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Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

A transcriptome-wide association study identifies associations of genetically predicted gene expression with breast cancer risk. This analysis finds 48 candidate genes implicated in breast cancer susceptibility, including 14 at novel loci.

Stig Bojesen, Georgia Chenevix-Trench, Alison Dunning and colleagues report common variants at the TERT-CLPTM1L locus associated with mean telomere length measured in whole blood. They also identify associations at this locus to breast or ovarian cancer susceptibility and report functional studies in breast and ovarian cancer tissue and cell lines.

The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Christopher Haiman and colleagues report a genome-wide association study for estrogen receptor (ER)-negative breast cancer in women of African and European ancestry. They identify a variant at the TERT-CLPTM1L locus on 5p15 as associated with ER-negative and triple-negative breast cancer. This locus also harbors multiple variants associated with a range of other cancers.

Montserrat Garcia-Closas and colleagues report a meta-analysis of three genome-wide association studies for estrogen receptor (ER)-negative breast cancer, including 4,193 ER-negative breast cancer cases and 35,194 controls, with replication using the iCOGS custom genotyping array in 40 studies, including 6,514 cases and 41,455 controls. They identify four loci associated with ER-negative but not ER-positive breast cancer.

HNF1B is overexpressed in the clear cell subtype and epigenetically silenced in the serous subtype of ovarian cancer. Pearce and colleagues now show that genetic variants in HNF1B are differentially associated with risks of developing these two cancer subtypes, possibly through an epigenetic mechanism.

This paper describes molecular subtypes of cervical cancers, including squamous cell carcinoma and adenocarcinoma clusters defined by HPV status and molecular features, and distinct molecular pathways that are activated in cervical carcinomas caused by different somatic alterations and HPV types.

Paul Pharoah, Joellen Schildkraut, Thomas Sellers and colleagues report a meta-analysis of genome-wide association studies for epithelial ovarian cancer and genotyping using the iCOGS array in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. They identify three new ovarian cancer susceptibility loci, including one specific to the serous subtype, and their integrated molecular analysis of genes and regulatory regions at these loci suggests disease mechanisms.

Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours.

Associations between of omega-3 fatty acids and mortality are not clear. Here the authors report that, based on a pooled analysis of 17 prospective cohort studies, higher blood omega-3 fatty acid levels correlate with lower risk of all-cause mortality.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Paul Pharoah and colleagues report a genome-wide association study for survival time after diagnosis of epithelial ovarian cancer and a parallel analysis of susceptibility to epithelial ovarian cancer. They identified two SNPs at 19p13.11 that associated with susceptibility to the serous subtype of epithelial ovarian cancer.

Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.

The Cancer Genome Atlas Research Network reports an integrative analysis of more than 400 samples of clear cell renal cell carcinoma based on genomic, DNA methylation, RNA and proteomic characterisation; frequent mutations were identified in the PI(3)K/AKT pathway, suggesting this pathway might be a potential therapeutic target, among the findings is also a demonstration of metabolic remodelling which correlates with tumour stage and severity.

The Cancer Genome Atlas Network describe their multifaceted analyses of primary breast cancers, shedding light on breast cancer heterogeneity; although only three genes (TP53, PIK3CA and GATA3) are mutated at a frequency greater than 10% across all breast cancers, numerous subtype-associated and novel mutations were identified.

The Cancer Genome Atlas Research Network report integrated genomic and molecular analyses of 164 squamous cell carcinomas and adenocarcinomas of the oesophagus; they find genomic and molecular features that differentiate squamous and adenocarcinomas of the oesophagus, and strong similarities between oesophageal adenocarcinomas and the chromosomally unstable variant of gastric adenocarcinoma, suggesting that gastroesophageal adenocarcinoma is a single disease entity.

An integrative genomic analysis of several hundred endometrial carcinomas shows that a minority of tumour samples carry copy number alterations or TP53 mutations and many contain key cancer-related gene mutations, such as those involved in canonical pathways and chromatin remodelling; a reclassification of endometrial tumours into four distinct types is proposed, which may have an effect on patient treatment regimes.

Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics.

STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components. STAAR accounts for population structure and relatedness and is scalable for analyzing large whole-genome sequencing studies.