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WO2006091969A2 - Prediction de la chimiosensibilite a des agents cytotoxiques - Google Patents

Prediction de la chimiosensibilite a des agents cytotoxiques Download PDF

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Publication number
WO2006091969A2
WO2006091969A2 PCT/US2006/007045 US2006007045W WO2006091969A2 WO 2006091969 A2 WO2006091969 A2 WO 2006091969A2 US 2006007045 W US2006007045 W US 2006007045W WO 2006091969 A2 WO2006091969 A2 WO 2006091969A2
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genes
chemosensitivity
gene
polynucleotide probes
array
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WO2006091969A3 (fr
Inventor
Wolfgang Sadee
Ying Huang
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Ohio State University Research Foundation
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Ohio State University Research Foundation
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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
    • 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
    • C12Q1/6813—Hybridisation assays
    • C12Q1/6834—Enzymatic or biochemical coupling of nucleic acids to a solid phase
    • C12Q1/6837—Enzymatic or biochemical coupling of nucleic acids to a solid phase using probe arrays or probe chips
    • 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
    • C12Q2600/136—Screening for pharmacological compounds
    • 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
    • C12Q2600/142—Toxicological screening, e.g. expression profiles which identify toxicity

Definitions

  • the present invention provides methods for detecting the chemosensitivity gene expression profile for a cancer cell.
  • the chemosensitivity gene expression profile reflects the expression levels of a plurality of target polynucleotides in a sample, wherein the target polynucleotides encode gene products that are markers for cancer cell chemosensitivity.
  • the method comprises contacting a polynucleotide sample obtained from cells of the specific cancer of interest to polynucleotide probes to detect and measure the amount of target polynucleotides in the sample.
  • the measured levels of expression of target polynucleotides provides an expression profile for the cancer cells that is compared to the drug- gene correlations described in the appendices hereto.
  • the chemo sensitivity expression profile can be used, for example: (a) in the prediction of the chemosensitivity of a particular cancer cell or cell type to a therapeutic agent; (b) in the choice of drug therapy for a patient in need of the same; (c) in the identification of targets for altering the chemosensitivity of a cancer; and (d) in the identification of novel agents for modulating the chemosensitivity of a cancer.
  • the present invention provides new methods for identifying and characterizing new agents that modulate the chemosensitivity of a cancer by altering the expression of one or more growth factor signaling genes, which are markers for cancer cell chemosensitivity.
  • the method comprises treating a sample of cells from the cancer with a test agent, obtaining polynucleotide samples from untreated cancer cells and the treated cancer cells, and contacting the polynucleotide samples to polynucleotide probes to detect and measure the amount of target polynucleotides in the sample and thereby obtain an expression profile of genes, such as genes that are involved in growth factor signaling, which are markers for chemosensitivity.
  • the method further comprises comparing the growth factor signaling gene expression profiles of the control and treated cells to determine whether the agent altered the expression of any of the genes correlated with chemosensitivity or chemoresistance to various drugs.
  • Figure 1 shows a hierarchical cluster analysis of 69 negatively correlated genes against the 119 anticancer drugs using gene-drug Pearson correlation coefficients. Genes and drugs cluster into two main groups, while drugs further cluster into subgroups according to their mechanisms of reaction.
  • Figure 2 shows gene-drug correlation profiles for EGFR (panel A) and ERBB2 (panel b) with 119 anticancer drugs. Pearson correlation coefficients against 119 drugs are sorted for EGFR, while the order of drugs is maintained for ERBB.
  • Figure 3 shows the relative mRNA (panel A, Iog2 transformed from the 70-mer microarray hybridization) and protein level (panel B) of EGFR and ERBB 2 in cell lines SK-OV-
  • Figure 4 shows the drug combination indexes with respect to fraction affected (Fa) for the combination of EGFR inhibitor AG1478 with camptothecin 10-OH (Panel A), and AG1478 with paclitaxel (Panel B).
  • the combination index of AG1478/camptothecin 10-OH is ⁇ 1, an indication of synergism, while that of AG1478/paclitaxel is >1, indicative of antagonism.
  • Figure 5 shows the genes negatively and negatively correlated with drug response. Only genes correlated with at least 5 drugs with P ⁇ 0.001 are included. For all genes with at least 1 drug at P ⁇ 0.001, see Supplemental Table 3 and 4.
  • Figure 6 shows the drug combination effects between AG1478 or AG825 and paclitaxel, cisplatin, or CPT, 10-OH, using the combination index (see Figure 4).
  • Figure 7 shows the genes occurring in predictive models more often than expected by chance, sorted by number of drugs.
  • Figure 8 is a comparison of prediction accuracy for select drugs, between a heuristic approach with all relevant genes (69, 49, and 343), and using only a short list of genes (top 12, 9, and 13) showing high frequencies as predictors (Figure 7). In the latter case all possible combinations were tested and the highest scoring set selected. A complete list of the 68 drugs tested is available in Figure 20.
  • Figure 9 is an example of a compound (mitomycin) with bimodal distribution of growth inhibition (-log(GI 5 o)).
  • Figure 10 shows a hierarchical cluster analysis of the NCI-60 cell-cell correlations. The analysis was based on gene expression of 107 probes representing genes that are differentially
  • BR breast cancer
  • CNS CNS cancer
  • CO colon cancer
  • LC lung cancer
  • LE leukemia
  • ME melanoma
  • OV ovarian cancer
  • PR prostate cancer
  • RE renal cancer.
  • Figure 11 shows a hierarchical cluster analysis of gene-cell correlations using expression of 69 genes that are negatively correlated with at least one drug with P ⁇ 0.001.
  • EGFR expression from 2 independent experiments were included (EGFR and EGFR_1), showing close proximity in the cluster.
  • Cell lines tend to cluster together according to tissue of origin, such as leukemia, colon cancer, melanoma, and renal cell carcinoma, which is consistent with Figure 1.
  • Figure 12 shows a hierarchical cluster analysis of gene-gene correlations using the expression for 69 genes with negative correlations as distance measures.
  • the two major gene clusters are similar to the two main groups in Figure 2, based on cell-gene expression correlation.
  • Figure 13 shows a hierarchical cluster analysis of gene-gene correlation for 69 genes negatively correlated with at least one drug, using gene-drug correlation coefficients as distance measures.
