Classifications

• • 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
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
  • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
  • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
  • G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
  • A61P35/00—Antineoplastic agents
• • C—CHEMISTRY; METALLURGY
  • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
  • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
  • C12Q2600/00—Oligonucleotides characterized by their use
  • C12Q2600/118—Prognosis of disease development
• • C—CHEMISTRY; METALLURGY
  • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
  • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
  • C12Q2600/00—Oligonucleotides characterized by their use
  • C12Q2600/158—Expression markers
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
  • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Definitions

• the invention relates generally to genomic prognostic genes and signatures for screening, diagnostics, and prognostics of cancer, which in some embodiments is melanoma.
• the invention relates to the utility of a gene signature in patient selection for future clinical trials.
• the invention relates to identifying patients who are likely to respond to or need further treatment with a PD-1 antagonist by determining if they are positive or negative for a gene expression based biomarker.
• Melanoma is a type of skin cancer that develops when melanocytes start to grow out of control. Melanoma accounts for only 1% of skin cancers but cause a large majority of skin cancer deaths (www.cancer.org/cancer/melanoma-skin-cancer/treating/immunotherapy). Melanoma is likely to spread to other parts of the body if early detection and treatment is not sought early.
• Pembrolizumab, nivolumab, and ipilimumab block proteins that normally suppress the T-cell immune response against melanoma cells.
• Pembrolizumab and nivolumab are drugs that target PD-L a protein on immune system cells called T cells that normally help keep these cells from attacking other cells in the body. By blocking PD-1, these drugs boost the immune response against melanoma cells.
• Gene expression based biomarkers have been implemented successfully for tumor characterization, classification, and prediction of disease outcome. Gene expression based biomarkers have been described in the literature and are currently used to guide the use of therapy for melanoma in the market.
• Prognostic factors are critical to distinguish patients with poor prognosis, likely to advance from primary melanoma to metastatic melanoma, and therefore, those that would benefit from further treatment. It is also critical to distinguish patients with favorable prognosis.
• PD-1 expression on tumor infiltrating lymphocytes was found to mark dysfunctional T cells in breast cancer and melanoma (Ghebeh et al., BMC Cancer. 8:5714-15 (2008); Ahmadzadeh et al., Blood 114: 1537-1544 (2009)) and to correlate with poor prognosis in renal cancer (Thompson et al.. Clinical Cancer Research 15: 1757-1761 (2007)).
• PD-L1 expressing tumor cells interact with PD-1 expressing T cells to attenuate T cell activation and evasion of immune surveillance, thereby contributing to an impaired immune response against the tumor.
• Immune checkpoint therapies targeting the PD-1 axis have resulted in technological improvements in clinical response in multiple human cancers (Brahmer et al.. N Engl J Med 2012, 366: 2455-65; Garon et al. N Engl J Med 2015, 372: 2018-28; Hamid et al., N Engl J Med 2013, 369: 134-44; Robert et al., Lancet 2014, 384: 1109-17; Robert et al., N Engl J Med 2015, 372: 2521-32; Robert et al., N Engl J Med 2015, 372: 320-30; Topalian et al., N Engl J Med 2012, 366: 2443-54; Topalian et al., J Clin Oncol 2014, 32: 1020-30; Wolchok et al., N Engl J Med 2013, 369: 122-33).
• PD-1 antagonists can induce durable anti -tumor responses in some patients in certain cancer ty pes, a significant number of patients fail to respond to therapies targeting PD-1/PD-L1. Thus, a need exists for diagnostic tools to identify which cancer patients are most likely to achieve a clinical benefit to treatment with a PD-1 antagonist.
• An active area in cancer research is the identification of intratumoral expression patterns for sets of genes, commonly referred to as gene signatures or molecular signatures, which are characteristic of particular types or subtypes of cancer, and which may be associated with clinical outcomes.
• PD-L1 immunohistochemistry- and gene expression profiles are associated with response to PD-1/PD-L1 inhibitor therapies in multiple tumor types (McDermott et al. Nat Med. 24:749-757 (2016); Ayers et al. J Clin Invest. 127:2930-2940 (2017); O’Donnell et al. J Clin Oncol. 35: 4502 (2017)).
• a gene expression based biomarker for use in prognosing or classifying a patient who has been diagnosed with melanoma.
• the invention also relates to patient selection using a signature score derived from a gene expression based biomarker or comparison to a pre-specified threshold to identify patients who are most likely to need treatment.
• the invention further relates to predicting the survival or determining the prognosis of a patient and classifying them into a poor survival prognosis group or a favorable survival prognosis group based on signature score. Additionally, the invention relates to the identification of prognostic gene expression based biomarkers associated with overall survival in primary melanoma.
• a method for determining the prognosis and predicting the overall survival of a melanoma patient comprising the steps: obtaining or receiving a sample from the tumor of a patient, determining the patient’s biomarker expression profile, obtaining a biomarker reference expression profile associated with overall survival, determining the signature score from the biomarker expression profile associated with metastatic disease progression, and classifying the patient with melanoma into a poor survival group or a favorable survival group, wherein the patient is classified into a poor survival prognosis group if the tumor is classified as biomarker positive, and wherein the patient with poor survival prognosis can be further treated as applicable.
• the patient is determined to have a poor prognosis if the tumor is classified as biomarker positive for a gene expression based biomarker defined by 5 or more genes from Table 2 and a favorable prognosis if the tumor is classified as biomarker negative for a gene expression based biomarker defined by 5 or more genes from Table 2.
• the invention relates to a method of treatment of a patient who is determined to have a poor prognosis using the methods defined herein, wherein the patient is treated with a PD-1 antagonist.
• the invention further relates to a method for treating cancer in a patient having a tumor which comprises administering to the patient a PD-1 antagonist if the tumor is postive for a gene expression based biomarker defined by 5 or more genes from Table 2. or administering to the patient a cancer treatment that does not include a PD-1 antagonist if the tumor is negative for the biomarker.
• FIG. 1 is a volcano plots showing statistically significant values (p-values, adjusted for false discovery rate) versus hazards ratio for all genes screened. See Example ID.
• FIG. 2A, 2B. and 2C are histograms and overlaid cumulative distribution plots that show distribution of hazards ratio, nominal two-sided p-value, and FDR-adjusted p-value by overall survival Cox proportional hazards regression performed genome wide in primary Merck- Moffitt melanoma tumors.
• FIG. 3A and 3B are histograms and overlaid cumulative distribution plots that show the distribution of all pairwise correlations between genes in sets identified in Merck- Moffitt melanoma data set to be associated with overall survival.
• FIG. 4 is a scatterplot that shows coherence of genes selected by univariate Cox proportional hazards regression model in primary melanoma tumors.
• FIG. 10 is a scatterplot illustrating the dependence of classification metrics as a function of cutoff from the proposed gene expression signature score as applied to stratify Merck -Moffitt primary melanoma patients who had or did not have event (death) within the first tw o years.
• FIG. 11 is a two-dimensional heat map plot showing correlations among metastatic versus primary status, proposed de novo signature scores, and additional gene expression signatures.
• FIG. 12 is a scatterplot that shows de novo prognostic signature score versus Stroma/EMT/TGFb consensus signature score in Merck-Moffitt melanoma tumor data.
• the invention relates to a gene expression based biomarker that is predictive of a patient’s prognosis, wherein the patient has melanoma. More specifically, the invention relates to a gene expression based biomarker that is predictive of a patient’s need to be treated, for example, treatment with a PD-1 antagonist.
• ⁇ ‘About” when used to modify a numerically defined parameter means that the parameter may vary by as much as 10% above or below the stated numerical value for that parameter.
• a gene signature consisting of about 10 genes may have between 9 and 11 genes.
• a reference gene signature score of about 2.462 includes scores of and any score between 2.2158 and 2.708.
• “about” can mean a variation of ⁇ 0.1%. ⁇ 0.5%, ⁇ 1%, ⁇ 2%, ⁇ 3%, ⁇ 4%.
• “about 6 weeks ’ refers to the stated time ⁇ a variation that can occur due to patient/clinician scheduling and availability around the 6-week target date.
• “about 6 weeks” can refer to 6 weeks ⁇ 5 days, 6 weeks ⁇ 4 days, 6 weeks ⁇ 3 days, 6 weeks ⁇ 2 days or 6 weeks ⁇ 1 day, or may refer to 5 weeks, 2 days through 6 weeks, 5 days.
• administering and “treatment” as it applies to an animal, human, experimental subject, patient, cell, tissue, organ, or biological fluid, refers to contact of an exogenous pharmaceutical, therapeutic, diagnostic agent, or composition to the animal, human, subject, cell, tissue, organ, or biological fluid.
• Treat” or “treating” a cancer means to administer a PD-1 antagonist, e.g., an anti -PD-1 antibody or antigen binding fragment thereof, to a patient having a cancer, or diagnosed with a cancer, to achieve at least one positive therapeutic effect, such as, reduced number of cancer cells, reduced tumor size, reduced rate of cancer cell infiltration into peripheral organs, or reduced rate of tumor metastasis or tumor growth.
• a PD-1 antagonist e.g., an anti -PD-1 antibody or antigen binding fragment thereof
