Normal tissues frequently harbor oncogenic mutations without progressing to cancer, but the cellular basis of this resistance remains poorly defined. We asked whether transformation requires selection of a rare, permissive state within normal-like cell populations. Dermal fibroblasts and mammary epithelial cells responded uniformly to combined HRAS-G12V expression and p53 disruption. Cellular barc

The peripheral nervous system innervates the pancreatic ductal adenocarcinoma (PDAC) microenvironment, and perineural invasion (PNI), the invasion of cancer cells in and around nerves, correlates with metastatic burden and poor outcomes. Though PDAC innervation is near universal and the majority of PDAC patients harbor PNI, the cellular and molecular composition of the heterocellular perineural ni

TFCP2-rearranged rhabdomyosarcoma is an exceptionally rare and highly aggressive malignancy driven by TFCP2 gene fusions and associated with a dismal clinical prognosis. Because standardized treatment regimens are lacking, developing representative preclinical models is critical for identifying effective therapies. Here, we present a case of a 29-year-old male with rapidly progressive, metastatic

Purpose: SWI/SNF (BAF) chromatin remodeling complex alterations are common in urothelial carcinoma, yet no biomarker-directed therapeutic strategies have been established for this population. We investigated whether BAF alterations delineate a biologically distinct, therapeutically actionable urothelial carcinoma subtype. Experimental Design: We performed integrative genomic and transcriptomic ana

Despite the clinical success of immune checkpoint inhibitors (ICIs) in the management of advanced clear cell renal cell carcinoma (ccRCC), many tumors develop acquired resistance, presumed to arise from a refractory subpopulation of persister cancer cells. Previous studies have provided insights into tumor microenvironment-specific drivers of ICI resistance in ccRCC. However, the extent to which c

Incomplete immune reconstitution (IIR) is a serious complication affecting 10 to 40% of people living with HIV (PLWH) despite effective antiretroviral therapy, leading to increased morbidity and mortality. Current risk prediction models rely on single-time point measurements and lack dynamic assessment capabilities. We developed a dynamic joint prediction system for IIR risk (DJPSIIR) using Bayesi

Liver tissue engineering offers a promising alternative for end-stage liver disease, yet the recreation of functional vasculature remains a major bottleneck to clinical translation. Here, we developed vascularized liver organoids by integrating human induced pluripotent stem cell (iPSC)-derived hepatoblasts and endothelial cells into decellularized scaffolds functionalized with an anti-CD31 aptame

Robots increasingly share spaces with people, supporting delivery services and mobility for the aging populations, yet their ability to share space comfortably lacks understanding and benchmarks for designers and policy-makers. We compared human-robot (HRI) and human-human (HHI) interactions across four real-world crowd datasets spanning Europe, North America, and Asia, using a unified pipeline to

Deep learning-based animal sound identification is regularly applied to large audio datasets for ecological monitoring and citizen science, but existing methods lack the fine temporal resolution required to extract insights into animal communication from these same datasets. Here we introduce Bird Communication Detector (BirdCODE), a deep learning model that detects and classifies the vocalization

Tumour single-cell datasets contain weak, sparse and context-restricted regulatory signals that are difficult to distinguish from noise using expression measurements alone. Here we present IMAS, an integrative multiomic augmentation system that learns transferable regulatory structure from a pan-cancer foundation of matched single-cell RNA and chromatin-accessibility profiles and adapts it to data

Liver cancer remains a major global health burden with high mortality and limited treatment response prediction tools. Patient-derived cancer organoids have emerged as promising preclinical models that recapitulate tumor heterogeneity; however, the biological significance of morphological diversity within established organoids remains poorly characterized in hepatocellular carcinoma (HCC). In this

Age-associated thymic involution is a major driver of immunosenescence, yet the cellular and spatial mechanisms coordinating age-related thymic remodeling remain incompletely understood. Combining single-cell transcriptomics, chromatin accessibility profiling, and spatial transcriptomics, we generated a spatially resolved multi-omic atlas of the aging mouse thymus. We show that thymic aging is not