  • the two major cluster patterns are nearly identical to the pattern in Figure 3 based on 2006/007045
  • Figure 14 shows 343 genes for which probes were included in the 70-mer oligonucleotide microarray.
  • Figure 15 shows the number of genes (out of 343 genes) negatively or positively correlated with at least 4, 2, or 1 drug(s) out of 119 drugs (using bootstrap P ⁇ 0.001 and Pearson correlation coefficient > 0.4 as the cutoffs).
  • Figure 16 shows the genes with predominantly negative correlations to drug response. Only three genes showed also positive correlations.
  • Figure 17 shows the genes with predominantly positive correlations with drug response.
  • Figure 18 shows prediction accuracy for 68 drugs using positively correlated or negatively correlated or all the 343 genes. Note the very low and variable accuracy for some drugs in all three groups, reflecting the heuristic nature of the selection algorithm.
  • Figure 19 shows predictive genes sorted by number of affected drugs where the gene is present in the optimized gene panel. Each included gene has at least one drug correlation at P ⁇ 0.001 for both positively and negatively correlated genes.
  • Figure 20 shows a comparison of prediction accuracy for select drugs, between a heuristic approach with all relevant genes (69, 49, and 343), and using only a short list of genes (top 12, 9, and 13) showing high frequencies as predictors (see Figures 7 and 8). In the latter case all possible combinations were tested and the highest scoring set selected.
  • Figure 21 shows prediction accuracy and predictive gene sets using only genes occurring in the predictive models for drugs more than by chance listed in Figure 7. Note the small US2006/007045
  • “Chemosensitivity” refers to the propensity of a cell to be affected by a cytotoxic agent, wherein a cell may range from sensitive to resistant to such an agent.
  • the expression of a chemosensitivity gene can be a marker for or indicator of chemosensitivity.
  • “Chemosensitivity gene” refers to a gene whose protein product influences the chemosensitivity of a cell to one or more cytotoxic agents. According to the instant invention, 2006/007045
  • chemosensitivity genes may themselves render cells more sensitive or more resistant to the effects of one or more cytotoxic agents, or may be associated with other factors that directly influence chemosensitivity.
  • chemosensitivity genes may or may not directly participate in rendering a cell sensitive or resistant to a drug, but expression of such genes may be related to the expression of other factors which may influence chemosensitivity.
  • Expression of a chemosensitivity gene can be correlated with the sensitivity of a cell or cell type to an agent, wherein a negative correlation may indicate that the gene affects cellular resistance to the drug, and a positive correlation may indicate that the gene affects cellular sensitivity to a drug.
  • chemosensitivity genes have been identified among known and putative growth factor signaling genes. The appendices hereto list the accession numbers for the known genes, whereby the full sequences of the genes may be referenced, and which are expressly incorporated herein by reference thereto as of the filing of this application for patent.
  • Array or “microarray” refers to an arrangement of hybridizable array elements, such as polynucleotides, which in some embodiments may be on a substrate.
  • the arrangement of polynucleotides may be ordered.
  • the array elements are arranged so that there are at least ten or more different array elements, and in other embodiments at least 100 or more array elements.
  • the hybridization signal from each of the array elements may be individually distinguishable.
  • the array elements comprise nucleic acid molecules.
  • the array comprises probes to tow or more chemosensitivity genes, and in other embodiments the array comprises probes to 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250 or more chemosensitivity genes. In some embodiments, the array comprises probes to genes that encode products other than chemosensitivity proteins. In some embodiments, the array comprises probes to 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or more genes that encode products other than chemosensitivity proteins.
  • Gene when used herein, broadly refers to any region or segment of DNA associated with a biological molecule or function. Thus, genes include coding sequence, and may further include regulatory regions or segments required for their expression. Genes may also include non-expressed DNA segments that, for example, form recognition sequences for other proteins. Genes can be obtained from a variety of sources, including cloning from a source of interest or synthesizing from known or predicted sequence information, and may include sequences encoding desired parameters. "Hybridization complex” refers to a complex between two nucleic acid molecules by virtue of the formation of hydrogen bonds between purines and pyrimidines.
  • nucleic acid or polypeptide sequences refer to two or more sequences or subsequences that may be the same or have a specified percentage of amino acid residues or nucleotides that are the same, when compared and aligned for maximum correspondence.
  • sequence comparison typically one sequence acts as a reference sequence to which test sequences are compared.
  • sequence comparison algorithm test and reference sequences are input into a computer, subsequence coordinates are designated, if necessary, and sequence algorithm program parameters are designated. The sequence comparison algorithm then calculates the percent sequence identity for the test sequence(s) relative to the reference sequence, based on the designated program parameters.
  • isolated when used herein in the context of a nucleic acid or protein, denotes that the nucleic acid or protein is essentially free of other cellular components with that it is associated in the natural state. It is preferably in a homogeneous state although it can be in either a dry or aqueous solution. Purity and homogeneity are typically determined using analytical chemistry techniques such as polyacrylamide gel electrophoresis or high performance liquid chromatography. A protein that is the predominant molecular species present in a preparation is substantially purified. An isolated gene is separated from open reading frames that flank the gene and encode a protein other than the gene of interest.
  • Marker as used herein in reference to a chemosensitivity gene, means an indicator of chemosensitivity.
  • a marker may either directly or indirectly influence the chemosensitivity of a cell to a cytotoxic agent, or it may be associated with other factors that influence chemosensitivity.
  • Naturally-occurring and wild-type are used herein to describe something that can be found in nature as distinct from being artificially produced by man.
  • a polypeptide or polynucleotide sequence that is present in an organism (including viruses) that can be isolated from a source in nature and that has not been intentionally modified by man in the laboratory is naturally-occurring.
  • wild-type is used herein to refer to the naturally-occurring or native forms of growth factor signaling proteins and their encoding nucleic acid sequences. Therefore, in the context of this application, 'wild-type' includes naturally occurring variant forms for growth factor signaling genes, either representing splice variants or genetic variants between individuals, which may require different probes for selective detection.
  • Nucleic acid when used herein, refers to deoxyribonucleotides or ribonucleotides, nucleotides, oligonucleotides, polynucleotide polymers and fragments thereof in either single- or double-stranded form.