• Treatment may include one or more of the following: inducing/increasing an antitumor immune response, decreasing the number of one or more tumor markers, halting or delaying the grow th of a tumor or blood cancer or progression of disease associated with PD-1 binding to its ligands PD-L1 and/or PD-L2 (“PD- 1 -related disease”) such as cancer, stabilization of PD-1 -related disease, inhibiting the growth or survival of tumor cells, eliminating or reducing the size of one or more cancerous lesions or tumors, decreasing the level of one or more tumor markers, ameliorating or abrogating the clinical manifestations of PD-1 -related disease, reducing the severity or duration of the clinical symptoms of PD-1 -related disease such as cancer, prolonging the survival of a patient relative to the expected survival in a similar untreated patient, and inducing complete or partial remission of a cancerous condition or other PD-1 related disease.
• PD- 1 -related disease such as cancer
• the treatment achieved by a therapeutically effective amount is any of progression free survival (PFS), disease free survival (DFS) or overall survival (OS).
• the treatment achieved by a therapeutically effective amount is any of partial response (PR), complete response (CR), PFS, DFS, overall response (OR) or OS.
• PFS also referred to as “Time to Tumor Progression” indicates the length of time during and after treatment that the cancer does not grow, and includes the amount of time patients have experienced a complete response or a partial response, as well as the amount of time patients have experienced stable disease.
• DFS refers to the length of time during and after treatment that the patient remains free of disease.
• OS refers to a prolongation in life expectancy as compared to naive or untreated individuals or patients.
• While an embodiment of the treatment methods, compositions and uses of the present invention may not be effective in achieving a positive therapeutic effect in even' patient, it should do so in a statistically significant number of patients as determined by any statistical test known in the art such as the Student’s t-test, the chi 2 - test, the U-test according to Mann and Whitney, the Kruskal-Wallis test (H-test), Jonckheere- Terpstra-test and the Wilcoxon-test.
• any statistical test known in the art such as the Student’s t-test, the chi 2 - test, the U-test according to Mann and Whitney, the Kruskal-Wallis test (H-test), Jonckheere- Terpstra-test and the Wilcoxon-test.
• antibody refers to any form of antibody that exhibits the desired biological or binding activity. Thus, it is used in the broadest sense and specifically covers, but is not limited to, monoclonal antibodies (including full length monoclonal antibodies), polyclonal antibodies, multispecific antibodies (e.g, bispecific antibodies), humanized, fully human antibodies, chimeric antibodies and camelized single domain antibodies.
• Monoclonal antibodies including full length monoclonal antibodies
• polyclonal antibodies include full length monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g, bispecific antibodies), humanized, fully human antibodies, chimeric antibodies and camelized single domain antibodies.
• Parental antibodies are antibodies obtained by exposure of an immune system to an antigen prior to modification of the antibodies for an intended use, such as humanization of a parental antibody generated in a mouse for use as a human therapeutic.
• the basic antibody structural unit comprises a tetramer.
• Each tetramer includes two identical pairs of polypeptide chains, each pair having one "light” (about 25 kDa) and one "heavy” chain (about 50-70 kDa).
• the amino-terminal portion of each chain includes a variable region of about 100 to 110 or more amino acids primarily responsible for antigen recognition.
• the carboxyl-terminal portion of the heavy chain may define a constant region primarily responsible for effector function.
• human light chains are classified as kappa and lambda light chains.
• variable regions of each light/heavy chain pair form the antibody binding site.
• an intact antibody has two binding sites.
• the two binding sites are, in general, the same.
• variable domains of both the heavy and light chains comprise three hypervariable regions, also called complementarity determining regions (CDRs), which are located within relatively conserved framework regions (FR).
• CDRs complementarity determining regions
• FR framework regions
• the CDRs are usually aligned by the framework regions, enabling binding to a specific epitope.
• both light and heavy chain variable domains comprise FR1, CDR1, FR2, CDR2, FR3, CDR3 and FR4.
• the assignment of amino acids to each domain is, generally, in accordance with the definitions of Sequences of Proteins of Immunological Interest, Kabat, et al. National Institutes of Health, Bethesda, Md.; 5 th ed.; NIH Publ. No.
• antibody fragment or “antigen binding fragment” refers to antigen binding fragments of antibodies, i.e., antibody fragments that retain the ability to bind specifically to the antigen bound by the full-length antibody, e.g., fragments that retain one or more CDR regions.
• antibody binding fragments include, but are not limited to, Fab, Fab', F(ab')2, and Fv fragments; diabodies; linear antibodies; single-chain antibody molecules, e.g., sc-Fv; nanobodies and multispecific antibodies formed from antibody fragments.
• An antibody that "specifically binds to" a specified target protein is an antibody that exhibits preferential binding to that target as compared to other proteins, but this specificity does not require absolute binding specificity.
• An antibody is considered “specific” for its intended target if its binding is determinative of the presence of the target protein in a sample, e.g., without producing undesired results such as false positives.
• Antibodies, or binding fragments thereof, useful in the present invention will bind to the target protein with an affinity' that is at least two fold greater, preferably at least ten times greater, more preferably at least 20- times greater, and most preferably at least 100-times greater than the affinity with non-target proteins.
• an antibody is said to bind specifically to a polypeptide comprising a given amino acid sequence, e.g., the amino acid sequence of a mature human PD-1 or human PD- L1 molecule, if it binds to polypeptides comprising that sequence but does not bind to proteins lacking that sequence.
• Chimeric antibody refers to an antibody in which a portion of the heavy’ and/or light chain is identical with or homologous to corresponding sequences in an antibody derived from a particular species (e.g., human) or belonging to a particular antibody class or subclass, while the remainder of the chain(s) is identical with or homologous to corresponding sequences in an antibody derived from another species (e.g., mouse) or belonging to another antibody class or subclass, as well as fragments of such antibodies, so long as they exhibit the desired biological activity.
• a particular species e.g., human
• another species e.g., mouse
• Human antibody refers to an antibody that comprises human immunoglobulin protein sequences only.
• a human antibody may contain murine carbohydrate chains if produced in a mouse, in a mouse cell, or in a hybridoma derived from a mouse cell.
• mouse antibody'’ or rat antibody refer to an antibody that comprises only mouse or rat immunoglobulin sequences, respectively.
• Humanized antibody refers to forms of antibodies that contain sequences from non-human (e.g., murine) antibodies as well as human antibodies. Such antibodies contain minimal sequence derived from non-human immunoglobulin.
• the humanized antibody will comprise substantially all of at least one, and typically two, variable domains, in which all or substantially all of the hypervariable loops correspond to those of a non-human immunoglobulin and all or substantially all of the FR regions are those of a human immunoglobulin sequence.
• the humanized antibody optionally also will comprise at least a portion of an immunoglobulin constant region (Fc). typically that of a human immunoglobulin.
• the humanized forms of rodent antibodies will generally comprise the same CDR sequences of the parental rodent antibodies, although certain amino acid substitutions may be included to increase affinity, increase stability of the humanized antibody, or for other reasons.
• Anti-tumor response when referring to a cancer patient treated with a therapeutic agent, such as a PD-1 antagonist, means at least one positive therapeutic effect, such as for example, reduced number of cancer cells, reduced tumor size, reduced rate of cancer cell infiltration into peripheral organs, reduced rate of tumor metastasis or tumor growth, or progression free survival. Positive therapeutic effects in cancer can be measured in a number of ways (See, W. A. Weber, J. Null. Med. 50: 1 S-l OS (2009); Eisenhauer et al., supra). In some embodiments, an anti-tumor response to a PD-1 antagonist is assessed using RECIST 1. 1 criteria, bidimensional irRC or unidimensional irRC.
• Bidimensional irRC refers to the set of criteria described in Wolchok JD, et al. Guidelines for the evaluation of immune therapy activity in solid tumors: immune-related response criteria. Clin Cancer Res. 2009;15(23):7412-7420. These criteria utilize bidimensional tumor measurements of target lesions, which are obtained by multiplying the longest diameter and the longest perpendicular diameter (cm 2 ) of each lesion.
• Biotherapeutic agent means a biological molecule, such as an antibody or fusion protein, that blocks ligand / receptor signaling in any biological pathway that supports tumor maintenance and/or grow th or suppresses the anti-tumor immune response.
• nonHodgkin lymphoma nonHodgkin lymphoma, acute myeloid leukemia (AML), multiple myeloma, gastrointestinal (tract) cancer, renal cancer, ovarian cancer, liver cancer, lymphoblastic leukemia, lymphocytic leukemia, colorectal cancer, endometrial cancer, kidney cancer, prostate cancer, thyroid cancer, melanoma, chondrosarcoma, neuroblastoma, pancreatic cancer, glioblastoma multiforme, cervical cancer, brain cancer, stomach cancer, bladder cancer, hepatoma, breast cancer, colon carcinoma, and head and neck cancer.
• Particularly preferred cancers that may be treated in accordance with the present invention include those characterized by elevated expression of one or both of PD-L1 and PD-L2 in tested tissue samples.
• CDR or “CDRs” as used herein means complementarity determining region(s) in an immunoglobulin variable region, generally defined using the Kabat numbering system.
• Consists essentially of and variations such as “consist essentially of 1 or “consisting essentially of,” as used throughout the specification and claims, indicate the inclusion of any recited elements or group of elements, and the optional inclusion of other elements, of similar or different nature than the recited elements, that do not materially change the basic or novel properties of the specified dosage regimen, method, or composition.
• a gene signature score is defined as the composite RNA expression score for a set of genes that consists of a specified list of genes, the skilled artisan will understand that this gene signature score could include the RNA level determined for one or more additional genes, preferably no more than three additional genes, if such inclusion does not materially affect the predictive power.
