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Synthetic receptors are a powerful approach for engineering cell-based therapies that can sense and respond to their environment. Here cytokine receptor domains have been repurposed to develop engineered T cells that can sense and respond to cues associated with cancer or immune dysfunction.

Analyses of whole-genome sequencing data from UK Biobank and All of Us identify rare variant burden signals associated with metabolic health, including effects of protein-truncating variants in IRS2 on type 2 diabetes and chronic kidney disease risk.

Glioblastoma (GBM) is an aggressive tumor characterized by an immunosuppressive microenvironment. Here, the authors present a therapeutic approach based on the implantation of a biodegradable scaffold for the sustained, local release of a TLR7/8 agonist at the time of tumor resection, to achieve anti-tumor immunity and protection from future tumor challenge.

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.

Polygenic risk scores can help identify individuals at higher risk of type 2 diabetes. Here, the authors characterise a multi-ancestry score across nearly 900,000 people, showing that its predictive value depends on demographic and clinical context and extends to related traits and complications.

Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic.

A modeling approach to assess the global risk of Plasmodium falciparum histidine-rich protein 2 and 3 gene deletions identifies ten priority African countries for surveillance and could inform malaria control policies.

In the CheckMate 142 study, nivolumab (anti-PD-1) alone and in combination with ipilimumab (anti-CTLA-4) was shown to induce durable clinical benefit in patients with previously treated microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer. Here, the authors perform exploratory biomarker analysis of the CheckMate 142 study.

A study of several longitudinal birth cohorts and cross-sectional cohorts finds only moderate overlap in genetic variants between autism that is diagnosed earlier and that diagnosed later, so they may represent aetiologically different conditions.

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.

A rhynchocephalian skeleton around 3–7 million years older than the oldest currently known lepidosaur fossil provides important insight into the origin of lizards and snakes.

This work demonstrates how a biphenyl-like scaffold targets RNA through a common base displacement mechanism by optimizing π-stacking interactions within the binding pocket, helping to inform the design of novel RNA-targeting small molecules.

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 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.

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.

Genome-wide association meta-analyses of attention-deficit/hyperactivity disorder symptom measures and clinical diagnoses identify new risk loci, highlight putative effector genes and yield improved polygenic risk scores.

Genome-wide sequencing of 180 ancient individuals shows a continuous gradient of ancestry in Early-to-Mid-Holocene hunter-gatherers from the Baltic to the Transbaikal region and distinct contemporaneous groups in Northeast Siberia, and provides insights into the origins of modern Uralic and Yeniseian speakers.

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

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.

Free energy calculations are an essential tool to identify targets for individual proteins. Here, authors describe free energy perturbation (FEP+) calculations to optimise on target and off-target potencies for the discovery of potent Wee1 inhibitors with kinome-wide selectivity.

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.

In two independent studies, Song et al. and Jiang, Dalgarno et al. present computational frameworks, perturbation-response score and Mixscale, respectively, to determine individual cellular variation in response to perturbation.

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.

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.

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.

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.

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.

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.

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.

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.

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.

In this study, Jirsaraie et al. analyze data from the Adolescent Brain Cognitive Developmental study and use machine learning to predict both current and future psychological symptoms and to determine rates of change in symptom severity over time.

Integrated multi-omic analyses using samples from the TRACERx study highlight cross-talk between DNA hypermethylation and genomic lesions in non-small cell lung cancer.

A post hoc analysis of a multicentre, randomised trial showed that prediabetes remission is possible without total weight loss—providing weight is distributed to subcutaneous deposits as opposed to visceral ones.

Ligand-Transformer is a deep learning framework that predicts protein–ligand binding and conformational changes using only sequence and 2D-structure inputs, enabling efficient virtual screening and uncovering mechanisms of drug action.

Here the authors combine a deep generative model with structure-based drug design and prospectively validate functionally active, nanomolar, A_2A adenosine receptor ligands and solve their crystal structures to close the Artificial Intelligence Structure-Based Drug Design loop.