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WO2013071066A1 - Signatures associées à la sensibilité vis-à-vis d'une thérapie de cancer - Google Patents

Signatures associées à la sensibilité vis-à-vis d'une thérapie de cancer Download PDF

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Publication number
WO2013071066A1
WO2013071066A1 PCT/US2012/064392 US2012064392W WO2013071066A1 WO 2013071066 A1 WO2013071066 A1 WO 2013071066A1 US 2012064392 W US2012064392 W US 2012064392W WO 2013071066 A1 WO2013071066 A1 WO 2013071066A1
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Prior art keywords
responsemarkers
cancer
cancer cell
level
effective amount
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WO2013071066A8 (fr
Inventor
Michelle Palmer
Jose R. PEREZ
Leigh C. CARMODY
Piyush Gupta
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Broad Institute Inc
Whitehead Institute for Biomedical Research
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Broad Institute Inc
Whitehead Institute for Biomedical Research
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates generally to the identification of biomarkers and methods of using such biomarkers to identify responsiveness to therapy of a subject having cancer.
  • CSCs Cancer stem cells
  • the invention is based upon the discovery that certain signature genes referred to herein as RESPONSEMARKERS are associated with responsiveness to cancer therapy.
  • the invention features methods of assessing the effectiveness of a treatment regimen of a subject having a cancer by detecting the level of an effective amount of one or more RESPONSEMARKERS in a sample from the subject and comparing the level of the effective amount of the one or more RESPONSEMARKERS to a reference value.
  • the cancer is breast cancer.
  • the invention also features methods of monitoring a treatment regimen of a subject with cancer by detecting the level of an effective amount of one or more
  • the cancer is breast cancer.
  • the invention further features methods of determining whether a subject with cancer would derive a benefit from a treatment regimen by detecting the level of an effective amount of one or more RESPONSEMARKERS and comparing the level of the effective amount of one or more RESPONSEMARKERS detected in the first step to a reference value.
  • the invention further features methods of identifying a biological target by identifying one or more RESPONSEMARKERS that are differentially expressed in cancer cell or cancer stem cell compared to a non-cancer cell to produce a gene target listand identifying one or more genes on said target list that is associated with toxicity against the cancer cell or cancer stem cell. Also included are methods of identifying a compound that modulates the expression or activity of the biological target identified by contacting a cell with a test compound and detecting modulation of the expression or activity of the biological target.
  • the invention further features methods of screening for a compound that induces cancer cell death and/or inhibits cancer cell proliferation by detecting the level of an effective amount of one or more RESPONSEMARKERS in a cell that has been contacted with the compound, and comparing the level of the effective amount of one or more RESPONSEMARKERS listed in any one of Tables 1-10, where a similarity of the level of the RESPONSEMARKERS detected in the first step with the level of
  • RESPONSEMARKERS listed in Tables 1-10 indicates that the compound induces cancer cell death and/or inhibits cancer cell proliferation.
  • the invention further provides methods of screening for a test compound that induces cancer cell death and/or inhibits cancer cell proliferation by detecting the level of an effective amount of one or more RESPONSEMARKERS in a cell that has been contacted with the test compound, and comparing the level of the effective amount of one or more RESPONSEMARKERS in a cell that has been treated with a reference compound, where the similarity of the level of the RESPONSEMARKERS detected in step (a) with the level of RESPONSEMARKERS in the cell treated with the reference compound indicates that the test compound induces cancer cell death and/or inhibits cancer cell proliferation.
  • the reference compound is ML239, ML245, ML243 or CID50904149 (an analogue of ML 245).
  • the cancer cell is a cancer stem cell.
  • the treatment regimen is ML239 and the one or more RESPONSEMARKERS are selected from Tables 1 or 2. In some aspects, the treatment regimen is ML245 and the one or more RESPONSEMARKERS are selected from Tables 3 and 4. In other aspects, the treatment regimen is ML243 and the one or more
  • RESPONSEMARKERS are selected from Tables 5 and 6.
  • the treatment regimen is CID50904149 (an analogue of ML 245) and the one or more
  • RESPONSEMARKERS are selected from Tables 7 and 8.
  • the treatment regimen is salinomycin and the one or more RESPONSEMARKERS are selected from Tables 9 and 10.
  • the invention disclosed herein also provides methods of treating or alleviating a symptom of cancer comprising administering a compound that modulates the expression of one or more RESPONSEMARKERS.
  • the invention further provides methods of treating or alleviating a symptom of cancer comprising administering a compound that modulates the expression of one or more genes in the NF- ⁇ pathway.
  • the RESPONSEMARKERS include, but are not limited to, at least one selected from the group comprising: ALDH1L2, ASNS, C10RF24, CBS, CDKN1A, EIF1, FBX032, GDF15, HERPUD1, HSPA5, LOC729779, MTHFD2, NCRNA00219, P8, PCK2, PSATl, RND3, SLC7A1, SNHG8, SQSTMl, and TRIB3.
  • the cancer is a breast cancer.
  • Figure 1 is a plot depicting the cancer stem cell- selective toxicity of compounds to HMLE_sh_ECad cells. Each compound was tested in duplicate and were highly correlated. The signal was normalized to neutral (DMSO) and positive
  • FIG. 2 is two graphs showing the representative dose curve data for ML239.
  • sh_ECad HMLE_sh_GFP
  • sh_Twist HMLE_sh_Twist
  • Figure 4 shows the gene expression profiling and characterizaing of identified RESPONSEMARKERS in HMLE_sh_ECad cells.
  • A Measurement of gene expression in response to treatment with ML239. Upregulated genes (black, right side of graph); downregulated genes (grey, left side of graph).
  • B 24 genes were identified with highest significant changes (p>0.005) with more than 2.5-fold change in expression.
  • C C
  • Ingenuity Network analysis was performed on the 24 genes from (B) to identify the pathways associated with the affected genes. Genes identified in the screen (solid lines); other known members of the pathway not identified in the screen (dotted lines).
  • the present invention relates to the identification of signatures associated with responsiveness to cancer therapy.
  • CSCs Cancer stem cells
  • ML239 Cancer stem cells
  • CID50904134 also referred to herein as ML245, CID50910523 (also referred to herein as ML243), CID50904149 (also referred to herein as Analog of ML245)
  • CID5417654 also referred to herein as Analog of ML239
  • CID24816775 also referred to herein as Analog of ML239
  • Salinomycin is represented by Formula I below:
  • ML239 is represented by Formula II below:
  • ML245 is represented by Formula III below:
  • ML243 is represented by Formula IV below:
  • CID5417654 is represented by Formula VI below:
  • CID24816775 is represented by Formula VII below:
  • RESPONSEMARKERS can include, but are not limited to, the nucleic acids or polypeptide sequences of: ALDH1L2, ASNS, C10RF24, CBS, CDKN1A, EIF1, FBX032, GDF15, HERPUD1, HSPA5, LOC729779, MTHFD2, NCRNA00219, P8, PCK2, PSAT1, RND3, SLC7A1, SNHG8, SQSTM1, and TRIB3.
  • RESPONSEMARKERS are useful for monitoring subjects undergoing treatments and therapies for cancer, and for assessing therapies and treatments that would be efficacious in subjects having cancer, wherein selection and use of such treatments and therapies slow the progression of the tumor, or substantially delay or prevent its onset, or reduce or prevent the incidence of tumor metastasis.
  • RESPONSEMARKERS are also useful for screening and identifying compounds that inhibit cancer cell proliferation or induce cancer cell death.
  • TP true positives
  • TN true negatives
  • FP false negatives
  • FN false negatives
  • Biomarker in the context of the present invention encompasses, without limitation, proteins, nucleic acids, and metabolites, together with their polymorphisms, mutations, variants, modifications, subunits, fragments, protein-ligand complexes, and degradation products, protein-ligand complexes, elements, related metabolites, and other analytes or sample-derived measures. Biomarkers can also include mutated proteins or mutated nucleic acids. Biomarkers also encompass non-blood borne factors or non- analyte physiological markers of health status, such as "clinical parameters" defined herein, as well as “traditional laboratory risk factors”, also defined herein.