• Framework region or “FR” as used herein means the immunoglobulin variable regions excluding the CDR regions.
• “Homology” refers to sequence similarity between two polypeptide sequences when they are optimally aligned. When a position in both of the two compared sequences is occupied by the same amino acid monomer subunit e.g., if a position in a light chain CDR of two different Abs is occupied by alanine, then the two Abs are homologous at that position. The percent of homology is the number of homologous positions shared by the two sequences divided by the total number of positions compared x 100. For example, if 8 of 10 of the positions in two sequences are matched or homologous when the sequences are optimally aligned then the two sequences are 80% homologous.
• the comparison is made when two sequences are aligned to give maximum percent homology 7 .
• the comparison can be performed by a BLAST algorithm wherein the parameters of the algorithm are selected to give the largest match between the respective sequences over the entire length of the respective reference sequences.
• BLAST ALGORITHMS Altschul, S.F., et al., (1990) J. Mol. Biol. 215:403-410; Gish, W., et al., (1993) Nature Genet. 3:266-272; Madden, T.L., et al., (1996) Meth. Enzymol. 266: 131-141; Altschul, S.F., et al., (1997) Nucleic Acids Res . 25:3389-3402; Zhang, J., et al., (1997) Genome Res. 7:649-656; Wootton, J.C., et al., (1993) Comput.
• isolated antibody and “isolated antibody fragment’ refers to the purification status and in such context means the named molecule is substantially free of other biological molecules such as nucleic acids, proteins, lipids, carbohydrates, or other material such as cellular debris and growth media. Generally, the term “isolated” is not intended to refer to a complete absence of such material or to an absence of water, buffers, or salts, unless they are present in amounts that substantially interfere with experimental or therapeutic use of the binding compound as described herein.
• “Kabaf ’ as used herein means an immunoglobulin alignment and numbering system pioneered by Elvin A. Kabat ((1991) Sequences of Proteins of Immunological Interest, 5th Ed. Public Health Service. National Institutes of Health, Bethesda, Md.).
• the monoclonal antibodies to be used in accordance with the present invention may be made by the hybridoma method first described by Kohler et al. (1975) Nature 256: 495, or may be made by recombinant DNA methods (see, e.g., U.S. Pat. No. 4,816,567).
• the "monoclonal antibodies” may also be isolated from phage antibody libraries using the techniques described in Clackson et al. (1991) Nature 352: 624-628 and Marks et al. (1991) J. Mol. Biol. 222: 581-597, for example. See also Presta (2005) J. Allergy’ Clin. Immunol. 116:731.
• Oligonucleotide refers to a nucleic acid that is usually between 5 and 100 contiguous bases in length, and most frequently between 10-50, 10-40, 10-30, 10-25. 10-20, 15- 50. 15-40, 15-30, 15-25. 15-20, 20-50, 20-40. 20-30 or 20-25 contiguous bases in length.
• PD-1 antagonist means any chemical compound or biological molecule that blocks binding of PD-L1 to PD-1 and preferably also blocks binding of PD-L2 to PD-1.
• a PD-1 antagonist blocks binding of PD-L1 expressed on a cancer cell to PD-1 expressed on an immune cell (T cell, B cell or NKT cell) and preferably also blocks binding of PD-L2 expressed on a cancer cell to the immune-cell expressed PD-1.
• PD-1 and its ligands include: PDCD1, PD1, CD279 and SLEB2 for PD- 1; PDCD1L1, PDL1, B7H1, B7-4, CD274 and B7-H for PD-L1; and PDCD1L2, PDL2, B7-DC, Btdc and CD273 for PD-L2.
• the PD-1 antagonist blocks binding of human PD-L1 to human PD-1, and preferably blocks binding of both human PD-L1 and PD-L2 to human PD-1.
• Human PD-1 amino acid sequences can be found in NCBI Locus No.:
• Human PD-L1 and PD-L2 amino acid sequences can be found in NCBI Locus No.: NP_054862 and NP_079515, respectively.
• PD-1 antagonists useful in the any of the various aspects and embodiments of the present invention include a monoclonal antibody (mAb), or antigen binding fragment thereof, which specifically binds to PD-1 or PD-L1, and preferably specifically binds to human PD-1 or human PD-L1.
• the mAb may be a human antibody, a humanized antibody or a chimeric antibody, and may include a human constant region.
• the human constant region is selected from the group consisting of IgGl, IgG2, IgG3 and IgG4 constant regions, and in some embodiments, the human constant region is an IgGl or IgG4 constant region.
• the antigen binding fragment is selected from the group consisting of Fab, Fab'- SH, F(ab')2, scFv and Fv fragments.
• mAbs that bind to human PD-1 are described in US 7,521,051, US 8,008,449, and US 8,354,509.
• Specific anti -human PD-1 mAbs useful as the PD-1 antagonist various aspects and embodiments of the present invention include: pembrolizumab, a humanized IgG4 mAb with the structure described in WHO Drug Information, Vol. 27, No. 2, pages 161-162 (2013), nivolumab (BMS-936558), a human IgG4 mAb with the structure described in WHO Drug Information, Vol. 27, No.
• pidilizumab CT-011, also known as hBAT or hBAT-1
• humanized antibodies h409Al 1, 11409A16 and h409A17 which are described in WO 2008/156712.
• Additional PD- 1 antagonists useful in any of the various aspects and embodiments of the present invention include a pembrolizumab biosimilar or a pembrolizumab variant.
• pembrolizumab biosimilar means a biological product that (a) is marketed by an entity other than Merck and Co., Inc. (Rahway, N.J., USA), or a subsidiary’ thereof, and (b) is approved by a regulatory agency in any country for marketing as a pembrolizumab biosimilar.
• a pembrolizumab biosimilar comprises a pembrolizumab variant as the drug substance.
• a pembrolizumab biosimilar has the same amino acid sequence as pembrolizumab.
• a “pembrolizumab variant'’ means a monoclonal antibody which comprises heavy chain and light chain sequences that are identical to those in pembrolizumab, except for having three, two or one conservative amino acid substitutions at positions that are located outside of the light chain CDRs and six, five, four, three, two or one conservative amino acid substitutions that are located outside of the heavy chain CDRs, e.g., the variant positions are located in the FR regions or the constant region.
• pembrolizumab and a pembrolizumab variant comprise identical CDR sequences, but differ from each other due to having a conservative amino acid substitution at no more than three or six other positions in their full length light and heavy chain sequences, respectively.
• a pembrolizumab variant is substantially the same as pembrolizumab with respect to the following properties: binding affinity to PD-1 and ability to block the binding of each of PD-L1 and PD-L2 to PD-1.
• mAbs that bind to human PD-L1 are described in WO2013/019906, W02010/077634 and US8383796.
• Specific anti-human PD-L1 mAbs useful as the PD-1 antagonist in the various aspects and embodiments of the present invention include atezolizumab, BMS-936559, MEDI4736, avelumab and durvalumab.
• immunoadhesin on molecules that specifically bind to PD-1 are described in WO 2010/027827 and WO 2011/066342.
• Specific fusion proteins useful as the PD-1 antagonist in the treatment method, medicaments and uses of the present invention include AMP -224 (also known as B7-DCIg), which is a PD-L2-FC fusion protein and binds to human PD-1.
• Probe as used herein means an oligonucleotide that is capable of specifically hybridizing under stringent hybridization conditions to a transcript expressed by a gene of interest.
• “RECIST 1.1 Response Criteria” as used herein means the definitions set forth in Eisenhauer et al., E.A. et al., Eur. J Cancer 45:228-247 (2009) for target lesions or non-target lesions, as appropriate based on the context in which response is being measured.
• “Gene expression based biomarker signature score” as used herein means the score for a gene expression based biomarker that has been determined to divide at least the majority of responders from at least the majority of non-responders in a reference population of patients who have the same tumor type as a test patient and may have been treated with a PD-1 antagonist or who will be evaluated for treatment with a PD-1 antagonist.
• responders in the reference population will have a gene expression based biomarker signature score that is above the selected reference score, while the gene expression based biomarker signature score for at least any of 60%, 70%, 80%, 90% or 95% of the non-responders in the reference population will be lower than the selected reference score.
• the negative predictive value of the reference score is greater than the positive predictive value.
• responders in the reference population are defined as patients who achieved a partial response (PR) or complete response (CR) as measured by RECIST 1. 1 criteria and non-responders are defined as not achieving any RECIST 1. 1 clinical response.
• patients in the reference population are treated with substantially the same anti-PD-1 therapy as that being considered for the test patient, i.e., administration of the same PD-1 antagonist using the same or a substantially similar dosage regimen.
• sample when referring to a tumor or any other biological material referenced herein, means a tissue sample that has been removed from the patient’s tumor; thus, the testing methods described herein are not performed in or on the patient (although the methods of treatment of the invention clearly include treating the patient).
• sustained response means a sustained therapeutic effect after cessation of treatment with a therapeutic agent, or a combination therapy described herein.
• the sustained response has a duration that is at least the same as the treatment duration, or at least 1.5, 2.0, 2.5 or 3 times longer than the treatment duration.
• tissue section refers to a single part or piece of a tissue sample, e.g., a thin slice of tissue cut from a sample of a normal tissue or of a tumor.
• Tumor as it applies to a patient diagnosed with, or suspected of having, a cancer refers to a malignant or potentially malignant neoplasm or tissue mass of any size, and includes primary tumors and secondary neoplasms.
• a solid tumor is an abnormal grow th or mass of tissue that usually does not contain cysts or liquid areas. Different types of solid tumors are named for the type of cells that form them. Examples of solid tumors are sarcomas, carcinomas, and lymphomas. Leukemias (cancers of the blood) generally do not form solid tumors (National Cancer Institute, Dictionary of Cancer Terms).
• the term “poor prognosis” in the context of melanoma means that a patient is expected to progress from primary melanoma to malignant or metastatic melanoma within five years of initial disagnosis of melanoma. Further, those with poor prognosis are more likely to progress from primary melanoma to metastatic melanoma.
