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WO2008116178A2 - Systèmes et procédés pour le diagnostic et le pronostic du cancer colorectal - Google Patents

Systèmes et procédés pour le diagnostic et le pronostic du cancer colorectal Download PDF

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Publication number
WO2008116178A2
WO2008116178A2 PCT/US2008/057884 US2008057884W WO2008116178A2 WO 2008116178 A2 WO2008116178 A2 WO 2008116178A2 US 2008057884 W US2008057884 W US 2008057884W WO 2008116178 A2 WO2008116178 A2 WO 2008116178A2
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WIPO (PCT)
Prior art keywords
peptide
markers
sample
set forth
amount
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Ceased
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PCT/US2008/057884
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WO2008116178A8 (fr
WO2008116178A3 (fr
Inventor
Robert J. Coffey
Bruce J. Aronow
Jeffrey L. Franklin
Timothy Yeatman
Sanne K. H. Olesen
Gregory Bloom
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Childrens Hospital Research Foundation
H Lee Moffitt Cancer Center and Research Institute Inc
Vanderbilt University
Original Assignee
Childrens Hospital Research Foundation
H Lee Moffitt Cancer Center and Research Institute Inc
Vanderbilt University
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Publication of WO2008116178A2 publication Critical patent/WO2008116178A2/fr
Publication of WO2008116178A3 publication Critical patent/WO2008116178A3/fr
Publication of WO2008116178A8 publication Critical patent/WO2008116178A8/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G01N33/57419—Specifically defined cancers of colon
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/60—Complex ways of combining multiple protein biomarkers for diagnosis

Definitions

  • the presently-disclosed subject matter relates to methods for diagnosis and prognosis of colorectal cancer.
  • the presently-disclosed subject matter relates to diagnostic and prognostic methods based on determining an amount of protein markers in a biological sample from a subject.
  • Colorectal cancer is the second leading cause of cancer-related deaths in the western world, and accounts for about 655,000 deaths/year worldwide. Surveillance by colonoscopy is currently considered to be the most effective screening method for colorectal cancer; however, the process is invasive, unpleasant, and time-consuming.
  • colorectal cancer biomarkers suitable for the early detection and diagnosis of colorectal cancer holds great promise for improving the clinical outcome of subjects, and would allow for more comprehensive population screening because it is less invasive, less expensive, and is less time consuming than methods currently in use.
  • the identification of such biomarkers would be especially important for subjects presented with vague or no symptoms, as well as subjects who have tumors that are relatively inaccessible to physical examination. Despite considerable effort directed at early detection, few reliable and cost- effective screening tests have been developed.
  • biomarkers that individually, or in combination with other biomarkers or diagnostic modalities, could deliver the required sensitivity and specificity for early detection and prognosis of colorectal cancer, as well as quantitative detection following diagnosis and successive stages of therapeutic management.
  • simple tests that can be performed on readily-accessible biological fluids are needed.
  • a method for making a diagnosis of a colorectal cancer in a subject includes: providing a biological sample from the subject; determining an amount in the sample of at least one peptide selected from the peptides set forth in Table A, Table B, and/or Table C; and comparing the amount of the at least one peptide in the sample, if present, to a control level of the at least one peptide, wherein the subject is diagnosed as having colorectal cancer or a risk thereof if there is a measurable difference in the amount of the at least one peptide in the sample as compared to the control level.
  • the method includes determining an amount in the sample of at least two peptides, at least five peptides, or at least ten peptides selected from the peptides set forth in Table A, Table B, and/or Table C.
  • the method includes determining an amount in the sample of at least one peptide selected from the peptides set forth in Table D, Table E, Table F, or Table G.
  • the method includes determining an amount in the sample of at least one peptide selected from the peptides set forth in Table A, and at least one peptide selected from the peptides set forth in Table B. In some embodiments, the method includes determining an amount in the sample of at least one peptide selected from the peptides set forth in Table A, and at least one additional peptide selected from the peptides set forth in Table C. In some embodiments, the method includes determining an amount in the sample of at least one peptide selected from the peptides set forth in Table B, and at least one additional peptide selected from the peptides set forth in Table C.
  • determining the amount in the sample of the at least one peptide is conducted using mass spectrometry (MS) analysis, immunoassay analysis, or both.
  • MS mass spectrometry
  • ELISA enzyme-linked immunosorbent assay
  • the method also includes selecting a treatment or modifying a treatment for the colorectal cancer based on the determined amount of the at least one peptide.
  • a method for making a diagnosis of a colorectal cancer in a subject includes: providing a biological sample from the subject; determining an amount in the sample of at least one peptide marker from at least one group of markers, selected from (i) the group of markers set forth in Tables H and/or I, which are associated with a first type of colorectal cancer; (ii) the group of markers set forth in Tables J and/or K, which are associated with a second type of colorectal cancer; (iii) the group of markers set forth in Tables L and/or M, which are associated with a third type of colorectal cancer; and (iv) the group of markers set forth in Tables N and/or O, which are associated with a fourth type of colorectal cancer; and comparing the amount of the at least one peptide marker in the sample, if present, to a control level of the at least one peptide marker; wherein the subject is diagnosed as having the type of colorectal cancer
  • the method includes determining the amount in the sample of at least one peptide marker from at least two groups of markers. In some embodiments, the method includes determining the amount in the sample of at least one peptide marker from at least three groups of markers. In some embodiments, the method includes determining the amount in the sample of at least one peptide marker from four of the groups of markers.
  • the biological sample includes blood, plasma, or serum.
  • the subject is human.
  • a system for making a diagnosis of a colorectal cancer in a subject includes: probes for selectively binding each of one or more peptide markers, wherein the peptide markers are selected from the peptides set forth in Table A, Table B, and/or Table C; and means for detecting the binding of said probes to said one or more peptide markers.
  • the system includes at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table A, and at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table B.
  • the system includes at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table B, and at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table C. In some embodiments, the system includes at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table A, and at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table C.
  • the system includes at least one probe for selectively binding each of one or more peptide markers selected from the peptides set forth in Table D, Table E, Table F, or Table G.
  • a system for making a diagnosis of a colorectal cancer in a subject includes: probes for selectively binding each of one or more peptide markers, wherein the peptide markers are selected from at least one group of markers, selected from (i) the group of markers set forth in Tables H and/or I, which are associated with a first type of colorectal cancer; (ii) the group of markers set forth in Tables J and/or K, which are associated with a second type of colorectal cancer; (iii) the group of markers set forth in Tables L and/or M, which are associated with a third type of colorectal cancer; and the group of markers set forth in Tables N and/or O, which are associated with a fourth type of colorectal cancer; and means for detecting the binding of said probes to said one or more peptide markers.
  • FIG. 1 Flow chart illustrating the steps involved in an embodiment of a method of the presently-disclosed subject matter.
  • FIG. 2. depicts a stratification of murine colon tumor models by localization of ⁇ -catenin and a plan for analysis.
  • FIG. 3. is a graph depicting the results of a study to determine the differential expression of transcripts identified by microarray analyses using quantitative real-time PCR (qRT-PCR).
  • FIG. 4. includes an analysis of genes over-expressed and under-expressed in embryonic colon and in tumors.
  • FIG. 5. includes an analysis of gene lists with criteria of over-expression or under-expression in development, or over-expression or under expression in human CRCs.
  • FIG. 6A is a schematic diagram of the canonical WNT signaling pathway showing elements present in C6 (gene symbols with gray background).