  • Biomarkers also include any calculated indices created mathematically or combinations of any one or more of the foregoing measurements, including temporal trends and differences. Where available, and unless otherwise described herein, biomarkers which are gene products are identified based on the official letter abbreviation or gene symbol assigned by the international Human Genome Organization Naming Committee (HGNC) and listed at the date of this filing at the US National Center for Biotechnology Information (NCBI) web site.
  • HGNC Human Genome Organization Naming Committee
  • NCBI National Center for Biotechnology Information
  • RESPONSEMARKER OR “RESPONSEMARKERS” encompass one or more of all nucleic acids or polypeptides whose levels are changed in a subject in response to a therapy.
  • Individual RESPONSEMARKERS are collectively referred to herein as, inter alia, “response-associated proteins” "response-associated polypeptides", “RESPONSEMARKER polypeptides”, or “RESPONSEMARKER proteins”.
  • the corresponding nucleic acids encoding the polypeptides are referred to as “response- associated nucleic acids", “response-associated genes", “RESPONSEMARKER nucleic acids”, or “RESPONSEMARKER genes”. Unless indicated otherwise,
  • RESPONSEMARKER “response-associated proteins”, “response -associated nucleic acids” are meant to refer to any of the biomarkers disclosed herein, e.g, Tables 1-10.
  • RESPONSEMARKERS include, but are not limited to, the nucleic acids or polypeptide sequences of: ALDH1L2, ASNS, C10RF24, CBS, CDKN1A, EIF1,
  • an appropriate number of RESPONSEMARKER (which may be one or more) is different than the predetermined cut-off point (or threshold value) for that RESPONSEMARKER(S) and therefore indicates a particular phenotype.
  • the measurement of an appropriate number of RESPONSEMARKER encompasses an increase or decrease in expression level of at least one nucleic acid or polypeptide RESPONSEMARKER sequence compared to a reference value.
  • an effective amount of RESPONSEMARKER encompasses the gene signature that is indicative of a particular phenotype.
  • a phenotype may be, for example, a particular stage of cancer, or a particular response to a cancer treatment regimen or administration of a compound.
  • the gene signature may be a gene or set of genes that indicates teatment/administration of the compound.
  • the gene signature is gene or set of genes that indicates a particular stage of a cancer, such as breast cancer or metastasis.
  • the gene signature is a gene or set of genes that indicate a particular response to a cancer therapeutic regimen.
  • a "clinical indicator” is any physiological datum used alone or in conjunction with other data in evaluating the physiological condition of a collection of cells or of an organism. This term includes pre-clinical indicators.
  • “Clinical parameters” encompasses all non-sample or non-analyte biomarkers of subject health status or other characteristics, such as, without limitation, age (Age), ethnicity (Race), gender (Sex), or family history (FamHX).
  • FN is false negative, which for a disease state test means classifying a disease subject incorrectly as non-disease or normal.
  • FP is false positive, which for a disease state test means classifying a normal subject incorrectly as having disease.
  • a “formula,” “algorithm,” or “model” is any mathematical equation, algorithmic, analytical or programmed process, or statistical technique that takes one or more continuous or categorical inputs (herein called “parameters”) and calculates an output value, sometimes referred to as an "index” or “index value.”
  • Parameters continuous or categorical inputs
  • Non-limiting examples of “formulas” include sums, ratios, and regression operators, such as coefficients or exponents, biomarker value transformations and normalizations
  • biomarkers include, without limitation, those normalization schemes based on clinical parameters, such as gender, age, or ethnicity
  • rules and guidelines including, without limitation, those normalization schemes based on clinical parameters, such as gender, age, or ethnicity
  • statistical classification models include neural networks trained on historical populations.
  • neural networks trained on historical populations.
  • biomarkers are linear and non-linear equations and statistical classification analyses to determine the relationship between biomarkers detected in a subject sample and the subject's responsiveness to chemotherapy.
  • AIC Akaike's Information Criterion
  • BIC Bayes Information Criterion
  • the resulting predictive models may be validated in other studies, or cross- validated in the study they were originally trained in, using such techniques as Bootstrap, Leave-One-Out (LOO) and 10-Fold cross-validation (10-Fold CV).
  • LEO Leave-One-Out
  • 10-Fold cross-validation 10-Fold CV.
  • false discovery rates may be estimated by value permutation according to techniques known in the art.
  • a "health economic utility function" is a formula that is derived from a combination of the expected probability of a range of clinical outcomes in an idealized applicable patient population, both before and after the introduction of a diagnostic or therapeutic intervention into the standard of care.
  • a cost and/or value measurement associated with each outcome, which may be derived from actual health system costs of care (services, supplies, devices and drugs, etc.) and/or as an estimated acceptable value per quality adjusted life year (QALY) resulting in each outcome.
  • the sum, across all predicted outcomes, of the product of the predicted population size for an outcome multiplied by the respective outcome's expected utility is the total health economic utility of a given standard of care.
  • the difference between (i) the total health economic utility calculated for the standard of care with the intervention versus (ii) the total health economic utility for the standard of care without the intervention results in an overall measure of the health economic cost or value of the intervention.
  • This may itself be divided amongst the entire patient group being analyzed (or solely amongst the intervention group) to arrive at a cost per unit intervention, and to guide such decisions as market positioning, pricing, and assumptions of health system acceptance.
  • Such health economic utility functions are commonly used to compare the cost-effectiveness of the intervention, but may also be transformed to estimate the acceptable value per QALY the health care system is willing to pay, or the acceptable cost-effective clinical performance characteristics required of a new intervention.
  • a health economic utility function may preferentially favor sensitivity over specificity, or PPV over NPV based on the clinical situation and individual outcome costs and value, and thus provides another measure of health economic performance and value which may be different from more direct clinical or analytical performance measures.
  • Inhibit as used herein, in reference to cancer stem cells, encompasses inhibiting, decreasing, preventing, or reducing the growth, proliferation, size, activity, or metastatic potential.
  • Inhibiting cancer stem cells can also mean killing, either directly or indirectly, cancer stem cells, i.e. by apoptosis or immunologic response.
  • Measurement or “measurement,” or alternatively “detecting” or “detection,” means assessing the presence, absence, quantity or amount (which can be an effective amount) of either a given substance within a clinical or subject-derived sample, including the derivation of qualitative or quantitative concentration levels of such substances, or otherwise evaluating the values or categorization of a subject's non-analyte clinical parameters.
  • NDV Neuronal predictive value
  • hazard ratios and absolute and relative risk ratios within subject cohorts defined by a test are a further measurement of clinical accuracy and utility.
  • Analytical accuracy refers to the reproducibility and predictability of the measurement process itself, and may be summarized in such measurements as coefficients of variation, and tests of concordance and calibration of the same samples or controls with different times, users, equipment and/or reagents. These and other considerations in evaluating new biomarkers are also summarized in Vasan, 2006.
  • Performance is a term that relates to the overall usefulness and quality of a diagnostic or prognostic test, including, among others, clinical and analytical accuracy, other analytical and process characteristics, such as use characteristics (e.g., stability, ease of use), health economic value, and relative costs of components of the test. Any of these factors may be the source of superior performance and thus usefulness of the test, and may be measured by appropriate "performance metrics," such as AUC, time to result, shelf life, etc. as relevant.
  • PSV Positive predictive value
  • “Risk” in the context of the present invention relates to the probability that an event will occur over a specific time period, as in the responsiveness to treatment, cancer recurrence or survival and can mean a subject's "absolute” risk or “relative” risk.
  • Absolute risk can be measured with reference to either actual observation post- measurement for the relevant time cohort, or with reference to index values developed from statistically valid historical cohorts that have been followed for the relevant time period.
