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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.

Coronary artery disease is a leading health threat, yet age- and sex-specific plaque patterns remain unclear. Here the authors show, using a 16,300-patient CCTA cohort, that females develop atherosclerosis ~20 years later, accelerating following menopause.

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.

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 Einstein Probe has discovered a fast X-ray transient, EP240414a, associated with a broad-lined type Ic supernova. Its unusually soft spectrum and weak jet add to the diversity of stellar deaths and suggest a previously unknown Wolf–Rayet star explosion mechanism.

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 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.

Interpreting bone metastases (BMs) from computed tomography (CT) images remains challenging. Here, the authors develop an AI-based Bone Lesion Detection System - BLDS - and validate it in a cohort of 2,518 patients across five hospitals, showing highly sensitive and accurate performance for BM detection from CT scans.

Volume delineation of organs-at risk (OARs) and target tumors is an indispensable process for creating radiotherapy treatment planning. Herein, the authors propose a lightweight deep learning framework to empower the rapid and precise volume delineation of whole-body OARs and target tumors.

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.

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.

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.

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.

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.

In optimally doped Nd_0.8Sr_0.2NiO₂H epitaxial film, combined state-of-the-art experimental and theoretical approaches show abundant hydrogen with zero resistivity, and its critical role in superconductivity in epitaxial infinite-layer nickelates.

Machine learning can be used to identify subtypes of psychiatric disease. Here the authors identified two neurostructural subgroups in schizophrenia, each showing reproducibility and generalizability across different collection locations and illness stages, using the SuStain algorithm.

Trained on a cohort of 45,064 cases and validated on data acquired from mobile computed tomography scanners deployed in rural China, a lung cancer screening deep learning model is shown to outperform existing lung cancer risk scores.

A ‘mouse atlas’, comprising single-cell transcriptomic data from more than 100,000 cells from 20 organs and tissues, has been created as a resource for cell biology.

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

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

A type II supernova (SN 2023ixf) was observed in the galaxy M101 at a distance of 6.85  ±  0.15 Mpc, at about 1.0  h after the explosion.

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.

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.

The authors summarize the data produced by phase III of the Encyclopedia of DNA Elements (ENCODE) project, a resource for better understanding of the human and mouse genomes.

Common genetic variants associated with plasma lipids have been extensively studied for a better understanding of common diseases. Here, the authors use whole-genome sequencing of 16,324 individuals to analyze rare variant associations and to determine their monogenic and polygenic contribution to lipid traits.

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.

The Human Microbiome Project Consortium has established a population-scale framework to study a variety of microbial communities that exist throughout the human body, enabling the generation of a range of quality-controlled data as well as community resources.

Genome-wide association meta-analyses identify more than 350 loci associated with atrial fibrillation. A polygenic score derived from these results improves atrial fibrillation risk prediction compared to published clinical and polygenic scores.

This resource describes a collection of neurons from a variety of light microscopy-based datasets, which can serve as a gold standard for testing automated tracing algorithms, as shown by comparison of the performance of 35 algorithms.

A transcriptomics study demonstrates cell-type-specific responses to differentially aged blood and shows young blood to have restorative and rejuvenating effects that may be invoked through enhanced mitochondrial function.

A single-cell transcriptomic atlas across the lifespan of the mouse, denoted Tabula Muris Senis, provides molecular information about the hallmarks of ageing in a range of tissues and cell types.

The Human Microbiome Project Consortium reports the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome.