WO2013130869A1 - Gene expression signatures in cancer - Google Patents

Abstract

The present invention relates generally to treatment of cancer utilizing gene signatures to predict response to cancer therapy as well as to predict patient survival. More particularly, the present invention relates to utilizing a combination of specific gene expression and other factors to predict tumor recurrence and survival in patients with colorectal cancer, thereby affecting treatment course for patients.

Description

GENE EXPRESSION SIGNATURES IN CANCER

SEQUENCE LISTING

[0000] The instant application contains a Sequence Listing which has been submitted in ASCII format via EFS-Web and is hereby incorporated by reference in its entirety. Said ASCII copy, created on February 28, 2013, is named 2012P04819WOSequenceListing.txt and is 20.8 KB (21,300 bytes) in size.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. provisional application Serial No.

61/604,058 filed February 28, 2012, which is incorporated herein by reference in its entirety.

FIELD OF INVENTION

[0002] The present invention relates generally to treatment of cancer utilizing gene signatures to predict response to cancer therapy as well as to predict patient survival. More particularly, the present invention relates to utilizing a combination of specific gene expression and other factors to predict tumor recurrence and survival in patients with colorectal cancer, thereby affecting treatment course for patients.

BACKGROUND OF THE INVENTION

[0003] Colorectal cancer (CRC) is a major public health problem as the third most common cancer and the second leading cause of cancer-related death in Western countries. The risk of developing this neoplasm in the general population is around 5-6% at the age of 70, rising exponentially with age.

[0004] To date, tumor stage at diagnosis remains the best predictor of recurrence and survival. According to the American Joint Committee on Cancer TNM staging system, stage III patients, which account for approximately 40% of all CRC, have a 5-year overall survival of less than 50%. In contrast, stage II patients, who represent approximately one quarter of CRC patients, have a relatively good prognosis after curative resection, with a 5-year survival ranging from 72% for pT4N0 to 85% for pT3N0 cases. [0005] At diagnosis, 75-80% of patients with CRC present with localized disease.

However, even after curative surgery, there is a significant chance of developing tumor recurrence. Indeed, nearly 40% of patients with initially non-metastatic disease will experience locoregional relapse or develop distant metastases, leading to significant morbidity and, eventually, mortality. This high probability of tumor recurrence after surgery provides the rationale for adjuvant chemotherapy.

[0006] The role of adjuvant chemotherapy in stage III CRC has been supported by large randomized studies performed by the National Surgical Adjuvant Breast and Bowel Project and National Cancer Institute sponsored cooperative groups (NCCN clinical practice guidelines in Oncology. Colon cancer. National comprehensive cancer network. v3-2011). These trials have consistently demonstrated improvement in disease-free and overall survival, which dictates the current standard of care with FOLFOX (the name given to the combination of Folinic acid, Fluorocil, and Oxaliplatin) for stage III CRC.

[0007] It is increasingly recognized that a subset of stage II patients are likely to benefit from adjuvant chemotherapy, and the decision to treat those patients is often made by pooling together the perceived additional clinico-pathological risk factors (Gray R, et al., Adjuvant chemotherapy versus observation in patients with colorectal cancer: a randomised study, Lancet 2007; 370:2020-9). In fact, several high-risk factors, e.g., pT4, vascular or perineural invasion, intestinal obstruction or perforation, poorly differentiated tumors, or less than 12 removed lymph nodes, have been identified. Tumor registry data show that patients with stage II CRC that exhibit these features have a 5-year survival of 60%, similar to the figures obtained in stage III patients and, therefore, adjuvant chemotherapy is usually offered to such patients (NCCN clinical practice guidelines in Oncology. Colon cancer. National comprehensive cancer network. v3-2011).

[0008] Despite the benefits of adjuvant chemotherapy following tumor resection in most non-metastatic CRC patients, there is a subset of patients that will experience tumor recurrence following this treatment. Identification of this subgroup of refractory patients would allow optimizing the therapeutic approach, thus avoiding potential toxicity associated with non-effective drugs and favoring alternative regimens.

[0009] In the last few years, molecular markers have emerged as potential tools for selecting patients that would benefit from adjuvant treatment, thus enabling a more effective and tailored therapy. However, most studies carried out to date have methodological limitations that have prevented meaningful conclusions.

[0010] There is therefore a need for methods that utilize patient gene expression in combination with other patient- specific parameters to predict how a cancer patient will respond to particular treatment regimens, to determine if patients are likely to experience tumor recurrence, and also to predict the likelihood of patient survival while being administered particular treatment regimens. The knowledge provided by these predictions is very useful for determining the future course of treatment best suited to each patient. In particular, there is a need to identify, for example, which CRC patients may benefit the most from adjuvant chemotherapy.

SUMMARY OF THE INVENTION

[0011] In accordance with the foregoing objectives and others, the present invention identifies a unique gene signature, which comprises an assessment of both S100A2 and S100A10 gene expression or expression products thereof, either alone or in combination with other patient factors, in order to predict tumor recurrence and survival of patients having colorectal cancer while on particular treatment regiments, such as adjuvant chemotherapy, thereby influencing the course of treatment in those patients. The gene expression (or protein expression) levels, either alone or in combination with other patient- specific factors, may be considered a gene signature.

[0012] In one aspect, the invention provides methods for treating a human patient diagnosed with cancer, that patient having been treated previously with a first treatment regimen. The method of treatment comprises obtaining a biological sample from the patient, measuring from the sample gene expression levels of S100A2 and S100A10, and determining if the level of gene expression is elevated above a pre-selected level. The method further comprises administering to the patient the first treatment regimen if the levels of S100A2 and S100A10 gene expression are not elevated above the pre-selected level, or administering to the patient a second treatment regimen if the gene expression levels are elevated above the pre-selected level.

[0013] In some embodiments, the patient has colorectal cancer (CRC), and in some embodiments, stage II or II CRC. In some embodiments, the administering step further comprises assessing one or more factors selected from the group consisting of age, gender, and TNM stage, among other patient-specific factors. In one embodiment, the biological sample is a tumor biopsy, and in other embodiments, the biological sample is obtained from a site of surgical resection.

[0014] In some embodiments, the patient has received surgical resection either prior to or in combination with the first treatment regimen. In one embodiment, the first treatment regimen comprises administration of a chemotherapeutic agent. In another embodiment, the first treatment regimen comprises administration of Fluorouracil (5FU) or a pro-drug of 5FU. The first treatment regimen may further comprise radiation therapy. In some embodiments, the first treatment regimen comprises monitoring the progression or recurrence of the patient's cancer, or the patient's tumors with a technique selected from the group consisting of colonoscopy, biopsy, or CT scan.

[0015] The second treatment regimen may comprise administering a reduced dose of

5FU of pro-drug of 5FU, or an increased dose of 5FU or pro-drug of 5FU compared to the dose of 5FU or pro-drug of 5FU administered in the first treatment regimen, or it may comprise a more aggressive chemotherapy regimen, such as the addition of another chemotherapeutic agent or agents, or radiation therapy. The second treatment regimen may further comprise a chemotherapeutic agent in the same class as 5FU, either to replace 5FU, or in addition to 5FU. The second treatment regimen may also include removing administration of 5FU from the treatment regimen. The second treatment regimen may also comprise monitoring the progression or recurrence of the patient's cancer or the patient's tumors, with a technique selected from the group consisting of colonoscopy, biopsy, or CT scan, on a more frequent basis than the monitoring of the patient's cancer or tumors as performed in the first treatment regimen. The second treatment regimen may also be a chemotherapeutic agent from a different class of drug compared to 5FU.

