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The MuTect algorithm for calling somatic point mutations enables subclonal analysis of the whole-genome or whole-exome sequencing data being generated in large-scale cancer genomics projects. Detection of somatic point substitutions is a key step in characterizing the cancer genome. However, existing methods typically miss low-allelic-fraction mutations that occur in only a subset of the sequenced cells owing to either tumor heterogeneity or contamination by normal cells. Here we present MuTect, a method that applies a Bayesian classifier to detect somatic mutations with very low allele fractions, requiring only a few supporting reads, followed by carefully tuned filters that ensure high specificity. We also describe benchmarking approaches that use real, rather than simulated, sequencing data to evaluate the sensitivity and specificity as a function of sequencing depth, base quality and allelic fraction. Compared with other methods, MuTect has higher sensitivity with similar specificity, especially for mutations with allelic fractions as low as 0.1 and below, making MuTect particularly useful for studying cancer subclones and their evolution in standard exome and genome sequencing data.

Tumors vary in their ratio of normal to cancerous cells and in their genomic copy number. Carter et al . describe an analytic method for inferring the purity and ploidy of a tumor sample, enabling longitudinal studies of subclonal mutations and tumor evolution. We describe a computational method that infers tumor purity and malignant cell ploidy directly from analysis of somatic DNA alterations. The method, named ABSOLUTE, can detect subclonal heterogeneity and somatic homozygosity, and it can calculate statistical sensitivity for detection of specific aberrations. We used ABSOLUTE to analyze exome sequencing data from 214 ovarian carcinoma tumor-normal pairs. This analysis identified both pervasive subclonal somatic point-mutations and a small subset of predominantly clonal and homozygous mutations, which were overrepresented in the tumor suppressor genes TP53 and NF1 and in a candidate tumor suppressor gene CDK12 . We also used ABSOLUTE to infer absolute allelic copy-number profiles from 3,155 diverse cancer specimens, revealing that genome-doubling events are common in human cancer, likely occur in cells that are already aneuploid, and influence pathways of tumor progression (for example, with recessive inactivation of NF1 being less common after genome doubling). ABSOLUTE will facilitate the design of clinical sequencing studies and studies of cancer genome evolution and intra-tumor heterogeneity.

Rameen Beroukhim and colleagues analyzed somatic structural alterations in 12 tumor types. Whole-genome doubling was found in over a third of all cancers, associated with TP53 mutation. Fifteen new significantly mutated candidate driver genes were found associated with recurrently amplified or deleted regions. Determining how somatic copy number alterations (SCNAs) promote cancer is an important goal. We characterized SCNA patterns in 4,934 cancers from The Cancer Genome Atlas Pan-Cancer data set. Whole-genome doubling, observed in 37% of cancers, was associated with higher rates of every other type of SCNA, TP53 mutations, CCNE1 amplifications and alterations of the PPP2R complex. SCNAs that were internal to chromosomes tended to be shorter than telomere-bounded SCNAs, suggesting different mechanisms underlying their generation. Significantly recurrent focal SCNAs were observed in 140 regions, including 102 without known oncogene or tumor suppressor gene targets and 50 with significantly mutated genes. Amplified regions without known oncogenes were enriched for genes involved in epigenetic regulation. When levels of genomic disruption were accounted for, 7% of region pairs were anticorrelated, and these regions tended to encompass genes whose proteins physically interact, suggesting related functions. These results provide insights into mechanisms of generation and functional consequences of cancer-related SCNAs.

After a prolonged response, an anaplastic thyroid cancer developed resistance to mammalian target of rapamycin (mTOR) inhibition by somatic mutation of mTOR at the everolimus binding site. The mutant enzyme retained in vitro responsiveness to an mTOR kinase inhibitor. A better understanding of the mechanisms of sensitivity and resistance to anticancer therapies may improve patient selection and allow the development of rational treatment designs. One approach involves studying paired biopsy samples of pretreatment and drug-resistant tumors obtained from patients with exquisite sensitivity or unusually durable responses to therapy. Everolimus is a Food and Drug Administration–approved oral allosteric inhibitor of mTOR. Tumors that exhibit a dependency on the mTOR pathway might have enhanced sensitivity to mTOR inhibition. Inactivating mutations in the tumor-suppressor genes TSC1, TSC2, and STK11 result in mTOR-pathway activation and are targetable by TOR inhibitors in hamartoma syndromes . . .

Whole-exome sequencing (WES) has emerged as a transformative technology for biological discovery, but technical difficulties have so far prevented its widespread clinical use. Here, Eliezer Van Allen and colleagues are able to perform production-scale WES on small amounts of clinically acquired formalin-fixed, paraffin-embedded tumor tissues. Using a newly created WES clinical interpretation algorithm, they apply the complete clinical WES framework prospectively to patients and demonstrate how it can be used to directly affect patient care. Translating whole-exome sequencing (WES) for prospective clinical use may have an impact on the care of patients with cancer; however, multiple innovations are necessary for clinical implementation. These include rapid and robust WES of DNA derived from formalin-fixed, paraffin-embedded tumor tissue, analytical output similar to data from frozen samples and clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival formalin-fixed, paraffin-embedded tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a 'long tail' of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15 out of 16 patients. In one patient, previously undetected findings guided clinical trial enrollment, leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.