• the term “overall survival’ 7 or “OS” is the length of time from either the date of diagnosis or the start of treatment for a disease, such as cancer, that patients diagnosed with the disease are still alive. In a clinical trial, measuring the overall survival is one way to see how well a new treatment works. A favorable overall survival is where a patient is expected to survive longer compared to a patient with poor or less favorable overall survival.
• the term as used in this document refers to a protein coding nucleic acid.
• the gene includes regulatory' sequences involved in transcription, or message production or composition.
• the gene comprises transcribed sequences that encode for a protein, polypeptide, or peptide.
• an “isolated gene” may comprise transcribed nucleic acid(s), regulatory sequences, coding sequences, or the like, isolated substantially away from other such sequences, such as other naturally occurring genes, regulatory' sequences, polypeptide or peptide encoding sequences, etc.
• Advanced melanoma comprises stages III and IV which includes melanoma that has spread locally or through the lymphatic system to a regional lymph node. Stage IV describes melanoma that has spread through the bloodstream to other parts of the body.
• Metalstatic tumor as used herein means a new tumor when the cancerous cells from the original tumor (primary tumor) get loose, spread through the lymph or blood circulation, and start a new tumor (metastatic tumor).
• “Favorable survival” or “favorable prognosis,” as used herein, refers to an increased chance of survival as compared to patients in a ‘poor survival’ group.
• the biomarkers of the application can prognose or classify patients into a favorable survival group.
• “Poor survival” or “poor prognosis,” as used herein, refers to an increased risk of death as compared to patients in a favorable survival group.
• the biomarkers of the application can prognose or classify patients into a poor survival group.
• the invention identifies a genome wide tumor derived gene expression based biomarker that is associated with poor prognosis for patients suffering from melanoma.
• the invention provides a set of 100 genes whose expression is correlated with identifying a patient with poor prognosis for treating early stage melanoma.
• the invention comprises a gene expression based biomarker comprising poor prognosis genes, wherein the gene expression based biomarker comprises 5 or more genes listed in Table 1.
• the invention provides the identification of a gene expression based biomarker that allows classification of a patient into a prognosis group, wherein the prognosis group is predictive of a patient’s need of further treatment.
• the invention relates to the identification of a genome-wide tumor derived gene expression based biomarker that can be used in identifying, classify ing, and/or selecting melanoma patients with early disease (Stage 0 or Stage I), who may be in need of treatment.
• the invention provides a gene expression based biomarker comprising at least 5 genes listed in Table I that is correlated with a need of treatment for a patient who has been diagnosed with melanoma.
• a patient is identified as a patient with poor prognosis if the patient has a higher expression of 5 or more poor prognosis genes listed in Table 1 (e.g., 5 or more, 6 or more. 7 or more, 8 or more, 9 or more, 10 or more,... 95 or more, 96 or more, 97 or more. 98. 99 or 100 genes from Table 1).
• a patient is identified as a patient with good prognosis if the patient has a lower expression of 5 or more poor prognosis genes listed in Table 1.
• the invention provides a method of using a gene expression based biomarker to identify melanoma patients with a poor prognosis in early stage disease.
• a patient is positive for the gene expression based biomarker if the patient has a higher expression of poor prognosis genes found in Table 1, or if a patient has a signature score about a pre-specified threshold. As a result, the tumor is classified as biomarker positive.
• the invention relates to identifying a melanoma patient having a poor prognosis.
• the patient having a poor prognosis is likely to have a reoccurrence of melanoma, metastatic disease progression, or poor overall survival.
• the melanoma is early stage. In one embodiment, the melanoma is primary melanoma. In another embodiment, the melanoma is metastatic melanoma.
• the invention relates to classifying a patient as having a favorable prognosis or a poor prognosis based on a gene expression level by calculating an elevated level of gene expression of 5 or more poor prognosis genes listed in Table 1.
• a further sub-embodiment comprises classifying a patient as having either a favorable prognosis or a poor prognosis based on a gene expression level by calculating an elevated level of a gene expression of 5 or more poor prognosis genes listed in Table 1, wherein an elevated gene expression level indicates a patient with a pathology related to metastatic melanoma, and wherein the patient is in need of further medical treatment.
• the invention relates to classifying a patient as having a poor prognosis based on a gene expression level by calculating an elevated level of a gene expression of 5 or more poor prognosis genes listed in Table 1. Additionally, the invention relates to the calculation of an elevated level of gene expression used in determining a threshold for patients in a clinical trial setting. A further sub-embodiment comprises changing the threshold dependent on clinical outcomes designated for the clinical trial.
• the invention relates to classifying a patient having a favorable prognosis based on a gene expression level by calculating a decreased level of gene expression of 5 or more poor prognosis genes listed in Table 1.
• the invention relates to identifying a gene expression based biomarker within a sample obtained from a patient to calculate a gene signature score. In a further embodiment, the invention relates to calculating a gene signature score based on the poor prognosis genes to determine a prognosis in a melanoma patient. In a further aspect, the classification of a prognosis in a melanoma patient allows for treatment with an appropriate treatment option. A patient having a favorable prognosis may not have a clinical need for additional treatment and can avoid possible side effects.
• the invention relates to the use of a gene expression based biomarker signature score for a gene expression based biomarker which comprises a set of at least about 5 of the poor prognosis genes listed in Table 1 to determine prognosis of a melanoma patient.
• the gene expression based biomarker comprises at least 5 (five) genes selected from the genes listed in Table 1. In other embodiments, the gene expression based biomarker comprises at least 5 genes, at least 6 genes, at least 7 genes, at least 8 genes, at least 9 genes, at least 10 genes, at least 11 genes, at least 12 genes, at least 13 genes, etc. or 100 genes from the genes listed in Table 1.
• the gene expression based biomarker comprises the following genes: AASDHPPT, ABCC5, ABI2, ANXA5, AP1S2, ARFGEF2, ASAHI, ATP6V1C1,ATP6V1H, BAX, BFAR, C12orf60, C20orf96, C5orf22, CASP2, CBX3, CC2D2A, CD320, CDC23, CPOX. DHODH, DLL3.
• the invention provides a genome wide tumor derived gene expression based biomarker that is associated with good prognosis in melanoma.
• the invention provides a set of 100 genes whose expression is negatively correlated with identifying a patient with poor prognosis for treating early stage melanoma.
• the invention comprises a gene expression based biomarker comprising good prognosis genes, wherein the gene expression based biomarker comprises genes listed in Table 2.
• the invention provides the identification of a gene expression based biomarker that allows classification of a patient into a prognosis group, wherein the prognosis group is predictive of a patient’s need of treatment.
• the invention relates to the identification of a genome w ide tumor derived gene expression based biomarker that can be used in identifying, classifying, and/or selecting melanoma patients with early disease (Stage 0 or Stage I) who may be in need of treatment.
• the invention provides a method of treating a melanoma patient with early stage disease by identification of the patient with a gene expression based biomarker.
• the invention relates to identification of a patient with a decreased level of gene expression based biomarker, wherein the gene expression based biomarker comprises 5 or more good prognosis genes from Table 2, and wherein the patient has metastatic melanoma, to evaluate for further treatment options.
• the invention relates to identifying a melanoma patient having a poor prognosis.
• the patient having a poor prognosis is likely to have a reoccurrence of melanoma, metastatic disease progression, or poor overall survival.
• the melanoma is early stage. In another embodiment, the melanoma is primary melanoma. In another embodiment, the melanoma is metastatic melanoma. In some embodiments, the invention relates to classifying a patient having a favorable prognosis or a patient having a poor prognosis based on a gene expression level by calculating an elevated level of a gene expression of 5 or more good prognosis genes listed in Table 2 or classifying a patient having a poor prognosis based on a gene expression level by calculating a decreased level of a gene expression of 5 or more good prognosis genes listed in Table 2.
• a further sub-embodiment is to classify a patient as having either a favorable prognosis or a poor prognosis based on a gene expression level by calculating a level of gene expression of 5 or more good prognosis genes listed in Table 2, wherein a lower gene expression level of good prognosis genes indicates a patient with a poor prognosis and a patient likely to have pathology related to metastatic melanoma and a higher gene expression level of good prognosis genes indicates a patient with a favorable prognosis and a patient not likely to have pathology related to metastatic melanoma.
• a patient is positive for a gene expression based biomarker if the patient has lower expression of at least 5 good prognosis genes found in Table 2. As a result, the tumor is classified as biomarker positive and the patient is in need of further treatment.
• the invention relates to classifying a patient having a favorable prognosis based on a gene expression level by calculating an elevated level of gene expression of 5 or more good prognosis genes listed in Table 2.