[0016] In another aspect, the invention provides methods for treating a human patient diagnosed with cancer, that patient having been treated previously with a first treatment regimen. The method of treatment comprises obtaining a biological sample from the patient, measuring from the sample gene expression levels of S100A2 and S100A10, and determining if the level of gene expression is elevated above a pre-selected level. The method further comprises generating a risk score based on said gene expression and optionally other patient- specific factors. The method further comprises administering to the patient the first treatment regimen if the risk score is not elevated above a pre-selected level, or administering to the patient a second treatment regimen if the risk score is elevated above the pre-selected level.

[0017] The pre-selected level of gene expression may be determined based on a statistic such as a receiver operator characteristic (ROC) curve, based on a statistic such as a univariate analysis, based on a statistic such as a correlation, or based on a risk score, among other statistical analyses. The risk score may be determined based on a statistic such as a multivariate regression analysis. The patient specific factors may be factors such as those selected from the group consisting of age, gender, and TNM stage.

[0018] In yet another aspect, the invention provides methods for treating a human patient diagnosed with colon cancer, that patient having been treated previously with a first treatment regimen. The method of treatment comprises obtaining a biological sample from the patient, measuring from the sample gene expression levels of S100A2 and SIOOAIO, and comparing the gene expression levels of the patients with expression levels of the same genes in in an average population of colon cancer patients treated with the first treatment regimen. The method further comprises administering to the patient the first treatment regimen if the patient's gene expression levels are not above the level of gene expression of the average population of colon cancer patients treated with the first treatment regimen, or administering to the patient a second treatment regimen if the patient's gene expression levels are above the level of gene expression of the average population of colon cancer patients treated with the first treatment regimen.

[0019] In another aspect of the invention, an assay method is provided, comprising obtaining nucleic acids from a human cellular sample, and determining from the human cellular sample if gene expression levels of S100A2 and SIOOAIO are elevated above a preselected level. In some embodiments the assay further comprises a step of lysing the cells in the cellular sample, such as by contacting the cells with a surfactant or detergent, such as SDS or any others known in the art. In some embodiments, the assay comprises obtaining protein from a human cellular sample and determining from the human cellular sample if protein expression levels of the proteins encoded by S100A2 and SIOOAIO are elevated above a pre-selected level. [0020] In some embodiments, the human cellular sample is obtained from a patient diagnosed with cancer, and in particular, colorectal cancer that is either at stage II or stage III. The human cellular sample may be obtained from, for example, a tumor biopsy or from a site of surgical resection.

[0021] Also provided are methods for predicting tumor recurrence in a patient diagnosed with cancer, for example, with CRC, or with stage II or II CRC, being treated with a first treatment regimen comprising, for example, a chemotherapeutic agent. The chemotherapeutic agent may be 5FU, or a pro-drug thereof. The method may comprise obtaining a biological sample from the patient, and measuring gene expression levels of S100A2 and S100A10 from the sample. The method may further comprise determining if the gene expression levels of S100A2 and S100A10 are elevated above a pre-selected level. In other embodiments, the method may comprise generating a risk score for patient responsiveness to treatment (i.e., likelihood of tumor recurrence and survival), based on gene expression and optionally one or more patient- specific factors selected from the group consisting of age, gender, and TNM stage.

[0022] In another aspect, the invention provides methods for predicting patient survival in a patient diagnosed with cancer, for example, with CRC, or with stage II or II CRC, being treated with a first treatment regimen comprising, for example, a chemotherapeutic agent. The chemotherapeutic agent may be 5FU, or a pro-drug thereof. The method may comprise obtaining a biological sample from the patient, and measuring gene expression levels of S100A2 and S100A10 from the sample. The method may further comprise determining if the gene expression levels of S100A2 and S100A10 are elevated above a pre-selected level. In other embodiments, the method may comprise generating a risk score for patient responsiveness to treatment (i.e., likelihood of tumor recurrence and survival), based on gene expression and optionally one or more patient-specific factors selected from the group consisting of age, gender, and TNM stage.

[0023] The outcome of predicting tumor recurrence or of predicting patient survival may effect a change in treatment course, such as reducing the dose of 5FU administered to a patient compared to that administered in a first treatment regimen, increasing the dose of 5FU compared to that administered in a first treatment regimen, or removing 5FU in a second treatment regimen, if the first treatment regimen comprises administering 5FU to the patient. The second treatment regimen may also comprise administering a different chemotherapeutic agent or agents, or a chemotherapeutic agent in the same class as 5FU, either to replace 5FU or in addition to 5FU, compared to what was administered in a first treatment regimen. The second treatment regimen may also comprise monitoring the progression or recurrence of the patient's cancer or the patient's tumors, with a technique selected from the group consisting of colonoscopy, biopsy, or CT scan, on a more frequent basis than the monitoring of the patient's cancer or tumors as performed in the first treatment regimen.

[0024] Also provided are methods for predicting tumor recurrence or patient survival in a patient diagnosed with cancer, following a treatment regimen, comprising obtaining a biological sample from the patient, extracting nucleic acids from the biological sample, measuring the gene expression of S100A2 and S100A10 from the sample, and correlating the gene expression levels with a likelihood of tumor recurrence, or with a likelihood of survival. In some embodiments, the patient has been diagnosed with stage II or stage III CRC, and the treatment regimen comprises 5FU or a prodrug thereof.

[0025] Also provided are methods for selecting appropriate patients diagnosed with cancer to be treated in clinical trials testing new treatments or new treatment regimens, based on patients' non-responsiveness to standard or current treatment regimens. A treatment regimen can comprise any type of cancer treatment, including, but not limited to chemotherapy, radiation, and surgery, and any combination thereof. Therefore, cancer patients for which there has been a prediction of likelihood of tumor recurrence and/or poor survival likelihood when being administered a particular treatment regimen may be selected as subjects to be tested for new or varied treatment regimens in clinical trials.

[0026] These and other aspects of the invention will become apparent to those skilled in the art after a reading of the following detailed description of the invention, including the figures and appended claims.

BRIEF DESCRIPTION OF THE FIGURES

[0027] FIG. 1. Kaplan-Meier estimates of the probability of being free of tumor recurrence according to the identified gene expression signature. The continuous line represents low-risk patients (RS <1.7), and the dotted line represents high-risk patients (RS >1.7). [0028] FIG. 2. Kaplan-Meier estimates of the probability of being free of tumor recurrence according to the identified gene expression signature in stage II (A) and stage III (B) colon cancer patients. The continuous line represents low-risk patients (RS <1.7), and the dotted line represents high-risk patients (RS >1.7).

[0029] FIG. 3. Provides the 4,723 base pair linear DNA sequence (SEQ ID NO: 1) of

S100 calcium binding protein A2 from homo sapiens; Official symbol: S100A2 (UniGene Hs.516484; OMIM 176993).

[0030] FIG. 4. Provides the 11,329 base pair linear DNA sequence (SEQ ID NO: 2) of S100 calcium binding protein A10 from homo sapiens; Official symbol: S100A10 (UniGene: Hs.143873; OMIM: 114085).

DETAILED DESCRIPTION

[0031] In its broadest sense, the present invention relates to methods for treating cancer, methods for predicting tumor responsiveness to treatment regimens, methods for predicting patient survival, and assay methods comprising the use of specific gene or protein expression values. More specifically, the invention relates to utilizing gene expression levels of S100A2 and S100A10 either alone or in combination, and alone or in combination with other patient-specific factors, to determine the likelihood of tumor recurrence and patient survival following particular treatment regimens. These methods further comprise the potential to alter a patient's treatment regimen based on the outcomes of the predictions and assays, and can aid in a more successful outcome for patients by providing individualized treatment plans. The gene expression values, either alone or in combination with other patient-specific factors may be considered a gene signature.