  • Relative risk refers to the ratio of absolute risks of a subject compared either to the absolute risks of low risk cohorts or an average population risk, which can vary by how clinical risk factors are assessed.
  • Odds ratios the proportion of positive events to negative events for a given test result, are also commonly used (odds are according to the formula p/(l-p) where p is the probability of event and (1- p) is the probability of no event) to no-conversion.
  • Risk evaluation or “evaluation of risk” in the context of the present invention encompasses making a prediction of the probability, odds, or likelihood that an event or disease state may occur, the rate of occurrence of the event or conversion from one disease state. Risk evaluation can also comprise prediction of future clinical parameters, traditional laboratory risk factor values, or other indices of cancer, either in absolute or relative terms in reference to a previously measured population.
  • the methods of the present invention may be used to make continuous or categorical measurements of the responsiveness to treatment thus diagnosing and defining the risk spectrum of a category of subjects defined as being responders or non-responders. In the categorical scenario, the invention can be used to discriminate between normal and other subject cohorts at higher risk for responding. Such differing use may require different
  • sample in the context of the present invention is a biological sample isolated from a subject and can include, by way of example and not limitation, tissue biopies, whole blood, serum, plasma, blood cells, endothelial cells, lymphatic fluid, ascites fluid, interstitital fluid (also known as "extracellular fluid” and encompasses the fluid found in spaces between cells, including, inter alia, gingival crevicular fluid), bone marrow, cerebrospinal fluid (CSF), saliva, mucous, sputum, sweat, urine, or any other secretion, excretion, or other bodily fluids.
  • sample may include a single cell or multiple cells or fragments of cells.
  • the sample is also a tissue sample.
  • the sample is or contains a circulating endothelial cell or a circulating tumor cell.
  • the sample includes a primary tumor cell, primary tumor, a recurrent tumor cell, or a metastatic tumor cell. Samples may also include cells in culture, such as those utilized for in vitro assays.
  • Samples can include various animal models for use in in vivo assays.
  • the sample can be a mouse tumor model or a mouse cancer model.
  • Specificity is calculated by TN/(TN+FP) or the true negative fraction of non-disease or normal subjects.
  • Statistical significance can be determined by any method known in the art. Commonly used measures of significance include the p-value, which presents the probability of obtaining a result at least as extreme as a given data point, assuming the data point was the result of chance alone. A result is considered highly significant at a p-value of 0.05 or less. Preferably, the p-value is 0.04, 0.03, 0.02, 0.01, 0.005, 0.001 or less.
  • a "subject" in the context of the present invention is preferably a mammal.
  • the mammal can be a human, non-human primate, mouse, rat, dog, cat, horse, or cow, but are not limited to these examples. Mammals other than humans can be
  • a subject can be male or female.
  • TN is true negative, which for a disease state test means classifying a non- disease or normal subject correctly.
  • TP i s rue positive, which for a disease state test means correctly classifying a disease subject.
  • Traditional laboratory risk factors correspond to biomarkers isolated or derived from subject samples and which are currently evaluated in the clinical laboratory and used in traditional global risk assessment algorithms.
  • Traditional laboratory risk factors for tumor recurrence include for example Proliferative index, tumor infiltrating lymphocytes. Other traditional laboratory risk factors for tumor recurrence known to those skilled in the art.
  • the methods disclosed herein are used with subjects undergoing treatment and/or therapies for cancer, subjects who are at risk for developing a reoccurrence of cancer and subjects who have been diagnosed with cancer.
  • the methods of the present invention are to be used to monitor or select a treatment regimen for a subject who has cancer, and to evaluate the efficacy or benefit of a treatment regimen for a subject who has cancer.
  • Treatment regimens include salinomycin, ML239, ML245, ML 243 aor CID50904149 (an analogue of ML 245).
  • Cancer includes solid tumors such as breast, ovarian, prostate, lung, kidney, gastric, colon, testicular, head and neck, pancreas, brain, melanoma, and other tumors of tissue organs and cancers of the blood cells, such as lymphomas and leukemias, including acute myelogenous leukemia, chronic lymphocytic leukemia, T cell
  • a “cellular proliferative disorder” includes those disorders that affect cell proliferation, activation, adhesion, growth, differentiation, or migration processes.
  • a “cellular proliferation, activation, adhesion, growth, differentiation, or migration process” is a process by which a cell increases in number, size, activation state, malignancy, or content, by which a cell develops a specialized set of characteristics which differ from that of other cells, or by which a cell moves closer to or further from a particular location or stimulus.
  • Disorders are characterized by aberrantly regulated growth, activation, adhesion, differentiation, or migration.
  • “Cell proliferative disorders” include autoimmune diseases and inflammation. For example, an inflammatory or immune system disorder, and/or a cellular proliferative disorder.
  • Subjects have varying degrees of responsiveness to therapy and methods are needed to distinguish the capability of the treatment in a dynamic manner.
  • Responsiveness e.g., resistance or sensitivity
  • Responsiveness e.g., resistance or sensitivity
  • Responsiveness of a cell to therapy is determined by measuring an effective amount of RESPONSEMARKER proteins, nucleic acids, polymorphisms, metabolites, and other analytes (which may be two or more) in a test sample (e.g., a subject derived sample), and comparing the effective amounts to reference or index values, often utilizing mathematical algorithms or formula in order to combine information from results of multiple individual RESPONSEMARKER and from non- analyte clinical parameters into a single measurement or index.
  • resistance it is meant that a cell fails to respond to an agent.
  • resistance to therapy means the cell is not damaged or killed by the drug.
  • sensitivity it is meant that that the cell responds to an agent.
  • sensitivity to therapy means the cell is damaged or killed by the drug.
  • the methods of the present invention are useful to treat, alleviate the symptoms of, monitor the progression of or delay the onset of cancer.
  • RESPONSEMARKER proteins, nucleic acids or metabolites allows for determination of whether a subject will derive a benefit from a particular course of treatment.
  • a biological sample is provided from a subject before undergoing treatment.
  • recipient a benefit it is meant that the subject will respond to the course of treatment.
  • responding it is meant that the treatment decreases in size, prevalence, or metastatic potential of a cancer in a subject.
  • responding means that the treatment retards or prevents a cancer recurrence from forming or retards, prevents, or alleviates a symptom. Assessment of cancers are made using standard clinical protocols.
  • biological samples are obtained from the subject at various time points before, during, or after treatment. Expression of an effective amount of
  • RESPONSEMARKER proteins, nucleic acids or metabolites is then determined and compared to a reference value are then identified, e.g. a control individual or population whose cancer state is known or an index value.
  • the reference sample or index value may be taken or derived from one or more individuals who have been exposed to the treatment.
  • the reference sample or index value may be taken or derived from one or more individuals who have not been exposed to the treatment.
  • samples may be collected from subjects who have received initial treatment for cancer and subsequent treatment for cancer to monitor the progress of the treatment.
  • a reference value can be relative to a number or value derived from
  • Reference values can be derived from statistical analyses and/or risk prediction data of populations obtained from mathematical algorithms and computed indices of cancer recurrence.
  • Reference RESPONSEMARKER indices can also be constructed and used using algorithms and other methods of statistical and structural classification.
  • the reference value is the amount of RESPONSEMARKERS in a control sample derived from one or more subjects who are responsive to therapy. In another embodiment of the present invention, the reference value is the amount of RESPONSEMARKERS in a control sample derived from one or more subjects who have higher disease free or overall survival rate from cancer. In the other embodiment of the present invention, the reference value is the amount of RESPONSEMARKERS in a control sample derived from one or more subjects who are not at risk or at low risk for developing a recurrence of cancer.
  • such subjects are monitored and/or periodically retested for a diagnostically relevant period of time ("longitudinal studies") following such test to verify continued absence of cancer (disease free or overall survival).
