGAGGACCCTCTACCGCCCCCGCCTTCAGAGAAGAAAC
    CAGAAAAAGTCACTCCGCCACCTC
    ZWINT 2627 ACCAAGGCCCTGACTCAGATGGAG 2628 TAGAGGCCATCAAAATTGGCCTCACCAAGGCCCTGACTCAGAT
    GGAGGAAGCCCAGAGGAAACGGA
  • TABLE B
    microRNA Sequence SEQ ID NO
    hsa-miR-1 UGGAAUGUAAAGAAGUAUGUAU 2629
    hsa-miR-103 GCAGCAUUGUACAGGGCUAUGA 2630
    hsa-miR-106b UAAAGUGCUGACAGUGCAGAU 2631
    hsa-miR-10a UACCCUGUAGAUCCGAAUUUGUG 2632
    hsa-miR-133a UUUGGUCCCCUUCAACCAGCUG 2633
    hsa-miR-141 UAACACUGUCUGGUAAAGAUGG 2634
    hsa-miR-145 GUCCAGUUUUCCCAGGAAUCCCU 2635
    hsa-miR-146b-5p UGAGAACUGAAUUCCAUAGGCU 2636
    hsa-miR-150 UCUCCCAACCCUUGUACCAGUG 2637
    hsa-miR-152 UCAGUGCAUGACAGAACUUGG 2638
    hsa-miR-155 UUAAUGCUAAUCGUGAUAGGGGU 2639
    hsa-miR-182 UUUGGCAAUGGUAGAACUCACACU 2640
    hsa-miR-191 CAACGGAAUCCCAAAAGCAGCUG 2641
    hsa-miR-19b UGUAAACAUCCUCGACUGGAAG 2642
    hsa-miR-200c UAAUACUGCCGGGUAAUGAUGGA 2643
    hsa-miR-205 UCCUUCAUUCCACCGGAGUCUG 2644
    hsa-miR-206 UGGAAUGUAAGGAAGUGUGUGG 2645
    hsa-miR-21 UAGCUUAUCAGACUGAUGUUGA 2646
    hsa-miR-210 CUGUGCGUGUGACAGCGGCUGA 2647
    hsa-miR-22 AAGCUGCCAGUUGAAGAACUGU 2648
    hsa-miR-222 AGCUACAUCUGGCUACUGGGU 2649
    hsa-miR-26a UUCAAGUAAUCCAGGAUAGGCU 2650
    hsa-miR-27a UUCACAGUGGCUAAGUUCCGC 2651
    hsa-miR-27b UUCACAGUGGCUAAGUUCUGC 2652
    hsa-miR-29b UAGCACCAUUUGAAAUCAGUGUU 2653
    hsa-miR-30a CUUUCAGUCGGAUGUUUGCAGC 2654
    hsa-miR-30e-5p CUUUCAGUCGGAUGUUUACAGC 2655
    hsa-miR-31 AGGCAAGAUGCUGGCAUAGCU 2656
    hsa-miR-331 GCCCCUGGGCCUAUCCUAGAA 2657
    hsa-miR-425 AAUGACACGAUCACUCCCGUUGA 2658
    hsa-miR-449a UGGCAGUGUAUUGUUAGCUGGU 2659
    hsa-miR-486-5p UCCUGUACUGAGCUGCCCCGAG 2660
    hsa-miR-92a UAUUGCACUUGUCCCGGCCUGU 2661
    hsa-miR-93 CAAAGUGCUGUUCGUGCAGGUAG 2662
    hsa-miR-99a AACCCGUAGAUCCGAUCUUGUG 2663

Claims (21)

1.-20. (canceled)
21. A method of analyzing expression of RNA transcripts of genes in a patient with prostate cancer, comprising:
measuring a level of an RNA transcript, in a sample from the patient comprising prostate tumor tissue, of a set of genes consisting of: (a) at least one gene selected from the group consisting of genes listed in Table 3A; and (b) at least one gene selected from the group consisting of genes listed in Table 3B; and (c) at least one reference gene.
22. The method of claim 21, wherein the at least one gene selected from the group consisting of genes listed in Table 3A includes at least one of BGN, COL1A1, SFRP4, and TPX2.
23. The method of claim 22, wherein the RNA transcript level of the at least one of BGN, COL1A1, SFRP4, and TPX2 is measured using at least one of the following sets of oligonucleotides:
SEQ ID Nos: 257, 258, and 259 (for BGN);
SEQ ID Nos: 501, 502, and 503 (for COL1A1);
SEQ ID Nos: 2157, 2158, and 2159 (for SFRP4); and
SEQ ID Nos: 2449, 2450, and 2451 (for TPX2).