  • FIG. 6B depicts relative gene expression for MYC and SOX4 for individual murine and human tumors.
  • FIG. 7A is a diagram showing that tumors exhibit large-scale activation of developmental patterns, where nuclear ⁇ -catenin-positive (Apc M ⁇ n + and AOM) tumors map more strongly to early development stages during (more proliferative, less differentiated), whereas nuclear ⁇ -catenin-negative (TgfbV ' ; Rag2 ⁇ ' and Smad3 ⁇ " ) tumors map more strongly to later stages consistent with increased epithelial differentiation.
  • FIG. 7B illustrates an overall representation of the relationship of mouse colon tumor models and human CRC to development and non-developmental expression patterns. DESCRIPTION OF EXEMPLARY EMBODIMENTS
  • the term "about,” when referring to a value or to an amount of mass, weight, time, volume, concentration or percentage is meant to encompass variations of in some embodiments ⁇ 20%, in some embodiments ⁇ 10%, in some embodiments ⁇ 5%, in some embodiments ⁇ 1%, in some embodiments ⁇ 0.5%, and in some embodiments ⁇ 0.1% from the specified amount, as such variations are appropriate to perform the disclosed method.
  • the presently-disclosed subject matter includes methods and systems for diagnosis and prognosis of colorectal cancer.
  • Colorectal cancer can include, for example, cancer of the colon, rectum, and/or appendix.
  • the presently-disclosed subject matter includes methods and systems for diagnosing colorectal cancer in a subject, and for determining whether to initiate or continue treatment of colorectal cancer in a subject.
  • the method includes identifying at least one marker in a biological sample from a subject.
  • the at least one marker can be a secreted protein.
  • the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof:
  • the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof:
  • the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof: [0029] In some embodiments, the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof:
  • the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof:
  • the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof:
  • the at least one marker is a polypeptide selected from the following, or a polypeptide fragment thereof:
  • stages of colorectal cancer can be defined according to different systems, as will be understood by those of ordinary skill in the art.
  • stages can be defined using the Dukes system, which stages cancer as Dukes A, B, C, or D.
  • Dukes A can refer to a cancer affecting the innermost lining of the colon or rectum.
  • Dukes B can refer to a cancer that has spread into the muscle layer of the colon or rectum.
  • Dukes C can refer to a cancer that has spread to a lymph node in the region of the colon or rectum.
  • Dukes D can refer to a primary colorectal cancer that has metastasized to a location elsewhere in the body.
  • polypeptide refers to a polymer of the 20 protein amino acids, including modified amino acids (e.g., phosphorylated, glycated, etc.) and amino acid analogs, regardless of size or function.
  • modified amino acids e.g., phosphorylated, glycated, etc.
  • exemplary polypeptides include gene products, naturally occurring proteins, homologs, orthologs, paralogs, fragments and other equivalents, variants, and analogs of the foregoing.
  • fragment when used with reference to a polypeptide, refers to a polypeptide in which amino acid residues are absent as compared to the full-length polypeptide itself, but where the remaining amino acid sequence is usually identical to the corresponding positions in the reference polypeptide. Such deletions can occur at the amino-terminus or carboxy-terminus of the reference polypeptide, or alternatively both. A fragment can retain one or more of the biological features of the reference polypeptide.
  • peptide is used herein, it is intended to include the full-length peptide as well as fragments of the peptide.
  • an identified fragment of a peptide e.g., by mass spectrometry
  • a method for diagnosing colorectal cancer in a subject is provided.
  • diagnosis and “diagnosis” as used herein refer to methods by which one of ordinary skill in the art can estimate and/or even determine whether or not a subject has a colorectal cancer or a risk thereof.
  • diagnostic indicators such as for example a marker, the amount (including presence or absence) of which is indicative of the presence, severity, or absence of the condition.
  • a method for diagnosing colorectal cancer in a subject 100 comprises providing a biological sample from the subject 102; determining an amount of at least one peptide marker 104; and identifying the subject as having colorectal cancer or a risk thereof if there is a measurable difference in the amount of the at least one peptide in the sample as compared to a control level 106.
  • the term "biological sample” as used herein refers to any body fluid or tissue potentially comprising secreted peptide markers, such as the peptides set forth in Tables A, B, and C.
  • the biological sample can be a blood sample, a serum sample, a plasma sample, or sub-fractions thereof.
  • the biological sample can be derived from a normal stool specimen or from a stool specimen obtained following a treatment with a GI tract prokinetic and or secretory stimulant.
  • identifying one or more markers in the biological sample 104 various methods known to those of ordinary skill in the art can be used to identify the one or more markers in the provided biological sample. For example, mass spectrometry and/or immunoassay devices and methods can be used, although other methods are well known to those of ordinary skill in the art (for example, the measurement of marker RNA levels). See, e.g.. U.S. Pat. Nos.
  • Immunoassay devices and methods can utilize labeled molecules in various sandwich, competitive, or non-competitive assay formats, to generate a signal that is related to the presence or amount of an analyte of interest.
  • biosensors and optical immunoassays can be employed to determine the presence or amount of analytes without the need for a labeled molecule. See, e ⁇ , U.S. Pat. Nos. 5,631,171; and 5,955,377, each of which is hereby incorporated by reference in its entirety.
  • the marker peptides are analyzed using an immunoassay.
  • the presence or amount of a marker can be determined using antibodies or fragments thereof specific for each marker, and detecting specific binding.
  • the antibody specifically binds SPARC, which is inclusive of antibodies that bind the full-length peptide or a fragment thereof.
  • antibodies are provided, wherein each antibody specifically binds a full-length peptide or a fragment thereof that is selected from: a peptide of Tables A, B, and C.
  • antibodies are provided, wherein each antibody specifically binds a particular isotype of a peptide or a fragment thereof.
  • the antibody or antibodies can be monoclonal.
  • any suitable immunoassay can be utilized, for example, enzyme-linked immunoassays (ELISA), radioimmunoassays (RIAs), competitive binding assays, and the like. Specific immunological binding of the antibody to the marker can be detected directly or indirectly.
  • Direct labels include fluorescent or luminescent tags, metals, dyes, radionuclides, and the like, attached to the antibody.
  • Indirect labels include various enzymes well known in the art, such as alkaline phosphatase, horseradish peroxidase and the like.
  • immobilized antibodies or fragments thereof specific for the markers is also contemplated by the presently-disclosed subject matter.
  • the antibodies can be immobilized onto a variety of solid supports, such as magnetic or chromatographic matrix particles, the surface of an assay plate (such as microtiter wells), pieces of a solid substrate material (such as plastic, nylon, paper), and the like.
  • An assay strip can be prepared by coating the antibody or a plurality of antibodies in an array on a solid support. This strip can then be dipped into the test biological sample and then processed quickly through washes and detection steps to generate a measurable signal, such as, for example, a colored spot.
  • mass spectrometry (MS) analysis can be used alone or in combination with other methods (e.g., immunoassays) to determine the presence and/or quantity of the one or more markers of interest in a biological sample.
  • the MS analysis comprises matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) MS analysis, such as for example direct-spot MALDI-TOF or liquid chromatography MALDI-TOF mass spectrometry analysis.
  • the MS analysis comprises electrospray ionization (ESI) MS, such as for example liquid chromatography (LC) ESI-MS.
  • Mass analysis can be accomplished using commercially-available spectrometers, such as for example triple quadrupole mass spectrometers.