• the invention relates to identifying biomarkers within a sample obtained from a patient, e.g., a patient’s tumor to calculate a gene signature score. In a further embodiment, the invention relates to calculating a gene signature score based on the good prognosis genes to predict a prognosis in a melanoma patient. In a further aspect, the classification of a prognosis in a melanoma patient allows for treatment with an appropriate treatment option. A patient having a favorable prognosis may not have a clinical need for additional treatment and can avoid possible side effects.
• the invention relates to calculating a gene signature score based on the poor prognosis genes listed in Table 1 and favorable prognosis genes listed in Table 2 to determine a prognosis for a melanoma patient.
• the gene signature score can take into account the desire for higher expression of poor prognosis genes and lower expression of favorable prognosis genes.
• the classification of a prognosis in a melanoma patient allows for treatment with an appropriate treatment option. A patient with favorable prognosis may not have a clinical need for additional treatment and can avoid possible side effects.
• the gene expression based biomarker comprises the following genes: AASDHPPT, ABCC5, ABI2, ANXA5, AP1S2, ARFGEF2. ASAHI, ATP6V1C1,ATP6V1H, BAX, BFAR, C12orf60. C20orf96, C5orf22, CASP2. CBX3.
• DNM1, ELF4, EML1, EMP2, EPHA1, EPHB6 DNM1, ELF4, EML1, EMP2, EPHA1, EPHB6.
• SEMA4A SEMA4A, SGMS1, SGPP2.
• SLC35F2 SLCO2A1, SLCO3A1.
• SMAGP SPTLC3, SYTL1, TOX2, TRERF1, TUBA4A, and ZNF385A (from Table 2).
• One embodiment of the invention relates to the use of the gene expression based biomarker to evaluate or compare tumor samples obtained from a patient and predict the patient’s response to cancer therapy agents, cancer progression, cancer reoccurrence, cancer prognosis and/or to determine a patient’s cancer prognosis and overall survival.
• Yet another embodiment of the invention relates to the use of mRNA whose expression levels are shown to correlate with the gene expression based biomarker to predict cancer progression, cancer reoccurrence, cancer prognosis, and overall survival in a cancer patient.
• the invention identifies 100 genes associated with good prognosis and 100 genes associated with poor prognosis in primary melanoma.
• the invention provides a method of determining the clinical need of a patient with melanoma for a drug treatment that induces a therapeutically beneficial response in cancer cells, wherein said patient is predicted to be in clinical need of said treatment if a sample of the cancer cells is classified as having a positive level of the gene expression based biomarker defined by 5 or more genes from Table 1.
• the invention provides a method of determining the clinical need of a patient with melanoma for a drug treatment that induces a therapeutically beneficial response in cancer cells, wherein said patient is predicted to be in clinical need of said treatment if a sample of the cancer cells is classified as having a level below a pre-specified threshold of the gene expression based biomarker defined by 5 or more genes from Table 2.
• the invention provides a method for testing a tumor for the presence or absence of a biomarker that predicts clinical need for treatment with a PD-1 antagonist, which comprises: (a) obtaining or receiving a sample from the tumor, (b) measuring the raw RNA expression level in the tumor for each gene in a gene expression based biomarker; (c) normalizing each of the measured raw RNA expression levels; (d) calculating the arithmetic mean of the normalized RNA expression levels for each of the genes to generate a score for the gene expression based biomarker; classifying the tumor as biomarker positive or biomarker negative; wherein the gene expression based biomarker comprises (i) at least 5 genes selected from the genes listed in Table 1 which have a positive correlation to the signature score, (ii) at least 5 genes selected from the genes listed in Table 2 which have a negative correlation to the signature score, or (iii) a combination of at least 5 genes selected from the genes listed in Table 1 having a positive correlation the signature score and/or the genes listed
• classifying the tumor as biomarker positive or negative comprises comparing the calculated score to a reference score.
• step (b) comprises normalizing each of the measured raw RNA levels for each gene in the gene expression based biomarker using the measured RNA levels of a set of normalization genes.
• the normalization gene set comprises 10 to 12 genes.
• the gene expression platform comprises the 11 genes listed in Table 3 below.
• Gene signature scores may be derived by using the entire clinical prognosis gene set (i.e., all of the genes specified in Table 1, all of the genes specified in Table 2, or all the genes specified in Tables 1 and 2, or a selection of genes from Table 1, a selection of genes from Table 2, or a selection of genes from Table 1 and Table 2), or any subset thereof, as a set of input covariates to multivariate statistical models that will determine signature scores using the fitted model coefficients, for example the linear predictor in a logistic or Cox regression.
• One specific example of a multivariate strategy is the use of elastic net modeling (Zou & Hastie, 2005, JR. Statist Soc. B. 67(2): 301-320; Simon et al., 2011. J.
• the LI penalty parameter may be set very low. effectively running a ridge regression.
• model-based signature scores would be to use a simple averaging approach, e.g., the signature score for each tumor sample would be defined as the average of that sample’s normalized RNA expression levels for those signature genes deemed to be positively associated with the poor prognosis minus the average of that sample’s normalized RNA expression levels for those signature genes deemed to be negatively associated with the poor prognosis.
• Also provided herein is a method for treating cancer in a patient having a tumor which comprises administering to the patient a PD-1 antagonist if the patient is positive for a gene expression based biomarker and is therefore associated with poor prognosis. Also provided herein is a method for treating cancer in a patient having a tumor which comprises administering to the patient a PD-1 antagonist if the patient has higher expression of poor prognosis genes (genes listed in Table 1), and is therefore associated with poor prognosis, and in need of additional treatments and would likely achieve a clinical benefit from treatment with a PD-1 antagonist.
• a method for treating cancer in a patient having a tumor which comprises administering to the patient a PD-1 antagonist if the patient has lower expression of favorable prognosis genes (genes listed in Table 2), and is therefore associated with poor prognosis and in need of additional treatments and would likely achieve a clinical benefit from treatment with a PD-1 antagonist.
• a gene signature score (also referred to as a positive or elevated level for the gene signature based biomarker) is determined in a sample of tumor tissue removed from a patient.
• a positive level for the gene signature based biomarker is determined by elevated levels for identified genes set forth in Table 1.
• the tumor may be primary or recurrent, and may be of any ty pe (as described above), any stage (e.g., Stage 0, 1, II, III, or IV or an equivalent of other staging system), and/or histology’.
• the patient may be of any age, gender, treatment history’ and/or extent and duration of remission.
• the gene signature score for a tumor is determined using FFPE tissue sections of about 3-4 millimeters, and preferably 4 micrometers, which are mounted and dried on a microscope slide.
• RNA transcript includes mRNA transcribed from the gene, and/or specific spliced variants thereof and/or fragments of such mRNA and spliced variants.
• RNA may be isolated from frozen tissue samples by homogenization in guanidinium isothiocyanate and acid phenol-chloroform extraction.
• Commercial kits are available for isolating RNA from FFPE samples. If the tumor sample is an FFPE tissue section on a glass slide, it is possible to perform gene expression analysis on whole cell lysates rather than on isolated total RNA.
• assaying a tumor sample for expression of the genes in Table 1, or gene signatures derived therefrom employs detection and quantification of RNA levels in real-time using nucleic acid sequence based amplification (NASBA) combined with molecular beacon detection molecules.
• NASBA nucleic acid sequence based amplification
• molecular beacon detection molecules employs detection and quantification of RNA levels in real-time using nucleic acid sequence based amplification (NASBA) combined with molecular beacon detection molecules.
• the PD-1 antagonist is nivolumab.
• the method comprises administering 240 mg of nivolumab to the patient about every two weeks.
• the method comprises administering 360 mg of nivolumab to the patient about every three weeks.
• the method comprises administering 480 mg of nivolumab to the patient about every four weeks.
• the invention provides methods of treating a patient (e.g. a human patient) with cancer comprising administering a PD-1 antagonist to the patient, wherein the patient’s tumor has tested positive for a gene expression based biomarker herein, using the methods described herein.
• a patient e.g. a human patient
• any PD-1 antagonist may be used, including for example, the PD-1 antagonists disclosed in this section.
• the invention provides a method for treating cancer in a patient having a tumor which comprises administering to the patient a PD-1 antagonist if the tumor is positive for a gene expression based biomarker, or administering to the patient a cancer treatment that does not include a PD-1 antagonist if the tumor is negative for the biomarker; wherein the determination of whether the tumor is positive or negative for the gene expression based biomarker was made using a method as described herein.
• a tumor is biomarker positive if the calculated score is higher than the reference score of the gene expression based biomarker, and wherein a tumor is biomarker negative if the calculated score is lower than the reference score of the gene expression based biomarker, and wherein a biomarker positive tumor indicates a need for further treatment with a PD-1 antagonist and biomarker negative tumor does not indicate a need for further treatment with a PD-1 antagonist.
• the invention further provides a method for treating cancer in a patient having a tumor, the method comprising:
• the PD-1 antagonist is nivolumab or a variant of nivolumab.
• the PD-1 antagonist is durvalumab or a variant of durvalumab.
• the PD-1 antagonist is cemiplimab or a variant of cemiplimab.
• the PD-1 antagonist is atezolizumab or a variant of atezolizumab.
• the PD-1 antagonist is dostarlimab or a variant of dostarlimab.