Functional domain identification in spatial transciptomics transforms spatial molecular measurements into mechanistic insights into tissue physiology and pathology. However, the inherent noise and sparsity of gene expression data, along with the locality-biased design of conventional graph-based approaches, fundamentally limit the accurate identification of complex tissue domains. In this study, w

Proteins are fundamental macromolecules involved in virtually all biological processes. Their physiological roles are tightly linked to their three-dimensional structure, which can be naturally abstracted as Protein Contact Networks (PCNs), i.e., graphs where residues are nodes and edges encode spatial proximity. This representation enables the application of graph machine learning to address the

Urinary tract infections (UTIs) are common infections that pose a critical burden on healthcare and society. Despite growing recognition that the human urinary tract harbors its own microbiome, its composition, functional potential, and alterations in UTI remain limited. Here, we leveraged the publicly available whole-metagenome shotgun sequencing data from 450 urinary microbiome samples collected

Single-cell trajectory inference methods assign pseudotime coordinates but provide limited information on assignment uncertainty, especially at transitional states and branch points. We introduce the Trajectory Uncertainty Framework (TUF), a modular, downstream approach that defines a 2D uncertainty coordinate system for single-cell data. TUF decomposes local uncertainty into the Temporal Entropy

Cognitive manifestations, including impairments in language and executive functions, are seen in amyotrophic lateral sclerosis (ALS), but the underlying mechanisms remain unclear. We mapped prefrontal cortex regions from ALS patients by integrating spatial and single-nucleus transcriptomics in a cognitively stratified patient cohort. We uncover that cognitive impairment in ALS is associated with d

Artificial intelligence (AI) is increasingly permeating healthcare, from serving as a physician assistant to powering consumer applications. The opacity of AI algorithms makes the ability of humans to interact with AI algorithms challenging. To overcome this limitation, explainable AI (XAI) provides insight into AI decision-making, but evidence suggests that XAI can paradoxically induce bias in th

Across cancer, one of the most frequent examples of histologic transformation is the evolution of follicular lymphoma (FL) to an aggressive large cell lymphoma. Despite recent progress, understanding of the molecular and cellular underpinnings of transformation remains incomplete. Here, we dissect the interplay of tumor and microenvironment cell populations across transformation through a multimod

BackgroundMutation-derived neoantigens, typically identified in primary tumors, are emerging therapeutic targets for personalized cancer vaccines and adoptive T-cell therapies. However, clinical efficacy of neoantigen-directed therapies in patients with metastatic disease remains limited, partly due to inter-site genetic heterogeneity. We investigated whether ubiquitous neoantigens-derived from mu

Intracellular dynamics span a broad range of time scales and biomolecular processes, offering insights into cell health, functional state, phenotype, and response to external perturbations. Several label-free optical imaging approaches have been used to capture intracellular dynamics but are limited by spatiotemporal resolution and biomolecular specificity required to distinguish unique subcellula

The Hippo pathway is an evolutionarily conserved regulator of growth, regeneration, and organ homeostasis, and while its dysregulation is well established in cancer, the effects of inhibiting this pathway on normal tissues are less understood. Here we have systematically investigated the impact of Hippo pathway inhibition by comparing pharmacologic perturbation using a covalent small-molecule TEAD

Mitochondria, often referred to as the "powerhouses of the cell," are particularly crucial in cancer cells due to their high energy demands. Mitochondrial fusion-fission dynamics play a critical role in regulating signaling pathways and metabolic activities in colorectal cancer (CRC) cells. Increased mitochondrial fission drives metabolic reprogramming, enabling CRCs to proliferate, metastasize, a

Brutons tyrosine kinase (BTK) transduces B-cell receptor (BCR), Toll-like receptor (TLR), and Fc receptor (FcR) signaling, and overactivation of these pathways drives B-cell malignancies and antibody-mediated autoimmune disease. Small molecule inhibitors block the enzymatic functions of BTK, but this inhibition is undermined by resistance mutations, several of which abolish BTKs kinase activity ye

Clear cell renal cell carcinoma (ccRCC) remains the most lethal urological malignancy, with high metastatic rates, both at initial diagnosis and during disease progression, contributing to poor survival outcomes. Current diagnostic and prognostic approaches rely primarily on histopathology, limiting early detection of localized disease and relevant intervention for metastatic patients. Here, we pe

