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Gastric cancers (GC) are driven by genomic alterations, but the underlying molecular mechanisms remain unclear. Here, the authors analyse the structural rearrangement landscape of 170 GCs using whole-genome sequencing, identify recurrent structural variant hotspots and find oncogene amplicons driven by extrachromosomal DNA.

A cross-ancestry genomic and transcriptomic cohort of gastric cancer highlights significantly mutated genes and mutational signatures, some of which are ancestry-specific.

Seishi Ogawa and colleagues report the results of a large-scale sequencing study of adult T cell leukemia/lymphoma. They find recurrent alterations enriched for T cell receptor/NF-κB signaling, T cell trafficking and other T cell pathways and highlight targets for the development of new therapeutics for this intractable cancer.

Tatsuhiro Shibata, David Wheeler, Hiroyuki Aburatani and colleagues report the genomic, exomic and oncoviral sequencing of hundreds of liver cancers from the United States and Japan. The authors analyzed mutation patterns and identified signatures unique to the Asian cases.

Hidewaki Nakagawa and colleagues report a comprehensive genome-wide mutational landscape of 300 liver cancers from Japanese individuals. They identify candidate driver mutations, including ones in noncoding regions, and structural mutations affecting the expression of nearby genes.

Tatsuhiro Shibata and colleagues molecularly characterize 260 biliary tract cancer samples by a combination of exome and transcriptome sequencing. They find genomic alterations that could potentially be therapeutic targets.

The authors report a new type of genetic alteration in lung adenocarcinoma. Fusions of KIF5B with RET kinase are found in 1–2% of lung cancer patients, segregate from other known alterations and can potentially be targeted using RET kinase inhibitors.

Structural variations disrupting the 3′ region of PD-L1 are shown to aid immune evasion in a number of human cancers, including adult T-cell leukaemia/lymphoma, and in a mouse tumour model, CRISPR/Cas9-mediated deletion of the 3'-UTR of Pd-l1 is also shown to result in immune escape, suggesting that PD-L1 3′-UTR disruption could provide a diagnostic marker to identify patients who will benefit from anti-PD-1/PD-L1 therapy.

Over evolutionary time genes can undergo duplication, and may accumulate mutations that render them non-functional pseudogenes, which are thought to be uninteresting. This study (and that of the group of Hannon) shows that pseudogenes can in fact influence gene expression.

Renal cell carcinoma (RCC) subtypes are associated with different molecular alterations and clinical outcomes, but they need to be characterised in diverse cohorts. Here, the authors perform genomic, transcriptomic, and epigenomic profiling in a large cohort of Japanese RCC cases, and identify epi-subtypes associated with a particular immune environment.

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.

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.

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.

Hidewaki Nakagawa and colleagues report the whole-genome sequencing of 27 hepatocellular carcinomas. They find that chromatin regulators were mutated in approximately 50% of tumors.

Myxofibrosarcoma occurs in adults and is associated with high local relapse. Here, based on exome/transcriptome sequencing and DNA methylation analysis, the authors identify driver genes and methylation clusters associated with unique combinations of mutations, outcomes, and immune cell compositions.

Self-renewal of cancer stem cells can contribute to glioma progression. Here, the authors show that Notch1 activation in glioma stem cells induces expression of the lncRNATUG1, which promotes self-renewal through the repression of differentiation genes, and that targeting TUG1 represses glioma growth in vivo.

Genomic aberrations contribute to the development of cancer; however, their interdependence remains poorly understood. Here the authors analyze liver cancer samples to find correlation between epigenetic features and genetic aberrations including somatic substitutions, mutation signatures, and HBV integration sites.

An analysis of mutations from over 7,000 cancers of diverse origins reveals the diversity of mutational processes underlying the development of cancer; more than 20 distinct mutational signatures are described, some of which are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are specific to individual tumour types.

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.

Tatsuhiro Shibata and colleagues report the sequencing of a hepatocellular carcinoma. The authors identified 63 somatic non-synonymous substitutions and 22 somatic chromosomal rearrangements in this liver tumor.