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The contribution of ether lipid species in cancer cell fate has not been fully understood yet. Here the authors show that malignant cancer cells employ ether lipids to modulate membrane biophysical properties, enhancing iron endocytosis and ferroptosis susceptibility.

Transcriptomic and clinical data analyses from multiple cohorts of patients with cancer receiving immunotherapy find that PD-1 blockade potentiates tumor-specific IgG1 plasma cell responses that complement cellular immunity and contribute to clinical benefit.

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.

In a phase 2 trial evaluating healthy donor fecal microbial transplantation plus either anti-PD-1 in patients with non-small cell lung cancer or anti-PD-1 and anti-CTLA-4 in patients with melanoma, encouraging efficacy was seen in both cohorts, with responses linked to significantly greater loss of baseline bacterial species.

Time-resolved serial femtosecond crystallography at X-ray free-electron lasers is a powerful approach for studying macromolecular dynamics, but its widespread use is limited by high sample consumption. Here, the authors introduce a segmented-droplet mix-and-inject strategy at the European XFEL that reduces sample consumption by up to 97% while preserving the data quality required for time-resolved structural studies of the enzyme NQO1.

Detection of hot intracluster gas in SPT2349−56 with the Atacama Large Millimeter/submillimeter Array provides new insights into early cluster formation.

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.

Chronic care manages long-term, progressive conditions, while acute care handles short-term ones. Here, authors show chronic conditions account for most of the global health burden, with 68% of DALYs and 93% of YLDs attributed to chronic care needs.

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.

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.

Visium spatial transcriptomics, single-nucleus RNA sequencing and co-detection by indexing are used to identify distinct spatial microregions in tumours and their microenvironment across six diverse solid cancer types.

The advantage of living in cities compared with rural areas with respect to height and BMI in children and adolescents has generally become smaller globally from 1990 to 2020, except in sub-Saharan Africa.

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.

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.

Enhanced polyamine depletion in neuroblastoma models decreases translation of mRNA codons with adenosine in the third position, reprogramming the tumour proteome away from cell cycle progression and towards differentiation.

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.

Here the authors present a computational method that expands the potential of multimodal single-cell analyses by delivering an accurate, fast, and user-friendly approach for normalizing and comparing surface protein expression across large and heterogeneous datasets.

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.

Federated learning (FL) algorithms have emerged as a promising solution to train models for healthcare imaging across institutions while preserving privacy. Here, the authors describe the Federated Tumor Segmentation (FeTS) challenge for the decentralised benchmarking of FL algorithms and evaluation of Healthcare AI algorithm generalizability in real-world cancer imaging datasets.

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.

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.

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.

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.

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.

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.

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 Mass Spectrometry Query Language (MassQL) is an open-source language that enables instrument-independent searching across mass spectrometry data for complex patterns of interest via concise and expressive queries without the need for programming skills.

The Cancer Genome Atlas reports on molecular evaluation of 295 primary gastric adenocarcinomas and proposes a new classification of gastric cancers into 4 subtypes, which should help with clinical assessment and trials of targeted therapies.

The Cancer Genome Atlas Research Network report integrated genomic and molecular analyses of 164 squamous cell carcinomas and adenocarcinomas of the oesophagus; they find genomic and molecular features that differentiate squamous and adenocarcinomas of the oesophagus, and strong similarities between oesophageal adenocarcinomas and the chromosomally unstable variant of gastric adenocarcinoma, suggesting that gastroesophageal adenocarcinoma is a single disease entity.

Enhanced sensitivity is a key parameter in quantum metrology. Here the authors demonstrate a distributed quantum phase sensing method that uses fewer photons than the number of parameters needed, and an enhanced quantum sensitivity is achieved.

Phytochrome photoreceptors are master regulators of plant development. This paper describes 3D structures of soybean phytochrome A in both Pr (inactive) and Pfr (signalling) states, revealing changes that might transmit the light signal to the cell.

Jayavelu, Samaha et al., apply machine learning models on hospital admission data, including antibody titers and viral load, to identify patients at high risk for Long COVID. Low antibody levels, high viral loads, chronic diseases, and female sex are key predictors, supporting early, targeted interventions.

The main protease, a key enzyme of SARS-CoV-2, can protect itself from oxidative damage. Here, Reinke, Schubert, and colleagues used XFEL radiation to image the enzyme, revealing the disulfide and NOS/SONOS bonds that form in response to oxygen.

Kates et al. propose that nitrogen-fixing symbiosis between bacteria and angiosperms has been gained and lost multiple times, based on ancestral reconstructions of nodulation across a deeply sampled, 13,000-species phylogeny, in contrast to a single origin with many losses.

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

The human endoderm-derived organoid cell atlas (HEOCA) presents an integrative analysis of single-cell transcriptomes across different conditions, sources and protocols. It compares cell types and states between models, and harmonizes cell annotations through mapping to primary tissues.

Chromosomal patterning of meiotic crossovers is mediated by pro-crossover HEI10 E3 ligase dynamics. This study reveals that a network of HSP40–HSP70 chaperones facilitates HEI10 proteolysis, thereby limiting formation of closely spaced crossovers.

Genomic analysis of Plasmodium DNA from 36 ancient individuals provides insight into the global distribution and spread of malaria-causing species during around 5,500 years of human history.

Divangahi and colleagues report that β-glucan pretreatment before influenza A virus challenge can increase survival by inducing long-term reprogramming of neutrophils, promoting disease tolerance irrespective of viral load.