[0032] In one aspect, the invention provides methods for treating a human patient diagnosed with cancer, that patient having been treated previously with a first treatment regimen. The method of treatment comprises obtaining a biological sample from the patient, measuring from the sample gene expression levels of S100A2 and S100A10, and determining if the levels of gene expression are elevated above a pre-selected level. The method further comprises administering to the patient the first treatment regimen if the levels of S100A2 and S100A10 gene expression are not elevated above the pre-selected level, or administering to the patient a second treatment regimen if the gene expression levels are elevated above the pre-selected level. In some embodiments, the method further comprises predicting the likelihood or risk of tumor recurrence and/or patient survival.

[0033] In some embodiments, the administering step further comprises assessing one or more factors selected from the group consisting of age, gender, and TNM stage.

[0034] In some preferred embodiments, the patient has colorectal cancer (CRC), and in some embodiments, the patient has stage II or II CRC.

[0035] In some embodiments, the patient has received surgical resection either prior to or in combination with the first treatment regimen. In one embodiment, the first treatment regimen comprises administration of a chemotherapeutic agent. In another embodiment, the first treatment regimen comprises administration of Fluorouracil (5FU) or a pro-drug of 5FU. The first treatment regimen may further comprise radiation therapy. In some embodiments, the first treatment regimen comprises monitoring the progression or recurrence of the patient's cancer, or the patient's tumors with a technique selected from the group consisting of colonoscopy, biopsy, or CT scan.

[0036] The second treatment regimen may comprise administering a reduced dose of

5FU of pro-drug of 5FU, or an increased dose of 5FU or pro-drug of 5FU compared to the dose of 5FU or pro-drug of 5FU administered in the first treatment regimen, or it may comprise a more aggressive chemotherapy regimen, such as the addition of another chemotherapeutic agent or agents, or radiation therapy. The second treatment regimen may further comprise a chemotherapeutic agent in the same drug class as 5FU, either to replace 5FU, or in addition to 5FU. The second treatment regimen may also include removing administration of 5FU from the treatment regimen. The second treatment regimen may also comprise monitoring the progression or recurrence of the patient's cancer or the patient's tumors, with a technique selected from the group consisting of colonoscopy, biopsy, or CT scan, on a more frequent basis than the monitoring of the patient's cancer or tumors as performed in the first treatment regimen.

[0037] The pre-selected level of gene expression may be determined based on a statistic such as a receiver operator characteristic (ROC) curve, or any other statistic that can provide a threshold level or cut-off level within a set of data. [0038] In another aspect, the invention provides methods for treating a human patient diagnosed with cancer, that patient having been treated previously with a first treatment regimen. The method of treatment comprises obtaining a biological sample from the patient, measuring from the sample gene expression levels of S100A2 and S100A10, and determining if the level of gene expression is elevated above a pre-selected level. The method further comprises generating a risk score based on said gene expression and optionally other patient- specific factors. The method further comprises administering to the patient the first treatment regimen if the risk score is not elevated above a pre-selected level, or administering to the patient a second treatment regimen if the risk score is elevated above the pre-selected level.

[0039] The risk score may determined based on a univariate regression analysis or a multivariate regression analysis, or both analyses, and may further comprise additional techniques such as ROC curve analyses.

[0040] The invention also provides methods for treating a human patient diagnosed with cancer, the patient having been treated previously with a first treatment regimen. The method of treatment comprises obtaining a biological sample from the patient, measuring from the sample gene expression levels of S100A2 and S100A10, and comparing the gene expression levels of the patients with expression levels of the same genes in in an average population of patients with the same cancer, treated with the first treatment regimen. An average population of colon cancer patients treated with the first regimen may be any group of colon cancer patients, not limited by number, from whom gene expression of S100A2 and S100A10 was measured, for example, after some length of time of treatment with the first treatment regimen. The gene expression from those patients may be measured, and an average obtained. The method further comprises administering to the patient the first treatment regimen if the patient's gene expression levels are not above the level of gene expression of the average population of colon cancer patients treated with the first treatment regimen, or administering to the patient a second treatment regimen if the patient's gene expression levels are above the level of gene expression of the average population of colon cancer patients treated with the first treatment regimen. A patient's gene expression values may be considered above or elevated above the average levels when, for example, the levels are statistically significantly above the average levels (e.g., with a p value of < 0.01 or < 0.05). [0041] In another aspect of the invention, an assay method is provided, comprising obtaining nucleic acids from a human cellular sample, and determining from the human cellular sample if gene expression levels of S100A2 and SIOOAIO are is elevated above a pre-selected level. In some embodiments the assay further comprises a step of lysing the cells in the cellular sample, such as by contacting the cells with a surfactant or detergent, such as SDS or any others known in the art. In some embodiments, the assay comprises obtaining protein from a human cellular sample and determining from the human cellular sample if protein expression levels of the proteins encoded by S100A2 and SIOOAIO are elevated above a pre-selected level. The nucleic acids may be RNA or DNA.

[0042] In some embodiments, the human cellular sample is obtained from a patient diagnosed with cancer, and in particular, from a patient diagnosed with colorectal cancer that is either at stage II or stage III. The human cellular sample may be obtained from, for example, a tumor biopsy or from a site of surgical resection, or from any other biological sample containing cancer cells.

[0043] In another aspect, the invention provides methods for predicting tumor recurrence of for predicting patient survival in a patient diagnosed with cancer, for example, with CRC, or with stage II or II CRC, following or during a first treatment regimen comprising, for example, a chemotherapeutic agent. The chemotherapeutic agent may be 5FU, or a pro-drug thereof. The method may comprise obtaining a biological sample from the patient, and measuring gene expression levels of S100A2 and SIOOAIO from the sample. The method may further comprise determining if the gene expression levels of S100A2 and SIOOAIO are elevated above a pre-selected level. In other embodiments, the method may comprise generating a risk score for patient responsiveness to treatment (e.g., likelihood of tumor recurrence and/or survival), based on gene expression levels and optionally one or more patient- specific factors selected from the group consisting of age, gender, and TNM stage.

[0044] The outcome of predicting tumor recurrence or of predicting patient survival may effect a change in treatment course, such as reducing the dose of 5FU administered to a patient compared to what was administered in a first treatment regimen, increasing the dose of 5FU compared to what was administered in a first treatment regimen, or removing 5FU in a second treatment regimen, if the first treatment regimen comprises administering 5FU to the patient. The second treatment regimen may also comprise administering a different chemotherapeutic agent or agents, or a chemotherapeutic agent in the same class as 5FU, either to replace 5FU or in addition to 5FU. The second treatment regimen may also comprise monitoring the progression or recurrence of the patient's cancer or the patient's tumors, with a technique selected from the group consisting of colonoscopy, biopsy, or CT scan, on a more frequent basis than the monitoring of the patient's cancer or tumors as performed in the first treatment regimen.

[0045] The monitoring of cancer or tumor progression or recurrence according to the methods of the invention can include any form of monitoring, including assessing biomarkers (e.g., tumor markers such as CEA), any form of imaging known to those of skill in the art (e.g., CT scans, MRI scans, PET scans, ultrasound), endoscopy, biopsy, diagnostic laparoscopy, and blood cell measurements.

[0046] In another aspect, the invention provides methods for predicting tumor recurrence or patient survival in a patient diagnosed with cancer, following a treatment regimen, comprising obtaining a biological sample from the patient, extracting nucleic acids (DNA or RNA) from the biological sample, measuring the gene expression of S100A2 and S100A10 from the sample, and correlating the gene expression levels with a likelihood of tumor recurrence, or with a likelihood of survival. In some embodiments, the patient has been diagnosed with stage II or stage III CRC, and the treatment regimen comprises 5FU or a prodrug thereof. Preferably, the nucleic acids are RNA.

