Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Double KRAS and BRAF mutations in surgically treated colorectal cancer liver metastases: An international, multi-institutional case series

Background: While previously believed to be mutually exclusive, concomitant mutation of Kirsten rat sarcoma viral oncogene homolog (KRAS)- and V-raf murine sarcoma b-viral oncogene homolog B1 (BRAF)-mutated colorectal carcinoma (CRC), has been described in rare instances and been associated with advanced-stage disease. The present case series is the first to report on the implications of concurrent KRAS/BRAF mutations among surgically treated patients, and the largest set of patients with surgically treated colorectal liver metastasis (CRLM) and data on KRAS/BRAF mutational status thus far described. Case Series: We present cases from an international, multi-institutional cohort of patients that underwent hepatic resection for CRLM between 2000-2015 at seven tertiary centers. The incidence of KRAS/BRAF mutation in patients with CRLM was 0.5% (4/820). Of these cases, patient 1 (T2N1 primary, G13D/V600E), patient 2 (T3N1 primary, G12V/V600E) and patient 3 (T4N2 primary, G13D/D594N) succumbed to their disease within 485, 236 and 79 days respectively, post-hepatic resection. Patient 4 (T4 primary, G12S/G469S) was alive 416 days after hepatic resection. Conclusion: The present case series suggests that the incidence of concomitant KRAS/BRAF mutations in surgical cohorts may be higher than previously hypothesized, and associated with more variable survival outcomes than expected. © 2018 International Institute of Anticancer Research. All rights reserved

Copy-number analysis and inference of subclonal populations in cancer genomes using Sclust

The genomes of cancer cells constantly change during pathogenesis. This evolutionary process can lead to the emergence of drug-resistant mutations in subclonal populations, which can hinder therapeutic intervention in patients. Data derived from massively parallel sequencing can be used to infer these subclonal populations using tumor-specific point mutations. The accurate determination of copy-number changes and tumor impurity is necessary to reliably infer subclonal populations by mutational clustering. This protocol describes how to use Sclust, a copy-number analysis method with a recently developed mutational clustering approach. In a series of simulations and comparisons with alternative methods, we have previously shown that Sclust accurately determines copy-number states and subclonal populations. Performance tests show that the method is computationally efficient, with copy-number analysis and mutational clustering taking < 10 min. Sclust is designed such that even non-experts in computational biology or bioinformatics with basic knowledge of the Linux/Unix command-line syntax should be able to carry out analyses of subclonal populations