As the sample size in cancer genome studies increases, the list of genes identified as significantly mutated is likely to include more false positives; here, this problem is identified as stemming largely from mutation heterogeneity, and a new analytical methodology designed to overcome this problem is described. Cancer genomic approaches have identified scores of genes responsible for the initiation and progression of cancer. But as the sample sizes increase, the list of putatively significant genes identified by current analytical methods continues to grow and is likely to include many false positives. This study shows that this situation stems largely from mutational heterogeneity and presents a novel methodology, MutSigCV, that overcomes the problem by incorporating mutational heterogeneity into the analysis. Application of MutSigCV to more than 3,000 tumour samples from 27 different tumour types shows that mutation frequencies vary more than 1,000-fold between extreme samples both between and within tumour types. And when applied to a data set on lung cancer, MutSigCV reduced the list of significantly mutated genes from 450 to a more manageable 11, most of them previously reported to be mutated in squamous cell lung cancer. Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer1,2,3,4,5,6,7,8,9. These studies involve the sequencing of matched tumour–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour–normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

Multiple myeloma is an incurable malignancy of plasma cells, and its pathogenesis is poorly understood. Here we report the massively parallel sequencing of 38 tumour genomes and their comparison to matched normal DNAs. Several new and unexpected oncogenic mechanisms were suggested by the pattern of somatic mutation across the data set. These include the mutation of genes involved in protein translation (seen in nearly half of the patients), genes involved in histone methylation, and genes involved in blood coagulation. In addition, a broader than anticipated role of NF-κB signalling was indicated by mutations in 11 members of the NF-κB pathway. Of potential immediate clinical relevance, activating mutations of the kinase BRAF were observed in 4% of patients, suggesting the evaluation of BRAF inhibitors in multiple myeloma clinical trials. These results indicate that cancer genome sequencing of large collections of samples will yield new insights into cancer not anticipated by existing knowledge.

John Maris, Matthew Meyerson, Marco Marra and colleagues report results of a large-scale sequencing study of neuroblastoma. They observe a low median exonic mutation frequency and strikingly few recurrently mutated genes in these tumors, highlighting challenges for developing targeted therapeutic strategies based on frequently mutated oncogenic drivers. Neuroblastoma is a malignancy of the developing sympathetic nervous system that often presents with widespread metastatic disease, resulting in survival rates of less than 50%. To determine the spectrum of somatic mutation in high-risk neuroblastoma, we studied 240 affected individuals (cases) using a combination of whole-exome, genome and transcriptome sequencing as part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative. Here we report a low median exonic mutation frequency of 0.60 per Mb (0.48 nonsilent) and notably few recurrently mutated genes in these tumors. Genes with significant somatic mutation frequencies included ALK (9.2% of cases), PTPN11 (2.9%), ATRX (2.5%, and an additional 7.1% had focal deletions), MYCN (1.7%, causing a recurrent p.Pro44Leu alteration) and NRAS (0.83%). Rare, potentially pathogenic germline variants were significantly enriched in ALK, CHEK2, PINK1 and BARD1. The relative paucity of recurrent somatic mutations in neuroblastoma challenges current therapeutic strategies that rely on frequently altered oncogenic drivers.

The success in lung cancer therapy with programmed death (PD)-1 blockade suggests that immune escape mechanisms contribute to lung tumor pathogenesis. We identified a correlation between EGF receptor (EGFR) pathway activation and a signature of immunosuppression manifested by upregulation of PD-1, PD-L1, CTL antigen-4 (CTLA-4), and multiple tumor-promoting inflammatory cytokines. We observed decreased CTLs and increased markers of T-cell exhaustion in mouse models of EGFR-driven lung cancer. PD-1 antibody blockade improved the survival of mice with EGFR-driven adenocarcinomas by enhancing effector T-cell function and lowering the levels of tumor-promoting cytokines. Expression of mutant EGFR in bronchial epithelial cells induced PD-L1, and PD-L1 expression was reduced by EGFR inhibitors in non–small cell lung cancer cell lines with activated EGFR. These data suggest that oncogenic EGFR signaling remodels the tumor microenvironment to trigger immune escape and mechanistically link treatment response to PD-1 inhibition. Significance: We show that autochthonous EGFR-driven lung tumors inhibit antitumor immunity by activating the PD-1/PD-L1 pathway to suppress T-cell function and increase levels of proinflammatory cytokines. These findings indicate that EGFR functions as an oncogene through non–cell-autonomous mechanisms and raise the possibility that other oncogenes may drive immune escape. Cancer Discov; 3(12); 1355–63. ©2013 AACR. See related commentary by Rech and Vonderheide, p. 1330 This article is highlighted in the In This Issue feature, p. 1317