[0047] The biological samples used in the methods and assays of the present invention can include any biological sample from a cancer patient, that contains cancer cells, including, for example, tissue that is obtained from a site of surgical resection, or from a tumor biopsy and comprises cancer cells. The type of biopsy performed to obtain the sample will vary depending on the nature of and location of the tumor, which will be readily apparent to those of skill in the art. In addition to tissue samples from an organ, the biological sample may also be blood, plasma, urine, skin, and any other tissue comprising cancer cells such that it can be processed for extraction and measurement of RNA, DNA, or protein. In a preferred embodiment, the biological sample is tissue obtained from a site of surgical resection of the colon or from a tumor biopsy of the colon. [0048] The methods and assays of the present invention relate to treating cancer and predicting outcomes in cancer patients. All types of cancer are contemplated by the invention, and in a preferred embodiment, the cancer is colorectal cancer (CRC) at any stage (i.e., stage I, stage II, stage III, or stage IV). In another preferred embodiment, the cancer is either stage II or stage III CRC.

[0049] Tumor TNM stage is a cancer staging system, according to the American Joint

Committee on Cancer, 7th edition (Edge SB, et al., AJCC Cancer Staging Manual. 7th ed. Springer, 2009), that identifies the extent of a person's cancer. It includes the size of the primary tumor and whether it has invaded nearby tissue ("T"); the degree of spread to regional lymph nodes ("N"); and the presence of distant metastasis ("M"). A patient with cancer at any stage identified by TNM stage is contemplated in the invention.

[0050] Furthermore, patients contemplated by the methods and assays of the invention may have pT4N0 or pT3N0 CRC, and/or may have pT4a or pT4b tumors. Patients contemplated by the methods and assays of the invention may also have vascular or perineural invasion, intestinal obstruction or perforation, or poorly differentiated tumors.

[0051] The cancer may also be gastric cancer, gastrointestinal carcinoma, esophageal adenocarcinoma, or gastric adenocarcinoma. Other non-limiting examples of cancer contemplated by the invention include breast cancer, ovarian cancer, lung cancer (small-cell or non- small-cell), prostate cancer, hepatocellular cancer, pancreatic cancer, cervical cancer, liver cancer, bladder cancer, cancer of the urinary tract, thyroid cancer, renal cancer, carcinoma, melanoma, and brain cancer.

[0052] The invention provides treatment methods, assays, and methods of predicting responsiveness of tumors and other cancers to particular treatment regimens, as well as predicting survival of patients with cancer while being treated with particular treatment regimens. Based on the outcome of the gene expression assays, or of the associations or correlations or comparisons of the invention, or of the risk scores determined, a treatment being administered to a cancer patient may be determined to be the appropriate course of treatment and will be continued, or it may be determined that it is not the appropriate course of treatment, and the treatment course will therefore be discontinued or varied. The treatment may be varied by changing drug dose, changing drugs altogether, adding additional drugs to the regimen, adding or removing radiation therapy, or adding surgery. The invention is not bound by any particular course of treatment, and can be used according to the methods described herein for predicting tumor recurrence likelihood and survival likelihood in response to various treatment regimens, and for treating cancer patients with appropriate treatment regimens based on the gene expression, protein expression, and/or the other factors and methods described herein utilized to determine outcome.

[0053] Various embodiments of the invention comprise treating a human patient diagnosed with cancer, being previously treated with a first treatment regimen. The first treatment regimen may be any treatment regimen appropriate for the type of cancer being treated, whether it involves surgical removal of tumors, chemotherapy, radiation, a specific tumor/cancer progression/recurrence monitoring regimen, or any combination thereof. Based on the outcome of the methods of the invention, the first treatment regimen may either remain the same throughout the patient's therapy, or if indicated by the methods of the invention, the first treatment regimen will be altered, such that the patient receives a second treatment regimen.

[0054] In one embodiment of the invention, the patient has been diagnosed with CRC, and in some preferred embodiments has been diagnosed with stage II or stage III CRS, has undergone surgical resection, and is receiving 5FU therapy as a first treatment regimen; that is the patient is being administered 5FU adjuvant therapy. In another aspect, the patient has not undergone surgical resection, and is receiving 5FU therapy as a first treatment regimen. The first treatment regimen may further comprise radiation therapy. In another embodiment, the patient undergoes surgical resection following 5FU therapy (neo-adjuvant therapy).

[0055] In some embodiments, the first treatment regimen comprises folinic acid, 5FU, and oxaliplatin, either alone or in combination (i.e., the FOLFOX regimen when in combination) in CRC patients that either have or have not undergone surgical resection. In other embodiments, the first treatment regimen comprises irinotecan, leucovorin, and oxaliplatin, either alone or in combination (i.e., the FOLFIRI regimen when in combination) in CRC patients that either have or have not undergone surgical resection. Any of these treatment regimens may further comprise radiation therapy, and/or additional chemotherapeutic agents. Any of these drugs alone or in combination may also be administered in the second treatment regimen. [0056] In other embodiments, the first treatment regimen comprises one or more prodrugs of 5FU, such as capecitabine, tegafur, tegafur-uracil (also known as UFT or UFUR), and S-l (a mixture of the 5FU prodrug tegafur, the dihydropyrimidine dehydrogenase (DPD) inhibitor 5-chloro-2,4-dihydroxypyridine (CDHP), and the phosphoribosyltransferase inhibitor, oxonic acid), or any other 5FU prodrug, in patients that either have or have nor undergone surgical resection, and which can further comprise radiation therapy, additional chemotherapeutic agents and/or surgery. Any of these drugs alone or in combination may also be administered in the second treatment regimen.

[0057] Many patients receive chemotherapy immediately following surgical removal of a tumor, and this approach is commonly referred to as adjuvant therapy. However, chemotherapy can be also administered before surgery, and is referred to as neoadjuvant treatment. Both adjuvant and neoadjuvant treatments are contemplated as treatment regimens according to any of the methods and assays of the invention.

[0058] Gene expression (or expression products thereof) may be measured from a biological sample obtained from a patient at any time throughout the course of a treatment regimen. For example, gene expression may be measured prior to surgical resection, and/or after surgical resection, and/or prior to and/or after a chemotherapeutic agent and/or radiation are administered. Gene expression may also be measured repeatedly in a patient, such that the responsiveness of a tumor to a treatment regimen, and likelihood of survival in response to a treatment regimen are measured over time throughout the course of a treatment regimen. Therefore, the likelihood of tumor recurrence and survival can be determined in a patient when administered any number of treatment regimens so that a comparison of the success of the treatment regimens can be made. Such a comparison can allow the most successful treatments to be administered to a patient.

[0059] Various embodiments of the invention involve determining gene expression from biological samples obtained from patients diagnosed with cancer Expression of any of the genes described herein for use in the invention may be accomplished by any of the many techniques known to those of skill in the art, whether based on measuring DNA, RNA, or any portion thereof, as well as any expression product thereof. Gene expression levels can be determined, for example, by RT-PCR; other PCR-based methods (e.g., differential display, amplified fragment length polymorphism, Beads Array for the detection of gene expression, i.e., BADGE, high coverage expression profiling) microarray; serial analysis of gene expression (SAGE); gene expression analysis by massively parallel signature sequencing (MPSS); immunohistochemistry; and promoter methylation analysis and by any other technique in the art.

