title: Burden of Nonsynonymous Mutations among TCGA Cancers and Candidate Immune Checkpoint Inhibitor Responses.
abstract: Immune checkpoint inhibitor treatment represents a promising approach toward treating cancer and has been shown to be effective in a subset of melanoma, non-small cell lung cancer (NSCLC), and kidney cancers. Recent studies have suggested that the number of nonsynonymous mutations (NsM) can be used to select melanoma and NSCLC patients most likely to benefit from checkpoint inhibitor treatment. It is hypothesized that a higher burden of NsM generates novel epitopes and gene products, detected by the immune system as foreign. We conducted an assessment of NsM across 7,757 tumor samples drawn from 26 cancers sequenced in the Cancer Genome Atlas (TCGA) Project to estimate the subset of cancers (both types and fractions thereof) that fit the profile suggested for melanoma and NSCLC. An additional independent set of 613 tumors drawn from 5 cancers were analyzed for replication. An analysis of the receiver operating characteristic curves of published data on checkpoint inhibitor response in melanoma and NSCLC data estimates a cutoff of 192 NsM with 74% sensitivity and 59.3% specificity to discriminate potential clinical benefit. Across the 7,757 samples of TCGA, 16.2% displayed an NsM count that exceeded the threshold of 192. It is notable that more than 30% of bladder, colon, gastric, and endometrial cancers have NsM counts above 192, which was also confirmed in melanoma and NSCLC. Our data could inform the prioritization of tumor types (and subtypes) for possible clinical trials to investigate further indications for effective use of immune checkpoint inhibitors, particularly in adult cancers. Cancer Res; 76(13); 3767-72. ©2016 AACR.
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
authors.forename: Leandro M
authors.initials: LM
authors.lastname: Colli
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
authors.forename: Mitchell J
authors.initials: MJ
authors.lastname: Machiela
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
authors.forename: Timothy A
authors.initials: TA
authors.lastname: Myers
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
authors.forename: Lea
authors.initials: L
authors.lastname: Jessop
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
authors.forename: Kai
authors.initials: K
authors.lastname: Yu
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland. chanocks@mail.nih.gov.
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Chanock
mesh_terms: D000911:Antibodies, Monoclonal / Q000627:therapeutic use*; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D060890:B7-H1 Antigen / Q000037:antagonists & inhibitors*; D014408:Biomarkers, Tumor / Q000235:genetics; D059447:Cell Cycle Checkpoints / Q000235:genetics*; D006801:Humans; D009154:Mutation / Q000235:genetics*; D009367:Neoplasm Staging; D009369:Neoplasms / Q000188:drug therapy* / Q000235:genetics / Q000276:immunology; D011379:Prognosis; D061026:Programmed Cell Death 1 Receptor / Q000037:antagonists & inhibitors*; D014407:Tumor Cells, Cultured
chemical_list: D000911:Antibodies, Monoclonal; D000970:Antineoplastic Agents; D060890:B7-H1 Antigen; D014408:Biomarkers, Tumor; C423236:CD274 protein, human; D061026:Programmed Cell Death 1 Receptor