  • a nucleic acid may be of natural or synthetic origin, double-stranded or single-stranded, and separate from or combined with carbohydrate, lipids, protein, other nucleic acids, or other materials, and may perform a particular activity such as transformation or form a useful composition such as a peptide nucleic acid (PNA).
  • PNA peptide nucleic acid
  • nucleic acids containing known analogues of natural nucleotides that have similar binding properties as the reference nucleic acid and may be metabolized in a manner similar to naturally-occurring nucleotides.
  • a particular nucleic acid sequence also implicitly encompasses conservatively modified variants thereof (e.g. degenerate codon substitutions) and complementary sequences and as well as the sequence explicitly indicated.
  • degenerate codon substitutions may be achieved by generating sequences in which the third position of one or more selected (or all) codons is substituted with mixed-base and/or deoxyinosine residues (Batzer et al. (1991) Nucleic Acid Res.
  • nucleic acid is used interchangeably with gene, cDNA, and niRNA encoded by a gene.
  • An "oligonucleotide” or “oligo” is a nucleic acid and is substantially equivalent to the terms amplimer, primer, oligomer, element, target, and probe, and may be either double or single stranded.
  • Polynucleotide refers to nucleic acid having a length from 25 to 3,500 nucleotides.
  • Probe or “Polynucleotide Probe” refers to a nucleic acid capable of hybridizing under stringent conditions with a target region of a target sequence to form a polynucleotide probe/target complex. Probes comprise polynucleotides that are 15 consecutive nucleotides in length. Probes maybe 15, 16, 17, 18 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
  • probes are 70 nucleotides in length. Probes may be less than 100% complimentary to a target region, and may comprise sequence alterations in the form of one or more deletions, insertions, or substitutions, as compared to probes that are 100% complementary to a target region.
  • nucleic acid or protein when used herein in the context of nucleic acids or proteins, denotes that a nucleic acid or protein gives rise to essentially one band in an electrophoretic gel. Particularly, it means that the nucleic acid or protein is at least 50, 55, 60, 65, 70, 75, 80, 85, 90, 91, 92, 93, 94,
  • sample refers to an isolated sample of material, such as material obtained from an organism, containing nucleic acid molecules.
  • a sample may comprise a bodily fluid; a cell; an extract from a cell, chromosome, organelle, or membrane isolated from a cell; genomic DNA, RNA, or cDNA in solution or bound to a substrate; or a biological tissue or biopsy thereof.
  • a sample may be obtained from any bodily fluid (blood, urine, saliva, phlegm, gastric juices, etc.), cultured cells, biopsies, or other tissue preparations.
  • “Stringent hybridization conditions” and “stringent hybridization wash conditions” in the context of nucleic acid hybridization experiments such as Southern and northern hybridizations are sequence dependent, and are different under different environmental parameters.
  • nucleic acids having longer sequences hybridize specifically at higher temperatures.
  • An extensive guide to the hybridization of nucleic acids is found in Tijssen (1993) Laboratory Techniques in Biochemistry and Molecular Biology — Hybridization with Nucleic Acid Probes part I chapter 2 "Overview of principles of hybridization and the strategy of nucleic acid probe assays," Elsevier, N. Y.
  • highly stringent hybridization and wash conditions are selected to be 5 0 C. lower than the thermal melting point (T m ) for the specific sequence at a defined ionic strength and pH.
  • T m thermal melting point
  • a probe will hybridize to its target subsequence, but to no other sequences.
  • the T m is the temperature (under defined ionic strength and pH) at which 50% of the target sequence hybridizes to a perfectly matched probe.
  • Very stringent conditions are selected to be equal to the T m for a particular probe.
  • An example of stringent hybridization conditions for hybridization of complementary nucleic acids that have more than 100 complementary residues on a filter in a Southern or northern blot is 50% formamide with 1 mg of heparin at 42 °C, with the hybridization being carried out overnight.
  • An example of highly stringent wash conditions is 0.15 M NaCl at 72 °C for 15 minutes.
  • An example of stringent wash conditions is a 0.2x SSC wash at 65 °C for 15 minutes ⁇ see, Sambrook, infra., for a description of SSC buffer).
  • a high stringency wash is preceded by a low stringency wash to remove background probe signal.
  • An example medium stringency wash for a duplex of, e.g., more than 100 nucleotides, is Ix SSC at 45 0 C for 15 minutes.
  • An example low stringency wash for a duplex of, e.g., more than 100 nucleotides is 4-6x SSC at 40 °C for 15 minutes.
  • stringent conditions typically involve salt concentrations of less than 1.0 M Na ion, typically 0.01 to 1.0 M Na ion concentration (or other salts) at pH 7.0 to 8.3, and the temperature is typically at least 30 0 C.
  • Stringent conditions can also be achieved with the addition of destabilizing agents such as formamide.
  • destabilizing agents such as formamide.
  • a signal to noise ratio of 2x (or higher) than that observed for an unrelated probe in the particular hybridization assay indicates detection of a specific hybridization.
  • Nucleic acids that do not hybridize to each other under stringent conditions are still substantially similar if the polypeptides that they encode are substantially similar. This occurs, e.g., when a copy of a nucleic acid is created using the maximum codon degeneracy permitted by the genetic code.
  • Substrate refers to a support, such as a rigid or semi-rigid support, to which nucleic acid molecules or proteins are applied or bound, and includes membranes, filters, chips, slides, wafers, fibers, magnetic or nonmagnetic beads, gels, capillaries or other tubing, plates, polymers, and microparticles, and other types of supports, which may have a variety of surface forms including wells, trenches, pins, channels and pores.
  • Target polynucleotide refers to a nucleic acid to which a polynucleotide probe can hybridize by base pairing and that comprises all or a fragment of a gene that encodes a protein that is a marker for chemosensitivity in cancer cells.
  • the sequences of target and probes may be 100% complementary (no mismatches) when aligned. In other instances, there may be up to a 10% mismatch.
  • Target polynucleotides represent a subset of all of the polynucleotides in a sample that encode the expression products of all transcribed and expressed genes in the cell or tissue from which the polynucleotide sample is prepared.
  • the gene products of target polynucleotides are markers for chemosensitivity of cancer cells; some may directly influence chemosensitivity through involvement in growth factor signaling. Alternatively, they may direct or influence cancer cell characteristics that indirectly confer or influence sensitivity or resistance.
