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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.

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.

Here, the authors perform large trans-ancestry fine-mapping analyses identifying large numbers of association signals and putative target genes for colorectal cancer risk, advancing our understanding of the genetic and biological basis of this cancer.

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide and genetic susceptibility to the disease is poorly understood. Here, the authors combine data from Japanese, African American and European samples and identify a common variant in VTI1Athat increases CRC risk across all populations.

Analysis of genomic data from 981 colorectal cancers from participants in 11 countries reveals variations in mutational signatures of microsatellite-stable cancers that are dependent on geographical origin and age at which the cancer was diagnosed.

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.

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.

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.

Allele-preferential transcription factor binding can influence pancreatic ductal adenocarcinoma risk loci function. Here, the authors show allele-specific JunB and JunD binding at chr1p36.33 and propose a role for KLHL17 in protein homeostasis by mitigating inflammation.

Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds.

A multi-ancestry genome-wide association study meta-analysis, combined with transcriptome- and methylome-wide association analyses, identifies risk loci associated with colorectal cancer. Credible effector genes and their target tissues are also highlighted, showing that over a third probably act outside the colonic mucosa.

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.

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.

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.

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.

Genome-wide association analyses based on whole-genome sequencing and imputation identify 40 new risk variants for colorectal cancer, including a strongly protective low-frequency variant at CHD1 and loci implicating signaling and immune function in disease etiology.

Luis Pérez-Jurado, Stephen Chanock and colleagues detect clonal chromosomal abnormalities in peripheral blood or buccal samples from individuals in the general population. They show that the frequency of such events increases with age and is associated with elevated risk of developing subsequent hematological cancers.

Previous studies have shown that both rare pathogenic mutations and common genetic variants contribute to the familial risk of developing colorectal cancer. Here, the authors carry out a two-stage genome-wide association study and identify six new loci associated with colorectal cancer.

Shlien and colleagues report on 300 patients from the SickKids Cancer Sequencing program and identify clinically actionable variants in 56% of the patients by profiling somatic and germline data at multiple clinical time points.

Genetic variants associated with susceptibility to pancreatic cancer have been identified using genome wide association studies (GWAS). Here, the authors combine data from over 9000 patients and perform a meta-analysis to identify five novel loci linked to pancreatic cancer.

Physical activity has been linked to lower risks of colorectal and breast cancer. Here, the authors present a Mendelian randomisation analysis supporting a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer.

Wei Zheng and colleagues report the results of a large-scale genome-wide association study of colorectal cancer in East Asians. They identify six new susceptibility loci, including variants near TCF7L2 and TGFB1.

Genetic variants at multiple loci of chr5p15.33 have been associated with susceptibility to numerous cancers. Here the authors show that the association of one of these loci may be explained by a variant, rs36115365, influencing telomerase reverse transcriptase (TERT) expression via ZNF148.

Stephen Chanock and colleagues report a genome-wide association study of pancreatic cancer. They identify common variants at the ABO blood group locus associated with susceptibility to pancreatic cancer, consistent with previous epidemiological evidence suggesting that individuals with A or B blood types have greater risk of this cancer than individuals with blood type O.

It is unclear how often genetic mosaicism of chromosome X arises. Here, the authors examine women with cancer and cancer-free controls and show that X chromosome mosaicism occurs more frequently than on autosomes, especially on the inactive X chromosome, but is not linked to non-haematologic cancer risk

Germline biallelic pathogenic MUTYH variants predispose patients to colorectal cancer (CRC); however, approaches to identify MUTYH variant carriers are lacking. Here, the authors evaluated mutational signatures that could distinguish MUTYH carriers in large CRC cohorts, and found MUTYH-associated somatic mutations.

Stephen Chanock and colleagues identify three new susceptibility loci for pancreatic cancer on chromosomes 13q22.1, 1q32.1 and 5p15.33. The association signal at 13q22.1 maps to a large nongenic region, whereas the signals at 1q32.1 and 5p15.33 map near the NR5A2 gene and CPTM1L-TERT region, respectively.

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.

In colorectal cancer (CRC), finding loci associated with risk may give insight into disease aetiology. Here, the authors report a genome-wide association analysis in Europeans of 34,627 CRC cases and 71,379 controls, and find 31 new risk loci and 17 new risk SNPs at previously reported loci.

There is a functional link between SNPs and epigenetic variations when they are in close range, but the long-range effect is unclear. Here, by analysing methylation quantitative trait loci, the authors demonstrate that methylation levels at CpG sites in lymphocytes are correlated with distal SNPs.

Genome-wide analyses identify eight independent loci associated with anorexia nervosa. Genetic correlations implicate both psychiatric and metabolic components in the etiology of this disorder, even after adjusting for the effects of common variants associated with body mass index.