Direct KRAS inhibitors have established mutant KRAS as a clinically actionable target, yet adaptive resistance remains a major barrier to durable responses. To identify therapeutically actionable resistance mechanisms, we performed an unbiased in vivo CRISPR activation screen in an autochthonous lung adenocarcinoma model, identifying the receptor tyrosine kinase AXL as a dominant adaptive resistan

Methods that map genetic risk to cells do not directly test whether spatially organized ligand-receptor (LR) gene annotations carry conditional heritability association. Here we introduce EdgeMap, which scores each gene by the spatial activity of its LR contexts in spatial transcriptomics data, maps these scores alongside cell-intrinsic annotations to SNP-level LD scores, and tests both jointly ag

Accurate and tightly coordinated cell cycle progression and cell proliferation are critical for development, growth and homeostasis of an organism. Recently, Zinc finger protein 768 (ZNF768) was identified as a transcription factor driving cellular proliferation, in both a p53-dependent and independent manner. ZNF768 interacts with and represses p53 functions to limit cell cycle delay. Independent

Epithelioid sarcoma (EpS) is an aggressive ultra-rare soft tissue sarcoma (STS) driven by INI1 loss and consequent hyperactivation of the chromatin-modifying enzyme EZH2. Although the EZH2 inhibitor tazemetostat has shown clinical activity, responses remain limited, highlighting the need for improved treatment strategies. Here, using two in-house generated patient-derived xenograft models and matc

PurposeThere is an urgent need for improved prognostic tools and biological understanding of chemoradiation resistance in head and neck squamous cell carcinoma (HNSCC). This study established a preclinical imaging dataset aimed at identifying prognostic imaging features from 18F-FDG micro-PET/CT scans in HNSCC mouse models. MethodsThree orthotopic murine models were utilized: two human papillomav

Ewing sarcoma (EwS) is an aggressive pediatric malignancy with poor outcomes for patients with metastatic or relapsed disease. Effective immunotherapeutic approaches, including CAR T-cell therapy, are limited by intratumoral heterogeneity, an incompletely characterized tumor microenvironment (TME), and a lack of well-defined, tumor-restricted target antigens. To address these limitations, we perfo

Community data resources that aggregate datasets across studies are critical infrastructure for modern biomedical research, accelerating discovery as rapidly advancing Artificial Intelligence (AI) models place ever-greater demand on large, well-described data corpora. However, building these resources involves a fundamental tension: comprehensive metadata is imperative for reuse, yet capturing thi

The mesenchymal-epithelial transition factor (c-MET) is a receptor tyrosine kinase best known for mediating hepatocyte growth factor (HGF) signaling in cancer, yet its role in HIV-1 infection remains undefined. Here we identify c-MET as a host factor that facilitates HIV-1 replication in CD4+ T cells by promoting viral entry. HIV-1 infection upregulates c-MET transcripts and phosphorylation in pri

Genomic foundation models are increasingly used to interpret and design DNA sequences, yet their susceptibility to training-data manipulation remains poorly understood. Here we systematically evaluate backdoor poisoning across three model families, seven parameter scales ranging from 50 million to 7 billion, and 18 genomic classification tasks. We introduce two complementary 48-nucleotide triggers

Discovery of pathway associations and druggability can leverage underutililized dark kinase genes for treating complex diseases (proven for cancer and neurodegeneration), boosted with computational methods. Herein, we employ BERT-based embeddings of proteins and pathways (refined via two-stage transformer and heterogeneous graph transformer) and protein-protein and protein-pathway associations- bo

Fine-tuning a large language model on new data degrades what it previously learned. We present Omega-S, a drop-in penalty computed from the weight matrix alone: it needs no previous-task data, no Fisher matrix and no stored copy of the old weights. It is three lines in an existing training loop and adds under 4% to the cost of a step. Retention. On Llama-3-8B with LoRA, fine-tuned from code to pro