  • Target Region means a stretch of consecutive nucleotides comprising all or a portion of a target sequence such as a gene or an oligonucleotide encoding a protein that is a marker for chemosensitivity.
  • Target regions may be 15, 16, 17, 18 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 5,6, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 200 or more
  • Polynucleotide Probes can be genomic DNA or cDNA or mRNA, or any RNA-like or DNA-like material, such as peptide nucleic acids, branched DNAs and the like.
  • the polynucleotide probes can be sense or antisense polynucleotide probes. Where target polynucleotides are double stranded, the probes may be either sense or antisense strands. Where the target polynucleotides are single stranded, the nucleotide probes are complementary single strands.
  • the polynucleotide probes can be prepared by a variety of synthetic or enzymatic schemes that are well known in the art.
  • the probes can be synthesized, in whole or in part, using chemical methods well known in the art Caruthers et al. (1980) Nucleic Acids Res. Symp. Ser. 215-233). Alternatively, the probes can be generated, in whole or in part, enzymatically.
  • Nucleotide analogues can be incorporated into the polynucleotide probes by methods well known in the art. The only requirement is that the incorporated nucleotide analogues must serve to base pair with target polynucleotide sequences.
  • certain guanine nucleotides can be substituted with hypoxanthine that base pairs with cytosine residues. However, these base pairs are less stable than those between guanine and cytosine.
  • adenine nucleotides can be substituted with 2,6-diaminopurine that can form stronger base pairs than those between adenine and thymidine.
  • the polynucleotide probes can include nucleotides that have been derivatized chemically or enzymatically. Typical chemical modifications include derivatization with acyl, alkyl, aryl or amino groups.
  • the polynucleotide probes may be labeled with one or more labeling moieties to allow for detection of hybridized probe/target polynucleotide complexes.
  • the labeling moieties can include compositions that can be detected by spectroscopic, photochemical, biochemical, bioelectronic, immunochemical, electrical, optical or chemical means.
  • the labeling moieties include radioisotopes, such as P 32 , P 33 or S 35 , chemiluminescent compounds, labeled binding proteins, heavy metal atoms, spectroscopic markers, such as fluorescent markers and dyes, magnetic labels, linked enzymes, mass spectrometry tags, spin labels, electron transfer donors and acceptors, and the like.
  • the polynucleotide probes can be immobilized on a substrate.
  • Preferred substrates are any suitable rigid or semi-rigid support, including membranes, filters, chips, slides, wafers, fibers, magnetic or nonmagnetic beads, gels, tubing, plates, polymers, microparticles and capillaries.
  • the substrate can have a variety of surface forms, such as wells, trenches, pins, channels and pores, to which the polynucleotide probes are bound.
  • the substrates are optically transparent.
  • a sample containing polynucleotides that will be assessed for the presence of target polynucleotides are obtained.
  • the samples can be any sample containing target polynucleotides and obtained from any bodily fluid (blood, urine, saliva, phlegm, gastric juices, etc.), cultured cells, biopsies, or other tissue preparations.
  • DNA or RNA can be isolated from the sample according to any of a number of methods well known to those of skill in the art. For example, methods of purification of nucleic acids are described in Tijssen (1993) Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part I.
  • RNA is isolated using the TRIZOL reagent (Life Technologies, Gaithersburg Md.), and niRNA is isolated using oligo d(T) column chromatography or glass beads.
  • the polynucleotides can be a cDNA reverse transcribed from an mRNA, an RNA transcribed from that cDNA, a DNA amplified from that cDNA, an RNA transcribed from the amplified DNA, and the like.
  • the polynucleotide is derived from DNA
  • the polynucleotide can be DNA amplified from DNA or RNA reverse transcribed from DNA.
  • Suitable methods for measuring the relative amounts of the target polynucleotide transcripts in samples of polynucleotides are Northern blots, RT-PCR, or real-time PCR, or RNase protection assays. Fore ease in measuring the transcripts for target polynucleotides, it is preferred that arrays as described above be used.
  • the target polynucleotides may be labeled with one or more labeling moieties to allow for detection of hybridized probe/target polynucleotide complexes.
  • the labeling moieties can include compositions that can be detected by spectroscopic, photochemical, biochemical, bioelectronic, immunochemical, electrical, optical or chemical means.
  • the labeling moieties include radioisotopes, such as P 32 , P 33 or S 35 , chemiluminescent compounds, labeled binding proteins, heavy metal atoms, spectroscopic markers, such as fluorescent markers and dyes, magnetic labels, linked enzymes, mass spectrometry tags, spin labels, electron transfer donors and acceptors, and the like.
  • Hybridization complexes Hybridization causes a denatured polynucleotide probe and a denatured complementary target polynucleotide to form a stable duplex through base pairing.
  • Hybridization methods are well known to those skilled in the art (See, e.g., Ausubel (1997; Short Protocols in Molecular Biology, John Wiley & Sons, New YorkN.Y., units 2.8-2.11, 3.18-3.19 and 4-6-4.9).
  • Conditions can be selected for hybridization where exactly complementary target and polynucleotide probe can hybridize, i.e., each base pair must interact with its complementary base pair.
  • conditions can be selected where target and polynucleotide probes have mismatches but are still able to hybridize. Suitable conditions can be selected, for example, by varying the concentrations of salt in the prehybridization, hybridization and wash solutions, or by varying the hybridization and wash temperatures. With some membranes, the temperature can be decreased by adding formamide to the prehybridization and hybridization solutions.
  • Hybridization conditions are based on the melting temperature (T m ) the nucleic acid binding complex or probe, as described in Berger and Kimmel (1987) Guide to Molecular Cloning Techniques, Methods in Enzymology, vol 152, Academic Press.
  • T m melting temperature
  • stringent conditions is the “stringency” that occurs within a range from Tm-5 (5° below the melting temperature of the probe) to 20° C below Tm.
  • highly stringent employ at least 0.2 x SSC buffer and at least 65° C.
  • stringency conditions can be attained by varying a number of factors such as the length and nature, i.e., DNA or RNA 5 of the probe; the length and nature of the target sequence, the concentration of the salts and other components, such as formamide, dextran sulfate, and polyethylene glycol, of the hybridization solution. All of these factors may be varied to generate conditions of stringency that are equivalent to the conditions listed above.
