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PubMed2026

highSpaClone enables copy number alteration inference and tumor subclone analysis for high-resolution spatial transcriptomics.

High-resolution spatially resolved transcriptomics (SRT) offers unprecedented opportunities to investigate tumor heterogeneity but poses substantial computational and analytical challenges. Here, we present highSpaClone, a computational framework for copy number alteration (CNA) inference and tumor subclone identification from high-resolution SRT data across multiple spatial scales. By integrating spatial constraints into CNA estimation and clonal clustering, highSpaClone enables neighboring spatial locations to share information, thereby improving the robustness of genomic signals and the accuracy of subclone delineation. Across multiple Xenium and Visium HD datasets, highSpaClone revealed unique transcriptional programs, clonal evolutionary trajectories, and distinct tumor-microenvironment interactions. Furthermore, in human colorectal cancer samples, highSpaClone detected CNA events in histologically normal epithelial regions, highlighting early genomic alterations associated with field cancerization. These findings establish highSpaClone as a scalable framework for studying clonal architecture and tumor evolution.

CP: cancer biology↗

PubMed2026

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals↗

PubMed2026

Modelling time-varying genetic effects on binary disease risk via functional Mendelian randomization.

MOTIVATION: Genome-wide association studies have identified thousands of genetic variants associated with complex traits, establishing Mendelian randomization (MR) as a powerful framework for causal inference using variants as natural experiments. However, existing MR methods treat causal effects as static, relying on cross-sectional exposure measurements and ignoring how genetic predispositions to disease operate dynamically across the life course. Recovering age-specific causal effect functions from longitudinal data requires combining functional data representations of exposure trajectories with instrumental variable estimation strategies suitable for binary disease endpoints, a methodological gap that has remained unaddressed. RESULTS: We develop a functional MR framework for binary outcomes that integrates functional principal component analysis with two-stage residual inclusion (2SRI), ensuring consistent estimation under the nonlinear logistic link function that renders standard instrumental variable estimators inconsistent. Simulations across different causal effect trajectory shapes, varying measurement densities, and varying instrument strengths demonstrate accurate recovery of time-varying genetically predicted effects with minimal bias. Applied to UK Biobank data, the framework identifies an age-specific causal effect of genetically predicted body mass index on type 2 diabetes risk concentrated in early mid-adulthood and progressively attenuating thereafter. Concordance between the proposed 2SRI estimator applied to type 2 diabetes and the established continuous-outcome functional MR estimator applied to the paired glycated haemoglobin marker in the same cohort provides indirect empirical support for the validity of the proposed approach. AVAILABILITY AND IMPLEMENTATION: The method is implemented in the R package mvfmr, with a full tutorial vignette.

Mendelian Randomization Analysis↗

PubMed2026

FIERCE: reconstructing dynamic trajectories from the differentiation potency of single cells.

MOTIVATION: Since the introduction of single-cell RNA sequencing (scRNA-seq), numerous computational approaches have been developed to reconstruct dynamic cellular processes from static transcriptional profiles. These methods order cells along continuous trajectories by assessing their similarity in the gene-expression space. However, they rely on several assumptions, such as prior knowledge of the structure and directionality of the expected genealogy. These assumptions can limit their application to complex cellular systems with poorly understood developmental paths. RESULTS: To address this challenge, we introduce FIERCE (Framework for InfERence of the veloCity of Entropy), a novel computational pipeline designed to predict the changes in the differentiation potency of single cells during dynamic processes. Through a fully unsupervised approach, FIERCE enables the inference of cell lineages directly on the differentiation landscape of the biological system, thus eliminating the need for prior specification of developmental parameters. We demonstrate the efficacy of FIERCE by reconstructing three well-known mouse differentiation systems and by quantifying its accuracy on simulated data. AVAILABILITY AND IMPLEMENTATION: The FIERCE R package is available on GitHub at https://github.com/bicciatolab/FIERCE.

Cell Differentiation↗

PubMed2026

Reconstruction of ancestral plant genomes for inter-crop translational research.

We present Ancestral Genome Reconstruction (AGR), an exploratory framework for the automated inference of "paleogenomes" from large-scale comparative datasets. By analyzing 84 extant angiosperm species, we reconstructed 10 key ancestral angiosperm genomes millions of years old. These reconstructed ancestors were instrumental in (1) estimating when angiosperms emerged, when major botanical families originated, and when shared ancestral whole-genome duplication events occurred; and (2) tracing the evolutionary trajectories of ancestral chromosomes and genes, especially those that may have driven the emergence of key life-history traits (e.g., woody vs. herbaceous, aquatic vs. terrestrial, C3 vs. C4, and symbiotic root-nodulating vs. non-nodulating species). We demonstrated that these paleogenomes serve as tractable backbones for inter-crop translational research. Through an open-access web tool, OrthoViewer, we identified orthologs that have retained the same ancestral genomic context, favoring the identification of genes associated with "phenologs"- orthologous genes across species driving analogous phenotypes, traits, or processes-exemplified by FUWA for yield components, FLC for flowering time, and DDM1 for DNA methylation. Taken together, this study provides a testable paleogenomic workflow, opening novel avenues for integrating evolutionary genomics data into modern climate-smart crop breeding and supporting the agroecological transition.

Genome, Plant↗

PubMed2026

Recurrent hybridization shapes the diversification of Western Palearctic common toads (Bufo bufo complex).

Glacial cycles repeatedly fragmented temperate species into refugial populations, fostering divergence as a first stage towards speciation. Yet, interglacial expansions often reconnected these lineages, allowing gene flow to erode differentiation and reshape phylogeographic trajectories. We investigate these dynamics in Western Palearctic common toads (Bufo bufo complex), integrating genome-wide ddRAD-seq loci with an extensive mitochondrial dataset. Phylogenomic analyses resolved the three recognized species B. eichwaldi, B. spinosus and B. bufo, and within the latter, four major lineages distributed across the Apennine Peninsula, the Balkans, the Caucasus, and northern Europe. Mitochondrial and nuclear patterns were deeply discordant, and different approaches of historical gene flow inferences all supported past hybridization. In particular, our analyses suggest that the Caucasian population, previously attributed to the disputed species "B. verrucosissimus" based on its deeply divergent mtDNA, represents a shallow nuclear lineage within B. bufo and forms a broad intergradation zone with the Balkan lineage in Anatolia, arguing against a species status. Altogether, these results highlight a recurrent process in which refugial lineages do not diverge in strict isolation but repeatedly experience gene flow, thus reducing opportunities to speciate, and blurring tree-based phylogeographic and systematic hypotheses.

Amphibia↗

PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗

PubMed2026

A guide to understanding tumour evolution through the lens of population genetics.

Every cancer carries the history of its own evolution, hidden in its genome. Modern DNA sequencing can catalogue millions of mutations and profile tumours across space and time, but sequencing alone struggles to answer the questions that matter most: when did key adaptations emerge, how strongly were they selected, why do some tumours relapse whereas others do not, and how will the cancer evolve next? The reason is fundamental: sequencing is a snapshot, whereas evolution is a dynamic process. Bridging this gap requires moving beyond descriptive cancer genomics towards quantitative evolutionary inference. In this Review, we argue that population genetics provides the mathematical framework needed to extract evolutionary dynamics from cancer genomes. We show how models of mutation, selection and drift transform allele frequencies from descriptive measurements into quantitative estimates of clonal fitness and evolutionary timings. We discuss how these principles extend to epigenetic inheritance, plasticity and ecological interactions within the tumour ecosystem, and examine the assumptions and limitations for their application to modern sequencing data. By reframing cancer genomes as quantitative records of evolutionary processes rather than catalogues of mutations, researchers have used population genetics to provide a foundation for understanding - and ultimately predicting - the trajectories of cancer evolution.

Journal Article↗

PubMed2026

Phylogeographic epidemiology of Dabie bandavirus in East Asia: divergent transmission networks and genotype‑linked clinical severity.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), caused by Dabie bandavirus (SFTSV), exhibits geographically decoupled incidence and fatality patterns across East Asia. We aimed to elucidate the distinct ecological drivers and phylogeographic dynamics underlying this inland-coastal epidemiological divergence. METHODS: Integrating 1820 high-quality global genomes of SFTSV with well-characterized clinical cohorts (936 patients) and nationwide surveillance data (27,457 cases) from China, we constructed a comprehensive analytical framework. Ecological modeling, Bayesian phylogeography, and genotype-phenotype association analyses were employed to trace the evolutionary trajectories and clinical implications of the virus. RESULTS: A pronounced "inland-high-incidence vs. coastal-high-fatality" pattern of SFTS was identified. The incidence of SFTS exhibited divergent sensitivities to meteorological factors; inland transmission was sensitive to thermal fluctuations, whereas coastal dynamics were constrained by a sunshine threshold (> 200 h/month). In contrast, spatial divergence in clinical severity correlated with the distribution of regional viral genetic structures. Inland regions mainly co-circulated genotypes A, C, and D, while coastal regions were dominated by genotype B. Zhejiang province was identified as a genetic hub with significantly higher recombination frequencies than inland regions (11.0% vs. 3.5%, P < 0.001). Bayesian phylogeographic inference indicated frequent lineage exchange of Zhejiang province in China with the Republic of Korea and Japan. Clinically, genotypes B and D were associated with elevated mortality in coastal and inland regions, respectively, suggesting that the severe coastal phenotype is shaped by its genotype B-dominated structure. Additionally, the RdRp-N828S mutation emerged as a robust molecular correlate of fatal outcomes, warranting further functional validation. CONCLUSIONS: Divergent meteorological factors and plausible maritime transmission networks may underlie the geographically decoupled epidemiology of SFTS. These findings highlight that risk assessment must extend beyond incidence alone and provide a phylogeographically informed framework for targeted surveillance and genotype-specific interventions in high-risk hotspots.