• the methods of treatment of the invention may be useful for treating cancer, wherein the cancer is selected from the group consisting of: melanoma, non-small cell lung cancer, head and neck squamous cell cancer, classical Hodgkin lymphoma, primary mediastinal large B-cell lymphoma, urothelial carcinoma, microsatellite instability-high or mismatch repair deficient cancer, microsatellite instability -high or mismatch repair deficient colorectal cancer, gastric cancer, esophageal cancer, cervical cancer, hepatocellular carcinoma, Merkel cell carcinoma, renal cell carcinoma, endometrial carcinoma, a cancer characterized by a tumor having a high mutational burden, cutaneous squamous cell carcinoma, and triple negative breast cancer.
• the cancer is selected from the group consisting of: melanoma, non-small cell lung cancer, head and neck squamous cell cancer, classical Hodgkin lymphoma, primary mediastinal large B-cell lymphoma, urothelial
• a physician may use a gene signature score as a guide in deciding how to treat a patient who has been diagnosed with a type of cancer that is susceptible to treatment with a PD-1 antagonist or other chemotherapeutic agent(s).
• the physician prior to initiation of treatment with the PD-1 antagonist or the other chemotherapeutic agent(s), the physician will order a diagnostic test to determine if a tumor tissue sample removed from the patient is positive or negative for a gene signature biomarker.
• the physician could order a first or subsequent diagnostic test at any time after the individual is administered the first dose of the PD-1 antagonist or other chemotherapeutic agent(s).
• a physician may be considering whether to treat the patient with a pharmaceutical product that is indicated for patients whose tumor tests positive for the gene signature biomarker. For example, if the reported score is at or above a pre-specified threshold score that is associated with response or better response to treatment with a PD-1 antagonist, the patient is treated with a therapeutic regimen that includes at least the PD-1 antagonist (optionally in combination with one or more chemotherapeutic agents), and if the reported gene signature score is below a pre-specified threshold score that is associated with no response or poor response to treatment with a PD-1 antagonist, the patient is treated with a therapeutic regimen that does not include any PD-1 antagonist.
• VEGF receptors other grow th factor receptors, CD20, CD40, CD-40L, GITR, CTLA-4, OX-40, 4-1BB, and ICOS
• an immunogenic agent for example, attenuated cancerous cells, tumor antigens, antigen presenting cells such as dendritic cells pulsed with tumor derived antigen or nucleic acids, immune stimulating cytokines (for example, IL-2, IFNa2, GM-CSF), and cells transfected with genes encoding immune stimulating cytokines such as but not limited to GM-CSF).
• an immunogenic agent for example, attenuated cancerous cells, tumor antigens, antigen presenting cells such as dendritic cells pulsed with tumor derived antigen or nucleic acids, immune stimulating cytokines (for example, IL-2, IFNa2, GM-CSF), and cells transfected with genes encoding immune stimulating cytokines such as but not limited to GM-CSF).
• chemotherapeutic agents include alky lating agents such as thiotepa and cyclosphosphamide; alkyl sulfonates such as busulfan, improsulfan and piposulfan; aziridines such as benzodopa, carboquone, meturedopa, and uredopa; ethylenimines and methylamelamines including altretamine, triethylenemelamine, trietylenephosphoramide, triethylenethiophosphoramide and trimethylolomelamine; acetogenins (especially bullatacin and bullatacinone); a camptothecin (including the synthetic analogue topotecan); bryostatin; callystatin; CC-1065 (including its adozelesin, carzelesin and bizelesin synthetic analogues); cryptophycins (particularly cryptophycin 1 and cryptophycin 8); dolastatin; duocarmycin (including the synthetic an
• chromomycins dactinomycin, daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, doxorubicin (including morpholinodoxorubicin, cyanomorpholino-doxorubicin, 2-pyrrolino-doxorubicin and deoxydoxorubicin), epirubicin, esorubicin, idarubicin, marcellomycin, mitomycins such as mitomycin C, mycophenolic acid, nogalamycin, olivomycins, peplomycin, potfiromycin, puromycin, quelamycin, rodorubicin, streptonigrin, streptozocin, tubercidin, ubenimex.
• doxorubicin including morpholinodoxorubicin, cyanomorpholino-doxorubicin, 2-pyrrolino-doxorubicin and deoxydoxorubicin
• epirubicin esor
• zinostatin, zorubicin anti-metabolites such as methotrexate and 5 -fluorouracil (5-FU); folic acid analogues such as denopterin, methotrexate, pteropterin, trimetrexate; purine analogs such as fludarabine, 6- mercaptopurine, thiamiprine, thioguanine; pyrimidine analogs such as ancitabine, azacitidine, 6- azauridine.
• cyclophosphamide thiotepa
• taxoids e.g., paclitaxel and doxetaxel
• chlorambucil gemcitabine
• 6-thioguanine mercaptopurine
• methotrexate platinum analogs such as cisplatin and carboplatin; vinblastine; platinum; etoposide (VP-16); ifosfamide; mitoxantrone; vincristine; vinorelbine; novantrone; teniposide; edatrexate; daunomycin; aminopterin; xeloda; ibandronate; CPT-11; topoisomerase inhibitor RFS 2000; difluoromethylornithine (DMFO); retinoids such as retinoic acid; capecitabine; and pharmaceutically acceptable salts, acids or derivatives of any of the above.
• DMFO difluoromethylornithine
• anti-hormonal agents that act to regulate or inhibit hormone action on tumors
• SERMs selective estrogen receptor modulators
• aromatase inhibitors that inhibit the enzyme aromatase, which regulates estrogen production in the adrenal glands, such as, for example, 4(5)-imidazoles, aminoglutethimide, megestrol acetate, exemestane, formestane, fadrozole, vorozole, letrozole, and anastrozole
• anti-androgens such as flutamide, nilutamide, bicalutamide. leuprolide, and goserehn; and pharmaceutically acceptable salts, acids or derivatives of any of the above.
• the physician may choose to treat the patient who tests biomarker positive with a combination therapy regimen that includes a PD-1 antagonist and hyaluronan degrading enzymes.
• Administration of PD-1 antagonist can be by any suitable route, and can be facilitated by agents such as hyaluronan degrading enzymes, including hyaluronidases, including soluble PH20 polypeptides, and variants thereof.
• the facilitating agents can be modified to increase pharmacological properties, such as serum half-life, by modifying the agents, such as with polymers. See, e.g., U.S. Patent Nos.7, 767, 429, 8,431,380, 7,871,607, International Publication No.
• compositions comprising PD-1 antagonist and any one of a hyaluronan degrading enzy me, hyaluronidase, soluble hyaluronidase, soluble PH20 polypeptide, or a variant of any of the foregoing.
• the pharmaceutical composition comprises PD-1 antagonist and a soluble PH20 polypeptide or a variant thereof.
• Each therapeutic agent in a combination therapy used to treat a biomarker positive patient may be administered either alone or in a medicament (also referred to herein as a pharmaceutical composition) which comprises the therapeutic agent and one or more pharmaceutically acceptable carriers, excipients and diluents, according to standard pharmaceutical practice.
• Each therapeutic agent in a combination therapy used to treat a biomarker positive patient may be administered simultaneously (i. e. , in the same medicament), concurrently (i.e. , in separate medicaments administered one right after the other in any order) or sequentially 7 in any order.
• Sequential administration is particularly useful when the therapeutic agents in the combination therapy are in different dosage forms (one agent is a tablet or capsule and another agent is a sterile liquid) and/or are administered on different dosing schedules, e.g., a chemotherapeutic that is administered at least daily and a biotherapeutic that is administered less frequently, such as once weekly, once every 7 two weeks, or once every three weeks.
• At least one of the therapeutic agents in the combination therapy is administered using the same dosage regimen (dose, frequency and duration of treatment) that is typically employed when the agent is used as monotherapy for treating the same cancer.
• the patient receives a lower total amount of at least one of the therapeutic agents in the combination therapy than when the agent is used as monotherapy, e.g., smaller doses, less frequent doses, and/or shorter treatment duration.
• Each therapeutic agent in a combination therapy used to treat a biomarker positive patient can be administered orally or parenterally, including the intravenous, intramuscular, intraperitoneal, subcutaneous, rectal, topical, and transdermal routes of administration.
• a patient may be administered a PD-1 antagonist prior to or following surgery to remove a tumor and may be used prior to. during or after radiation therapy.
• a PD-1 antagonist is administered to a patient who has not been previously treated with a biotherapeutic or chemotherapeutic agent, i.e., is treatment-naive. In other embodiments, the PD-1 antagonist is administered to a patient who failed to achieve a sustained response after prior therapy with a biotherapeutic or chemotherapeutic agent, i.e., is treatment-experienced.
• a therapy comprising a PD-1 antagonist is typically used to treat a tumor that is large enough to be found by palpation or by imaging techniques well known in the art, such as MRI, ultrasound, or CAT scan. In some embodiments, the therapy is used to treat an advanced stage tumor having dimensions of at least about 200 mm 3 300 mm’, 400 mm 3 , 500 mm 3 . 750 mm 3 , or up to 1000 mm 3 .
• a dosage regimen for a therapy comprising a PD-1 antagonist depends on several factors, including the serum or tissue turnover rate of the entity, the level of symptoms, the immunogenicity of the entity, and the accessibility of the target cells, tissue or organ in the individual being treated.
• a dosage regimen maximizes the amount of the PD-1 antagonist that is delivered to the patient consistent with an acceptable level of side effects. Accordingly, the dose amount and dosing frequency depends in part on the particular PD-1 antagonist, any other therapeutic agents to be used, and the severity of the cancer being treated, and patient characteristics. Guidance in selecting appropriate doses of antibodies, cytokines, and small molecules are available.
• Determination of the appropriate dosage regimen may be made by the clinician, e.g., using parameters or factors known or suspected in the art to affect treatment or predicted to affect treatment, and will depend, for example, the patient's clinical history (e.g., previous therapy), the type and stage of the cancer to be treated and biomarkers of response to one or more of the therapeutic agents in the combination therapy.
• Biotherapeutic agents used in combination with a PD-1 antagonist may be administered by continuous infusion, or by doses at intervals of, e.g., daily, every' other day, three times per week, or one time each week, two weeks, three weeks, monthly, bimonthly, etc.
