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This paper uses multiomics to profile a large cohort of meningioma samples to highlight the role of the tumor microenvironment in driving the epigenetic changes underpinning tumor classification and prediction of outcome.

Standard of care in patients with unresectable stage III non-small cell lung cancer (NSCLC) is concurrent chemo-radiotherapy followed by immunotherapy. Here, the authors report a phase II trial investigating induction chemo-immunotherapy (atezolizumab, carboplatin and paclitaxel) followed by concurrent chemoradiotherapy and immunotherapy maintenance in patients with stage III NSCLC.

Genome-wide analyses identify 30 independent loci associated with obsessive–compulsive disorder, highlighting genetic overlap with other psychiatric disorders and implicating putative effector genes and cell types contributing to its etiology.

A liver-intrinsic mechanism is presented that suppresses effective anti-hepatitis virus B responses in mice and humans by rendering virus-specific CD8 T cells refractory to activation causing loss of effector functions.

Exome sequencing within a structured diagnostic process for rare diseases in Germany shows how facial image analysis and machine learning can guide variant prioritization and uncover many ultrarare diseases.

The low dielectric constants and high porosity of MOFs are of interest for applications in electronics and sensors, but patterning techniques for these materials are in their infancy. Here, direct X-ray and electron-beam lithography at sub-50-nm resolution are reported that leave porosity and crystallinity intact.

Bone marrow contains adipocytes, which have been thought to form one type of marrow adipose tissue (MAT). Here, the authors identify two MAT subpopulations in mice and humans—‘regulated’ and ‘constitute’ MAT—which show distinct phenotypic and cellular traits, and respond differently to cold exposure.

In breast cancer the contribution of different genetic variants to disease heritability is complex and not fully understood. Here, the authors present a network-based analysis in 84,567 patients studying ~7.3 million variants, identifying gene modules associated with breast cancer survival.

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 multi-ancestry genome-wide association study for age at menarche followed by fine mapping and downstream analysis implicates 665 pubertal timing genes, such as the G-protein-coupled receptor 83 (GPR83) and other genes expressed in the ovaries involved in the DNA damage response.

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.

Fine-mapping of causal variants and integration of epigenetic and chromatin conformation data identify likely target genes for 150 breast cancer risk regions.

Breast cancer risk for BRCA1/BRCA2 mutation carriers varies depending on other genetic factors. Here, the authors perform a case-only genome-wide association study and highlight novel loci associated with breast cancer risk for BRCA1/BRCA2 mutation carriers.

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.

Response to drug therapy in colorectal cancer (CRC) patients has been associated with tumour heterogeneity. Here the authors analyse DNA copy number aberrations in primary tumours from CRC patients and identify genetic variants that influence drug response.

Over 170 susceptibility loci have been identified by genome-wide association studies in breast cancer. Here, the authors interrogated the role of risk-associated variants from non-breast tissue, and using expression quantitative trait loci, identify potential target genes of known breast cancer susceptibility variants, as well as 11 regions not previously known to be associated with breast cancer risk.

A large-scale meta-analysis across eight biobank datasets identifies common genetic variants associated with mosaic loss of the X chromosome in female participants.

The genetic basis of metabolic diseases is incompletely understood. Here, by high-throughput phenotyping of 2,016 knockout mouse strains, Rozman and colleagues identify candidate metabolic genes, many of which are associated with unexplored regulatory gene networks and metabolic traits in human GWAS.

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.

Endometrial cancer is the most common invasive gynaecological cancer in developed countries. Here a meta-analysis identifies an additional nine novel endometrial cancer risk loci and eQTL analysis reveals risk variants associate with reduced expression of negative regulators of oncogenic signal transduction proteins.

The chemosynthetic symbionts of the bivalve Loripes lucinalis and nematode Laxus oneistus are found to encode nitrogen fixation genes, with evidence for active nitrogen fixation.

Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade.

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.

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.