  • Methods for utilizing MS analysis including MALDI-TOF MS and ESI-MS, to detect the presence and quantity of biomarker peptides in biological samples are known in the art. See, e ⁇ , U.S. Patents 6,925,389; 6,989,100; and 6,890,763 for further guidance, each of which is incorporated herein by this reference.
  • a subject is identified as having colorectal cancer upon identifying in a biological sample obtained from the subject one or more markers selected from: a peptide of Table A.
  • a subject is identified having colorectal cancer upon identifying in a biological sample obtained from the subject one or more markers selected from: a peptide of Table B. In some embodiments of the method, a subject is identified having colorectal cancer upon identifying in a biological sample obtained from the subject one or more markers selected from: a peptide of Table C. In some embodiments of the method, the identification of one or more of such markers in a biological sample obtained from the subject results in the subject being identified as having a risk of colorectal cancer.
  • control sample that is analyzed concurrently with the biological sample, such that the results obtained from the biological sample can be compared to the results obtained from the control sample.
  • standard curves can be provided, with which assay results for the biological sample can be compared. Such standard curves present levels of protein marker as a function of assay units, i.e., fluorescent signal intensity, if a fluorescent signal is used. Using samples taken from multiple donors, standard curves can be provided for control levels of the one or more markers in normal tissue.
  • the efficacy, accuracy, sensitivity, and/or specificity of the method can be enhanced by probing for multiple markers in the biological sample.
  • the biological sample can be probed for at least one marker selected from: the peptides of Table A, Table B, or Table C.
  • the biological sample can be probed for 2-5 markers selected from: the peptides of Table A, Table B, or Table C.
  • the biologic sample can be probed for 6-10 markers selected from: the peptides of Table A, Table B, or Table C.
  • markers can be carried out separately or simultaneously with additional markers within one test sample. For example, several markers can be combined into one test for efficient processing of a multiple of samples and for potentially providing greater diagnostic and/or prognostic accuracy.
  • markers can be combined into one test for efficient processing of a multiple of samples and for potentially providing greater diagnostic and/or prognostic accuracy.
  • one of ordinary skill in the art would recognize the value of testing multiple samples (for example, at successive time points) from the same subject. Such testing of serial samples can allow the identification of changes in marker levels over time.
  • Increases or decreases in marker levels, as well as the absence of change in marker levels, can provide useful information about the disease status that includes, but is not limited to: identifying the approximate time from onset of the event; identifying the presence and amount of salvageable tissue; identifying the appropriateness of drug therapies, including starting, stopping, and/or changing drug therapies; identifying the relative effectiveness of various therapies; and identifying the prediction and optimization of the subject's outcome, including risk of future events.
  • markers can be carried out in a variety of physical formats as well.
  • the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples.
  • single sample formats could be developed to facilitate immediate treatment and diagnosis in a timely fashion, for example, in ambulatory transport or emergency room settings.
  • the subject is identified as having colorectal cancer or a risk thereof if there is a measurable difference in the amount of the at least one peptide in the sample as compared to a control level 106.
  • the subject can be identified as not having colorectal cancer or a risk thereof, or as having a low risk of colorectal cancer.
  • identification of the one or more markers can be a qualitative determination of the presence or absence of the markers, or it can be a quantitative determination of the concentration of the markers.
  • the step of identifying the subject as having colorectal cancer or a risk thereof requires that certain threshold measurements are made, i.e., the levels of the one or more markers in the biological sample exceed control level.
  • the control level is any detectable level of the marker.
  • the control level is the level of detection in the control sample.
  • the control level is based upon and/or identified by a standard curve.
  • control level is a specifically identified concentration, or concentration range.
  • control level can be chosen, within acceptable limits that will be apparent to those of ordinary skill in the art, based in part on the embodiment of the method being practiced and the desired specificity, etc.
  • markers can be associated with particular types of colorectal cancer that differ with respect to their activation of cell cycle proliferation, tissue disruption, and angiogenesis gene programs.
  • the biomarkers set forth in Tables A, B, and C, above can be divided into groups or modules, as set forth in Tables H-G, below.
  • the relative activity of genes in each of these modules indicates tumor state and predicts behavior and can be used to guide the selection of therapies and to better predict outcome than simple single measures.
  • Tables H and I include markers that are the products of genes associated with tissue disruption and angiogenesis.
  • Tables J and K include markers that are the products of genes associated with cell cycle progression, replication, cancer, tumor morphology, and cellular movement, and genes highly correlated with transformation.
  • Tables L and M include markers that are the products of genes highly associated with the disruption of basement membranes, invasion and cell cycle progression, as well as altered transcriptional control.
  • Tables N and O include markers that are associated with advanced stages of colorectal cancer.
  • a method for diagnosing a type of colorectal cancer in a subject comprises providing a biological sample from the subject; determining an amount in the sample of at least one peptide marker from at least one group of markers, wherein each group of markers is associated with a different type of colorectal cancer; comparing the amount of the at least one peptide marker in the sample, if present, to a control level of the at least one peptide marker, wherein the subject is diagnosed as having the type of colorectal cancer associated with a group of markers of which the at least one peptide marker is a member if there is a measurable difference in the amount of the at least one peptide in the sample as compared to the control level.
  • the at least one group of markers is selected from the group of markers set forth in Tables H and I; the group of markers set forth in Tables J and I; the group of markers set forth in Tables L and M; or the group of markers set forth in Tables N and O. In some embodiments, the at least one group of markers is selected from the group of markers set forth in Table I; the group of markers set forth in Table K; the group of markers set forth in Table M; or the group of markers set forth in Table O. In some embodiments, the at least one group of markers is selected from the group of markers set forth in Table H; the group of markers set forth in Table J; the group of markers set forth in Table L; or the group of markers set forth in Table N.
  • the method includes determining the amount in the sample of at least one peptide marker from at least two groups of markers. In some embodiments, the method includes determining the amount in the sample of at least one peptide marker from at least three groups of markers. In some embodiments, the method includes determining the amount in the sample of at least one peptide marker from four groups of markers.
  • the groups can be selected from: the group of Tables H and I; the group of Tables J and K; the group of Tables L and M; and the group of Tables N and O. In some embodiments, the groups can be selected from: the group of Table H; the group of Table J; the group of Table L; and the group of Table N. In some embodiments, the groups can be selected from: the group of Table I; the group of Table K; the group of Table M; and the group of Table O.
  • an amount of at least one peptide marker selected from the a group of markers set forth in Table H, Table I, Table J, Table K, Table L, Table M, Table N, or Table O is determined, and if there is a measurable difference in the amount of the at least one peptide marker from the group in the sample as compared to a control level, then the subject is identified as having a type of colorectal cancer associated the group.
  • an amount of at least one peptide marker selected from a group of markers set forth in Tables F and G is determined, and if there is a measurable difference in the amount of the at least one peptide marker from the group in the sample as compared to a control level, then the subject is identified as having a particularly malignant form of colorectal cancer that will require particular modalities of treatment to be designed based on knowledge of the implicated activated pathways, as will be understood by one of ordinary skill in the art.
  • an amount of at least one peptide marker selected from the a group of markers set forth in Tables H and I; the group of Tables J and K; the group of Tables L and M; and the group of Tables N and O is determined, and if there is a measurable difference in the amount of the at least one peptide marker from the group in the sample as compared to a control level, then the subject is identified as having a type of colorectal cancer associated the group.
