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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.

Moscot is an optimal transport approach that overcomes current limitations of similar methods to enable multimodal, scalable and consistent single-cell analyses of datasets across spatial and temporal dimensions.

An understanding of the molecular mechanisms promoting the generation of immunoregulatory and tumour-promoting monocytes and macrophages is key to breaking the cycle of tumour myelopoiesis and developing more effective myeloid-targeting therapies.

Some cancer cells exhibit high loads of reactive iron in lysosomes, and this feature is exploited by using fentomycin-1, a newly developed small molecule, to induce ferroptosis.

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.

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.

Plasma proteomic analysis of presymptomatic individuals with amyotrophic lateral sclerosis identifies novel disease-associated proteins and enables the development of an accurate diagnostic biomarker panel.

The Cancer Genome Atlas Research Network reports an integrative analysis of more than 400 samples of clear cell renal cell carcinoma based on genomic, DNA methylation, RNA and proteomic characterisation; frequent mutations were identified in the PI(3)K/AKT pathway, suggesting this pathway might be a potential therapeutic target, among the findings is also a demonstration of metabolic remodelling which correlates with tumour stage and severity.

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.

Fe–N–C catalysts are a promising alternative to precious metals in fuel cell cathodes, but they suffer from durability issues. Now, a preparation method is reported that allows increasing the active site density while also improving durability.

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

A strategy for protecting redox-active ortho-quinones, which show promise as anticancer agents but suffer from redox-cycling behaviour and systemic toxicity, has been developed. The ortho-quinones are derivatized to redox-inactive para-aminobenzyl ketols. Upon amine deprotection, an acid-promoted, self-immolative C–C bond-cleaving 1,6-elimination releases the redox-active hydroquinone. The strategy also enables conjugation to a carrier for targeted delivery of ortho-quinone species.

Here the authors perform a trans expression quantitative trait locus meta-analysis study of over 3,700 people and link a USP18 variant to expression of 50 inflammation genes and lupus risk, highlighting how genetic regulation of immune responses drives autoimmune disease and informs new therapies.

Whole-genome sequence analysis identifies five independent risk loci for Lewy body dementia and demonstrates overlapping genetic architecture with Alzheimer’s and Parkinson’s diseases.

Interferon-α (IFN-α) is linked to type 1 diabetes (T1D), but how IFN-α impacts auto-antigen presentation is still unclear. Here the authors compare resting and IFN-α-treated islet β cells in vitro to find IFN-α inducing increased HLA-B expression, presentation of alternative epitopes, and activation of HLA-B-restricted T cells, thereby serving clues for T1D onset.

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.

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.

Comprehensive molecular profiles are required to understand and treat sarcomas, which comprise more than 70 different subtypes. Here, the authors profile the genomic landscape of 7494 sarcomas across 44 histologies using targeted panel sequencing and identify potential therapeutic targets.

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.

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.

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.

Multiple myeloma evolves continuously. Here the authors chronologically reconstruct driver events in multiple myeloma, noting a limited repertoire of initiating driver events that shape the evolutionary trajectory of the disease.

For many neurodevelopmental disorder (NDD) risk genes, the significance for mutational burden is unestablished. Here, the authors sequence 125 candidate NDD genes in over 16,000 NDD cases; case-control mutational burden analysis identifies 48 genes with a significant burden of severe ultra-rare mutations.

The hippocampus in mammalian brain varies in size across individuals. Here, Hibar and colleagues perform a genome-wide association meta-analysis to find six genetic loci with significant association to hippocampus volume.

In a GWAS study of 32,438 adults, the authors discovered five novel loci for intracranial volume and confirmed two known signals. Variants for intracranial volume were also related to childhood and adult cognitive function and to Parkinson's disease, and enriched near genes involved in growth pathways, including PI3K-AKT signaling.

A report detailing genotype data for over 500,000 markers in the human genome by examining 29 populations in the Human Genome Diversity Project.

Processes for efficient production of primary, secondary or ternary aminated compounds are constant challenges for chemical and pharmaceutical industries. Here, the authors develop selective and sustainable amination chemistry widely applicable to chemical substrates via formic acid.

Multidecadal global-mean temperature fluctuations over the past 2,000 years are consistent in comprehensive climate reconstructions and model simulations, and volcanic eruptions had the most important influence at that timescale between 1300 and 1800 CE.

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.

The authors defined a roadmap for investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders. Their proof-of-concept study using the largest available common variant data sets for schizophrenia and volumes of several (mainly subcortical) brain structures did not find evidence of genetic overlap.

Analyses of real-world evidence from digital clinical practice data provide important insights for healthcare decision makers. Here, authors test reproducibility of 150 peer-reviewed studies, reporting strong reproducibility, which could be further improved through more complete reporting in future original studies

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.

Ageing increases the risk of many diseases. Here the authors compare blood cell transcriptomes of over 14,000 individuals and identify a set of about 1,500 genes that are differently expressed with age, shedding light on transcriptional programs linked to the ageing process and age-associated diseases.

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