  • a diagnostically relevant period of time may be one year, two years, two to five years, five years, five to ten years, ten years, or ten or more years from the initial testing date for determination of the reference value.
  • retrospective measurement of RESPONSEMARKERS in properly banked historical subject samples may be used in establishing these reference values, thus shortening the study time required.
  • a reference value can also comprise the amounts of
  • RESPONSEMARKERS derived from subjects who show an improvement in risk factors as a result of treatments and/or therapies for the cancer.
  • a reference value can also comprise the amounts of RESPONSEMARKERS derived from subjects who show an improvement in responsiveness to therapy as a result of treatments and/or therapies for the cancer.
  • a reference value can also comprise the amounts of RESPONSEMARKERS derived from subjects who have higher disease free /overall rate, or are at high risk for developing cancer, or who have suffered from cancer.
  • the reference value is an index value or a baseline value.
  • An index value or baseline value is a composite sample of an effective amount of RESPONSEMARKERS from one or more subjects who do not have a cancer or subjects who are asymptomatic for a cancer.
  • a baseline value can also comprise the amounts of RESPONSEMARKERS in a sample derived from a subject who has shown an improvement in cancer responsiveness to therapy or disease free /overall survival rate as a result of cancer treatments or therapies.
  • the amounts of RESPONSEMARKERS are similarly calculated and compared to the index value.
  • subjects identified as having cancer, or being at increased risk of developing a cancer are chosen to receive a therapeutic regimen to slow the progression the cancer, or decrease or prevent the risk of developing cancer.
  • the progression of a cancer, or effectiveness of a cancer treatment regimen can be monitored by detecting a RESPONSEMARKER in an effective amount (which may be two or more) of samples obtained from a subject over time and comparing the amount of RESPONSEMARKERS detected.
  • a first sample can be obtained prior to the subject receiving treatment and one or more subsequent samples are taken after or during treatment of the subject.
  • the cancer is considered to be progressive (or, alternatively, the treatment does not prevent progression) if the amount of
  • RESPONSEMARKER changes over time relative to the reference value, whereas the cancer is not progressive if the amount of RESPONSEMARKERS remains constant over time (relative to the reference population, or "constant” as used herein).
  • the term “constant” as used in the context of the present invention is construed to include changes over time with respect to the reference value.
  • therapeutic or prophylactic agents suitable for administration to a particular subject can be identified by detecting one or more of the
  • RESPONSEMARKERS in an effective amount (which may be two or more) in a sample obtained from a subject, exposing the subject-derived sample to a test compound that determines the amount (which may be two or more) of RESPONSEMARKERS in the subject-derived sample. Accordingly, treatments or therapeutic regimens for use in subjects having a cancer, or subjects with non-responsiveness to therapy or lower disease free /overall survival rate can be selected based on the amounts of
  • RESPONSEMARKERS in samples obtained from the subjects and compared to a reference value. Two or more treatments or therapeutic regimens can be evaluated in parallel to determine which treatment or therapeutic regimen would be the most efficacious for use in a subject to delay onset, or slow progression of the cancer.
  • the present invention further provides a method for screening for changes in marker expression associated with a cancer, by determining one or more of the
  • RESPONSEMARKERS in a subject-derived sample, comparing the amounts of the RESPONSEMARKERS in a reference sample, and identifying alterations in amounts in the subject sample compared to the reference sample.
  • the reference sample e.g., a control sample
  • the reference sample is from a subject that does not have a cancer, from cells that are sensitive to a therapeutic compound or radiation, or if the reference sample reflects a value that is relative to a person that has a high likelihood of responsiveness to the therapy, low risk of developing recurrence or higher rate of disease free /overall survival, a similarity in the amount of the RESPONSEMARKER in the test sample and the reference sample indicates that the treatment is efficacious.
  • a difference in the amount of the RESPONSEMARKER in the test sample and the reference sample indicates a less favorable clinical outcome or prognosis.
  • the reference sample e.g., a control sample is from cells that are resistant to a therapeutic compound or if the reference sample reflects a value that is relative to a person that has a high likelihood of non-responsiveness to the therapy, high risk of developing a recurrence or lower rate of disease free /overall survival
  • a similarity in the amount of the RESPONSEMARKER proteins in the test sample and the reference sample indicates that the treatment with that compound will result in a less favorable clinical outcome or prognosis.
  • a change in the amount of the reference sample indicates that the treatment with that compound will result in a less favorable clinical outcome or prognosis.
  • the reference value is the level of an effective amount of RESPONSEMARKERS detected after treatment with any one of the probes disclosed herein. In some embodiments, the reference value is the level of an effective amount of RESPONSEMARKERS detected after treatment with ML239.
  • Efficacious it is meant that the treatment leads to a decrease in the amount or activity of a RESPONSEMARKER protein, nucleic acid, polymorphism, metabolite, or other analyte. Assessment of the risk factors disclosed herein can be achieved using standard clinical protocols. Efficacy can be determined in association with any known method for diagnosing, identifying, or treating a cancer.
  • the present invention also comprises a kit with a detection reagent that binds to two or more of the RESPONSEMARKERS proteins, nucleic acids, polymorphisms, metabolites, or other analytes. Also provided by the invention is an array of detection reagents, e.g., antibodies and/or oligonucleotides that can bind to two or more
  • the present invention can also be used to screen patient or subject populations in any number of settings.
  • a health maintenance organization, public health entity or school health program can screen a group of subjects to identify those requiring interventions, as described above, or for the collection of epidemiological data.
  • Insurance companies e.g., health, life or disability
  • Data collected in such population screens, particularly when tied to any clinical progression to conditions like cancer, will be of value in the operations of, for example, health maintenance organizations, public health programs and insurance companies.
  • Such data arrays or collections can be stored in machine -readable media and used in any number of health-related data management systems to provide improved healthcare services, cost effective healthcare, improved insurance operation, etc.
  • Each program can be implemented in a high level procedural or object oriented programming language to communicate with a computer system.
  • the programs can be implemented in assembly or machine language, if desired.
  • the language can be a compiled or interpreted language.
  • Each such computer program can be stored on a storage media or device (e.g., ROM or magnetic diskette or others as defined elsewhere in this disclosure) readable by a general or special purpose programmable computer, for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein.
  • the health-related data can be stored on a storage media or device (e.g., ROM or magnetic diskette or others as defined elsewhere in this disclosure) readable by a general or special purpose programmable computer, for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein.
  • the health-related data can be stored on a storage media or device (e.g., ROM or magnetic diskette or others as defined elsewhere in this disclosure) readable by
  • management system of the invention may also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner to perform various functions described herein.
  • the present invention also provides methods for screening for a test compound that induces cancer cell death and/or inhibits cancer cell proliferation.
  • a cell i.e., a cell isolated from a subject
  • a candidate compound can be incubated in the presence of a candidate compound and the level of an effective amount of
  • RESPONSEMARKER in the test sample can be measured by the various assays described herein.
  • the pattern or level of an effective amount of RESPONSEMARKERS in a cell that has been contacted with the test compound can be compared to a reference profile.
  • the level of an effective amount of RESPONSEMARKERS in a cell that has been contacted with the test compound can also be compared to the level of the effective amount of one or more RESPONSEMARKERS listed in any one of Tables 1-10, wherein a similarity indicates the compound' s ability to induce cancer cell death and/or inhibit cancer cell proliferation.
  • RESPONSEMARKER in a cell that has been contacted with the test compound can also be compared to the level of an effective amount of one or more RESPONSEMARKERS in a cell treated with a reference compound.
  • RESPONSEMARKERS include, but are not limited to, the nucleic acids or polypeptide sequences of: ALDH1L2, ASNS, C10RF24, CBS, CDKN1A, EIF1, FBX032, GDF15, HERPUD1, HSPA5, LOC729779, MTHFD2, NCRNA00219, P8, PCK2, PSAT1, RND3, SLC7A1, SNHG8, SQSTM1, and TRIB3.