Humans↗

PubMed2026

When Neurodevelopment Meets Autoimmunity: Pemphigus Foliaceus in Rett Syndrome Expands the Clinical Spectrum-A Case Report.

Rett syndrome (RTT, OMIM 312750) is a complex multisystem neurodevelopmental disorder. Evidence suggests that RTT may have an autoimmune component and inflammatory activation. However, the autoimmune manifestations remain poorly described. Pemphigus foliaceus is a debilitating autoimmune blistering condition caused by IgG autoantibodies that target desmoglein-1 (Dsg1), resulting in widespread skin blistering and lesions. We report a case of pemphigus foliaceus in a 20-year-old female with RTT and discuss its clinical implications. Clinical data obtained from electronic health records were extracted and reviewed. Genetic testing was performed to identify the specific methyl-CpG-binding protein 2 (MECP2) mutation and on an expanded panel of 55 genes associated with pemphigus foliaceus and related blistering disorders. The individual had pemphigus foliaceus, which required immunosuppression, intravenous immunoglobulin (IVIg) therapy, and Rituximab. The disease trajectory was complicated by infections, aspiration pneumonia, and hypoxic cardiac arrest. There was progressive functional decline, and disease control was difficult to achieve, with frequent flares. Genetic testing confirmed a heterozygous pathogenic MECP2 variant (NM_001110792.1:c.952C>T; p.(Arg318Cys)). HLA genotyping identified alleles consistent with the HLA-DRB1*04:02-HLA-DQA1*03:01-HLA-DQB1*03:02 (DR4/DQ8) haplotype. Furthermore, genetic analysis identified a heterozygous DSG1 variant rs12967407. This study reports the first case of pemphigus foliaceus in RTT, expanding the clinical spectrum of RTT beyond its neurodevelopmental phenotype. The DR4/DQ8 haplotype, previously associated with pemphigus susceptibility, supports a background of genetic susceptibility in this individual. No causal association between RTT and pemphigus foliaceus can be inferred from this single case. Rather, this case demonstrates that a rare autoimmune disorder such as pemphigus foliaceus can co-occur with a pathogenic MECP2 mutation. The coexistence of a genetic and autoimmune disease can result in a more complex clinical presentation and treatment course. The case further emphasises the need for increased vigilance in identifying new and emerging systemic pathology alongside RTT.

Humans↗

PubMed2026

Shielding the First 24 Postnatal Months of Life: A Proposal for a Prospective Cohort Study of Early-Life Electromagnetic Exposure and Autism Risk.