  • an amount of at least one peptide marker selected from the group of markers set forth in Table H, Table J, Table L, or Table N is determined, and if there is a measurable difference in the amount of the at least one peptide marker from the group in the sample as compared to a control level, then the subject is identified as having a type of colorectal cancer associated the group.
  • an amount of at least one peptide marker selected from the a group of markers set forth in Table I, Table K, Table M, or Table O is determined, and if there is a measurable difference in the amount of the at least one peptide marker from the group in the sample as compared to a control level, then the subject is identified as having a type of colorectal cancer associated the group.
  • Clinical cancer prognosis is also an area of great concern and interest. It is useful to know the aggressiveness, stage, and/or type of the cancer cells and the likelihood of tumor recurrence in order to plan the most effective treatment. If a more accurate prognosis can be made, appropriate treatment, and in some instances less severe treatment for the subject can be chosen.
  • a method for determining whether to initiate or continue treatment of a colorectal cancer in a subject comprises: providing a series of biological samples over a time period from the subject; analyzing the series of biological samples to determine an amount in each of the biological samples of at least one peptide marker; and comparing any measurable change in the amounts of the at least one peptide marker in each of the biological samples to thereby determine whether to initiate or continue the treatment.
  • treatment or treating relate to any treatment of a condition of interest, including but not limited to prophylactic treatment, i.e., prophylaxis, and therapeutic treatment
  • the terms treatment or treating include, but are not limited to: preventing or arresting the development of a cancer; inhibiting the progression of a cancer; reducing the severity of a cancer; ameliorating or relieving symptoms associated with a cancer; and causing a regression of cancer or one or more of the symptoms associated with the cancer.
  • multiple determination of the peptide markers over time can be made to facilitate diagnosis and/or prognosis.
  • a temporal change in the marker can be used to monitor the progression of the cancer and/or efficacy of appropriate therapies directed against the cancer. In such an embodiment, for example, one might expect to see a decrease in the amount of one or more of the marker peptides in a biological sample over time during the course of effective treatment.
  • a system for diagnosing colorectal cancer in a subject is provided, or a system for determining whether to initiate or continue treatment of colorectal cancer in a subject is provided.
  • Such systems can be provided, for example, as commercial kits that can be used to test a biological sample, or series of biological samples, from a subject.
  • the system includes probes for selectively binding each of one or more peptide markers; and means for detecting the binding of said probes to said one or more markers.
  • the system can also include certain samples for use as controls.
  • the system can further include one or more standard curves providing levels of markers as a function of assay units.
  • a system for the analysis of biomarkers comprises antibodies having specificity for one or more markers associated with colorectal cancer, including a marker as set forth in Table A, B, and C.
  • Such a system can comprise devices and reagents for the analysis of at least one test sample.
  • the system can further comprise instructions for using the system and conducting the analysis.
  • the systems can contain one or more reagents or devices for converting a marker level to a diagnosis or prognosis of the subject.
  • a system including probes for selectively binding each of one or more peptide markers selected from the peptides of Table A. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers selected from the peptides of Table B. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers selected from the peptides of Table C.
  • a system including probes for selectively binding each of one or more peptide markers selected from a group of peptides set forth in Tables H and I, Tables J and K, Tables L and M, or Tables N and O.
  • a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from at least two of the following groups of peptides: Tables H and I, Tables J and K, Tables L and M, or Tables N and O.
  • a system including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from at least three of the following groups of peptides: Tables H and I, Tables J and K, Tables L and M, or Tables N and O. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from four of the following groups of peptides: Tables H and I, Tables J and K, Tables L and M, or Tables N and O.
  • a system including probes for selectively binding each of one or more peptide markers selected from a group of peptides set forth in Table H, Table J, Table L, or Table N. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from at least two of the following groups of peptides: Table H, Table J, Table L, or Table N. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from at least three of the following groups of peptides: Table H, Table J, Table L, or Table N. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from four of the following groups of peptides: Table H, Table J, Table L, or Table N.
  • a system including probes for selectively binding each of one or more peptide markers selected from a group of peptides set forth in Table I, Table K, Table M, and Table O. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from at least two of the following groups of peptides: Table I, Table K, Table M, and Table O. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from at least three of the following groups of peptides: Table I, Table K, Table M, and Table O. In some embodiments, a system is provided including probes for selectively binding each of one or more peptide markers, wherein at least one peptide marker is selected from four of the following groups of peptides: Table I, Table K, Table M, and Table O.
  • the term "subject” includes both human and animal subjects.
  • veterinary therapeutic uses are provided in accordance with the presently-disclosed subject matter.
  • the presently-disclosed subject matter provides for the diagnosis of mammals such as humans, as well as those mammals of importance due to being endangered, such as Siberian tigers; of economic importance, such as animals raised on farms for consumption by humans; and/or animals of social importance to humans, such as animals kept as pets or in zoos.
  • Examples of such animals include but are not limited to: carnivores such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels; and horses.
  • carnivores such as cats and dogs
  • swine including pigs, hogs, and wild boars
  • ruminants and/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels
  • horses are also provided.
  • domesticated fowl i.e., poultry, such as turkeys, chickens, ducks, geese, guinea fowl, and the like, as they are also of economic importance to humans.
  • livestock including, but not limited to, domesticated swine, ruminants, ungulates, horses (including
  • the presently-disclosed subject matter is further illustrated by the following specific but non-limiting examples.
  • the following examples may include prophetic examples, and may also include compilations of data that are representative of data gathered at various times during the course of development and experimentation related to the presently-disclosed subject matter.
  • the present inventors developed a gene expression database of genome-wide expression derived from about 350 human colon cancer and normal specimens. By evaluating about 54,000 genetic elements for each tumor or normal specimen, the present inventors were able to develop a list of genes that were substantially over-expressed in tumor samples versus normal controls. A genetic approach, described below, was then used to identify the genes that might produce secreted proteins. This approach ultimately identified potential biomarker proteins that could be used as serum or plasma makers. These markers could have utility for predicting the diagnosis, prognosis, of a cancer or potentially its response to a particular therapy. The markers could also be useful to develop diagnostic imaging agents to image a cancer's location, size, or extent of spread.
  • GenBank Nucleotide IDs matching Affymetrix probe IDs from a U133 Plus 2.0 GeneChip (Affymetrix, Santa Clara, CA) were retrieved from the Affymetrics website.
  • GenBank Nucleotide IDs were then translated into GenBank Protein IDs using the Batch Entrez function at http://www.ncbi.nlm.nih.gov/entrez/batchentrez.cgi.
  • the Protein IDs were translated into batches of individual FASTA sequences. These FASTA sequences were run through the publicly available SIGCLEAVE database at http://bioweb.pasteur.fr/seqanal/interfaces/sigcleave.html.
  • the output from SIGCLEAVE was then sorted, giving two lists of proteins: 1) proteins with one or more predicted signal cleavage sites, and 2) proteins with no predicted signal cleavage sites.
  • the sorting was carried out using Perl Script.
  • GenBank Protein IDs were translated back to GenBank Nucleotide IDs and then Affymetrix probe IDs. This provided a list of potentially secreted proteins with genes represented on the Affymetrix U133 Plus 2.0 GeneChip.
  • the first list (Table P) was composed of genes 4 times or more increased in expression in colon tumors relative to normal colonic mucosa stratified by the four Dukes' stages individually.
  • the second list (Table Q) was composed of genes 4 times or more increased between the mean expression of normal colon tissue and the mean expression of colon tumors of at least one of the four Dukes' stages individually.
  • the first comparison produced a list of genes that are 4 times or more increased from normal in all four Dukes stages, which genes have products that are potentially secreted.
  • the second comparison produced a list of genes that is 4 times or more increased from normal to at least one of the four Dukes stages and potentially secreted.
  • Table R include a list of genes, the expression of which is 4 times or more increased from normal in all four Dukes stages, which genes have products that are potentially secreted:
  • Table S include a list of genes, the expression of which is 4 times or more increased from normal in three of four Dukes stages, which genes have products that are potentially secreted: I Table S I
  • Table T include a list of genes, the expression of which is 4 times or more increased from normal in two of four Dukes stages, which genes have products that are potentially secreted:
  • Table U include a list of genes, the expression of which is 4 times or more increased from normal in one of four Dukes stages, which genes have products that are potentially secreted:
  • the colon is composed of a dynamic and self-renewing epithelium that turns over every 3-5 days. Without wishing to be bound by theory, it is thought that at the base of the crypt, variable numbers (between one and 16) of slowly dividing, stationary, pluripotent stem cells give rise to more rapidly proliferating, transient amplifying cells. These cells differentiate chiefly into post-mitotic columnar colonocytes, mucin-secreting goblet cells and enteroendocrine cells as they migrate from the crypt base to the surface where they are sloughed into the lumen [I].
  • the Apc M ⁇ n/+ (multiple intestinal neoplasia) mouse model harbors a germline mutation in the Ape tumor suppressor gene and exhibits multiple tumors in the small intestine and colon [8].
  • a major function of APC is to regulate the canonical WNT signaling pathway as part of a ⁇ - catenin degradation complex. Loss of APC results in a failure to degrade ⁇ -catenin, which instead enters the nucleus to act as a transcriptional co-activator with the lymphoid enhancer factor/T-cell factor (LEF/TCF) family of transcription factors [9].
  • LEF/TCF lymphoid enhancer factor/T-cell factor
  • TGFBR2 TGF ⁇ type II receptor
  • mice In the mouse, a deficiency of TGF ⁇ 1 combined with an absence of T-cells ⁇ Tgfb ⁇ ' ⁇ ; Rag2 ⁇ ' ⁇ ) results in a high occurrence of colon cancer [13]. These mice develop adenomas by two months of age, and adenocarcinomas, often mucinous, by 3-6 months of age. Immunohistochemical analyses of these tumors are negative for nuclear ⁇ -catenin, suggesting that TGF ⁇ l does not suppress tumors via a canonical WNT signaling-dependent pathway. [0082] The SMAD-family proteins are critical downstream transcription regulators activated by TGFB signaling, in part through the TGFB type II receptor. Smadi ⁇ ' ⁇ mice also develop intestinal lesions that include colon adenomas and adenocarcinomas by six months of age [14].
  • this cross-species, cross-models analytical approach filtered through the lens of embryonic colon development, provides an integrated view of gene expression that implicates the adoption of a broad program that encompasses embryonic activation, developmental arrest, and failed differentiation as fundamental characteristics of human CRC.
  • Example Methods - Mouse models, human CRC patients, and tumor collection.
  • mice Three-to-four month old mice from various AXB recombinant inbred lines were treated with AOM doses chosen for enhancement of inter-strain differences in susceptibility [H]. Mice were given four weekly i.p. injections of 10 mg AOM per kg body weight, and tumors were collected six months after the first injection. Animals were euthanized with CO 2 , colons removed, flushed with IX PBS, and laid out on Whatman 3MM paper. A summary of the mouse strains, mutant alleles and source laboratories is presented in Table V.
  • Sample collection protocol and analyses were performed as described in Kwong, et al, Genomics (2005) [36]. Information collected with the samples for this study includes TNM and Dukes staging/presentation criteria, pathological diagnosis and differentiation criteria.
  • RNA samples were purified using Trizol Reagent (Invitrogen Systems, Inc.) from finely dissected tumors and were subjected to quality control screening using the Agilent Bio Analyzer 2100.
  • Example Methods - Microarray procedures and data analysis
  • RNA samples were labeled for hybridization to Affymetrix HG-U133plus2 microarrays using the Affymetrix-recommended standard labeling protocol (Small-scale labeling protocol version 2.0 with 0.5 ⁇ g of total RNA; Affymetrix Technical Bulletin). Microarrays were scanned with MicroarraySuite version 5.0 to generate "CEL" files that were processed using the RMA algorithm as implemented by Bioconductor [15].
  • the four different mouse models of CRC were compared for model-specific differences, then compared to mouse colon development stages, and then to human CRC samples (FIG. 2).
  • Colon tumors from four etiologically distinct mouse models of CRC were subjected to microarray gene expression profiling.
  • the gene expression profiles from the different mouse model tumors were compared and contrasted to each other, as well as to those from embryonic mouse colon development and 100 human CRCs.
  • the two nuclear beta-catenin-positive mouse tumors (azoxymethane- treated [AOM] and ApcMin/+), exhibited strong activation of genes characteristic of those expressed in the earliest embryonic stages, while tumors from two other models (Smad37- and Tgfbl-/- x Rag2-/-) exhibited lower activation of early stage-specific genes but substantial expression of general embryonic colon genes.
  • Human colon cancer cases over-expressed genes characteristic of both early and late embryonic stages. Examining tumor gene expression through the lens of development has revealed an extensive network of therapeutic targets for cancer control.
  • Overall design Four colorectal tumor models were compared using the approach of finding model-specific differences with gene expression levels referenced to the median gene expression value across all models.
  • a second complementary strategy compared the gene expression levels of the murine tumors to those of mouse normal adult colon).
  • the first approach to referencing was to compare normalized ratios across the tumor series. To do this, for each gene, the Lowess-corrected ratio for each probe element (sample vs. E17.5 whole fetal mouse reference) was divided by the median ratio for that probe across the entire tumor sample series. This is termed the median-per-tumor expression ratio and was useful for identifying, clustering and visualizing differences that occur between the different tumor samples.
  • Mouse expression data had been collected for normal E13.5-E18.5 colon samples from inbred C57BL/6J and outbred CD-I mice [15] using the identical E17.5 whole fetal mouse reference, allowing the data to be combined directly.
  • probe sets were assigned to represent a given transcript if at least 50% of the perfect match probes of the probe set matched to that transcript. The newly assigned transcript identifiers were then used to map probe sets to ortholog genes.
  • Mouse-human RefSeq gene ortholog assignments can be found at http://genometrafac.cchmc.org/. All ortholog assignments and cross-species mapping annotations were incorporated into annotations associated with the Affymetrix HG-U133 plus2.0 genome. Gene expression ratios obtained for the mouse samples were then represented as expression values within the human platform for all of the probe sets that mapped to the corresponding mouse gene ortholog.
  • Example Methods - Ontology-based analysis of gene cluster-associated functional correlates.
  • FIG. 6A shows a diagram of the canonical WNT signaling pathway and an associated- gene network that was a top-ranked association of the clusters that exhibited significant overexpression in AOM and Apc Mm/+ versus Smadi ⁇ ' ⁇ and Tgfbl '/' ; Ragl' ' mouse models.
  • Genes or gene products are represented as nodes, and biological relationships between nodes are represented as edges (lines). All edges are supported by at least one literature reference from a manuscript, or from canonical information stored in the Ingenuity Pathways Knowledge Base.
