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Understanding the pathology in the lungs of patients with COVID-19 might provide clues as to the susceptibility of patients and how the SARS-CoV-2 virus can be fatal. Here the authors analyze cadaveric pulmonary tissue and show one group with high viral load, early death, inflammation and inflammatory damage, and another with low viral load, longer duration of disease, and more M2-like polarization and fibrotic lung damage.

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

Stress release at stepped platinum surfaces is shown to influence the strain experienced by atoms near the steps, resulting in effects on the catalytic activity of the whole surface.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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-exome sequencing in a large autism study identifies over 100 autosomal genes that are likely to affect risk for the disorder; these genes, which show unusual evolutionary constraint against mutations, carry de novo loss-of-function mutations in over 5% of autistic subjects and many function in synaptic, transcriptional and chromatin-remodelling pathways.

In a large, partially prospective cohort of patients with molecularly profiled and clinically annotated meningioma, the extent of surgical resection and radiotherapy (RT) response correlate with molecular classification, which can be used in a molecular model to predict clinical outcomes in response to RT.

Electrochemical water splitting using renewable electricity is a promising method for the sustainable production of hydrogen. This Primer overviews considerations, techniques and methods for water electrolysis and describes methods to improve rigour and reproducibility when analysing electrochemical data.

Michael Taylor, Marco Marra and colleagues analyze spatial tumor heterogeneity in 9 medulloblastomas, 16 high-grade gliomas and 10 renal cell carcinomas, using a combination of transcriptomic and genomic profiling of multiregional biopsies. They find that medulloblastomas have spatially homogeneous transcriptomes, whereas somatic mutations that affect genes suitable for targeted therapeutics are spatially heterogeneous.

Enterovirus 71 is a leading cause of hand-foot-and-mouth disease and herpangina. Here, the authors characterize a large panel of plasmablast-derived IgG mAbs that target the capsid of EV71 to identify neutralizing antibodies induced by natural infection.

To address the question of whether a recurrent tumour is genetically similar to the tumour at diagnosis, the evolution of medulloblastoma has been studied in both an in vivo mouse model of clinical tumour therapy as well as in humans with recurrent disease; targeted tumour therapies are usually based on targets present in the tumour at diagnosis but the results from this study indicate that post-treatment recurring tumours (compared with the tumour at diagnosis) have undergone substantial clonal divergence of the initial dominant tumour clone.

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.

Although genetically bland, the posterior fossa group A subgroup of ependymomas, found often in infants and associated with poor prognosis, exhibit widespread epigenetic alterations, namely a CpG island methylator phenotype; these tumours are shown to be susceptible both in vitro and in vivo to various compounds that target epigenetic modifications, such as DNA methylation and H3K27 tri-methylation.

Focusing on two ill-characterized subtypes of medulloblastoma (group 3 and group 4), this study identifies prevalent genomic structural variants that are restricted to these two subtypes and independently bring together coding regions of GFI1 family proto-oncogenes with active enhancer elements, leading to their mutually exclusive oncogenic activation.

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.

A randomized trial in patients hospitalized with COVID-19 showed no benefit and potentially increased harm associated with the use of convalescent plasma, with subgroup analyses suggesting that the antibody profile in donor plasma is critical in determining clinical outcomes.

Software to model, pack and integrate biological structures at the scale of macromolecular complexes and cellular organelles is described. It is applied in several contexts, including hypothesis generation and testing.

Pineoblastoma is a rare pediatric cancer. Here, the authors present inactivation of Rb plus p53 via a WAP-Cre transgene induces metastatic pineoblastoma resembling human disease, and using this model, predict tricyclic antidepressants as a potential therapy for pineoblastoma, supported by their pre-clinical model.