BACKGROUND: Autism Spectrum Disorder (ASD) involves Mirror Neuron System (MNS) dysfunction, driving core social and imitative impairments. Systemic physiological alterations such as autonomic dysregulation, mitochondrial dysfunction and neuroinflammation are known to impair synchronization and plasticity of neuronal clusters. A less-evident environmental cofactor, coinciding with rising ASD prevalence, is the considerable world-wide increase in electromagnetic radiation (EMR) overall exposure among children. Experimental evidence shows how low-intensity EMR influences cellular processes, via voltage-gated calcium channels (VGCCs), oxidative stress, and mitochondrial metabolism. The Resonant Convergence framework, allow to predict how chronic EMR exposure during the first 24 postnatal months of life can act as a factor in ASD pathogenesis. The best candidate mechanism is chronic Ion Cyclotron Resonance (ICR) detuning the Ca2+-calmodulin pathway, thus disrupting MNS synchronization. METHODS AND ANALYSIS: A prospective observational pilot cohort study (24-month follow-up) proposes to enroll 1000 full-term newborns into two arms: an EMR-reduced cohort (n = 500, rest and sleep-phase Faraday shielding) and a standard exposure cohort (n = 500). Exposure is quantified via radiofrequency (RF)/extremely low frequency(ELF) measurements, proximity analysis, device inventories and wearable dosimetry. The primary endpoint is a continuous neurodevelopmental trajectory score (joint attention, language, electroencephalogram (EEG) mu-rhythm); binary ASD diagnosis (Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), Autism Diagnostic Interview-Revised (ADI-R)) is a secondary, exploratory endpoint. Moreover, an optional genomic screening will evaluate gene-environment interactions within extremely low-frequency electromagnetic field (ELF-EMF) vulnerable pathways, including ASD-associated genes upregulated by RF via bromodomain and extraterminal protein (BET)-mediated epigenetic mechanisms. Analyses will employ risk ratios, Fisher's exact tests and logistic regression adjusted for confounders; mixed-effects and Bayesian modeling will evaluate longitudinal outcomes and exposure reduction effects. Given a 2-3% baseline prevalence, approximately 20-30 ASD cases are expected. The study is therefore powered for exploratory signal detection rather than definitive causal inference, providing the critical baseline data required to justify and design future confirmatory trials. Sex-stratified modeling will address the 4:1 male-to-female prevalence ratio. ETHICS AND DISSEMINATION: Ethics committee approval is not yet sought; full protocol review and approval will be obtained prior to the study initiation, in strict accordance with the Declaration of Helsinki. Written parental informed consent will be mandatory for all participants prior to enrollment. Study findings and methodological milestones will be disseminated through peer-reviewed international scientific publications. This protocol provides a structured methodological framework for the first prospective investigation of sleep-phase EMR reduction as a potential modulator of ASD incidence during early neurodevelopment. Results will inform adequately powered confirmatory trials in electromagnetic neurodevelopmental epidemiology.

autism spectrum disorder↗

PubMed2026

Unraveling causal links between chronic rhinosinusitis and peripheral artery diseases: insights from genetic correlations through genome-wide association studies.

OBJECTIVES: Chronic Rhinosinusitis (CRS) shares epidemiological links with Cardiovascular Diseases (CVDs), however, their shared genetic basis remains unclear. We hypothesized that pleiotropic genetic variants underlie CRS-CVDs links via distinct biological pathways. METHODS: Using large-scale GWAS data from European-ancestry individuals, we assessed global and local genetic correlations. We applied Genomic Structural Equation Modeling (Genomic SEM) to dissect shared genetic architecture, performed bidirectional Mendelian Randomization (MR) to infer causality, and conducted cis-eQTL colocalization to identify shared genetic signals. Finally, in vitro endothelial models (HUVECs) validated the functional dynamics of candidate genes under CRS-mimicking inflammatory stress. RESULTS: CRS showed significant genetic correlations with multiple CVDs. Genomic SEM revealed a latent factor structuring shared genetic risk through three pathways: artery diseases, myocardial diseases, and heart failure. Local genetic correlations identified significant local genetic correlations specifically between CRS and Peripheral Atherosclerosis (PAS)/Peripheral Artery Disease (PAD) specifically within the chr6: 31.57‒33.24 Mb locus. MR demonstrated causal effects of CRS on PAD (OR = 1.23, p = 0.022) and PAS (OR = 1.21, p = 0.011), but not vice versa. Genetically predicted HLA-DRB1, APOM, and COL11A2 expression conferred protection, while HLA-DQA2 increased risk. Crucially, in vitro validation corroborated these pathogenic trajectories, inflammatory stress significantly downregulated the protective APOM and upregulated the risk-associated HLA-DQA2 alongside pro-atherogenic VCAM-1, while HLA-DRB1 exhibited a compensatory upregulation (p < 0.05). CONCLUSION: CRS shares global genetic liability with CVDs, structured through three primary etiological pathways. Causal effects of CRS on peripheral artery diseases are mediated by immune and lipid-related genes within the chr6 locus, revealing divergent pleiotropic mechanisms. Our integrated genetic and in vitro evidence provides a mechanistic framework wherein chronic mucosal inflammation contributes to systemic endothelial vulnerability, thereby highlighting candidate targets for mechanism-directed therapy.

Humans↗

PubMed2026

dGAMLSS: an exact, distributed algorithm to fit Generalized Additive Models for Location, Scale, and Shape for privacy-preserving population reference charts.

MOTIVATION: There is growing interest in estimating population reference ranges across age and sex to better identify atypical clinically-relevant measurements throughout the lifespan. For this task, the World Health Organization recommends using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), which can model non-linear growth trajectories under complex distributions that address the heterogeneity in human populations.Fitting GAMLSS models requires large, generalizable sample sizes, especially for accurate estimation of extreme quantiles, but obtaining such multi-site data can be challenging due to privacy concerns and practical considerations. In settings where patient data cannot be shared, privacy-preserving distributed algorithms for federated learning can be used, but no such algorithm exists for GAMLSS. RESULTS: We propose distributed GAMLSS (dGAMLSS), a distributed algorithm that can fit GAMLSS models across multiple sites without sharing patient-level data. This includes specific considerations for the fitting of smooth functions at varying levels of communication efficiency. We demonstrate the effectiveness of dGAMLSS in constructing population reference charts across clinical, genomics, and neuroimaging settings and show that dGAMLSS is able to reproduce pooled reference charts and inference down to numerical differences. AVAILABILITY AND IMPLEMENTATION: An R package providing examples of the dGAMLSS algorithm, as well as functions for sharing and aggregating site-specific parameters, is available at https://github.com/hufengling/dGAMLSS.

Algorithms↗

PubMed2026

Revisiting the genome assembly of Lupinus species reveals differential diploidization after a shared whole-genome duplication.

Accurate genome assemblies are essential for comparative genomics, yet Hi-C-guided scaffolding can introduce structural errors that misrepresent chromosome architecture and bias evolutionary inferences. Here, we identified pervasive scaffolding errors-including artificial fusions, internal inversions, and incomplete contig mounting-in 2 previously published Lupinus genomes (L. cosentinii and L. digitatus) using a segmentation method based on long terminal repeat (LTR) retrotransposon density. We reassembled both genomes, producing chromosome-level references of 472.7 Mb (16 chromosomes) and 427.2 Mb (21 chromosomes), with BUSCO completeness >98.5%. Synteny validation and reapplication of LTR profiling confirmed that all prior errors were resolved. Using these corrected genomes together with 4 additional Lupinus species and 2 outgroup legumes, we investigated postpolyploid evolution. Synonymous substitution rate (Ks) analysis revealed a genus-specific whole-genome duplication (WGD) event (Ks = 0.17) shared by all 6 Lupinus species. The proportion of WGD-derived genes varied markedly, from 60% in L. digitatus to only 36% in L. mutabilis, indicating differential diploidization. While all species retained a core set of WGD duplicates enriched in cytoskeleton organization, ion transport, and defense responses, each exhibited lineage-specific functional trajectories: cell wall modification in L. cosentinii and L. digitatus, nitrogen metabolism in L. albus and L. angustifolius, flower development in L. luteus, and stress/lipid metabolism in L. mutabilis. Our corrected assemblies provide optimal references for Lupinus comparative genomics, and our findings demonstrate that a shared WGD event can lead to both conserved and highly divergent postpolyploid fates, likely underpinning adaptive diversification within the genus.

Lupinus↗

PubMed2026

Competing subclones and fitness diversity shape tumor evolution across cancer types.

MOTIVATION: Intratumor heterogeneity arises from ongoing somatic evolution and complicates cancer diagnosis, prognosis, and treatment. Reconstructing evolutionary dynamics typically requires spatiotemporal samples, which are often unavailable in clinical settings. Computational approaches that can infer tumor evolutionary history from single-timepoint bulk sequencing data remain limited. RESULTS: We present estimating evolutionary events through single-timepoint sequencing (TEATIME), a novel computational framework that models tumors as mixtures of two competing cell populations: an ancestral clone with baseline fitness and a derived subclone with elevated fitness. Using cross-sectional bulk sequencing data, TEATIME estimates mutation rates, timing of subclone emergence, relative fitness, and number of generations of growth. To quantify intratumor fitness asymmetries, we introduce a novel metric-fitness diversity-which captures the imbalance between competing cell populations and serves as a measure of functional intratumor heterogeneity. Applying TEATIME to 33 tumor types from The Cancer Genome Atlas, we revealed divergent as well as convergent evolutionary patterns. Notably, we found that immune-hot microenvironments constraint subclonal expansion and limit fitness diversity. Moreover, we detected temporal dependencies in mutation acquisition, where early driver mutations in ancestral clones epistatically shape the fitness landscape, predisposing specific subclones to selective advantages. These findings underscore the importance of intratumor competition and tumor-microenvironment interactions in shaping evolutionary trajectories, driving intratumor heterogeneity. Lastly, we demonstrate that TEATIME-derived evolutionary parameters and fitness diversity offer novel prognostic insights across multiple cancer types. AVAILABILITY AND IMPLEMENTATION: R implementation of TEATIME is available on GitHub (https://github.com/liliulab/TEATIME) and Zenodo (https://zenodo.org/records/17422174).

Neoplasms↗