[0060] Quantification of mRNA expression from the biological samples of the invention may be performed from various methods known in the art, including, for example, real time quantitative PCR, northern blotting, in situ hybridization, and RNAse protection assays. In a preferred embodiment, gene expression levels are determined using real time quantitative PCR. For example, kinetic reverse transcriptase polymerase chain reaction may be carried out using the Superscript III Platinum One-Step Quantitative RT-PCR System with ROX (Invitrogen, Karlsruhe, Germany) in an ABI PRISM 7900HT (Applied Biosystems). If the source of mRNA is a tumor, mRNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g., formalin-fixed) tissue samples. Methods for RNA extraction and RNA isolation are well known in the art, and any such methods for extracting and isolating RNA may be utilized in the methods and assays of the invention.

[0061] The gene expression levels of certain genes have important predictive value for tumor recurrence and survival of patients diagnosed with cancer, and that are being administered particular treatment regimens. In certain preferred embodiments, when the expression of the genes, S100A2 and S100A10, are elevated above a pre-selected value in a biological sample obtained from a patient, there is an increased likelihood that the patient will have tumor recurrence, and a decreased likelihood of survival. In some embodiments, the expression levels of S100A2 and S100A10 have important predictive value regarding tumor recurrence and survival individually, as well as in combination, and in some embodiments, further in combination with other patient-specific factors, such as age, gender, TNM stage, and gene expression of other genes, such as those described herein.

[0062] Expression of other genes that are useful in the methods and assays of the invention include S100A3 and SPON1. Expression of additional genes that can be useful in the invention are listed in Table 1.

[0063] The expression of portions of the genes described herein may also be used in accordance with the methods and assays of the invention. For example, greater than about 60%, about 70%, about 80%, about 85%, about 90%, about 95%, or about 99% sequence identity to the genes described herein is preferred, and measurement of the expression of those genes with sequence identity to the genes described herein may be used in the methods and assays of the invention. In one embodiment, measurement of the expression of genes having greater than about 60%, about 70%, about 80%, about 85%, about 90%, about 95%, or about 99% sequence identity to S100A2 and S100A10 can be used in the methods and assays of the invention.

[0064] Furthermore, proteomics methods may be used alone or in combination with gene expression measurements, to detect the protein products of the genes useful in the present invention, the levels of which may have predictive value regarding a patient' s tumor recurrence and/or survival. For example, a quantitative immunoassay may be used to measure protein expression. Any methods known in the art to measure and quantify proteins may be used, such as immunohistochemistry and microscopy, Immunoelectrophoresis (e.g., Western blotting), immunoblotting, BLA protein assays, spectrophotometry, and enzyme assays.

[0065] The gene expression of the genes described herein (and the expression of their protein products), and their use in connection with other patient factors, such as age, gender, and TNM stage have predictive and prognostic value, such as being utilized to predict tumor recurrence and predict survival following certain treatment regimens. The broadest aspect of the invention involves measuring gene expression levels from patients diagnosed with cancer, however, further refinements, such as the addition of other patient- specific factors, can strengthen the prognostic value of the methods. Correlating the levels of gene expression with the likelihood of tumor recurrence and with the likelihood of death is also contemplated by the invention, with the addition of other patient- specific factors aiding in the predictive and prognostic value of the methods.

[0066] In some embodiments, a method is provided that comprises measurement of gene expression levels (and/or the expression of their protein products) from patients diagnosed with cancer, and comparing those levels to levels of gene expression of the same genes in an average population of patients diagnosed with the same cancer that have been subject to the same treatment regimen. If gene expression is elevated compared to the average gene expression level, then the patients have an increased likelihood or risk of tumor recurrence and/or death. In such embodiments, the level above which there is an increased likelihood or risk of tumor recurrence or death may be a level that is statistically significantly higher than that of the average population of patients (e.g., with a p value of < 0.01 or < 0.05).

[0067] The methods for assessing the likelihood of tumor recurrence and the likelihood of survival may be based on the many different analyses, with non-limiting examples described herein, either in part, or when various analyses are combined, for example, to generate a risk score (RS). A risk score may be generated such that patients whose risk score is above a pre-selected level (i.e., a threshold or cut-off level) are more likely to have tumor recurrence and are less likely to survive, relative to patients whose risk score is below the pre-selected value. A risk score (RS) may be generated based on a variety of factors, including gene expression (such as the expression levels of S100A2 and S100A10), in order to assess the likelihood of tumor recurrence and the likelihood of survival in patients diagnosed with cancer. The risk score may also comprise a variety of different statistical methods known to those of skill in the art, which can generate a level above which patients are more likely to be at risk of tumor recurrence and at risk of death, relative to patients below that level.

[0068] Gene expression may be measured from a biological sample to assess levels of candidate genes, utilizing for example, PCR methods, normalizing for "housekeeping" or reference genes (e.g., RPL37A and CALM2). The gene expression values may be subject to a receiver operator characteristic (ROC) curve, for example, in order to determine a threshold or cut-off value (i.e., a pre-selected level) for each individual candidate gene, above which the gene expression is associated with an increased risk of the outcome; that is, associated with increased risk of tumor recurrence or with increased risk of death (i.e., reduced survival likelihood). Likewise, gene expression values below the determined threshold or cut-off value (i.e., a pre-selected level) is associated with a lower risk of the outcome; that is, associated with reduced risk of tumor recurrence or increased survival (i.e., lower risk of death). The ROC curve analysis allows the conversion of continuous data to binary data (i.e., dichotomous data). Having the data in binary form allows for the assignment of a standard value to be utilized as dichotomous variables in the final RS formula (e.g., a 1 or a 0, based on being above or below the threshold or cut-off value). Any statistical method that can estimate a discrimination threshold value, or a cut-off value, such as an ROC curve, can be used in the methods of the invention, and can be used to determine the pre- selected level, above which patients are at increased risk of tumor recurrence and death.

[0069] A univariate analysis (for example, a Cox regression analysis, or another suitable statistic based on the specific type of variables utilized) may be performed to determine which of the candidate genes, as well as other patient- specific factors, such as, for example, age, gender, tumor location, MMR status, and TNM stage, can be included in the multivariate regression analysis, which may serve as the basis of the RS calculation. The genes and other factors may be chosen based on which ones are associated with the outcomes of interest, such as tumor recurrence and survival. The univariate analysis can determine which genes or other factors are associated with an increased risk or likelihood of tumor recurrence and which genes or other factors are associated with an increased risk or likelihood of death (i.e., reduced likelihood of survival).

[0070] A multivariate regression analysis (for example, a Cox regression, or another suitable statistic) may be performed utilizing a regression model that contains the candidate genes and may also contain other patient- specific factors that either may influence the outcomes of interest (e.g., tumor recurrence, survival), or which need to be adjusted for (e.g., adjusting for age, gender, and so on). The final multivariate regression model may be built using a Wald statistic (e.g., with a p value of < 0.05), to select the independent variables included in the model, adjusting by, for example, age and gender. The regression coefficient β_; for each variable is obtained from the final multivariate regression analysis, and these regression coefficients may be used in the RS formula. An ROC curve analysis may be performed on the RS in order to determine a threshold value or cut-off (i.e., a pre-selected level) for predicting tumor recurrence or survival.

[0071] The RS may be represented as follows: RS (risk score) = exp∑B_;x_is where i =

1, ..., k index variables, β, represents the coefficient for each variable estimated from the Cox regression model, and x_is the corresponding value for each variable in a given patient.