  • the compound, or test compound can be any agent, drug, compound, or composition or combination thereof, including, dietary supplements.
  • the test agents are agents frequently used in cancer treatment regimens.
  • ML239, ML245, ML 243 or CID50904149 an analogue of ML 245).
  • the methods disclosed herein are useful to treat, alleviate the symptoms of, diagnose, prognose, monitor the progression, predict the progression of, or delay the onset of cancer in a subject.
  • the method of treating or alleviating a symptom of cancer comprises administering a compound that modulates the expression of one or more RESPONSEMARKERS.
  • the method of treating or alleviating a symptom of cancer comprises administering a compound that modulates the expression of one or more genes in the NF- ⁇ pathway.
  • the RESPONSEMARKERS include, but are not limited to, ALDH1L2, ASNS, C10RF24, CBS, CDKN1A, EIF1, FBX032, GDF15, HERPUD1, HSPA5, LOC729779, MTHFD2, NCRNA00219, P8, PCK2, PSAT1, RND3, SLC7A1, SNHG8, SQSTM1, and TRIB3.
  • treating in its various grammatical forms in relation to the present invention refers to preventing, curing, reversing, attenuating, alleviating, ameliorating, minimizing, suppressing, or halting the deleterious effects of a cancer or a cell proliferative disorder, cancer or disorder progression.
  • the term "alleviate” or “ameliorate” in its various grammatical forms in relation to the present invention is meant to describe a process by which the severity of a sign or symptom of a cancer or cell proliferative disorder is decreased.
  • a sign or symptom can be alleviated without being eliminated.
  • the administration of a compound as disclosed herein leads to the elimination of a sign or symptom, however, elimination is not required.
  • Therapeutically effective dosages are expected to decrease the severity of a sign or symptom.
  • the term “alleviate” or “ameliorate” in its various grammatical forms in relation to the present invention is meant to describe a process by which the severity of a sign or symptom of a cancer or cell proliferative disorder is decreased.
  • a sign or symptom can be alleviated without being eliminated.
  • the administration of a compound as disclosed herein leads to the elimination of a sign or symptom, however, elimination is not required.
  • Therapeutically effective dosages are expected to decrease the severity
  • symptom is defined as an indication of disease, illness, injury, or something that is not right in the body.
  • the proliferation or growth of cells is inhibited, e.g., reduced by contacting a cell with a compound that modulates expression of one or more RESPONSEMARKERS.
  • inhibition of cell proliferation or growth is meant the cell divides at a lower rate or has decreased viability compared to a cell not exposed to the composition.
  • Cell growth is measured by methods know in the art such as, the MTT cell proliferation assay, BrDU incorporation, immunohistochemical staining for proliferation markers or measurement of total GFP from GFP expressing cell lines.
  • inducing cell death inducing apoptosis.
  • the process of apoptosis is characterized by, but not limited to, several events. Cells lose their cell junctions and microvilli, the cytoplasm condenses and nuclear chromatin marginates into a number of discrete masses. As the nucleus fragments, the cytoplasm contracts and mitochondria and ribosomes become densely compacted. After dilation of the endoplasmic reticulum and its fusion with the plasma membrane, the cell breaks up into several membrane-bound vesicles, apoptotic bodies, which are usually phagocytosed by adjacent bodies.
  • DNA cleavage patterns can be used as and in vitro assay for its occurrence (Cory, Nature 367: 317-18, 1994).
  • Many methods for measuring apoptosis including those described herein, are known to the skilled artisan including, but not limited to, the classic methods of DNA ladder formation by gel electrophoresis, immunohistochemical staining for apoptotic markers, measurement of apoptotic gene expression and of morphologic examination by electron microscopy. The more recent and readily used method for measuring apoptosis is flow cytometry.
  • the compound is administered systemically.
  • Compounds are administered in an amount sufficient to decrease (e.g., inhibit) cell proliferation or induce apoptosis.
  • the cells are cancer cells, i.e., cancer stem cells.
  • the cancer cells are breast cancer cells.
  • cancer stem cells collectively refer to cells found within tumors or hematological cancers that possess stem cell properties, e.g., the ability to give rise to all cell types found in a particular cancer sample.
  • Cancer stem cells may generate tumors through the processes of self-renewal and differentiation into multiple cell types. Such cells may persist in tumors as a distinct population (e.g., after surgical or radiation treatment, or therapeutic regimens) and cause relapse and metastasis by giving rise to new tumors.
  • CSCs may also possess the ability to undergo epithelial-mesenchymal transition (EMT).
  • EMT epithelial-mesenchymal transition
  • Treatment is efficacious if the treatment leads to clinical benefit such as, a decrease in size, prevalence, or metastatic potential of the tumor in the subject.
  • "efficacious" means that the treatment retards or prevents tumors from forming or prevents or alleviates a clinical symptom of the tumor. Efficaciousness is determined in association with any known method for diagnosing or treating the particular tumor type.
  • the compounds described herein can be formulated into pharmaceutical compositions for treating or alleviating a symptom of cancer in a subject. The
  • the compounds can be administered to a subject using methods known in the art.
  • the compound is administered orally, rectally, nasally, topically or parenterally, e.g., subcutaneously, intraperitoneally, intramuscularly, and intravenously.
  • the inhibitors are optionally formulated as a component of a cocktail of therapeutic drugs to treat cancers.
  • the performance and thus absolute and relative clinical usefulness of the invention may be assessed in multiple ways as noted above.
  • the invention is intended to provide accuracy in clinical diagnosis and prognosis.
  • the accuracy of a diagnostic, predictive, or prognostic test, assay, or method concerns the ability of the test, assay, or method to distinguish between subjects responsive to treatment and those that are not, is based on whether the subjects have an "effective amount” or a "significant alteration" in the levels of a
  • RESPONSEMARKER By “effective amount” or “significant alteration,” it is meant that the measurement of an appropriate number of RESPONSEMARKER (which may be one or more) is different than the predetermined cut-off point (or threshold value) for that RESPONSEMARKER(S) and therefore indicates that the subject responsiveness to therapy or disease free/overall survival for which the RESPONSEMARKER(S) is a determinant.
  • the difference in the level of RESPONSEMARKER between normal and abnormal is preferably statistically significant. As noted below, and without any limitation of the invention, achieving statistical significance, and thus the preferred analytical and clinical accuracy, generally but not always requires that combinations of several RESPONSEMARKER be used together in panels and combined with
  • an "acceptable degree of diagnostic accuracy” is herein defined as a test or assay in which the AUC (area under the ROC curve for the test or assay) is at least 0.60, desirably at least 0.65, more desirably at least 0.70, preferably at least 0.75, more preferably at least 0.80, and most preferably at least 0.85.
  • a "very high degree of diagnostic accuracy” it is meant a test or assay in which the AUC (area under the ROC curve for the test or assay) is at least 0.80, desirably at least 0.85, more desirably at least 0.875, preferably at least 0.90, more preferably at least 0.925, and most preferably at least 0.95.
  • the predictive value of any test depends on the sensitivity and specificity of the test, and on the prevalence of the condition in the population being tested. This notion, based on Bayes' theorem, provides that the greater the likelihood that the condition being screened for is present in an individual or in the population (pre-test probability), the greater the validity of a positive test and the greater the likelihood that the result is a true positive. Thus, the problem with using a test in any population where there is a low likelihood of the condition being present is that a positive result has limited value (i.e., more likely to be a false positive). Similarly, in populations at very high risk, a negative test result is more likely to be a false negative.
  • ROC and AUC can be misleading as to the clinical utility of a test in low disease prevalence tested populations (defined as those with less than 1% rate of occurrences (incidence) per annum, or less than 10% cumulative prevalence over a specified time horizon).
  • absolute risk and relative risk ratios as defined elsewhere in this disclosure can be employed to determine the degree of clinical utility.
