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Results of the phase 2 POLAR trial show that biomarker-guided treatment in patients with metastatic pancreatic cancer based on homologous repair deficiency leads to encouraging clinical response rates in immune cell-infiltrated tumors.

The APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer’s disease, but it is not deterministic. Here, the authors show that common genetic variation changes how APOE-ε4 influences cognition.

Whole-genome and transcriptome analysis of 1,364 cases of breast cancer from South Korea broadens our understanding of breast cancer biology and reveals genomic features that connect tumour biology with treatment responses and clinical outcomes.

cellSTAAR advances noncoding rare variant association analysis by integrating single-cell genomics data.

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.

CytoTRACE 2 is an interpretable deep learning framework that leverages single-cell RNA sequencing data to predict absolute developmental potential across datasets.

Genetic variation associated with gene expression changes has mostly been studied in the context of single nucleotide variants. Here, Jakubosky et al. report eQTL analysis of structural variants and short tandem repeats and find properties, such as length of variation, that affect the association.

A study finds that a protease called granzyme K can activate the entire complement cascade, explaining how it can drive destructive inflammation in inflammatory diseases such as rheumatoid arthritis.

Cell type labelling in single-cell datasets remains a major bottleneck. Here, the authors present AnnDictionary, an open-source toolkit that enables atlas-scale analysis and provides the first benchmark of LLMs for de novo cell type annotation from marker genes, showing high accuracy at low cost.

Analyses of genome and exome sequencing data identify rare coding and structural variants associated with atrial fibrillation and highlight genetic links between atrial fibrillation and cardiomyopathies.

Using data from a single time point, passenger-approximated clonal expansion rate (PACER) estimates the fitness of common driver mutations that lead to clonal haematopoiesis and identifies TCL1A activation as a mediator of clonal expansion.

MultiSTAAR provides a general and flexible statistical framework for functionally informed multi-trait rare variant analysis of biobank-scale sequencing studies by jointly analyzing multiple traits and incorporating annotation information.

A dataset of coding variation, derived from exome sequencing of nearly one million individuals from a range of ancestries, provides insight into rare variants and could accelerate the discovery of disease-associated genes and advance precision medicine efforts.

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.

A study describes an approach using designed building blocks that are far more regular in geometry than natural proteins to construct modular multicomponent protein assemblies.

The Pharma Proteomics Project generates the largest open-access plasma proteomics dataset to date, offering insights into trans protein quantitative trait loci across multiple biological domains, and highlighting genetic influences on ligand–receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks.

A cell-based phenotypic screen identifying inhibitors of Notch signaling led to the discovery of NVS-ZP7-4, which blocks the activity of the zinc transporter SLC39a7 (ZIP7) and induces cell death through an ER stress mechanism.

Together with a companion paper, the generation of a transcriptomic atlas for the mouse lemur and analyses of example cell types establish this animal as a molecularly tractable primate model organism.

Together with an accompanying paper presenting a transcriptomic atlas of the mouse lemur, interrogation of the atlas provides a rich body of data to support the use of the organism as a model for primate biology and health.

It is unclear how microbial-induced inflammation promotes neoplastic transformation in colitis-associated cancer (CAC). Here, the authors use models of CAC to show that inflammation induces 8-oxoguanine lesions in DNA, and that antioxidants can reduce these DNA lesions as well as CAC.

Light-sheet microscopes are increasingly used for imaging cleared tissues, but have imposed constraints on sample geometries and protocols. Here the authors present a multi-immersion open-top light-sheet microscope to overcome these limitations and enable high-throughput imaging of samples processed with various clearing protocols.

Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.

A comparison of fetal hemoglobin gene editing strategies using human sickle cell disease donor cells and in vivo transplantation finds that adenine base editing of the –175A>G site in the γ-globin gene promoters results in durable and potent expression.

The process of protein crystallization is poorly understood and difficult to program through the primary sequence. Here the authors develop a computational approach to designing three-dimensional protein crystals with prespecified lattice architectures with high accuracy.

A genome-wide-association meta-analysis of 18,381 austim spectrum disorder (ASD) cases and 27,969 controls identifies five risk loci. The authors find quantitative and qualitative polygenic heterogeneity across ASD subtypes.

Analysis of whole-genome sequences of 25,465 individuals of European ancestry shows that rare variants contribute substantially to the heritability of height and body mass index.

The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.