[0072] A non-limiting example of such an RS generated according to the methods of the invention, wherein the genes S100A2 and S100A10, among other genes, were assessed is as follows: RS = exp(0.7106*5700A2 + 0 .5291*S100A10 + 0.7516*TNM stage - 0.0148*age - 0.2462*gender). In this equation, S100A2 and S100A10 gene expression, TNM stage, and gender were introduced as dichotomous variables (S100A2 expression: >-9.68=l, <-9.68=0; S100A10 expression: >-1.53=l, <-1.53=0; tumor TNM: stage 111=1, stage 11=0; gender: male=l, female=0). In this example, the threshold or cut-off value for determining if patients were at high risk vs. low risk for tumor recurrence, as well as whether patients were at high risk vs. low risk of death, was a RS of 1.7 (i.e., the pre-selected level for RS).

[0073] Gene expression levels (or protein levels, for example), are assessed from a patient as described herein, and the levels may be used in the various methods and assays of the invention, for example, in comparisons to average patient population levels (such as the kind of average populations of particular cancers on particular treatment regimens described herein), correlated to a likelihood of tumor recurrence and survival, or compared to preselected gene expression levels.

[0074] The gene expression levels, for example, may be compared to pre-selected gene expression levels (e.g., as obtained from an ROC curve analysis as described herein), and if the levels exceed the pre-selected gene expression level, then the patient has a higher likelihood of tumor recurrence or of death, than a patient whose levels are below the preselected level. Likewise, the gene expression levels obtained from patients may be used either alone or in combination with other patient- specific factors to provide that patient with a risk score. The patient's risk score may then be compared to a pre-selected risk score level, above which the patient has a higher likelihood of tumor recurrence or of death, and below which the patient has a lower risk of tumor recurrence and death, relative to a patient with a risk score lower than the pre-selected risk score.

[0075] Based on the outcome of the gene expression (or protein expression) measurements of the invention (in addition to the optionally assessed other patient-specific factors), a treatment being administered to a patient diagnosed with cancer may be determined to be the appropriate course of treatment and will be continued, or it may be determined that it is not the appropriate course of treatment, and the treatment course will therefore be discontinued or varied, comprising a second treatment regimen. The second treatment regimen may include several courses of treatment that change over time, based on patient outcomes. That is, the second treatment regimen indicated for a patient based on the methods of the invention may be one more successive treatment regimens. The second treatment regimen may be a variation of the first treatment regimen, such as by changing drug dose, changing drugs altogether, adding additional drugs to the regimen, or adding or removing radiation therapy. The invention is not bound by any particular second regimen that might be selected because a first treatment regimen demonstrated a high risk of tumor recurrence and/or a poor likelihood of survival (i.e., high risk of death).

[0076] In some embodiments, the second treatment regimen comprises radiation therapy that either was not previously administered to a patient in a first treatment regimen, or which comprises increasing or decreasing the dose of radiation administered to said patient. In some embodiments, the second treatment regimen comprises using a chemotherapeutic agent.

EXAMPLES

[0077] The following examples describe specific aspects of the invention to illustrate the invention but should not be construed as limiting the invention, as the examples merely provide specific methodology useful in the understanding and practice of the invention and its various aspects.

EXAMPLE 1

[0078] The following study was performed to identify a gene-expression signature to predict tumor recurrence in patients with stage II and III colorectal cancer (CRC) treated with 5'fluoruracil (5FU)-based adjuvant chemotherapy following tumor resection, the most common treatment regimen used in this setting.

[0079] Patients and methods

[0080] Since 1990, all patients with CRC diagnosed and treated at the Colorectal

Cancer Unit of the Hospital Clinic of Barcelona were prospectively registered in a database including baseline (demographic, clinical, and tumor-related characteristics) and follow-up (primary and secondary treatments, recurrence and survival) data (Rodriguez-Moranta F, Salo J, Arcusa A, et al., Postoperative surveillance in patients with colorectal cancer who have undergone curative resection: a prospective, multicenter, randomized, controlled trial. / Clin Oncol 2006;24:386-93; Soriano A, Castells A, Lacy AM, et al., Evaluation of the efficacy and efficiency of a multidisciplinary unit for the treatment of patients with colorectal cancer, Gastroenterol Hepatol 2002;25:579-84). For this study, we selected consecutive patients with stage II and III colon adenocarcinoma submitted to curative-intent surgical resection from 1998 to 2005, that were receiving 5FU-based adjuvant chemotherapy, and with complete follow-up in our Unit. Exclusion criteria were personal or family history of polyposis or Lynch syndromes, personal history of inflammatory bowel disease, Rl or R2 resections (microscopic or macroscopic neoplastic involvement of surgical margins, respectively), and lack of available FFPE block. Patients with rectal cancer were intentionally excluded since the therapeutic approach usually differs from the one employed in patients with colon cancer. The study was approved by the institutional Ethics Committee of the hospital.

[0081] Demographic, clinical and tumor-related parameters included: age at diagnosis, gender, tobacco habit, personal and family history of neoplasia, presenting symptoms, baseline serum carcinoembryonic antigen concentration, presence of synchronous colorectal neoplasms, tumor location and size, histological type and grade, presence of vascular and/or perineural infiltration, perforation, microscopic tumor extension, pathologic TNM stage (American Joint Committee on Cancer, AJCC/UICC TNM, 7th edition) and treatment.

[0082] RNA extraction from formalin-fixed, paraffin-embedded tissue samples

[0083] Hematoxilin and eosin slides and FFPE blocks of all patients included in the study were retrieved from the Pathology Department archives. All slides were re-evaluated by a unique pathologist. Samples were obtained from tumors from patients during surgical resection of the colon.

[0084] Four 10 μΜ thick slices were obtained from each FFPE block and used to isolate total nucleic acids using a fully automated method of iron oxide beads coated with a nanolayer of silica on a modified VERSANT^® kPCR Molecular System (Siemens Healthcare Diagnostics, Tarrytown, NY)(Bohmann K, Hennig G, Rogel U, et al. RNA extraction from archival formalin-fixed paraffin-embedded tissue: a comparison of manual, semiautomated, and fully automated purification methods. Clin Chem 2009;55: 1719-27; Hennig G, Gehrmann M, Stropp U, et al. Automated extraction of DNA and RNA from a single formalin-fixed paraffin-embedded tissue section for analysis of both single-nucleotide polymorphisms and mRNA expression. Clin Chem 2010;56: 1845-53). Briefly, FFPE sections were heat lysed for 30 minutes at 80°C followed by 30 minutes at 65°C in the presence of proteinase K and detergent. Residual debris was removed from the lyses fluid through unspecific binding to silica-coated iron oxide beads. Beads were subsequently separated on a magnet and lysates were transferred to a 2-mL deep-well plate. During magnetization, the melted paraffin separated and formed a ring around the tube wall via hydrophobic interactions. Total RNA and DNA were bound to a fresh volume of beads under chao tropic conditions in the deep-well plate. Then, beads were magnetically separated and supernatants were discarded. Surface-bound nucleic acids were washed 3 times and eluted by incubation of the beads with 100 μΐ_^ of elution buffer for 10 minutes at 70°C with shaking. Subsequently, a modified automated pipetting protocol was programmed, which allowed splitting of the 100 μΐ_^ of eluate into 2 aliquots of 50 μΐ_^ each. One aliquot containing total nucleic acid was separated from the beads and collected into a 96-place rack of 0.75-mL round-bottom tubes. The second 50 μΐ_^ was incubated in 2-mL deep-well plates with 12 μL· of DNase I mix (Applied Biosystems, Darmstadt, Germany) to remove genomic DNA for subsequent mRNA expression analysis. After incubation for 30 minutes at 37°C, DNA-free total RNA solution was obtained and collected in the same collection plate as was used for the undigested fraction (second 48 wells) and stored at -80°C until analysis.