  • Hybridization can be performed at low stringency with buffers, such as 6. times. S SPE with 0.005% Triton X-100 at 37.degree. C, which permits hybridization between target and polynucleotide probes that contain some mismatches to form target polynucleotide/probe complexes. Subsequent washes are performed at higher stringency with buffers, such as 0.5.times.SSPE with 0.005% Triton X-100 at 50.degree. C, to retain hybridization of only those target/probe complexes that contain exactly complementary sequences. Alternatively, hybridization can be performed with buffers, such as 5.times.SSC/0.2% SDS at ⁇ O.degree. C.
  • nucleic acid sequences can be used in the construction of arrays, for example, microarrays. Methods for construction of microarrays, and the use of such microarrays, are known in the art, examples of which can be found in U.S. Patent Nos. 5,445,934, 5,744,305, 5,700,637, and 5,945,334, the entire disclosure of each of which is hereby incorporated by reference.
  • Microarrays can be arrays of nucleic acid probes, arrays of peptide or oligopeptide probes, or arrays of chimeric probes — peptide nucleic acid (PNA) probes.
  • PNA peptide nucleic acid
  • the in situ synthesized oligonucleotide Affymetrix GeneChip system is widely used in many research applications with rigorous quality control standards. (Rouse R. and Hardiman G., "Microarray technology - an intellectual property retrospective," Pharmacogenomics 5:623-632 (2003).).
  • the Affymetrix GeneChip uses eleven 25- oligomer probe pair sets containing both a perfect match and a single nucleotide mismatch for each gene sequence to be identified on the array.
  • highly dense glass oligo probe array sets (>1, 000,000 25- oligomer probes) can be constructed in a ⁇ 3 x 3 -cm plastic cartridge that serves as the hybridization chamber.
  • the ribonucleic acid to be hybridized is isolated, amplified, fragmented, labeled with a fluorescent reporter group, and stained with fluorescent dye after incubation. Light is emitted from the fluorescent reporter group only when it is bound to the probe.
  • the intensity of the light emitted from the perfect match oligoprobe, as compared to the single base pair mismatched oligoprobe, is detected in a scanner, which in turn is analyzed by bioinformatics software (http://www.affymetrix.com).
  • bioinformatics software http://www.affymetrix.com.
  • the GeneChip system provides a standard platform for array fabrication and data analysis, which permits data comparisons among different experiments and laboratories.
  • Microarrays according to the invention can be used for a variety of purposes, as further described herein, including but not limited to, screening for the resistance or susceptibility of a cancer to a drug based on the genetic expression profile of the cancer.
  • the present invention provides a chemosensitivity gene expression analysis system comprising a plurality of polynucleotide probes, wherein each of said polynucleotide probes comprises a nucleic acid sequence that is complimentary under strict hybridization conditions to at least a portion of a gene that encodes a protein that is a marker for the sensitivity of cancer cells to cytotoxic agents, as presented in the appendices hereto.
  • polynucleotides probes are provided on an array.
  • the array elements are organized in an ordered fashion so that each element is present at a specified location on the substrate. Because the array elements are at specified locations on the substrate, the hybridization patterns and intensities (which together create a unique expression profile) can be interpreted in terms of expression levels of particular genes and can be correlated with a particular disease or condition or treatment.
  • the gene expression analysis system in some embodiments in the form of an array, can be used for gene expression analysis of target polynucleotides that represent the expression products of cells of interest, particularly cancer cells.
  • the array can also be used in the prediction of the responsiveness of a patient to a therapeutic agent, such as the response of a cancer patient to a chemotherapeutic agent. Further, as described below, the array can be employed to investigate the profile of a cancer cell in terms of its likely sensitivity or resistance to chemotherapeutic agents. Furthermore, as described below, the array can be employed to characterize a therapeutic agent's chemosensitivity profile for use in treating various cancers.
  • the array can also be used to identify new agents, as described below, which can modulate the chemosensitivity of a cancer cell to one or more therapeutic agents by altering the expression of genes that are markers for and influence chemosensitivity.
  • the gene expression analysis system can be used to purify a subpopulation of mRNAs, cDNAs, genomic fragments and the like, in a sample.
  • samples will include target polynucleotides and other non-target nucleic acids that may undesirably affect the hybridization background. Therefore, it may be advantageous to remove these non-target nucleic acids from the sample.
  • One method for removing the non-target nucleic acids is by contacting the polynucleotide sample with the array, hybridizing the target polynucleotides contained therein with immobilized polynucleotide probes under hybridizing conditions.
  • the non-target nucleic acids that do not hybridize to the polynucleotide probes are then washed away, and thereafter, the immobilized target polynucleotide probes can be released in the form of purified target polynucleotides.
  • Examples of the types of molecules that may be used as probes are cDNA molecules, oligonucleotides that contain 15, 16, 17, 18 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 5,6, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 61, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 or more nucleotides, and other gene probes that comprise nucleobases including synthetic gene probes such as, for example, peptide nucleic acids
  • At least some of said polynucleotide probes comprise a polynucleotide sequence that is complementary to a target region of a gene that encodes a protein associated with growth factor signaling and that is a marker for the sensitivity or resistance of cancer cells to cytotoxic agents.
  • the plurality of polynucleotide probes comprises at least two or more probes, each of which comprises a polynucleotide sequence that is complementary to a target region of a chemosensitivity gene as described in the appendices hereto.
  • the present invention provides a physical embodiment of the expression profile for a cancer cell of proteins that are involved in growth factor signaling and that are markers for the sensitivity of cancer cells to cytotoxic agents.
  • the expression profile comprises the polynucleotide probes of the invention.
  • the expression profile also includes a plurality of detectable complexes, in some embodiments in the form of a gene expression analysis system, and in some embodiments in the form of an array.
  • Each complex is formed by hybridization of one or more polynucleotide probes to one or more complementary target polynucleotides in a sample.
  • the polynucleotide probes are hybridized to a complementary target polynucleotide forming target/probe complexes.
  • a complex is detected by incorporating at least one labeling moiety in the complex. Labeling moieties are described herein and are well known in the art.
  • the chemosensitivity expression profile comprises a printed report that shows the expression of the analysis of an array.
  • the printed report may be in the form of a developed or digital film of the hybridized and developed gene expression analysis system.
  • the printed report may also be a manually or computer generated numerical analysis of the developed gene expression analysis system.
  • the printed report may optionally contain gene- drug correlation information.
  • the expression profiles provide "snapshots" that can show unique expression patterns that are characteristic of susceptibility or resistance of a cell to one or more cytotoxic chemotherapeutic agents.
  • the chemosensitivity expression profile can be used, as further described below: (a) in the prediction of the chemosensitivity of a particular cancer cell or cell type to a therapeutic agent; (b) in the choice of drug therapy for a patient in need of the same; (c) in the identification of targets for altering the chemosensitivity of a cancer; and (d) in the identification of novel agents for modulating the chemosensitivity of a cancer.
  • the present invention provides a method of predicting the response of a specific cancer, and more particularly a cancer in a patient, to treatment with a therapeutic agent.
  • the method comprises contacting a polynucleotide sample obtained from the cells of the specific cancer to polynucleotide probes to measure the levels of expression of one or, in some embodiments, a plurality of target polynucleotides.
  • the expression levels of the target polynucleotides are then used to provide an expression profile for the cancer cells that is then compared to the drug-gene correlations described in the appendices hereto, wherein a positive correlation between a drug and a gene expressed in the cancer cells indicates that the cancer cells would be sensitive to the drug, and wherein a negative correlation between a drug and a gene expressed in the cancer cells indicates that the cancer cells would be resistant to the drug.
  • Methods of Identifying New Therapeutic Agents The present invention provides novel methods for identifying and characterizing new agents that modulate the chemosensitivity of a cancer by altering the expression of one or more growth factor signaling genes.
  • the method comprises treating a sample of cells from the cancer with an agent, and thereafter determining any change in expression of genes, such as growth factor signaling genes, which are markers for chemosensitivity. This is done by obtaining polynucleotide samples from untreated cancer cells and the treated cancer cells, and contacting the polynucleotide samples to polynucleotide probes to determine the levels of target polynucleotides to obtain growth factor signaling gene chemosensitivity expression profiles. In some embodiments, the measurement is made using an array or micro array as described above that comprises one or more probes. The method further comprises comparing the growth factor signaling gene expression profiles of the control and treated cells to determine whether the agent alters the expression of any of the chemosensitive or chemoresistant genes.
  • genes such as growth factor signaling genes, which are markers for chemosensitivity. This is done by obtaining polynucleotide samples from untreated cancer cells and the treated cancer cells, and contacting the polynucleotide samples to polynucleotide probe
  • separate cultures of cells are exposed to different dosages of the candidate agent.
  • the effectiveness of the agent's ability to alter chemosensitivity can be tested using standard assays that use, for example, the one or more of the NCI60 cancer cell lines.
  • the agent is tested by conducting assays in that sample cancer cells are co treated with the newly identified agent along with a previously known therapeutic agent.
  • the choice of previously known therapeutic agent is determined based upon the gene-drug correlation between the gene or genes whose expression is affected by the new agent.
  • the present invention further provides novel methods for identifying and characterizing new agents that modulate the chemosensitivity of a cancer by altering the activity of one or more growth factor signaling genes.
  • the method comprises treating a sample of cells from the cancer with an agent, which is capable of inhibiting the activity of a protein implicated in chemosensitivity by correlation analysis between gene expression and drug potency in multiple cancer cell lines.
  • an agent which is capable of inhibiting the activity of a protein implicated in chemosensitivity by correlation analysis between gene expression and drug potency in multiple cancer cell lines.
  • an inhibitor of an efflux pump will increase the potency of an anticancer drug if the efflux pump is highly expressed. This permits one to search either for inhibitors of the chemosensitivity gene or to test whether an anticancer agent is subject to influence by the chemosensitivity gene product.
  • the cell line is a human cell line, such as, for example, any one of the cells from the NCI60 cell lines.
  • RNA is extracted from such cells, converted to cDNA and applied to arrays to that probes have been applied, as described above.
  • Cytotoxic potencies of 119 drugs against 60 neoplastic cell lines were correlated with expression of 343 genes, including 90 growth factors and receptors, 63 metalloproteinases, and 92 ras-like GTPases as downstream signaling factors.
  • Correlating gene expression with drug potency yielded two sets of genes showing either negative or positive drug correlations (P ⁇ 0.001), indicative of a role in chemoresistance and -sensitivity.
  • Known chemoresistance factors showed significant negative correlations with multiple drugs, but several novel candidate genes also scored highly.
  • Negatively correlated genes clustered into two main groups with distinct expression profiles and drug correlations, represented by EGFR and ERBB2 (Her-2/Neu), which displayed distinct drug correlation patterns. Synergism and antagonism between EGFR and ERBB2 inhibitors, in combination with classical anticancer drugs, were not directly related to EGFR and ERBB2 expression in four cells lines tested. Good accuracy in predicting drug potency against the NCI- 60 was attainable with subset of only 13 genes ⁇ RAB5B, TGFBR3, RAB6A, ARF4, ARHC, ERBB3 (negative correlations), and PLCL2, RAN, PLCD4, RAB37, RAC2, RAB39B (positive)). Our approach reveals known and potentially novel biomarkers and drug targets in cancer chemotherapy.
  • Growth factor signaling regulates cell proliferation, differentiation, and apoptosis (5, 9). Amplification, point mutations, or chromosomal translocation can result in uncontrolled activation of growth factor signaling pathways, as exemplified by ERBB2 in breast cancer (10). This has prompted the targeting of growth factor signaling as a therapeutic strategy, including growth factor receptors such as EGFR (11) and ERBB2 (HER-2) (9, 12). Growth factor signaling also conveys chemoresistance against classical anticancer drugs (13), involving suppression of apoptosis (14) and activation of multi-drug resistance genes, such as the drug efflux pump MDRl (15).
  • MDRl multi-drug resistance genes
  • the NCI-60 a set of 60 diverse human cancer cell lines (22) has served in the screening of more than 100,000 candidate drugs.
  • Gene-drug correlations can reveal novel drug targets or mechanisms of chemoresistance (1, 23, 24), while clustering of drug potency against the NCI60 cells can reveal mechanisms of action (25).
  • mRNA expression profiles of subsets of 20-200 genes can serve as predictors of cytotoxic drag potencies (8, 26).
  • the underlying mechanisms remain unclear.
