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A follow-up analysis of a clinical trial that evaluated anti-PD-1 therapy in patients with cancer who are living with HIV provides mechanistic insights into transcriptomic, cellular and cytokine changes related to immune checkpoint inhibitor treatment and identifies a signature associated with clinical response.

Nitazenes are potent synthetic opioids that are difficult to detect. Here, authors computationally redesign a plant receptor to create sensitive sensors capable of detecting diverse nitazenes and their metabolites in biological samples.

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

Brain organoid models reported to date lack cells of mesodermal origin, such as microglia. Here, the authors demonstrate that mature microglia-like cells are generated within their cerebral organoid model, providing new avenues for studying human microglia in a three-dimensional brain environment.

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.

The ability of T cells to migrate is a central component of their functionality and is known to require WNK1 kinase that is linked to the influx of ions into the cell. Here the authors show that T cell migration requires WNK1 mediated ion and water influx to swell the membrane of the leading edge and support actin polymerisation and forward motility.

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.

Food systems are increasingly globalized and interdependent. Using food supply data from over 170 countries, Bentham et al. characterize global patterns of food supply change over five decades, highlighting the decline in the supply of animal source food and sugar in many Western countries, the increase in the supply of such foods in Asian countries and remarkably little change in food supply in the sub-Saharan Africa region.

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.

A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

Walsh and colleagues use prospective sequencing in a large cohort of pediatric patients with solid tumors to detect mutations in cancer predisposition genes and guide downstream clinical care.

An integrated analysis of de novo and inherited coding variants in 42,607 individuals with autism spectrum disorder identifies 60 risk genes of which five have not previously been associated with neurodevelopmental disorders.

Relatives of patients with amyotrophic lateral sclerosis have an unexpectedly high incidence of schizophrenia. Here, the authors show a genetic link between the two conditions, suggesting shared neurobiological mechanisms.

Whole tissue RNA profiling can help identify altered molecular pathways underlying neurodegenerative disease, but often masks cell type-specific transcriptional changes. Here, the authors compare transcriptomes of neurons, astrocytes, and microglia from Alzheimer's disease model brains and identify hundreds of cell-type specific changes.

Transcriptomic analyses of acute phase whole blood from a large cohort of patients with COVID-19 identify molecular determinants of post-infection long-term sequelae.