  • FIGS. 8A and 8B the up-regulated signature in tumors from Apc M ⁇ n/+ (M) and AOM (A) models (cluster C6) is enriched with genes associated with the activation of the canonical WNT signaling pathway, as determined by nuclear ⁇ -catenin positivity.
  • FIG. 6A depicts a schematic diagram of the canonical WNT signaling pathway showing elements present in C6 (gene symbols with gray background). Key elements of this pathway (Ctnnbl, Lefl, Tc/ and Myc) are outlined in blue.
  • FIG. 6B depicts relative gene expression for MYC and SOX4 is plotted for individual murine and human tumors.
  • MYC and SOX4 The relative expression level of MYC and SOX4 is normalized to adult colon. Note that whereas Sox4, a canonical WNT target gene, is expressed at high levels in all human CRCs, A/M tumors and during embryonic mouse colon development, it is not expressed in S and T tumors (black). In contrast, MYC is over-expressed in all human and murine tumors and during colonic embryonic development (red), irrespective of the activation of canonical WNT signaling, as determined by nuclear ⁇ -cateninpositivity.
  • RTQ-PCR quantitative real-time polymerase chain reaction
  • RNAs from C57BL6 Apc Mm/+ and 129 Smadi '1' tumor samples (20 ⁇ g) were reverse-transcribed to cDNA using the High Capacity cDNA Archive Kit (oligo-dT primed; Applied Biosystems).
  • RTQ-PCR reactions (20 ⁇ l) were set up in 96-well MicroAmp Reaction Plates (Applied Biosystems) using 10 ng of cDNA template in Taqman Universal PCR Master Mix and 6-FAM-labeled Assays-on-Demand primer-probe sets (Applied Biosystems). Reactions were run on an MX3000P (Stratagene) with integrated analysis software.
  • Threshold cycle numbers were determined for each target gene using an algorithm that assigns a fluorescence baseline based on measurements prior to exponential amplification. Relative gene expression levels were calculated using the ⁇ Ct method [59], with the Gush gene as a control. Fold-change was determined relative to expression in normal adult colon from two C57BL/6J mice.
  • a large-scale expression module based on increased expression by embryonic colon, all mouse tumor models, and human CRCs was composed of genes responsible for control of cell cycle progression, proliferation, and migration such as MYC, AKT2, ANLN, BIRC5, CSElL, ITGB5, MAD2L1, MIF, MSF, PLKl and SPARC.
  • colon tumors from four etiologically distinct mouse models of CRC were subjected to microarray gene expression profiling.
  • the gene expression profiles from the different mouse model tumors were compared and contrasted to each other, as well as to those from embryonic mouse colon development and 100 human CRCs.
  • the strategy for the characterization of mouse models of human CRC relies on gene expression differences and relative patterning across a range of mouse CRC models, normal mouse colon developmental stages, and human CRCs. Achieving this comparison was facilitated by the use of reference RNAs from whole-mouse and normal adult colon reference RNAs for both mouse and human measurements.
  • Mouse tumor samples were profiled on cDNA microarrays using the embryonic day (E)17.5 whole mouse reference RNA identical to that described in Park, et al., Genesis (2005) [15] to examine embryonic mouse colon gene expression dynamics during from E13.5 to E18.5 during which time the primitive, undifferentiated, pseudo-stratified colonic endoderm becomes a differentiated, single-layered epithelium.
  • This strategy allowed us to construct a gene expression database of mouse colon tumors in which gene expression levels of the tumors could be referenced, ranked, and statistically compared to an average value among the tumors or to embryonic or adult colon gene expression levels on a per-gene basis.
  • the four models were compared with each other, then to mouse colon development, and finally to human CRCs using gene ortholog mapping (FIG. 2).
  • cluster Cl composed of transcripts that exhibited lower expression in SmadS "7" tumors and higher expression in AOM, Apc Mm/+ and Tgfbl 7" ; Rag2 7" tumors, contains 391 transcripts including Cdk4, Ctnnbl, Myc, Ezh2, Mcm2 and Tcf3.
  • DAVID and Ingenuity Pathway Analysis applications demonstrated highly significant associations to cell cycle progression, replication, post-transcriptional control and cancer.
  • cluster C2 composed of 663 transcripts that exhibited high expression in AOM and Apc Ml + tumors, but low in Smad3 " " and Tgfbl " “ ; Rag2 " " tumors, included transcripts for contact growth inhibition (Metapl, Pcyoxl), mitosis (Mif, Pikl), cell cycle progression and checkpoint control (Id2, Ptp4A2, Tp53).
  • Active canonical WNT signaling stratifies the four murine colon tumor models into two groups. 1798 gene transcripts are identified as differentially expressed among any of the four mouse tumor models (Kruskal-Wallis test + Student-Newman-Keuls test + FDR ⁇ 5.10 "5 ) (Data not shown). Results demonstrate that AOM (A) and Apc M ⁇ n + (M) tumors are transcriptionally more similar to each other than to tumors from Smad3 ⁇ A (S) and Tgfb ⁇ 1' ; Rag2 ⁇ / ⁇ (T) mice. Five clusters have been identified (C1-C5) that correspond to the K-means functional clusters listed in Table W.
  • the lower panel illustrates the extent of the similarity between A/M and S/T tumors by identifying the top-ranked 1265 transcripts of the 1798 that were higher or lower in the two tumor super-groups (rank based on Wilcoxon-Mann- Whitney test for between-group differences with a FDR ⁇ 5.10 5 cutoff).
  • Up- regulated transcripts in A/M tumors are highly enriched for genes associated with canonical WNT signaling activity, cell proliferation, chromatin remodeling, cell cycle progression and mitosis; transcripts over-expressed in S/T tumors are highly enriched for genes related to immune and defense responses, endocytosis, transport, oxidoreductase activity, signal transduction and metabolism. Representative histologies for each of the four tumor models were obtained (data not shown). Model-dependent localization of ⁇ -catenin was shown. Tumors from M and A (not shown) mice exhibited prominent nuclear ⁇ -catenin accumulation and reduced cell surface staining. Conversely, tumors from 5 * and 7 (not shown) mice exhibited retention of plasma membrane ⁇ -catenin immunoreactivity.
  • cluster C6 genes i.e. genes with greater up-regulation in tumors from Apc Mm/+ and AOM models than in SmadS 7" and Tgfbl 7" ; Rag2 7"
  • tumor cell proliferation e.g. Myc, Pcna
  • cytokinesis e.g. Amot, Cxcl5
  • chromatin remodeling e.g. Ets2, Hdac2, Set
  • cell cycle progression and mitosis e.g. Cdkl, Cdk4, Cull, Plkl.
  • Myc is up-regulated in all four mouse tumors models relative to normal colon tissue (see FIG. 7B).
  • immune and defense responses e.g. 1118, Ml, Myd88
  • endocytosis e.g. Lrpl, LdIr, Racl
  • transport e.g. Abca3, Slc22a5, Slc30a4
  • oxidoreductase activity e.g. Gcdh, Prdx ⁇ , Xdh
  • mouse colon tumor models and human CRC overall representation of the relationship of mouse colon tumor models and human CRC to development and non-developmental expression patterns is shown. Gene expression clusters mapped to the progression of adenomatous and carcinomatous transformation are shown. Both mouse colon tumor models and human CRC share in the activation of embryonic colon expression, the repression of adult differentiation, and the loss of shared tumor suppressor genes. Many human CRCs also lack the expression of additional tumor suppressor programs and gain the expression of oncogenes that are not overexpressed during normal developmental morphogenesis.
