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Neurotrophic factor Nerve Growth Factor (NGF) is involved in bladder physiopathology. Here the authors report that mast-cell derived NGF sustains the pro-tumoral functions of ILC2s in bladder cancer (BC), showing that selective targeting of the NGF receptor TrkA improves survival and response to immune checkpoint blockade in BC models.

Here the authors compare genetic testing strategies in rare movement disorders, improve diagnostic yield with genome analysis, and establish CD99L2 as an X-linked spastic ataxia gene, showing that CD99L2–CAPN1 signaling disruption likely drives neurodegeneration.

Integrating complex multi-omics data for individual patient decision making can be challenging. Here, the authors develop Knowledge Connector as a decision support system to generate and document Molecular Tumor Board recommendations and support medical decision-making.

Strongly enhanced optical nonlinearities and an ultrafast transition from coherent to incoherent polariton excitations are demonstrated by coupling an atomically thin WS₂ layer to a plasmonic nanostructure using ultrafast multidimensional spectroscopy.

Humanity’s Last Exam, a multi-modal benchmark at the frontier of human knowledge, is designed to be an expert-level closed-ended academic benchmark with broad subject coverage.

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.

Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders.

Radiation reaction (RR) on particles in strong fields is the subject of intense experimental research, but previous efforts lacked statistical significance due to the extreme regimes required. Here, the authors report a 5σ observation of RR and obtain strong, quantitative evidence favouring quantum models over classical, using an all-optical setup where electrons are accelerated by a laser in a gas jet before colliding with a second, intense pulse.

Bauer et al. analyze blood-based immune and transcriptomic markers in tuberculosis patients to identify treatment failure and recurrence. They find that specific markers reliably detect microbiological non-conversion during treatment and recurrence after therapy, providing a sputum-independent tool for patient monitoring.

Pathogenic variants in UNC13A underlie a novel neurodevelopmental syndrome, with three subtypes defined by distinct genotypes with varying clinical and functional impacts characterized in cellular and animal models.

Here, the authors examine the mechanisms behind cheatgrass’s successful invasion of North American ecosystems. Their genetic analyses and common garden experiments demonstrate that multiple introductions and migrations facilitated cheatgrass local adaptation.

The 4D Nucleome Project demonstrates the use of genomic assays and computational methods to measure genome folding and then predict genomic structure from DNA sequence, facilitating the discovery of potential effects of genetic variants, including variants associated with disease, on genome structure and function.

Many genetic loci have been identified to be associated with kidney disease, but the molecular mechanisms are not well understood. Here, the authors perform epigenome-wide association studies on kidney function measures to identify epigenetic marks and pathways involved in kidney function.

Serum urate concentration can be studied in large datasets to find genetic and epigenetic loci that may be related to cardiometabolic traits. Here the authors identify and replicate 100 urate-associated CpGs, which provide insights into urate GWAS loci and shared CpGs of urate and cardiometabolic traits.

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.

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.

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.

Human transplantation with allogeneic donor organs results in non-matching of MHC and differential presentation of T cell antigens. Here the authors show that in a lung transplanted SARS-CoV-2 infected patient T cell responses generated from the host may not be able to recognise infected cells within the graft and this may contribute to virus persistence.

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.

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.

Here, the authors demonstrate the electrical tunability of the nonlinear interactions, ultrafast formation and decay dynamics of layer-hybridized excitons in a field-effect device based on natural homobilayer MoS₂.

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.

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 framework based on actor–critic temporal difference learning and employing a biologically plausible network architecture that mimics reward-based learning on memristors and enables full in-memory training for navigation tasks is discussed.

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.

The primitive hominins from Dmanisi in the Republic of Georgia are often thought to be akin to Homo erectus and are arguably the earliest known members of the human family outside Africa. This conclusion has come, so far, from the presentation of postcranial material: now a partial skeleton of an adolescent individual associated with a skull, and remains from three adult individuals, suggest that the Dmanisi hominids are even more primitive than that, akin to Homo habilis.

Monolayer graphene can support the quantum Hall effect up to room temperature. Here, the authors provide evidence that graphene encapsulated in hexagonal boron nitride realizes a novel transport regime where dissipation in the quantum Hall phase is mediated predominantly by electron-phonon scattering rather than disorder scattering.

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.

In this work, Beyer and colleagues have utilized display screening technologies to comprehensively chart RAS proteins “druggability” and in doing so unravel a targetable ligand-induced pocket in RAS opening unprecedented anti-RAS targeted opportunities.

CellWhisperer uses multimodal learning of transcriptomes and text to answer questions about single-cell RNA-sequencing data.