[0085] Gene expression analysis

[0086] Target genes selected for analysis are presented below in Table 1.

Table 1

[0087] Relative expression of evaluated genes, as well as expression of the genes,

RPL37A and CALM2, used for normalization, was assessed in triplicate by kinetic reverse transcriptase polymerase chain reaction using the Superscript III Platinum One-Step Quantitative RT-PCR System with ROX (Invitrogen, Karlsruhe, Germany) in an ABI PRISM 7900HT (Applied Biosystems). Relative expression levels of selected genes were calculated for each sample as ACt values [ACt = Ct of target gene - geometric average Ct of the two control genes] . [0088] Mismatch repair status assessment

[0089] Mismatch repair (MMR) status, a molecular characteristic associated with tumor response to 5FU (Jover R et al., Mismatch repair status in the prediction of benefit from adjuvant fluorouracil chemotherapy on colorectal cancer, Gut 2006;55:848-855) was initially assessed by microsatellite instability testing. For this purpose, tumor DNA was extracted from FFPE tissue samples using the previously mentioned method to isolate total nucleic acids. Microsatellite instability status was assessed using five mononucleotide markers (Xicola RM et al., Performance of different microsatellite marker panels for detection of mismatch repair-deficient colorectal tumors, J Natl Cancer Inst 2007; 99:244-52) BAT25, BAT26, NR21, NR24 and MON027 (MSI Analysis System, Version 1.2 Promega, Madison, WI) according to the manufacturers' instructions. PCR products were analyzed in the 3130 Genetic Analyzer (Applied Biosystems). Tumors with instability at >3 of these markers were classified as microsatellite unstable and those showing instability at <2 markers were classified as microsatellite stable.

[0090] In cases with inconclusive results, immuno staining for MMR proteins was performed. For this purpose, tumor tissue was evaluated using mouse monoclonal antibodies anti-MLHl, anti-MSH2, anti-MSH6 and anti-PMS2 (BD PharMingen, San Diego, CA), according to standard protocols (Pinol V et al., Accuracy of revised Bethesda guidelines, microsatellite instability, and immunohistochemistry for the identification of patients with hereditary nonpolyposis colorectal cancer, JAMA 2005;293: 1986-94). Tumor cells were considered to be negative for protein expression only if they lacked staining in a sample in which healthy colonocytes, lymphocytes and stromal cells were stained. If no immuno staining of healthy tissue could be repeatedly demonstrated, the results were considered undetermined.

[0091] Statistical methods

[0092] Probability of tumor recurrence was calculated from surgical resection to confirmation of either locoregional relapse and/or distant metastases. Development of metachronous colorectal lesions was not considered. Patients without tumor recurrence were censored at the last follow-up contact. Overall survival was calculated from surgical resection to death. Patients alive were censored at the last follow-up contact. [0093] Initially, expression values of evaluated genes were subject to a receiver operator characteristic (ROC) curve analysis in order to choose an individual threshold for each gene. The cut-off value was selected to minimize the distance between the curve and the upper left corner of the graph (Zhou XH, et al., Statistical methods in diagnostic Medicine. Wiley, 2002). Thus, continuous data were converted to binary form. Univariate Cox regression analysis was performed on each covariate to examine its influence on tumor recurrence, computing hazard ratios (HR) with the corresponding 95% confidence interval (95% CI). Thereafter, a multivariate stepwise Cox regression analysis was performed by including all variables achieving a p value <0.2 in the univariate analysis. A Wald statistic p value <0.05 was used as the criterion for selecting independent variables and including them in the final multivariate model, adjusting by age and gender. Both univariate and multivariate Cox proportional hazards were performed using the coxph function from Survival R Package.

[0094] After establishing the multivariate model, a risk score (RS) was calculated for each patient according to the general form RS (risk score) = exp∑B_;¾ where i = 1, k index variables, β_; represents the coefficient for each variable estimated from the Cox regression model, and x_« the corresponding value for each variable in a given patient. RS was subjected to a ROC analysis in order to choose the most appropriate threshold for predicting tumor recurrence. For this approach, specificity was prioritized over sensitivity. Thereafter, Kaplan-Meier curves were generated using the selected cut-off point and compared according to the log-rank test.

[0095] Finally, robustness of the mathematical algorithm resulting from the multivariate analysis was evaluated by bootstrapping with 1,000 resamples (Pencina MJ et al., Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation. Statistics in Medicine 2004; 23:2109-2123). For this purpose, validate function from RMS Package was used and the concordance index was computed.

[0096] Results

[0097] During the study period, 228 patients diagnosed with stage II (78 patients) and

III (150 patients) colon cancer and treated with surgical resection and 5FU-based adjuvant chemotherapy were included. Demographic, clinical and tumor- related characteristics are shown in Table 2 below. Table 2

CEA = carcinoembryonic antigen.

Expressed as mean + standard deviation

Tumor TNM stage, according to the American Joint Committee on Cancer, 7th edition (Edge SB, et al., AJCC Cancer Staging Manual. 7th ed. Springer, 2009)

Tumor location, defined as proximal or distal according to the splenic flexure.

[0098] After a median follow-up of 42 months (range, 6 to 152 months), 79 patients

(34.8%) exhibited tumor recurrence, either as locoregional relapse (8 patients) or distant metastases (71 patients). Moreover, at the end of this period, 57 patients (25.0%) had died, 48 of them (84.2%) due to colon cancer.

[0099] RNA was successfully extracted and correctly analyzed for target genes from all FFPE tissue samples taken from patients.

[00100] Univariate Cox regression analysis identified tumor TNM stage (HR, 1.99;

95% CI, 1.21-3.28; p=0.007), SIOOAIO (HR, 1.78; 95% CI, 1.14-2.77; p=0.01), S100A2 (HR, 1.99; 95% CI, 1.17-3.42; p=0.01), S100A3 (HR, 1.67; 95% CI, 1.03-2.69; p=0.03), and SPON1 (HR, 1.64; 95%C1, 1.01-2.66; p=0.04) as predictors of tumor recurrence. The results of the univariate analysis of predictors of tumor recurrence are presented in Table 3 below. Table 3

CASP4 5.719 1.035 0.664-1.611 0.880

MMP1 6.571 0.980 0.623-1.539 0.929

MMP12 5.778 0.989 0.625-1.563 0.961

CD68 6.633 0.992 0.634-1.552 0.971

MMR, mismatch repair; HR, hazard ratio; 95% CI, 95% confidence interval.

Tumor TNM stage, according to the American Joint Committee on Cancer, 7th edition (Edge SB, et al., AJCC Cancer Staging Manual. 7th ed. Springer, 2009)

Tumor location, defined as proximal or distal according to the splenic flexure.

[00101] After including the above-mentioned predictors, as well as those genes achieving near significance in the univariate analysis (i.e., OAZ1, ABCC6, S100A4, and CXCL9) in the multivariate stepwise regression analysis, adjusted by age and gender, only tumor stage, S100A2 and SIOOAIO gene expression were identified as independently associated with tumor recurrence. See Table 4 below.

Table 4

HR, hazard ratio; 95% CI, 95% confidence interval.