T/B cell receptors (T/BCR), coordinating antigen-targeting immune response, play crucial roles in anti-tumor immune response. Tracking T and B cell clonal evolution in situ at single-cell resolution is essential for understanding the adaptive immune responses. To address the lack of tools for in situ single-cell T/BCR (XCR) sequencing, we develop Stereo-XCR-seq, an efficient method for retrieving

Clinical sleep studies capture multiple physiologic signals, yet interpretation is often reduced to single summary measures of limited prognostic value, such as the apnea-hypopnea index. We present a foundation model that learns rich representations of sleep physiology from more than 10,000 clinical sleep recordings linked to electronic medical records. Here we show that sleep physiology contains

Three-dimensional (3D) histology provides volumetric insights into tissue microarchitectures across entire specimens, holding great promise for more accurate prognostication. However, existing methods are too slow for intraoperative consultations. We present ULTRA (ultrarapid cleared stimulated Raman with AI), a label-free, stain-free, fixation-free, and section-free platform that leverages the ch

Diffuse large B-cell lymphomas (DLBCL) are genetically and phenotypically heterogeneous, making diagnosis and treatment challenging. Current models suggest DLBCLs derive from follicular B cells engaged in adaptive immune responses. By studying cooccurring truncating mutations in SPEN and NOTCH2 in the BN2-DLBCL subtype, our data suggest a previously unrecognized extrafollicular trajectory. Using a

Spatial transcriptomics and proteomics have enabled profound insights into tissue organization, yet these technologies remain largely disparate, and emerging same-slide multiomics approaches are limited in plex, spatial resolution, signal retention, and integrative analytics. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined, resource-efficient,

Spatial proteomics measures multiple proteins in situ, capturing tissue complexity. However, cell classification in densely packed tissues remains challenging because of the lack of efficient classification algorithms, annotation tools and high-quality labeled datasets to benchmark computational methods. We introduce CellTune, an integrated software for analysis of large spatial proteomics dataset

Spatially resolved multimodal data enable the exploration of transcriptional, proteomic and metabolic regulation, yet analytical tools to integrate these spatial omics modalities, particularly spatial metabolomics, remain limited. We developed SpaMTP, an end-to-end framework that implements functions within a common Seurat architecture. It introduces analyses for metabolite annotation, joint clust

Recent rapid progress in the field of computational pathology has been enabled by foundation models. These models are beginning to move beyond encoding image patches toward whole-slide understanding, but their clinical utility remains limited. Here we present PRISM2, a multimodal slide-level foundation model trained on 2.3 million whole-slide images and 14 million question-answer pairs derived fro

In this issue of Cancer Cell, Liu et al. apply spatial multi-omics to map colorectal cancer micrometastases across primary tumors and matched liver and lung metastases, revealing liver micrometastases as an early evolved, stem-like, immune-suppressed residual disease state linked to a six-gene recurrence signature.

The brain vasculature comprises diverse specialized cells that are essential for brain function, yet their spatial organization remains poorly understood. Here, we construct a comprehensive cerebrovascular cell atlas encompassing 314,535 transcriptomes that captures the arteriovenous axis and defines consensus cell states. We then perform spatial transcriptomics to map 1,529,740 cells across the h

Pancreatic ductal adenocarcinoma (PDAC) remains highly aggressive, with a five-year survival rate under 13.3%, due to late diagnosis, rapid progression, and therapeutic resistance, highlighting the need for advanced treatments. GAIP-interacting protein C terminus 1 (GIPC1), a scaffolding protein overexpressed in PDAC, drives tumor growth and chemoresistance but has remained "undruggable" due to it

Electronic skin powered with artificial intelligence could enable next-generation robotic and medical devices, yet integrating multimodal sensors and analyzing heterogeneous, multifrequency time series remain challenging. Most wearable machine learning architectures are time-invariant and trained for a specific task, limiting transfer across modalities and users. We present a multimodal electronic

The human genome encodes ~1,900 secreted proteins, many of which mediate intercellular communication. Secreted proteins do not act cell-autonomously, limiting systematic approaches to characterize their functions. Here we introduce SecAct (Secreted Activity, https://secact.ccr.cancer.gov ), a computational framework that infers the signaling activities of 1,170 human secreted proteins from spatial

Evolution has used cell-cell communication as a strategy to coordinate organ development, enabling the reproducible generation of intricate structures. Classically, these interactions have been studied one at a time in model organisms, limiting our understanding of how cellular interplay coordinates human development. We investigated human kidney development using single-cell RNA sequencing and sp

Forest ecosystems are vital to the global carbon cycle, yet their long-term aboveground carbon (AGC) dynamics remain uncertain. Here, we integrate multi-source satellite observations with probabilistic deep learning models to reconstruct a harmonized, uncertainty-aware global forest AGC record from 1988 to 2021 at 0.25^∘. We find that, although global forests sequestered 6.2 PgC, moist t

Artificial intelligence may transform molecular biology not by always providing the correct answer, but by exploring mechanistic possibilities unconstrained by the assumptions that shape expert thinking. Its greatest contribution may be exposing the intellectual blind spots of scientists, while experimental validation remains the ultimate arbiter of truth.

The mechanisms underlying the interactions between disseminated tumor cells (DTCs) and their tissue microenvironment during metastatic colonization are currently poorly understood. We integrated multimodal single-cell and spatial profiling from liver cancer mouse models and human metastases to track the spatiotemporal dynamics of DTCs and their microenvironments from single-cell seeding to overt l

Transposable elements are hypothesized to have driven gene regulatory innovation, yet their contributions to primate brain development at the cell type level remain underexplored. Here, we use single-cell multiomics data from human, macaque, marmoset, and mouse cerebella to show that transposable element contributions to different cell types are shaped by varying degrees of constraints across cell

Cellular function depends on the precise deployment and distribution of nanoscale structures, but these features remain difficult to measure and compare between cells and datasets. This challenge is pronounced for astrocytes, whose intricate nanostructures interface with neurons, glia, and vasculature, to control brain development, synaptic development/plasticity, homeostasis, and responses to inj

Proteins have evolved over billions of years through coordinated substitutions, insertions and deletions, yet computational protein design cannot fully replicate nature's ability to engineer new proteins from existing templates. Protein language models^1-3 generate informative per-residue representations, but harnessing them for large-scale, function-preserving sequence modifications has

The proliferation of deep learning applications has intensified the demand for electronic hardware with low energy consumption and fast computing speed. Neuromorphic photonics have emerged as a viable alternative to process high-throughput information at the physical space. However, the simultaneous attainment of high linear and nonlinear expressivity poses a considerable challenge due to the powe

Liquid biopsy is a promising, noninvasive approach for cancer detection, but current methods often trade off accuracy, operability, and cost. To address these limitations, we introduce an artificial perception system (APS) for liquid biopsy that combines a structurally defined DNA-carbon nanotube sensor array with machine learning (ML) models. The array produces multichannel fluorescence fingerpri

Pancreatic islets, in which β cells constitute 50%-80% of the endocrine mass, are the body's site for glucose-regulated insulin secretion. Pancreatic islet dysfunction is a hallmark of type 2 diabetes. Nevertheless, the molecular changes that impair their function remain insufficiently understood. To determine how islet cellular organization supports function and how it deteriorates in disease, we

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and pro

In the progression from inflammatory bowel disease to associated cancer, the clonal mutational landscape shifts from selection of mutations in inflammatory genes to selection for cancer-driver mutations. How prevalence and expansion of either type of mutant clones could be impacted by the cellular environments in which they arise and how this affects the neoplastic outcome of colitis remains unkno

Plants recruit antagonistic microbes to defend against phytopathogens, offering a route to rational biocontrol beyond empirical screening. Here, using six generations of leaf-microbiome data from natural Arabidopsis populations infected by the oomycete Albugo laibachii, we show that microbial diversity is driven by infection, site, and host genotype, and that infected plants form modular networks

Recent advances in AI inspire visions of universal models of biology. Yet living systems are evolved, emergent processes whose behaviors cannot be inferred from their parts alone. We propose grounding AI in canonical biological processes, constructing data-driven world models with explicit mechanistic links across molecules, cells, and their dynamics in space and time.