Adam Bass, Gad Getz, Scott Carter and colleagues report the whole-exome sequences of 25 pairs of esophageal adenocarcinoma and Barrett's esophagus. They identify two pathways by which Barrett's esophagus can develop into esophageal adenocarcinoma. Barrett's esophagus is thought to progress to esophageal adenocarcinoma (EAC) through a stepwise progression with loss of CDKN2A followed by TP53 inactivation and aneuploidy. Here we present whole-exome sequencing from 25 pairs of EAC and Barrett's esophagus and from 5 patients whose Barrett's esophagus and tumor were extensively sampled. Our analysis showed that oncogene amplification typically occurred as a late event and that TP53 mutations often occurred early in Barrett's esophagus progression, including in non-dysplastic epithelium. Reanalysis of additional EAC exome data showed that the majority (62.5%) of EACs emerged following genome doubling and that tumors with genomic doubling had different patterns of genomic alterations, with more frequent oncogenic amplification and less frequent inactivation of tumor suppressors, including CDKN2A . These data suggest that many EACs emerge not through the gradual accumulation of tumor-suppressor alterations but rather through a more direct path whereby a TP53 -mutant cell undergoes genome doubling, followed by the acquisition of oncogenic amplifications.

We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors.

Leptomeningeal disease (LMD) is a common complication from solid tumor malignancies with a poor prognosis and limited treatment options. We present a single arm Phase II study of 18 patients with LMD receiving combined ipilimumab and nivolumab until progression or unacceptable toxicity (NCT02939300). The primary end point is overall survival at 3 months (OS3). Secondary end points include toxicity, cumulative time-to-progression at 3 months, and progression-free survival. A Simon two-stage design is used to compare a null hypothesis OS3 of 18% against an alternative of 44%. Median follow up based on patients still alive is 8.0 months (range: 0.5 to 15.9 months). The study has met its primary endpoint as 8 of 18 (OS3 0.44; 90% CI: 0.24 to 0.66) patients are alive at three months. One third of patients have experienced one (or more) grade-3 or higher adverse events. Two patients have discontinued protocol treatment due to unacceptable toxicity (hepatitis and colitis, respectively). The most frequent adverse events include fatigue (N = 7), nausea (N = 6), fever (N = 6), anorexia (N = 6) and rash (N = 6). Combined ipilimumab and nivolumab has an acceptable safety profile and demonstrates promising activity in LMD patients. Larger, multicenter clinical trials are needed to validate these results. Leptomeningeal metastases from solid tumors are a rare complication with a very poor prognosis. Here the authors report the efficacy and safety of combined ipilimumab and nivolumab in patients with leptomeningeal carcinomatosis.

Despite continued widespread use, the genomic effects of cisplatin-based chemotherapy and implications for subsequent treatment are incompletely characterized. Here, we analyze whole exome sequencing of matched pre- and post-neoadjuvant cisplatin-based chemotherapy primary bladder tumor samples from 30 muscle-invasive bladder cancer patients. We observe no overall increase in tumor mutational burden post-chemotherapy, though a significant proportion of subclonal mutations are unique to the matched pre- or post-treatment tumor, suggesting chemotherapy-induced and/or spatial heterogeneity. We subsequently identify and validate a novel mutational signature in post-treatment tumors consistent with known characteristics of cisplatin damage and repair. We find that post-treatment tumor heterogeneity predicts worse overall survival, and further observe alterations in cell-cycle and immune checkpoint regulation genes in post-treatment tumors. These results provide insight into the clinical and genomic dynamics of tumor evolution with cisplatin-based chemotherapy, suggest mechanisms of clinical resistance, and inform development of clinically relevant biomarkers and trials of combination therapies. The impact of cisplatin-based chemotherapy on tumor genomes is complex. Here, the authors study matched pre- and post-chemotherapy primary samples in muscle-invasive bladder cancer, finding a cisplatin-based mutational signature, and highlighting the impact of intratumor heterogeneity on survival.

Helga Salvesen, Rameen Beroukhim, Scott Carter and colleagues study the evolutionary landscape of endometrial cancer by performing whole-exome sequencing of complex atypical hyperplasias, primary tumors and metastases. They identify recurrent alterations in primary tumors and suggest that driver events are generally shared by primary and metastatic tumors. Recent studies have detailed the genomic landscape of primary endometrial cancers, but the evolution of these cancers into metastases has not been characterized. We performed whole-exome sequencing of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed The Cancer Genome Atlas (TCGA) data, identifying new recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor gene NRIP1 in 12% of patients. We found that likely driver events were present in both primary and metastatic tissue samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses indicated that the sampled metastases typically arose from a common ancestral subclone that was not detected in the primary tumor biopsy. These data demonstrate extensive genetic heterogeneity in endometrial cancers and relative homogeneity across metastatic sites.