Adjusted by age and gender

Tumor TNM stage, according to the American Joint Committee on Cancer, 7th edition (Edge SB, et al., AJCC Cancer Staging Manual. 7th ed. Springer, 2009)

[00102] The risk score (RS) was calculated for each patient according to the following mathematical algorithm: RS = exp(0.7106*5700A2 + 0 .5291*S100A10 + 0.7516*TNM stage - 0.0148*age - 0.2462* gender). In this equation, S100A2 and SIOOAIO gene expression, TNM stage, and gender were introduced as dichotomous variables (S100A2 expression: >- 9.68=1, <-9.68=0; SIOOAIO expression: >-1.53=l, <-1.53=0; tumor TNM: stage 111=1, stage 11=0; gender: male=l, female=0). The median value of this RS was 1.04 (range, 0.23-4.35). Thereafter, a ROC analysis allowed us to select a cut-off value of 1.70 to classify patients in a high-risk group (47 patients, 20.6%) and a low-risk group (181 patients, 79.4%) for tumor recurrence (specificity, 0.86). Figure 1 depicts Kaplan-Meier curves generated using the selected cut-off point. As it is shown, risk score generated by the multivariate model was able to discriminate two groups with a highly significant different probability of tumor recurrence (HR, 2.75; 95% CI, 1.71-4.39; p=0.0001). Moreover, importantly, when patients were stratified according to tumor stage, the risk score continued discriminating two subgroups of different probability of relapse in both stage II (HR, 5.21; 95% CI, 2.48-10.95; p=0.0001) and III (HR, 1.85; 95% CI, 1.02-3.47; p=0.05) colon cancer patients (Figure 2).

[00103] Although it did not constitute a primary outcome, accuracy of the risk score was also evaluated regarding the probability of being a predictor of overall survival. Using the same cut-off point, the mathematical algorithm was also able to distinguish two groups with significantly different overall survival (HR, 2.68; 95% CI, 1.12-6.42; p=0.03).

[00104] Finally, robustness of the mathematical model was evaluated by bootstrapping with 1000 re-samples, obtaining a C-index of 0.6239.

[00105] The results of this study demonstrate that S100A2 and S100A10 gene expression, as well as TNM stage, independently predict tumor recurrence in patients with stage II and III colon cancer after 5FU-based adjuvant chemotherapy. This gene signature, along with tumor TNM stage, provides a robust, easy-to-use and reliable mathematical formula to identify a subgroup of patients with higher probability of tumor relapse and shorter survival that may eventually benefit from a different therapeutic regimen, such as a different or more aggressive therapeutic regimen, as well as more intensive surveillance.

[00106] All references including patent applications and publications cited herein are incorporated herein by reference in their entirety and for all purposes to the same extent as if each individual publication or patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety for all purposes. Many modifications and variations of this invention can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. The specific embodiments described herein are offered by way of example only, and the invention is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

CLAIMS What is claimed:

1. A method for treating a human patient diagnosed with cancer, said patient being previously treated with a first treatment regimen, said method comprising:

(a) obtaining a biological sample from said patient;

(b) measuring from said biological sample gene expression levels of S100A2 and S100A10, and determining if said levels are elevated above a pre-selected level; and

(c) administering to said patient (1) said first treatment regimen if said gene expression levels are not elevated above said pre-selected level, or (2) a second treatment regimen if said gene expression levels are elevated above said pre-selected level.

2. The method according to claim 1, wherein said patient has stage II or stage III colon cancer.

3. The method according to claim 1, wherein said administering step further comprises assessing one or more patient- specific factors selected from the group consisting of age, gender, and TNM stage.

4. The method according to claim 1, wherein said biological sample is a tumor biopsy.

5. The method according to claim 1, wherein said biological sample is obtained from a site of surgical resection.

6. The method according to claim 1, wherein said first treatment regimen comprises administration of a chemotherapeutic agent.

7. The method according to claim 6, wherein said chemotherapeutic agent is Fluorouracil or a pro-drug thereof.

8. The method according to claim 7, wherein said second treatment regimen comprises administering a reduced dose of Fluorouracil or pro-drug thereof, relative to the dose of Fluorouracil or pro-drug thereof administered in said first treatment regimen.

9. The method according to claim 1, wherein said first treatment regimen comprises monitoring progression or recurrence of said patient's cancer with a technique selected from the group consisting of colonoscopy, biopsy, and CT scan.

10. The method according to claim 1, wherein said second treatment regimen comprises increasing frequency of said monitoring of said patient's cancer, compared with the monitoring in said first treatment regimen.

11. The method according to claim 1, wherein said pre-selected level is determined based on a receiver operator characteristic curve.

12. A method for treating a human patient diagnosed with cancer, said patient being previously treated with a first treatment regimen, said method comprising:

(a) obtaining a biological sample from said patient;

(b) measuring from said biological sample gene expression levels of S100A2 and S100A10, and determining if said levels are elevated above a pre-selected level;

(c) generating a risk score based on said gene expression and optionally additional patient-specific factors; and

(d) administering to said patient (1) said first treatment regimen if said risk score is not above a pre-selected level, or (2) a second treatment regimen if said risk score is above a pre-selected level.

13. The method according to claim 12, wherein said additional patient-specific factors are selected from the group consisting of age, gender, and TNM stage.

14. The method according to claim 12, wherein said patient has stage II or stage III colon cancer.

15. The method according to claim 12, wherein said biological sample is a tumor biopsy.

16. The method according to claim 12, wherein said biological sample is obtained from a site of surgical resection.

17. The method according to claim 12, wherein said first treatment regimen comprises administration of a chemotherapeutic agent.

18. The method according to claim 17, wherein said chemotherapeutic agent is Fluorouracil or a pro-drug thereof.

19. The method according to claim 18, wherein said second treatment regimen comprises administering a reduced dose of Fluorouracil or pro-drug thereof, relative to the dose of Fluorouracil or pro-drug thereof administered in said first treatment regimen.

20. The method according to claim 12, wherein said first treatment regimen comprises monitoring progression or recurrence of said patient's cancer with a technique selected from the group consisting of colonoscopy, biopsy, and CT scan.

21. The method according to claim 12, wherein said second treatment regimen comprises increasing frequency of said monitoring of said patient's cancer, compared with the monitoring in said first treatment regimen.

22. The method according to claim 12, wherein said risk score is determined based on a multivariate regression analysis.

23. A method for treating a human patient diagnosed with colorectal cancer, said patient being previously treated with a first treatment regimen, said method comprising:

(a) obtaining a biological sample from said patient;

(b) measuring from said biological sample gene expression levels of S100A2 and S100A10; (c) comparing said gene expression levels with average gene expression levels of S100A2 and S100A10 in patients diagnosed with colorectal cancer and treated with said first treatment regimen; and

(d) administering to said patient (1) said first treatment regimen if said patient's gene expression levels are not above said average gene expression levels, or (2) a second treatment regimen if said patient's gene expression levels are above said average gene expression levels.

24. An assay method comprising:

(a) obtaining nucleic acids from a human cellular sample; and

(b) determining from said human cellular sample if gene expression levels of S 100A2 and S100A10 are elevated above a pre-selected level.

25. The assay method according to claim 24, wherein said human cellular sample is obtained from a patient having colorectal cancer.

26. The assay method according to claim 24, wherein said cellular sample is further contacted with a surfactant that lyses cells in said sample.

27. A method for predicting tumor recurrence and/or patient survival in response to a treatment regimen in a patient diagnosed with cancer, said method comprising:

(a) obtaining a biological sample from said patient;

(b) extracting nucleic acids from said biological sample;

(c) measuring gene expression levels of S100A2 and S100A10 from said extracted nucleic acids; and

(d) correlating said gene expression levels with likelihood of tumor recurrence and/r patient survival.

28. The method of claim 27 further comprising correlating said gene expression levels with likelihood of survival.

29. The method according to claim 27, wherein said patient has stage II or stage III colon cancer.

30. The method according to claim 27, wherein the treatment regimen comprises administration of a chemotherapeutic agent.

31. The method according to claim 30, wherein said chemotherapeutic agent is Fluorouracil or a pro-drug thereof.