  • Populations of subjects to be tested can also be categorized into quartiles by the test's measurement values, where the top quartile (25% of the population) comprises the group of subjects with the highest relative risk for therapeutic unresponsiveness, and the bottom quartile comprising the group of subjects having the lowest relative risk for therapeutic unresponsiveness.
  • values derived from tests or assays having over 2.5 times the relative risk from top to bottom quartile in a low prevalence population are considered to have a "high degree of diagnostic accuracy," and those with five to seven times the relative risk for each quartile are considered to have a "very high degree of diagnostic accuracy.” Nonetheless, values derived from tests or assays having only 1.2 to 2.5 times the relative risk for each quartile remain clinically useful are widely used as risk factors for a disease; such is the case with total cholesterol and for many inflammatory biomarkers with respect to their prediction of future events. Often such lower diagnostic accuracy tests must be combined with additional parameters in order to derive
  • a health economic utility function is yet another means of measuring the performance and clinical value of a given test, consisting of weighting the potential categorical test outcomes based on actual measures of clinical and economic value for each.
  • Health economic performance is closely related to accuracy, as a health economic utility function specifically assigns an economic value for the benefits of correct classification and the costs of misclassification of tested subjects.
  • As a performance measure it is not unusual to require a test to achieve a level of performance which results in an increase in health economic value per test (prior to testing costs) in excess of the target price of the test.
  • diagnostic accuracy In general, alternative methods of determining diagnostic accuracy are commonly used for continuous measures, when a disease category or risk category has not yet been clearly defined by the relevant medical societies and practice of medicine, where thresholds for therapeutic use are not yet established, or where there is no existing gold standard for diagnosis of the pre-disease.
  • measures of diagnostic accuracy for a calculated index are typically based on curve fit and calibration between the predicted continuous value and the actual observed values (or a historical index calculated value) and utilize measures such as R squared, Hosmer- Lemeshow P- value statistics and confidence intervals.
  • any formula may be used to combine RESPONSEMARKER results into indices useful in the practice of the invention.
  • indices may indicate, among the various other indications, the probability, likelihood, absolute or relative chance of responding to chemotherapy or chemoradiotherapy. This may be for a specific time period or horizon, or for remaining lifetime risk, or simply be provided as an index relative to another reference subject population.
  • model and formula types beyond those mentioned herein and in the definitions above are well known to one skilled in the art.
  • the actual model type or formula used may itself be selected from the field of potential models based on the performance and diagnostic accuracy characteristics of its results in a training population.
  • the specifics of the formula itself may commonly be derived from RESPONSEMARKER results in the relevant training population.
  • such formula may be intended to map the feature space derived from one or more RESPONSEMARKER inputs to a set of subject classes (e.g. useful in predicting class membership of subjects as normal, responders and non-responders), to derive an estimation of a probability function of risk using a Bayesian approach (e.g. the risk of cancer or a metastatic event), or to estimate the class-conditional probabilities, then use Bayes' rule to produce the class probability function as in the previous case.
  • subject classes e.g. useful in predicting class membership of subjects as normal, responders and non-responders
  • Bayesian approach e.g. the risk
  • Preferred formulas include the broad class of statistical classification algorithms, and in particular the use of discriminant analysis.
  • the goal of discriminant analysis is to predict class membership from a previously identified set of features.
  • LDA linear discriminant analysis
  • features can be identified for LDA using an eigengene based approach with different thresholds (ELD A) or a stepping algorithm based on a multivariate analysis of variance (MAN OVA). Forward, backward, and stepwise algorithms can be performed that minimize the probability of no separation based on the Hotelling-Lawley statistic.
  • ELD A Eigengene-based Linear Discriminant Analysis
  • biomarkers in a multivariate framework using a modified eigen analysis to identify features associated with the most important eigenvectors.
  • "Important” is defined as those eigenvectors that explain the most variance in the differences among samples that are trying to be classified relative to some threshold.
  • a support vector machine is a classification formula that attempts to find a hyperplane that separates two classes. This hyperplane contains support vectors, data points that are exactly the margin distance away from the hyperplane. In the likely event that no separating hyperplane exists in the current dimensions of the data, the dimensionality is expanded greatly by projecting the data into larger dimensions by taking non-linear functions of the original variables (Venables and Ripley, 2002).
  • features can be identified for a support vector machine using a non-parametric Kruskal-Wallis (KW) test to select the best univariate features.
  • KW non-parametric Kruskal-Wallis
  • a random forest RF, Breiman, 2001
  • RPART recursive partitioning
  • Both KW and RF require that a number of features be selected from the total.
  • RPART creates a single classification tree using a subset of available biomarkers.
  • an overall predictive formula for all subjects, or any known class of subjects may itself be recalibrated or otherwise adjusted based on adjustment for a population's expected prevalence and mean biomarker parameter values, according to the technique outlined in D'Agostino et al, (2001) JAMA 286: 180-187, or other similar normalization and recalibration techniques.
  • Such epidemiological adjustment statistics may be captured, confirmed, improved and updated continuously through a registry of past data presented to the model, which may be machine readable or otherwise, or occasionally through the retrospective query of stored samples or reference to historical studies of such parameters and statistics. Additional examples that may be the subject of formula recalibration or other adjustments include statistics used in studies by Pepe, M.S.
  • numeric result of a classifier formula itself may be transformed post-processing by its reference to an actual clinical population and study results and observed endpoints, in order to calibrate to absolute risk and provide confidence intervals for varying numeric results of the classifier or risk formula.
  • An example of this is the presentation of absolute risk, and confidence intervals for that risk, derived using an actual clinical study, chosen with reference to the output of the recurrence score formula in the Oncotype Dx product of Genomic Health, Inc. (Redwood City, CA).
  • a further modification is to adjust for smaller sub-populations of the study based on the output of the classifier or risk formula and defined and selected by their Clinical Parameters, such as age or sex.
  • RESPONSEMARKERS can be determined at the protein or nucleic acid level using any method known in the art. For example, at the nucleic acid level, Northern and Southern hybridization analysis, as well as ribonuclease protection assays using compounds which specifically recognize one or more of these sequences can be used to determine gene expression. Alternatively, amounts of RESPONSEMARKERS can be measured using reverse-transcription-based PCR assays (RT-PCR), e.g., using primers specific for the differentially expressed sequence of genes or by branch-chain RNA amplification and detection methods by Panomics, Inc.
  • RT-PCR reverse-transcription-based PCR assays
  • RESPONSEMARKERS include, but are not limited to DNA microarrays, such as Bioanalyzer Chips (Agilent) or Human HT-12 Expression BeadChip (Illumina); SAGE (Serial analysis of gene expression); tiling arrays; and RNA-Seq.
  • DNA microarrays such as Bioanalyzer Chips (Agilent) or Human HT-12 Expression BeadChip (Illumina); SAGE (Serial analysis of gene expression); tiling arrays; and RNA-Seq.
  • Amounts of RESPONSEMARKERS can also be determined at the protein level, e.g., by measuring the levels of peptides encoded by the gene products described herein, or subcellular localization or activities thereof using technological platform such as for example AQUA.
  • Such methods are well known in the art and include, e.g., immunoassays based on antibodies to proteins encoded by the genes, aptamers or molecular imprints. Any biological material can be used for the detection/quantification of the protein or its activity.
  • a suitable method can be selected to determine the activity of proteins encoded by the marker genes according to the activity of each protein analyzed.
  • polymorphisms thereof can be detected in any suitable manner, but is typically detected by contacting a sample from the subject with an antibody which binds the
  • the antibody may be
  • the step of detecting the reaction product may be carried out with any suitable immunoassay.
  • the sample from the subject is typically a biological fluid as described above, and may be the same sample of biological fluid used to conduct the method described above.
  • Immunoassays carried out in accordance with the present invention may be homogeneous assays or heterogeneous assays.