• a total weekly dose is generally at least 0.05 pg/kg. 0.2 pg/kg, 0.5 pg/kg, 1 pg/kg, 10 pg/kg. 100 pg/kg. 0.2 mg/kg, 1.0 mg/kg, 2.0 mg/kg, 10 mg/kg, 25 mg/kg, 50 mg/kg body weight or more. See, e.g., Yang et al. (2003) New Engl. J. Med.
• a patient is administered an intravenous (IV) infusion of a medicament comprising any of the PD-1 antagonists described herein, and such administration is part of a treatment regimen employing the PD-1 antagonist as a monotherapy regimen or as part of a combination therapy.
• IV intravenous
• the PD-1 antagonist is pembrolizumab, which is administered in a liquid medicament at a dose selected from the group consisting of 200 mg Q3W, 400 mg Q6W. 1 mg/kg Q2W. 2 mg/kg Q2W. 3 mg/kg Q2W. 5 mg/kg Q2W, 10 mg/kg Q2W, 1 mg/kg Q3W, 2 mg/kg Q3W, 3 mg/kg Q3W, 5 mg/kg Q3W, and 10 mg/kg Q3W or equivalents of any of these doses.
• pembrolizumab is administered as a liquid medicament which comprises 25 mg/ml pembrolizumab, 7% (w/v) sucrose, 0.02% (w/v) polysorbate 80 in 10 mM histidine buffer pH 5.5, and the selected dose of the medicament is administered by IV infusion over a time period of 30 minutes.
• the optimal dose for pembrolizumab in combination with any other therapeutic agent may be identified by dose escalation.
• the present invention also provides a medicament which comprises a PD-1 antagonist as described above and a pharmaceutically acceptable excipient.
• a PD-1 antagonist is a biotherapeutic agent, e.g., a mAb
• the antagonist may be produced in CHO cells using conventional cell culture and recovery/purification technologies.
• a medicament comprising an anti -PD-1 antibody as the PD-1 antagonist may be provided as a liquid formulation or prepared by reconstituting a lyophilized powder with sterile water for injection prior to use.
• WO 2012/135408 describes the preparation of liquid and lyophilized medicaments comprising pembrolizumab, which are suitable for use in the present invention.
• a medicament comprising pembrolizumab is provided in a glass vial which contains about 100 mg of pembrolizumab.
• Merck-Moffitt data set a molecular profiling data set of melanoma tumors was used for analysis.
• Merck-Moffitt melanoma data set was generated as part of Merck-Moffitt Cancer Center collaboration.
• the Merck-Moffitt data is a comprehensive data set of tumor molecular profiling as well as carefully curated clinical data base. It has over thirty different cancer types represented and over 18,000 tumor samples.
• tumor samples were profiled on Merck custom Affymetrix chip (HRSTA-2.0) using custom Chip Description File (CDF) (GPL10379 in NCBI GEO public repository) at GEL (Gene Expression Laboratory) at Rosetta Inpharmatics (wholly owned subsidiary’ of Merck & Co., Inc, Rahway, NJ, USA).
• CDF Chip Description File
• analysis was restricted to 16,120 protein coding genes, with subsequent exclusion of genes with mean and standard deviation below the 25th percentile, leading to 8,728 protein coding genes. This was done to exclude genes with either low expression levels or low variance which would not be expected to yield robust data suitable for biomarker development as well as to control false discovery rate.
• Merck-Moffitt probe set intensities generated by using Ref-RMA algorithm as implemented in Affymetrix APT tools /www.affymetrix.com/support/developer/powertools/changelog/index) was summarized on the individual gene level by adding up loglO-transformed intensities over all probe sets annotated with common gene symbol, and further subject to within each individual sample normalization by the 75th percentile evaluated over all protein coding genes within given sample.
• Table 6 Number of profiled melanoma tumor samples in each data set, stratified by primary and metastatic tumors.
• the analyses performed were focused on the relationship between tumor gene expression patterns (individual genes as well as a limited set of pre-specified gene expression signatures as described in ‘Transcriptomic Determinants of Response to Pembrolizumab Monotherapy across Solid Tumor Types’ (Cristescu, et al., Transcriptomic Determinants of Response to Pembrolizumab Monotherapy across Solid Tumor Types, Clin Cancer Res, 28(2) 1680-1689 (2022)) and the following clinical endpoint: overall survival and metastatic disease versus primary disease.
• Metastatic disease status of individual tumor sample was taken directly from patient clinical data provided alongside of molecular profiling data. Analysis of gene expression data association with primary versus metastatic disease was performed using Wilcoxon rank sum test as implemented in ranksum function of Matlab R2020b. All figures and tables show two- sided p-values, nominal as well as FDR (False Discovery Rate) adjusted to account for multiple testing. This adjustment was performed Benjamini & Hochberg method (Benjamini, Y., & Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289- 300 (1995)).
• Overall survival endpoints used yvere overall survival time, measured from the time of profiled tumor sample collection, taken at the time of diagnostic biopsy, and censoring status based on whether the patient yvas reported to be alive or dead at the time of last follow up. Overall survival was right censored for patients with reported overall survival above ten years, and subjects who yvere reported dead or alive beyond ten years were treated as censored at the end of ten-year follow up yvindow.
• Directionality 7 and degree of association with overall survival are represented by univariate p-value (two-sided) as reported by Cox proportional hazards regression model and by Hazard Ratio (HR) equal to exp(beta), where beta is regression coefficient.
• Hazards ratio above 1.0 indicates association with yvorse (shorter) survival (positive sign of regression coefficient), and hazards ratio beloyv 1.0 indicates association yvith better (longer) survival, via negative sign of regression coefficient.
• EXAMPLE 1C Application of T-cell inflamed GEP and consensus signature score.
• Table 7 shows the statistical significance of differential expression between metastatic and primary melanoma tumors in Merck-Moffitt as well as association with overall survival for for 11 pre-specified gene expression signatures.
• Numerical values shown are ROC AUC as well as signed loglO-transformed two-sided nominal p-value by Wilcoxon rank sum test.
• Directionality of ROC AUC is chosen to be such that positive values correspond to ROC AUC > 0.5 associated with up-regulation in metastatic tumors compared to primary, and vice versa: negative value for ROC AUC ⁇ 0.05 indicating down-regulation in metastatic tumors.
• Two-sided nominal p-values by univariate Cox proportional hazards regression model are shown. HR>1 indicate association with worse overall survival and HR ⁇ 1 indicate association with better overall survival.
• FIG 1 shows observed ranges of values and relationship between two metrics used to represent genome wide association w ith overall survival in primary' melanoma tumors: hazards ratio (HR) (on x-axis) and univariate Cox proportional hazards regression model two-sided p- value, adjusted for multiple hypothesis testing by Benjamini & Hochberg method shown on loglO-scale.
• HR hazards ratio
• FIG 2 shows the extent of genome wide association with overall survival represented by hazards ratio values for individual genes (evaluated over 8,728 protein coding genes screened after filtering out genes with mean expression and variance below 25th percentile calculated over all 16,324 protein coding genes represented by probe sets on custom Affymetrix chip used to profile Merck-Moffitt melanoma tumors.
• Each plot shows histogram generated by discretizing the set of hazards ratio values into 100 bins with left y-axis displaying number of genes in each bin, and right y-axis showing empirical cumulative distribution density function evaluated at given hazard ratio x-value.
• FIG. 2A shows distribution of hazards ratio
• FIG. 2B and FIG. 2C show- results for two-sided nominal p- values before and after FDR-adjustment respectively.
• two complementary sets of 100 top genes were selected based on their p-value and w ere assigned to two gene sets: 100 genes associated with worse overall survival into proposed prognostic signature up arm, and 100 genes associated with better overall survival into proposed prognostic signature down arm.
• Each set of genes is observed to be highly coherent and consisting of highly co-expressed genes, as shown in FIG 3 indicating that the mode of distribution for pairwise correlations between genes in each gene set is above 0.35 for the top 100 (ranked by p-value) genes associated with worse overall survival in primary melanoma tumors, and also approximately 0.40 for top 100 (also selected based on p-value from Cox regression model) genes associated with better overall survival in primary melanoma tumors.
• FIG 3A shows distributions of all pairwise Spearman correlation coefficients among 100 top genes selected for being associated with w orse overall survival.
• FIG 3B shows distributions of all pairwise Spearman correlations among 100 top genes selected for being statistically significantly associated with better overall survival.
• FIG 4 shows a scaterplot showing signatureup score, defined as mean expression of selected set of genes found to be statistically significantly associated w ith worse overall survival in primary melanoma tumors on x-axis versus signaturedow n score on y-axis, defined as mean expression of complementary set of genes selected for being statistically significantly associated with beter overall survival in primary melanoma tumors.
• Each dot represents a tumor sample in given data set, labeled by the tumor type (primary or metastatic).
• Robust linear regression fited line is shown as well as three correlation coefficients and associated p-values (Pearson, Spearman, and Kendall’s tau).
• FIG 4 displays the observed relationship between tw o scores evaluated in Merck-Moffit data, primary and metastatic tumors combined.
• FIG 5 illustrates the degree of commonality between genome wide association with overall survival between primary and metastatic melanoma tumors. It shows a scater plot for hazards ratio values for each of 8,728 genes screened.
• FIG 6 illustrates the degree of commonality between genome wide association with overall survival and baseline differential expression between primary 7 and metastatic melanoma tumors. It show s hazards ratios values for each of 8,728 genes screened in primary tumors versus ROC AUC. Correlation coefficients for Pearson, Spearman, and Kendall’s tau as well as corresponding p-values are displayed, along with the robust linear fit line. HR values above 1.0 represent association with poor overall survival, and values below 1.0 are associated with genes associated with better overall survival. ROC AUC values above 0.5 indicate up-regulation in metastatic tumors compared to primary and AUC values below 0.5 indicate down-regulation in metastatic tumors versus primary.