24. The method of claim 21, wherein the at least one gene selected from the group consisting of genes listed in Table 3B includes at least one of FLNC, GSN, GSTM2, TPM2, AZGP1, KLK2, FAM13C, and SRD5A2.
25. The method of claim 24, wherein the RNA transcript level of the at least one of FLNC, GSN, GSTM2, TPM2, AZGP1, KLK2, FAM13C, and SRD5A2 is measured using at least one of the following sets of oligonucleotides:
SEQ ID Nos: 929, 930, and 931 (for FLNC);
SEQ ID Nos: 1029, 1030, and 1031 (for GSN);
SEQ ID Nos: 1037, 1038, and 1039 (for GSTM2);
SEQ ID Nos: 2441, 2442, and 2443 (for TPM2);
SEQ ID Nos: 225, 226, and 227 (for AZGP1);
SEQ ID Nos: 1361, 1362, and 1363 (for KLK2);
SEQ ID Nos: 857, 858, and 859 (for FAM13C); and
SEQ ID Nos: 2273, 2274, and 2275 (for SRD5A2).
26. The method of claim 21, wherein the at least one gene selected from the group consisting of genes listed in Table 3A includes at least one of BGN, COL1A1, SFRP4, and TPX2; and wherein the at least one gene selected from the group consisting of genes listed in Table 3B includes at least one of FLNC, GSN, GSTM2, TPM2, AZGP1, KLK2, FAM13C, and SRD5A2.
27. The method of claim 26, wherein the RNA transcript level of the at least one of BGN, COL1A1, SFRP4, and TPX2 is measured using at least one of the following sets of oligonucleotides:
SEQ ID Nos: 257, 258, and 259 (for BGN);
SEQ ID Nos: 501, 502, and 503 (for COL1A1);
SEQ ID Nos: 2157, 2158, and 2159 (for SFRP4); and
SEQ ID Nos: 2449, 2450, and 2451 (for TPX2); and
wherein the RNA transcript level of the at least one of FLNC, GSN, GSTM2, TPM2, AZGP1, KLK2, FAM13C, and SRD5A2 is measured using at least one of the following sets of oligonucleotides:
SEQ ID Nos: 929, 930, and 931 (for FLNC);
SEQ ID Nos: 1029, 1030, and 1031 (for GSN);
SEQ ID Nos: 1037, 1038, and 1039 (for GSTM2);
SEQ ID Nos: 2441, 2442, and 2443 (for TPM2);
SEQ ID Nos: 225, 226, and 227 (for AZGP1);
SEQ ID Nos: 1361, 1362, and 1363 (for KLK2);
SEQ ID Nos: 857, 858, and 859 (for FAM13C); and
SEQ ID Nos: 2273, 2274, and 2275 (for SRD5A2).
28. The method of claim 21, wherein the at least one gene selected from the group consisting of genes listed in Table 3A includes each of BGN, COL1A1, SFRP4, and TPX2.
29. The method of claim 21, wherein the at least one gene selected from the group consisting of genes listed in Table 3B includes each of FLNC, GSN, GSTM2, TPM2, AZGP1, KLK2, FAM13C, and SRD5A2.
30. The method of claim 21, wherein the at least one gene selected from the group consisting of genes listed in Table 3A includes each of BGN, COL1A1, SFRP4, and TPX2; and wherein the at least one gene selected from the group consisting of genes listed in Table 3B includes each of FLNC, GSN, GSTM2, TPM2, AZGP1, KLK2, FAM13C, and SRD5A2.
31. The method of claim 21, wherein the at least one reference gene is a gene that does not exhibit a significantly different RNA expression level in cancerous prostate tissue compared to non-cancerous prostate tissue.
32. The method of claim 21, wherein the at least one reference gene consists of from 1 to 6 reference genes.
33. The method of claim 21, wherein the at least one reference gene comprises one or more of AAMP, ARF1, ATP5E, CLTC, EEF1A1, GPS1, GPX1, and PGK1.
34. The method of claim 21, wherein the biological sample has a positive TMPRSS2 fusion status.
35. The method of claim 21, wherein the biological sample has a negative TMPRSS2 fusion status.
36. The method of claim 21, wherein the patient has early-stage prostate cancer.
37. The method of claim 21, wherein the biological sample comprises prostate tumor tissue with the primary Gleason pattern for said prostate tumor.
38. The method of claim 21, wherein the biological samples comprises prostate tumor tissue with the highest Gleason pattern for said prostate tumor.
39. The method of claim 21, wherein the tissue sample comprises non-tumor prostate tissue.
40. The method of claim 21, wherein the patient is receiving active surveillance treatment.
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US20250129432A1 (en) 2025-04-24
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