  • With a more focused approach measuring expression of genes involved in transmembrane transport in the NCI-60 we have identified numerous new drug-transporter relationships relevant to drug targeting and potency (28) that can be extrapolated to in vivo studies because causal interactions are implied.
  • Oligonucleotide microarrays 70-mer oligonucleotide probes (total 343 genes) were designed for 90 growth factors and their receptors (e.g., EGF, IGF, FGF, PDGF, VEGF, TGF and 27VF families), 63 metalloproteinases and their inhibitors (20 MMPs, 4 TIMPs, 20 ADAMs and 19 ADAMTSs), and 92 small GTP-binding proteins (GTPases).
  • 98 probes were targeted to GPCRs, heterotrimeric G proteins, phospho lipases, etc ( Figure 14), for comparison.
  • the 70-mer oligonucleotides were designed and synthesized by Operon (Alameda, CA), Qiagen (http ://omad. qiagcn. com/human2/index .php) . Probes for these genes were added to the transporter and channel gene microarray described previously (27, 29) , with 25 genes overlapping with the current study. Each probe was printed 4 times on poly-L-lysine glass slides to permit assessment of intra-assay variability of mRNA measurements. The 25 genes analyzed in duplicate served as quality control, in addition to comparison with cDNA arrays with 144 overlapping genes. 6 007045
  • NCI-60 cancer cell lines purchased from the Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health
  • EGFR inhibitor. AG1478 and ERBB2 inhibitor AG825 were purchased from Calbiochem (San Diego, CA). Cisplatin was obtained from Sigma (St. Louis, MO). Paclitaxel and camptothecin, 10-OH (CPT, 10-OH) were from the Developmental Therapeutics Program at NCI (Bethesda, MD).
  • Clustering of cell lines, genes, and drugs on the basis of gene expression and drug potency profile can be used to group cell lines and genes in terms of their patterns of gene expression (23, 33).
  • To obtain cell-cell cluster trees for 107 genes that showed distinct expression patterns across the 60 cell lines (i.e., genes that passed the filter S.D. > 0.35), we used the programs "Cluster” and "Tree View” (34) with average linkage clustering and a correlation metric.
  • Cells and drugs were also clustered by drug potency profiles (23), and moreover, genes and drugs were classified using correlations between each gene (expression across the NCI-60) and each drug (potency across the NCI-60) as distance measure.
  • Cytotoxicity assay Drug potency was tested using a proliferation assay with sulforhodamine B (SRB)(35). 3000 - 5000 cells per well were seeded in 96-well plates and incubated for 24 hours. Drags were added in a dilution series in 3 replicate wells. After 3 days, incubation was
  • Unbound dye was washed off with 1% acetic acid. After air-drying and re-solubilization of the protein-bound dye in 10 mM Tris-HCl (pH 8.0), absorbance was read in a micro-plate reader at 570 run.
  • combination index a measure of synergism or antagonism between two co-administrated agents.
  • This step differs from the one used in (26) by using information from all cell lines for prediction purposes and by incorporating into the analysis the bimodal behavior of growth inhibition distributions.
  • the final predictor genes are then selected as the smallest set of genes producing a model within 5% from the highest percentage of correct classifications obtained in the stepwise search described above. This reduces the number of predictor genes, by accepting predictor sets within 5% of the optimally observed values, which may lead to more robust predictor sets. This led to a list of genes ranked by frequency of presence in the predictor sets for a subgroup of 68 drugs (pruned from 119 to avoid redundancy between similar drugs).
  • Basal mRNA expression of 343 genes was measured in the NCI-60 panel.
  • Basal mRNA expression of 343 genes was measured in the NCI-60 panel.
  • gene-gene Pearson correlation coefficient ranged from 0.3 to 0.78.
  • expression data were compared to previous results obtained with a cDNA array platform (23).
  • MMP24, ADAM9, and the inhibitor TIMP2 ranked highly, with multiple negative correlations. Furthermore, small GTPases scored strongly, with seven genes showing negative correlations with 10 drugs or more, including ARHC, RRAS2, RAB 5B, and RALB, consistent with their pervasive role in cellular signaling. Among the other signaling factors (98 genes involved in various signaling pathways, such as GPCRs and G protein subunits), considerably fewer genes produced multiple negative correlations (Figure 16), such as GNGlO and GNGIl with 15 and 7 negatively correlated genes, respectively. Of 29 G-protein coupled receptors, only 4 showed strong negative correlation (P ⁇ 0.001) with 1 or 2 out of 119 drugs. This result suggests that these pathways are less germane to chemoresistance.
  • ADAM9 a metalloproteinase mediating release of membrane-tethered growth factors such as HB-EGF
  • EGFR a metalloproteinase mediating release of membrane-tethered growth factors such as HB-EGF
  • EGFR a metalloproteinase mediating release of membrane-tethered growth factors such as HB-EGF
  • EGFR a metalloproteinase mediating release of membrane-tethered growth factors such as HB-EGF
  • GTPase ARHC RhoQ clustered within the same group in all analyses and hence may represent members of a signaling pathway relevant to chemoresistance for a portion of the drug panel.
  • Network analysis indicates that EGFR and ADAM9 are close neighbors (to be published).
  • ERBB2 and RALB clustered together implying a functional relationship.
  • the close receptor homologues, EGFR and ERBB2 presumed to have similar signaling pathways, clustered at some distance
  • EGFR and ERBB2 examples from the two gene groups with distinct drug correlations
  • Figure 3 A shows the mRNA levels of EGFR and ERBB2 in four cancer cells based on our array data, which is consistence with reported protein levels
  • Prediction accuracy ranged mainly from 0.6 - 0.9, usually with 5-10 genes selected as predictors. Using all 343 genes or only the 69 negatively correlated genes yielded similar results in most cases, while only the 49 positively correlated genes tended to score somewhat lower. As not all possible combinations of genes can be tested in our heuristic algorithm with a large number of genes, better scoring gene sets may well exist.
  • the top genes with negative correlations include TGFBR3, RAB6A, RALB, TIMP2, ARHC, RABl 7 and ARF4, while the top positive genes are RAB37, RAC2, PLCL2, PDElB, PLCD4 and ADAM12. It is noted that these genes are not always the highest-ranking genes sorted by number of highly correlated drugs ( Figure 5 and Figures 16 and 17). It remains to be determined which measure is more accurate. Further tests will be needed to determine whether the selected genes are functionally most relevant. To limit the effect of the heuristic approach on the prediction models, we reduced the number of candidate predictor genes to those appearing most frequently in predictive sets of drug potency.