Landscapes

• Health & Medical Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Chemical & Material Sciences (AREA)
• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Genetics & Genomics (AREA)
• Bioinformatics & Cheminformatics (AREA)
• Proteomics, Peptides & Aminoacids (AREA)
• Biophysics (AREA)
• Molecular Biology (AREA)
• Organic Chemistry (AREA)
• Biotechnology (AREA)
• General Health & Medical Sciences (AREA)
• Analytical Chemistry (AREA)
• Theoretical Computer Science (AREA)
• Wood Science & Technology (AREA)
• Medical Informatics (AREA)
• Evolutionary Biology (AREA)
• Zoology (AREA)
• Immunology (AREA)
• Spectroscopy & Molecular Physics (AREA)
• Pathology (AREA)
• Bioinformatics & Computational Biology (AREA)
• Microbiology (AREA)
• Oncology (AREA)
• Hospice & Palliative Care (AREA)
• Biochemistry (AREA)
• General Engineering & Computer Science (AREA)
• Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Applications Claiming Priority (2)

Publications (1)

Family

ID=91196544

Family Applications (1)

Country Status (2)

Families Citing this family (1)

Family Cites Families (4)

• 2023
  • 2023-11-17 EP EP23895297.2A patent/EP4623092A1/de active Pending
  • 2023-11-17 WO PCT/US2023/080378 patent/WO2024112609A1/en not_active Ceased

Also Published As

Similar Documents

Legal Events