Search

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.

Using a combination of eye organoids and mouse models the authors identify a bioenergetic independent role of lactate as a cell signaling molecule required during early stages of eye formation in mice.

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 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.

An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Glucose uptake in astrocytes is thought to rely on GLUT1. Here, the authors show that adult mice tolerate astrocyte-specific GLUT1 deletion, which increases astrocytic glucose metabolism and confers neuroprotection in a model of stroke.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

Peroxisome proliferator-activated receptors (PPARs) are important transcriptional regulators of genes involved in energy metabolism. Hydrolysis of cardiac lipid droplets by adipose triglyceride lipase (ATGL) is now shown to be required for PPAR-mediated gene regulation and mitochondrial function, suggesting new therapeutic possibilities for neutral lipid storage disease caused by mutations in ATGL (also known as PNPLA2) (pages 1076–1085).

Brain functions require a constant supply of glucose. However, the brain energy stores are unclear. Here, the authors show that oligodendroglial fatty acid metabolism can be an energy reserve for white matter axons, supporting their function.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

Timothy Frayling, Joel Hirschhorn, Peter Visscher and colleagues report a meta-analysis of genome-wide association studies for adult height in 253,288 individuals. They identify 697 variants in 423 loci significantly associated with adult height and find that these variants cluster in pathways involved in growth and together explain one-fifth of the heritability for this trait.

Sah and colleagues show that the volume-sensitive ion channel SWELL1 regulates adipocyte insulin-PI(3)K-AKT2 signalling, glucose uptake and lipid content through interactions with GRB2/Cav1.

Tham and Bernardo et al. show that cardiomyocyte-specific knockout of estrogen receptor alpha induces increased adiposity and tissue metabolic alterations specifically in female mice, likely in part due to changes in the proteomic content of the heart-derived extracellular vesicles.

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.

A genome-wide association study of critically ill patients with COVID-19 identifies genetic signals that relate to important host antiviral defence mechanisms and mediators of inflammatory organ damage that may be targeted by repurposing drug treatments.

NAD⁺ is an important coenzyme that mediates cellular metabolism and defends against stresses due to age and overnutrition. Here the authors demonstrate unique bioavailability of the NAD⁺ precursor vitamin nicotinamide riboside (NR) in mice and humans, and show that NR safely elevates human NAD⁺.

Dennis et al. investigate potential breast cancer associations with rare germline copy number variants (CNVs) by conducting a genome-wide analysis in a large breast cancer case-control dataset. The authors detected associations with exonic deletions in established breast cancer susceptibility genes and suggestive associations for a number of non-coding CNVs.

Metabolic substrate partitioning underlies myocardial homeostatic capacity and adaptation to stress. Zhang et al. show that decreasing mitochondrial pyruvate carrier expression redirects glycolytic intermediates and leads to heart failure, which is prevented or reversed with a high-fat or ketogenic diet.

It is unclear how metabolic regulation affects development of the skeleton. Here, the authors show that deletion of the glucose transporter Glut1 (Slc2a1) both prior to and following chondrogenesis in the mouse limb impairs chondrocyte proliferation and shortening of the limbs, modulated by BMP signaling.

Keratinocytes require glucose for injury- or inflammation-driven but not homeostatic proliferation, and glucose-transport blockade blocks psoriasis-like pathology in experimental models.

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