  • Predictive accuracy for only these highest scoring genes is listed in Figure 8 (and Figure 20), with optimal predictions derived from all possible gene combinations for each drug. This improved the prediction accuracy, especially for those drugs with previously low prediction values, resulting from the heuristic approach used to detect predictor genes.
  • Figure 21 shows examples of predictive gene sets for individual compounds. Hence, starting from 343 genes in this study, we have identified a small subset of genes yielding good predictions for a majority drugs. Discussion: We have evaluated the role of three gene families related to growth factor signaling in chemoresistance.
  • CYR61 was included because of its association with breast cancer chemoresistance (47), converging on growth factor signaling through the NF- lcappaB/XIAP pathway (48). Furthermore, vascular endothelial growth factor-165 receptor (VEGFl 65R), showing strong negative drag correlations, had been shown to be involved in tumor angiogenesis, progression, chemoresistance, and poor prognosis (49, 50).
  • VEGFl 65R vascular endothelial growth factor-165 receptor
  • TGFBR3 scored highest as a predictor for chemoresistance. While devoid of
  • TGFBR3 appears to be a necessary component of the TGF ⁇
  • receptor signaling complex 52
  • Additional growth factors implicated by negative correlations include FGF 17, 18, and 19, IGF2, and NRGl. Their relevance to chemoresistance needs to be validated in each case.
  • ADAM9 a disintegrin and metalloproteinase domain 9
  • ADAM9 is highly expressed in hepatocellular carcinoma (53), and in pancreatic ductal adenocarcinomas where cytoplasmic expression is correlated with poor prognosis (54).
  • ADAM9 is part of the signaling cascade evading apoptosis induced by cytotoxic drags (55), possibly by mediating release of heparin- binding EGF-like growth factor (HB-EGF) (56).
  • TC21/RRAS2 mediates transformation of cancer cells involving phosphatidylinositol 3-kinase (PD-K) (59, 60), and is activated by growth factors (61), including FGFl and FGF2 shown to convey chemoresistance (62).
  • PD-K phosphatidylinositol 3-kinase
  • 61 growth factors
  • FGFl and FGF2 shown to convey chemoresistance
  • RALB clusters together with ERRB2 by gene expression and drug potency correlations Lastly, ARHC (RhoC) promotes tumor metastasis (64), and appears to contribute to chemoresistance via growth factor signaling (65).
  • RAB37 shows multiple drug correlations.
  • ARHGDIA encodes a Rho GDP dissociation inhibitor, and is predictive as a chemosensitivity factor for 14 drugs, possibly by regulating Rho activity.
  • IGFALS is an insulin-like growth factor-binding protein (acid labile subunit), which complexes IGF and IGFBP3 into a 150 kD aggregate (see OMM, 601489). This could account for the positive correlation and predictive power for 15 drugs.
  • EGFL4 and L5 encode EGF-like polypeptides containing multiple EGF repeats, and function in cell adhesion, but the physiological role remains uncertain.
  • EGFR and ERBB2 belong to different gene clusters with distinct expression patterns, which indicated that different mechanisms of drug resistance might be involved. This was surprising as EGFR and ERBB2 are coexpressed in some tumors and can heterodimerize (9).
  • AG1478 not only inhibits EGFR, but could also ERBB4 (68), and parallel signaling pathways can bypass the block. Inhibition of growth factor signaling at different junctions might improve anticancer potency, as shown with combined inhibition of both mutated EGFR and
  • ERBB receptors might induce cell death under some circumstances (71, 72).
  • Step A Cytotoxic drug potency in training cell lines.
  • the probability of cell line i to be resistant can be computed by:
  • the class assignment for the test cell lines will be based on the predictive probabilities of class membership (p, 1- p) (3).
  • Step B Ranking genes according to their ability to discriminate between resistant and sensitive cell lines.
  • pi is the previously determined predictive probability of sample i for being in the resistant class
  • Step C Predicting drug resistance in test cell lines.
  • Step D Prediction accuracy.
  • the final set of predictor genes is then selected as the smallest set of genes producing a model with prediction accuracy within 5% from the highest percentage of correct classifications obtained in the stepwise search described above. This reduces the number of predictor genes, by accepting predictor sets within 5% of the optimally observed values, which may lead to more robust predictor sets. In this way we can generate a list of genes ranked by frequency of presence in the predictor sets for a subgroup of 68 drugs (pruned from 119 to avoid redundancy between similar drugs), hi a further iteration, we compared the observed frequencies of presence in the predictor sets (see Figure 19) with the ones one would expect if these models would be random.
  • Average gene expression values for all probes on each array in the dataset were 200.
  • Gene expression levels were also evaluated for the top-scoring 12 negatively and 9 positively correlated genes, and 13 genes selected from all 343 genes ( Figure 7) showing significantly higher frequencies as predictors than expected.

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Abstract

L'invention concerne des systèmes d'analyse d'expression génique permettant d'identifier le profil génique de la chimiosensibilité d'une cellule cancéreuse. Ces systèmes d'analyse comprennent une pluralité de sondes polynucléotidiques, chaque sonde comportant une séquence de polynucléotides complémentaire à une région cible d'un gène qui code une protéine associée au transport de molécules dans et hors des cellules et qui constitue un marqueur de la sensibilité ou de la résistance des cellules cancéreuses à des agents cytotoxiques.
PCT/US2006/007045 2005-02-25 2006-02-27 Prediction de la chimiosensibilite a des agents cytotoxiques Ceased WO2006091969A2 (fr)

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CN113584133A (zh) * 2021-08-30 2021-11-02 中国药科大学 基于颜色编码与可编程性荧光探针的多重靶标原位检测方法

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DAN ET AL. CANER RESEARCH vol. 62, 15 February 2002, pages 1139 - 1140, 1146 *

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CN113584133A (zh) * 2021-08-30 2021-11-02 中国药科大学 基于颜色编码与可编程性荧光探针的多重靶标原位检测方法
CN113584133B (zh) * 2021-08-30 2024-03-26 中国药科大学 基于颜色编码与可编程性荧光探针的多重靶标原位检测方法

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