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IMiD-based PROTACs may degrade IKZF1/3 with hematologic effects. This study profiles these liabilities using hematopoietic assays showing stem cell rewiring and interferon activation and introduces a CRBN ligand that reduces them.

Robustness checks and reproduction of analyses with existing and updated data based on 110 articles in economics and political science journals with data and code-sharing requirements found high levels of robustness and reproducibility and determined that robustness was not dependent on author characteristics or data availability.

As Nature Aging celebrates its fifth anniversary, the journal asks some of the researchers who contributed to the journal early on to reflect on the past and the future of aging and age-related disease research, the impact of the field on human health now and in the future, and what challenges need to be addressed to ensure sustained progress.

CellVoyager is an artificial intelligence agent capable of exploring new biological hypotheses by autonomously analyzing single-cell RNA sequencing datasets and accounting for background information and prior analyses.

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

Here the authors present scLong, a billion parameter foundation model trained on 48M single cells, using self attention across all 28k human genes and Gene Ontology knowledge. It captures long range gene context in single Cell transcriptomics.

Jacquemyn et al. identify key lipid determinants controlling ectosome shedding from neurons. They find that ectosomes are a major route for the intercellular transport of misfolded α-synuclein, with relevance to Parkinson’s disease pathology.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

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.

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.

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.

A laser pulse can switch certain crystals from an insulating phase to a highly conducting phase. The ultrafast molecular motions that drive the transition have been directly observed using electron diffraction. See Letter p.343

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.

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.

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.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

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.

Spiking neural networks are generally used for sequential information and event data processing but still lack high performance. Through algorithm and hardware co-design, Zhang et al. report a State Space Model based approach to implement on compute-in memory hardware, enabling asynchronous and real-time processing capability with high energy efficiency for event sequences.

Resistance to first line treatment is a major hurdle in cancer treatment, that can be overcome with drug combinations. Here, the authors provide a large drug combination screen across cancer cell lines to benchmark crowdsourced methods and to computationally predict drug synergies.

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.

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.

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.

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.

Meta-analyses in up to 1.3 million individuals identify 87 rare-variant associations with blood pressure traits. On average, rare variants exhibit effects ~8 times larger than the mean effects of common variants and implicate candidate causal genes at associated regions.

Assessing the degree to which medical large language models reliably convey existing, trustworthy knowledge is crucial. This study introduces SourceCheckup, an automated framework revealing that large language models frequently cite medical references that do not fully support, or even contradict, their responses, showing significant gaps in reliability for clinical use.

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.

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.

This global study shows that short-term exposure to landscape fire sourced PM_2.5 increases hospital admissions for multiple diseases in children, especially those aged 5-9 years and in low-SES areas, highlighting the need for targeted protection.

A gene therapy method using AAV can help deliver HIV-fighting antibodies long-term, but the body often rejects them. Here the authors show that a short course of the drug rapamycin helps prevent host anti-drug antibody responses, showing successful antibody delivery in mice and monkeys.

The potential of mammogram-based biological age predictors remains to be fully explored. Here this group introduces a deep learning model to estimate the biological age of the breast using healthy mammograms.

Every spring, Bogong moths use the starry night sky as a compass to navigate up to 1,000 km towards their alpine migratory goal.

A multi-ancestry genome-wide gene–smoking interaction study identifies 13 new loci associated with serum lipids.

An atomic stencilling method based on the co-adsorption of iodide and 2-naphthalenethiol on gold is described, yielding more than 20 different types of nanoparticle with masked and painted regions and patchy particle morphologies not reported previously.

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 authors present a multiomics study of type 2 diabetes and quantitative blood lipid and lipoprotein traits in Hispanic/Latino populations. They demonstrate how integrating GWAS with omics characterization can advance precision medicine.