  • K-means clustering was used to generate C8- ClO cluster patterns as shown in a hierarchical tree heatmap (Table X). Several sub-patterns were evident, some of which clearly separated Apc Ml + and AOM from Smad3 " " and Tgfbl “ “ ; Rag2 " " tumors.
  • One strong cluster, cluster C8, consisted of genes more strongly expressed in Apc Mm/+ and AOM than SmadS 7" and Tgfbl 7" ; Rag2 7 ⁇ tumors.
  • transcripts associated with increased differentiation and maturation observed at later stages of colon development E16.5-E18.5 (e.g. Klf4 [20], Crohn's disease-related Slc22a5/Octn2 [21], Slc30a4/Znt4 [22], Sst [23]), were expressed at higher levels by tumors from Smad3 7" and Tgft>r / ⁇ ; Rag2 ⁇ / ⁇ mice.
  • Embryonic gene expression can be further refined into genes expressed differentially during early (ED; E13.5-15.5) and late (LD; E16.5-18.5) embryonic development.
  • ED early
  • LD late
  • a heatmap was generated showing the relative behaviors of 750 transcripts that are highest-ranked for early versus late embryonic regulation (not shown).
  • transcripts with the highest early embryonic expression were expressed at higher levels in nuclear ⁇ -catenin-positive tumors (A and M), whereas nuclear Bcatenin negative tumors (S and T) were representative of later stages of embryonic development.
  • Sample groups ED, early development (E13.5-E15.5); LD, late development (E16.5-E18.5); A, AOM-induced; M, Apc Min/+ ; T, Tgfbl ⁇ ; Ragl 1' ; S, Smad ⁇ ).
  • Cluster 15 contained a set of genes (principally metallothionein genes) recently identified to be predictive of microsatellite instability [24, 25]. This analysis indicates that human CRCs have a greater level of complexity than the mouse colon tumors studied here. There was no correlation between these distinguishing clusters and the stage of the tumor (note the broad overlapping distributions of Dukes stages A-D across these different clusters). However, as shown in Table Y, gene ontology and network analysis of the individual gene clusters (Cl 1 -C 17) that were differentially active in subgroups of the tumors, map to genes highly associated with a diverse set of biological functions, including lipid metabolism, digestive tract development and function, immune response and cancer.
  • Human CRCs exhibit gene expression profile complexity consistent with significant tumor subclasses. Genes potentially able to distinguish cancer subtypes were identified from Affymetrix HG-U133 plus2 Genechip expression profiles by filtering for 3285 probe sets that were top-ranked by raw expression and their differential regulation in at least 10 out of 100 human colorectal cancer tumors. Coordinately regulated transcripts and similarly behaving samples were identified via hierarchical tree clustering. Seven different gene clusters (Cl 1-17) were identified that distinguished 10 or more tumors from the other tumors. Gene clusters were found to be highly enriched for gene functions listed in Table Y.
  • RMA microarray analysis
  • Both human CRCs and mouse colon tumors reactivate an embryonic gene signature. When human and murine tumors are compared, they both broadly re-express an embryonic gene expression pattern. Gene expression profiles from the mouse tumor models and human CRC samples were combined into a single non-redundant gene ortholog genome table structure and subjected to comparative profile analysis. Informative probe-sets from human and mouse platforms were selected, mapped to corresponding ortholog genes, and used to populate a table in which normalized expression for each gene is relative to normal adult colon.
  • cluster C20 are genes down-regulated in human CRCs that are routinely over-expressed in mouse tumors and development;
  • cluster C21 are genes robustly expressed in human CRC that are rarely expressed in embryonic colon or murine tumors.
  • Table Z Detailed cluster analysis; Differential and statistically significant biological functions in clusters C18-C23.
  • Cluster C22 (860 transcripts of genes strongly expressed both developmentally and across all tumors) is highly enriched with genes associated with cell cycle progression, replication, cancer, tumor morphology and cellular movement.
  • Cluster C18 (258 transcripts down-regulated in mouse and human tumors, as well as in development) is highly enriched in genes associated with digestive tract function, biochemical and lipid metabolism. This cluster is clearly composed of genes associated with the mature GI tract.
  • the cluster Cl 8 pattern indicates a corresponding arrest of differentiation in both mouse and human tumors.
  • Cluster C23 (142 transcripts over-expressed in all mouse models and human CRC, but with low expression in development) maps to genes highly associated with the disruption of basement membranes, invasion and cell cycle progression, as well as altered transcriptional control.
  • Cluster C21 (313 transcripts in which human tumors somewhat variably express a set of genes that are rarely expressed by the mouse tumors) is remarkable for its composition of genes associated with cell cycle proliferation, tissue disruption and angiogenesis.
  • the genes in cluster C21 represent a separately regulated module that is enriched for genes associated with invasion.
  • Clusters C21 and C23 reveal sets of genes likely involved in tumor progression.
  • Cluster C22 (with genes over- expressed in all mouse and human tumors and strongly expressed in embryonic colon) represents a group of genes highly correlated with transformation.
  • Myc was lower in expression in the Smad3 7" tumors compared to tumors from the other three models, it was elevated in all four models relative to normal adult colon.
  • Myc/MYC was over-expressed in all mouse and human tumors as well as in development.
  • Myc/MYC over-expression may be independent of nuclear ⁇ -catenin status. Increased Myc/MYC expression may reflect both activation of canonical Wnt signaling, as it is a target of nuclear ⁇ -catenin/TCF [27], and deregulation of TGFB signaling, as TGFBl is known to repress Myc/MYC [28-30].
  • mice models and human CRC To shed light on the underlying molecular changes in tumors from mouse models and human CRC, the relationship was assessed at the molecular level of four widely used, but genetically distinct, mouse models that develop colon tumors. A subsequent analysis of the models in the context of embryonic mouse colon development was also undertaken. Finally, to identify consensus species-independent cancer signatures that may define gene expression changes common to all CRCs, relevant mouse model signatures were projected onto a large set of human primary CRCs of varied histopathology and stage.
  • Tumors from mouse models of CRC exhibit significant phenotypic diversity [6], and therefore were expected to exhibit differential gene expression patterns.
  • the analysis of tumors from mouse models of CRC has revealed a low complexity between models and strains, and has identified common and unique transcriptional patterns associated with a variety of biological processes and pathway-associated activities.
  • the results demonstrate an imbalance between proliferation and differentiation with nuclear B-catenin-positive tumors being more proliferative, less differentiated and with lower immunogenic characteristics than tumors from nuclear B- catenin-negative tumors.
  • canonical WNT signaling leads to nuclear translocation of ⁇ -catenin and, through its interaction with LEF/TCF, the regulation of genes relevant to embryonic development and proliferation [16], as well as stem cell self-renewal [32]. Consequently, the activated canonical WNT signaling observed in Apc M ⁇ n/+ and AOM models suggests that tumors may arise as a consequence of proliferation of the stem cell or "transient amplifying" compartment. In the colonic crypt, loss of TCF4 [33] or DKKl over-expression [34] promotes loss of stem cells, suggesting that canonical WNT signaling is required for the maintenance of the intestinal stem cell compartment [33-35].