  • a homogeneous assay the
  • immunological reaction usually involves the specific antibody (e.g., anti- RESPONSEMARKER protein antibody), a labeled analyte, and the sample of interest.
  • the signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labeled analyte.
  • Immunochemical labels which may be employed include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.
  • the reagents are usually the sample, the antibody, and means for producing a detectable signal. Samples as described above may be used.
  • the antibody can be immobilized on a support, such as a bead (such as protein A and protein G agarose beads), plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase.
  • a support such as a bead (such as protein A and protein G agarose beads), plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase.
  • the support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal.
  • the signal is related to the presence of the analyte in the sample.
  • Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels. For example, if the antigen to be detected contains a second binding site, an antibody which binds to that site can be conjugated to a detectable group and added to the liquid phase reaction solution before the separation step.
  • the presence of the detectable group on the solid support indicates the presence of the antigen in the test sample.
  • suitable immunoassays are oligonucleotides, immunoblotting, immunofluorescence methods, immunoprecipitation, quantum dots, multiplex fluorochromes, chemiluminescence methods,
  • ECL electrochemiluminescence
  • enzyme-linked immunoassays enzyme-linked immunoassays
  • Antibodies can be conjugated to a solid support suitable for a diagnostic assay (e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding.
  • a diagnostic assay e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene
  • Antibodies as described herein may likewise be conjugated to detectable labels or groups such as radiolabels (e.g., 35S, 1251, 1311), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein, Alexa, green fluorescent protein, rhodamine) in accordance with known techniques.
  • radiolabels e.g., 35S, 1251, 1311
  • enzyme labels e.g
  • Highly sensitivity antibody detection strategies may be used that allow for evaluation of the antigen-antibody binding in a non-amplified configuration.
  • antibodies may be conjugated to oligonucleotides, and followed by Polymerase Chain Reaction (PCR) and a variety of oligonucleotide detection methods.
  • PCR Polymerase Chain Reaction
  • Antibodies can also be useful for detecting post-translational modifications of RESPONSEMARKER proteins, polypeptides, mutations, and polymorphisms, such as tyrosine phosphorylation, threonine phosphorylation, serine phosphorylation,
  • glycosylation e.g., O-GlcNAc
  • Such antibodies specifically detect the phosphorylated amino acids in a protein or proteins of interest, and can be used in immunoblotting, immunofluorescence, and ELISA assays described herein. These antibodies are well- known to those skilled in the art, and commercially available. Post-translational modifications can also be determined using metastable ions in reflector matrix-assisted laser desorption ionizationtime of flight mass spectrometry (MALDI-TOF) (Wirth, U. et al. (2002) Proteomics 2(10): 1445-51).
  • MALDI-TOF reflector matrix-assisted laser desorption ionizationtime of flight mass spectrometry
  • these processes may be coupled to localization of the protein, such that a re-localization process is monitored, and the RESPONSEMARKER is evaluated in a relative fashion exhibited by the constancy or change to the ratio of the RESPONSEMARKER in different compartments.
  • RESPONSEMARKERS Important to several of the proteins in RESPONSEMARKERS, nuclear, nuclear foci, and cytoplasmic sites in tumor cells are evident.
  • the activities can be determined in vitro using enzyme assays known in the art.
  • enzyme assays include, without limitation, kinase assays, phosphatase assays, reductase assays, among many others.
  • Modulation of the kinetics of enzyme activities can be determined by measuring the rate constant KM using known algorithms, such as the Hill plot, Michaelis-Menten equation, linear regression plots such as Lineweaver-Burk analysis, and Scatchard plot.
  • RESPONSEMARKER sequences expression of the RESPONSEMARKER sequences can be detected (if present) and measured using techniques well known to one of ordinary skill in the art. For example, sequences within the sequence database entries
  • RESPONSEMARKER sequences can be used to construct probes for detecting RESPONSEMARKER RNA sequences in, e.g., Northern blot hybridization analyses or methods which specifically, and, preferably, quantitatively amplify specific nucleic acid sequences.
  • the sequences can be used to construct primers for specifically amplifying the RESPONSEMARKER sequences in, e.g., amplification-based detection methods such as reverse-transcription based polymerase chain reaction (RT-PCR).
  • RT-PCR reverse-transcription based polymerase chain reaction
  • RNA levels can be measured at the RNA level using any method known in the art. For example, Northern hybridization analysis using probes which specifically recognize one or more of these sequences can be used to determine gene expression. Alternatively, expression can be measured using reverse transcription- based PCR assays (RT-PCR), e.g., using primers specific for the differentially expressed sequences. RNA can also be quantified using, for example, other target amplification methods (e.g., TMA, SDA, NASBA), or signal amplification methods (e.g., bDNA), and the like.
  • RT-PCR reverse transcription- based PCR assays
  • RNA can also be quantified using, for example, other target amplification methods (e.g., TMA, SDA, NASBA), or signal amplification methods (e.g., bDNA), and the like.
  • RESPONSEMARKER protein and nucleic acid metabolites can be measured.
  • the term "metabolite” includes any chemical or biochemical product of a metabolic process, such as any compound produced by the processing, cleavage or consumption of a biological molecule (e.g., a protein, nucleic acid, carbohydrate, or lipid).
  • Metabolites can be detected in a variety of ways known to one of skill in the art, including the refractive index spectroscopy (RI), ultra-violet spectroscopy (UV), fluorescence analysis, radiochemical analysis, near-infrared spectroscopy (near-IR), nuclear magnetic resonance spectroscopy (NMR), light scattering nalysis (LS), mass spectrometry, pyrolysis mass spectrometry, nephelometry, dispersive Raman
  • RI refractive index spectroscopy
  • UV ultra-violet spectroscopy
  • fluorescence analysis radiochemical analysis
  • near-IR near-infrared spectroscopy
  • NMR nuclear magnetic resonance spectroscopy
  • LS light scattering nalysis
  • mass spectrometry pyrolysis mass spectrometry
  • nephelometry dispersive Raman
  • RESPONSEMARKER analytes can be measured using the above-mentioned detection methods, or other methods known to the skilled artisan.
  • circulating calcium ions (Ca2+) can be detected in a sample using fluorescent dyes such as the Fluo series, Fura-2A, Rhod-2, among others.
  • Other RESPONSEMARKER metabolites can be similarly detected using reagents that are specifically designed or tailored to detect such metabolites.
  • the invention also includes a RESPONSEMARKER-detection reagent, e.g., nucleic acids that specifically identify one or more RESPONSEMARKER nucleic acids by having homologous nucleic acid sequences, such as oligonucleotide sequences, complementary to a portion of the RESPONSEMARKER nucleic acids or antibodies to proteins encoded by the RESPONSEMARKER nucleic acids packaged together in the form of a kit.
  • the oligonucleotides can be fragments of the RESPONSEMARKER genes.
  • the oligonucleotides can be 200, 150, 100, 50, 25, 10 or less nucleotides in length.
  • the kit may contain in separate containers a nucleic acid or antibody (either already bound to a solid matrix or packaged separately with reagents for binding them to the matrix), control formulations (positive and/or negative), and/or a detectable label such as fluorescein, green fluorescent protein, rhodamine, cyanine dyes, Alexa dyes, luciferase, radiolabels, among others.
  • Instructions e.g., written, tape, VCR, CD-ROM, etc.
  • the assay may for example be in the form of a Northern hybridization or a sandwich ELISA as known in the art.
  • RESPONSEMARKER detection reagents can be immobilized on a solid matrix such as a porous strip to form at least one RESPONSEMARKER detection site.
  • the measurement or detection region of the porous strip may include a plurality of sites containing a nucleic acid.
  • a test strip may also contain sites for negative and/or positive controls. Alternatively, control sites can be located on a separate strip from the test strip.
  • the different detection sites may contain different amounts of immobilized nucleic acids, e.g., a higher amount in the first detection site and lesser amounts in subsequent sites.
  • the number of sites displaying a detectable signal provides a quantitative indication of the amount of RESPONSEMARKERS present in the sample.
  • the detection sites may be configured in any suitably detectable shape and are typically in the shape of a bar or dot spanning the width of a test strip.
  • the kit contains a nucleic acid substrate array comprising one or more nucleic acid sequences.
  • the nucleic acids on the array specifically identify one or more nucleic acid sequences represented by RESPONSEMARKERS.
  • the substrate array can be on, e.g., a solid substrate, e.g., a "chip” as described in U.S. Patent No.5,744,305.
  • the substrate array can be a solution array, e.g., xMAP (Luminex, Austin, TX), Cyvera (Illumina, San Diego, CA), CellCard (Vitra Bioscience, Mountain View, CA) and Quantum Dots' Mosaic (Invitrogen, Carlsbad, CA).
  • HMLE Human breast epithelial cells
  • CSCs cancer stem cells
  • HMLE cell lines can be driven to a CSC-like state by knocking down genes that regulate the epithelial-mesenchymal transition, such as E-Cadherin and Twist.
  • E-Cadherin epithelial-mesenchymal transition
  • Twist Twist
  • HMLE_sh_GFP green fluorescent protein
  • HMLE_sh_ECad, HMLE_sh_Twist, and HMLE_sh_GFP were propagated in 1: 1 mixture of 10% fetal bovine serum (FBS; HyClone), 1% Penicillin/Streptomycin (Pen/Strep; Cellgro), 1% Glutamax-1 (Invitrogen), 70 nM Hydrocortisone (Sigma), 12 ⁇ g/ml Insulin (Sigma), 50 ⁇ g/ml Gentamicin (Sigma), 12.5 ⁇ g/ml Plasmocin
  • EGF 10 ng/ml EGF in DMEM (Cellgro) with Mammary Epithelial Cell Growth Medium (MEGM complete medium; Lonza, Basel, Switzerland) at 37 °C, 5% C0 2 .
  • MEGM Mammary Epithelial Cell Growth Medium
  • CID49843203 (ML239), CID50904134 (ML245), CID50904149 (Analog 2 of ML 245), CID50910523 (ML243) and Salinomycin (Sal) were selectively toxic to HMLE_sh_ECad cell lines (over HMLE_sh_GFP cell lines) in 3-day toxicity assays.
  • the IC50 concenttion of toxicity towards HMLE_sh_ECad cell line in these 3-day toxicity assay was the same concentration used for experiments below (1.2 ⁇ , 0.54 ⁇ , 6.7 ⁇ , 2 ⁇ , and 1 ⁇ ).
  • HMLE_sh_GFP cells were treated with vehicle, ML239, ML245, CID50904149 (an analogue of ML245) ML243, or Salinomycin (Sal)) at the above concentrations for 24 hours prior to isolation of RNA.
  • Total RNA was isolated using the RNeasy Protect Mini Kit (Qiagen). Quality control (QC) processing of the RNA samples and the gene expression analysis were performed by the Genome Analysis Platform (GAP) at the Broad Institute.
  • GAP Genome Analysis Platform
  • RNA samples were analyzed for quality using Aglient Bioanalyzer Chips.
  • cDNA synthesis from the total RNA samples passing QC was prepared for analysis on a HumanHT-12 Expression BeadChip (Illumina, San Diego, CA) according to the manufacturer's instructions. QC checks, and analyses were done with
  • GenomeStudio version 2010.3; Illumina, San Diego, CA. All of the samples were run in replicates (3-4) and the entire data set was normalized using the quantile module available in open source program GenePattern (http://genepattern.broadinstitute.org/). After the samples were normalized, gene expression was compared between the DMSO- treated and compound-treated using the ComparitiveSelection Module in GenePattern. Those genes with a significant difference (p>0.005) and had 1.50-fold change in expression were selected.
  • EXAMPLE 2 A SCREEN FOR ADDITIONAL PROBES IDENTIFIED ML239.
  • MLSMR Molecular Libraries Small Molecule Repository
  • Luminescence 0.1 sec/well Each assay plate is normalized to the 32 neutral control (DMSO-treated) wells and the 32 positive control (Puromycin-treated) wells on each plate. The signal was normalized to the neutral (DMSO) and positive (Puromycin) controls. Hits were defined as showing a greater than 75% reduction in viability (i.e ATP level) cutoff at an average screening concentration of 7.5 ⁇ was used to define a hit. Using these criteria, 3,190 hits were identified as inhibitors of HMLE_sh_Ecad ( Figure 1). Duplicate samples correlated highly with one another showing that the data were reproducible.
  • ML239 is potently toxic to CSCs and at least one other cancer cell line, but does not display toxicity to control mammary epithelial cells (HMLE_sh_GFP) .
  • HMLE_sh_GFP mammary epithelial cells
  • Gene expression profiling was performed using ML239 to evaluate breast cancer stem cell pathways that may be used for future target development. This assay identified early gene expression alterations, additional RESPONSEMARKERS associated with responsiveness to cancer treatment, and a potential pathway for targeting by future therapeutics.
  • RNA Total RNA was isolated using the RNeasy Protect Mini Kit (Qiagen). Quality control (QC) processing of the RNA samples and the gene expression analysis were performed by the Genome Analysis Platform (GAP) at the Broad Institute. Briefly, RNA samples were analyzed for quality using Aglient Bioanalyzer Chips. RNA synthesis from the total RNA samples passing QC was prepared for analysis on a HumanHT-12
  • HMLE_sh_GFP A similar study was conducted with the control line, HMLE_sh_GFP. Only 5 genes were differentially regulated in HMLE_sh_GFP after treatment with ML239 (ATP6V0C, PKM2, PPDPF, RPL23, and SERINC2), and none overlapped with genes regulated in HMLE_sh_ECad cells, indicating that there were different responses to the compound in the two cell types.
  • TRIB3 is a putative protein kinase that is induced by NF- ⁇ B and that is correlated with both pro-apoptotic and anti-apoptotic features. High levels of TRIB3 have been correlated with poor prognosis in breast cancer and TRIB3 expression is increased in hypoxic conditions. ML239 increases TRIB3 expression in HMLE_sh_ECad ( Figure 4) and this increase may induce TRIB 3 -regulated apoptosis.
  • Table 5 Com arison between DMSO treated and ML243 treated HMLE_shECad cells
  • Table 6 Com arison between DMSO treated andML243 treated HMLE_shGFP cells
  • Table 7 Com arison between DMSO treated and CID50904149 (an analogue of ML245) treated HMLE_shECad cells

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Abstract

La présente invention concerne des méthodes de traitement du cancer et des méthodes d'estimation/analyse de la sensibilité d'une cellule cancéreuse vis-à-vis d'un composé thérapeutique. La présente invention concerne donc des méthodes de criblage pour l'identification de composés thérapeutiques qui induisent une apoptose ou inhibent la prolifération de cellules cancéreuses. Des marqueurs différentiellement exprimés en réponse à des composés qui sont sélectivement toxiques vis-à-vis des cellules de type cellules souches cancéreuses ont été identifiés pour être utilisés dans une des méthodes de la présente invention, notamment, des lignées de cellules du cancer du sein de type cellules souches cancéreuses générées par inactivation d'E-cadhérine et de Twist dans des cellules épithéliales mammaires humaines (HMLE sh Ecad, HMLE sh Twist). Des marqueurs différentiellement exprimés en réponse aux composés ML239, ML245, CID50904149 (analogue de ML 245), ML243 et Salinomycine, qui étaient sélectivement toxiques vis-à-vis des cellules de type CSC, ont été identifiés. La voie NF-kappaB était la plus significativement associée aux gènes régulés en réponse à ML239.
PCT/US2012/064392 2011-11-11 2012-11-09 Signatures associées à la sensibilité vis-à-vis d'une thérapie de cancer Ceased WO2013071066A1 (fr)

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