  • Proliferation-related characteristics of nuclear ⁇ - catenin-positive tumors include increased expression of CCNDl, MYC, PCNA [17], and SoxA [16]. These genes were also identified as a component of the nuclear- ⁇ -catenin-positive signatures.
  • increased MYC decreases intestinal cell differentiation by binding to and repressing the Cdknla (coding for p21 CIP1/WAF1 ) promoter [36], the gene encoding Wnt-inhibitory factor Wifl, the gene encoding the negative regulator of WNT Nakedl [37], and the gene encoding the Takl /Nemo-like kinase, NIk [38].
  • Wifl displays a graded expression in colonic tissue, with higher expression in the stem cell compartments and lower expression in the more differentiated cells at the luminal surface, suggesting that Wifl may contribute to stem cell pool maintenance independent of WNT signaling inhibition. [39].
  • Canonical WNT signaling not only governs intestinal cell proliferation, but also cell differentiation and cell positioning along the crypt-lumen axis of epithelial differentiation. Increased canonical WNT signaling activity enhances MATHl -mediated amplification of the gut secretory lineages [40]. Canonical WNT signaling also influences cell positioning by regulating the gradient of EPHB2/EPHB3 and EPHBl ligand expression [41, 42]. Together, the data suggest a complex imbalance of crypt homeostasis due to enhanced canonical WNT activity.
  • TGFB1/SMAD4 tumors arising in response to abnormal TGFB1/SMAD signaling [14, 43] are similar to one another in their specific gene signatures and broadly distinct from those with activated canonical WNT signaling by their absence of nuclear ⁇ -catenin.
  • Unique to the dysregulated TGFB1/SMAD4 signaling models is the strong signature of an immunologically altered state, with up-regulation of genes determining immune and defense responses such as 1118, Irfl and mucin pathway-associated genes.
  • these tumors are usually characterized by a strong inflammatory component when evaluated histopathologically, even in the absence of T- and B-cells such as in the TgfbV ' ; Rag2 ⁇ ' background.
  • microarray patterns of gene expression for AOM and Apc M ⁇ n/+ tumors are mirror images of those for Tgfbr A ; Rag2 ⁇ ' ⁇ tumors. It is perhaps not surprising that combining these two transcriptional programs results in increased number and invasiveness of colonic tumors as recently reported for Apc Mm/+ mice crossed to SmadS 7" mice [44]. Moreover, combined activation of canonical WNT signaling and inhibition of TGFB signaling also results in more advanced intestinal tumors (Apc delta716/+ ; Smad4 +I ⁇ mice [45] and intestine-specific deletion of the type II TGFB receptor in Ape 1638N/wt mice [46].
  • Example - Discussion - Embryology provides insight into the biology of mouse and human colon tumors
  • cancer represents a reversion to an embryonic state, partly based upon the observation that several oncofetal antigens are diagnostic for some tumors [47, 48].
  • the transcriptomes of normal mouse colon development and models of CRC were analyzed and compared. The data show that developmentally regulated genes represent -56% of mouse tumor signatures, and that the tumor signatures from the four mouse models recapitulate -85% of developmentally regulated genes.
  • HDACs histone acetyltransferases and histone deacetylases
  • This report constitutes a comprehensive molecular evaluation and comparison of mouse and human colon tumor gene expression profiles.
  • the ability to compare tumor gene expression profiles between mouse and human tumors has been improved by using a referencing strategy in which gene expression levels in the tumor samples are analyzed in relation to gene expression in corresponding normal colon epithelium.
  • This approach has revealed that gene expression patterns are both shared and distinct between mouse models and human CRCs.
  • the present study actually demonstrates the magnitude of the similarity between tumors and embryonic gene expression.
  • Heath JP Epithelial cell migration in the intestine. Cell Biol Int 1996, 20(2): 139-146.
  • Zbar AP The immunology of colorectal cancer. Surg Oncol 2004, 13(2-3):45-53.
  • Valk-Lingbeek ME Bruggeman SW, van Lohuizen M: Stem cells and cancer; the polycomb connection. Cell 2004, 118(4):409-418.
  • Kim DH, Kim M, Kwon HJ Histone deacetylase in carcinogenesis and its inhibitors as anti-cancer agents. JBiochem MoI Biol 2003, 36(1): 110-119.
  • Livak KJ, Schmittgen TD Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25(4):402-408.

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Abstract

L'invention propose des procédés et systèmes à utiliser dans un diagnostic du cancer colorectal chez un sujet. Un procédé peut inclure la fourniture d'un échantillon biologique provenant du sujet; la détermination d'une quantité d'un échantillon d'au moins un marqueur peptidique, choisi parmi un groupe de marqueurs tels que décrits ici; et la comparaison de la quantité du au moins un marqueur peptidique dans l'échantillon, s'il est présent, à un niveau témoin du au moins un marqueur peptidique, le sujet étant diagnostiqué comme ayant un cancer colorectal ou présentant un risque de développer celui-ci s'il existe une différence mesurable entre la quantité du au moins un marqueur peptidique dans l'échantillon et le niveau témoin.
PCT/US2008/057884 2007-03-21 2008-03-21 Systèmes et procédés pour le diagnostic et le pronostic du cancer colorectal Ceased WO2008116178A2 (fr)

Applications Claiming Priority (8)

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US89602007P 2007-03-21 2007-03-21
US60/896,020 2007-03-21
US93830707P 2007-05-16 2007-05-16
US60/938,307 2007-05-16
US96898807P 2007-08-30 2007-08-30
US60/968,988 2007-08-30
US97183907P 2007-09-12 2007-09-12
US60/971,839 2007-09-12

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Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102803967A (zh) * 2009-04-07 2012-11-28 基督教高等教育科学研究及病人护理协会 用于结直肠腺癌的诊断的基于蛋白质的方法和组合物
CN103140760A (zh) * 2010-07-14 2013-06-05 联邦科学与工业研究组织 结肠直肠癌的诊断
JP2013533977A (ja) * 2010-07-14 2013-08-29 コモンウェルス サイエンティフィック アンド インダストリアル リサーチ オーガニゼイション 大腸癌の診断
EP2593795A4 (fr) * 2010-07-14 2014-01-22 Commw Scient Ind Res Org Diagnostic en matière de cancer colorectal
EP2829881A3 (fr) * 2010-07-14 2015-05-13 Commonwealth Scientific and Industrial Research Organisation Diagnostic de cancer colorectal
CN103140760B (zh) * 2010-07-14 2016-01-27 联邦科学与工业研究组织 结肠直肠癌的诊断
US10877039B2 (en) 2010-07-14 2020-12-29 Vision Tech Bio Pty. Ltd. Diagnostic for colorectal cancer
US10867706B2 (en) 2010-07-20 2020-12-15 Applied Invention, Llc Multi-scale complex systems transdisciplinary analysis of response to therapy
US9689874B2 (en) 2015-04-10 2017-06-27 Applied Proteomics, Inc. Protein biomarker panels for detecting colorectal cancer and advanced adenoma
JP2018155506A (ja) * 2017-03-15 2018-10-04 国立大学法人金沢大学 血中ケモカインをマーカーとして用いた大腸癌の検出
EP4008317A1 (fr) 2020-12-03 2022-06-08 Sanovel Ilac Sanayi Ve Ticaret A.S. Formulations pharmaceutiques solides de dapagliflozine amorphe

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WO2008116178A3 (fr) 2008-12-04

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