Genome Medicine最新文献

{"title":"VariantMedium: sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental data.","authors":"Özlem Muslu, Thomas Bukur, Pablo Riesgo-Ferreiro, Sameesh Kher, Shaya Akbarinejad, Luis Kress, Stefania Gangi Maurici, Muhammad Nabeel Asim, Alina Henrich, Sheraz Ahmed, Andreas Dengel, Martin Löwer, Jonas Ibn-Salem, Ugur Sahin","doi":"10.1186/s13073-026-01675-1","DOIUrl":"10.1186/s13073-026-01675-1","url":null,"abstract":"<p><strong>Background: </strong>Accurately identifying somatic variants from genomic sequencing is crucial for understanding and treating cancer. Previously, methods based on statistics and heuristics, as well as methods based on machine learning were proposed for somatic single nucleotide variant (SNV) calling from matched tumor-normal data, but they suffer from low sensitivity especially in certain genomic regions.</p><p><strong>Methods: </strong>Here we present VariantMedium, a somatic variant caller that combines a tree-based classifier with a 3D densely connected convolutional network (DenseNet) architecture. We trained and evaluated our model on experimentally confirmed variant data and improved it with an active learning strategy by experimentally confirming the predicted variants via targeted deep sequencing experiments. Overall, we used 336,839 variants from 2,956 samples with whole exome or genome sequencing for training and validation, and 118,887 variants from two independent studies with deep sequencing data for evaluation and benchmarking.</p><p><strong>Results: </strong>VariantMedium shows highest sensitivity amongst benchmarked callers and achieves similar or better F1 scores in SNV calling. Its performance is particularly pronounced on genomic regions characterized by high sequencing error rates, achieving higher F1 scores than Mutect2 and Strelka2.</p><p><strong>Conclusions: </strong>Our results demonstrate the strength of combining machine learning with high-quality experimental confirmation, enabling accurate somatic mutation detection even in low-mappability regions. We provide VariantMedium ( https://github.com/TRON-Bioinformatics/VariantMedium ) as an end-to-end pipeline to advance somatic mutation calling for precision medicine.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13285312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148277327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging tumor dynamics to discover mutations influencing progression and treatment response for precision oncology.","authors":"Ella Petter, Jaclyn LoPiccolo, Stefan Groha, Richard Border, Bogdan Pasaniuc, Kenneth L Kehl, Noah Zaitlen, Alexander Gusev","doi":"10.1186/s13073-026-01695-x","DOIUrl":"10.1186/s13073-026-01695-x","url":null,"abstract":"<p><strong>Background: </strong>Current research in precision oncology focuses on progression-free survival (PFS) and overall survival (OS) as the key outcomes. This stands in stark contrast to the primary outcomes guiding cancer treatment in the clinic- dynamic changes in tumor size in response to treatment. While PFS and OS are meaningful, highly interpretable and easily collected, we hypothesize that revealing associations between somatic mutations and tumor size dynamics can uncover genetic factors that can influence treatment response and generate hypotheses for future clinical investigation, while further improving our understanding of tumor biology.</p><p><strong>Methods: </strong>We propose and benchmark a new statistical framework - Andersen-Gill based Tumor Dynamics (AG-TD) to model recurrent outcomes and apply it to data from ~ 17 K radiology reports of patients with non-small cell lung cancer undergoing routine treatment at the Dana-Farber Cancer Institute. Our approach enables modeling recurrent outcomes while considering the time-dependent nature of biomarker-treatment interaction, patient mortality, and loss to follow-up.</p><p><strong>Results: </strong>We identify 27 somatic mutations that lead to differential response to common treatments including both protective and hazardous effects. Among these, deletions in MYBL1 and GATA3 were independently validated by replication in an external EGFR-TKI drug sensitivity screen, reaching Bonferroni correction significance. We also identify 13 somatic mutations associated with differential rates of progression and response during the entire treatment course, of which 9 are undetectable using conventional OS or PFS models. We further verify that the results are consistent in a homogeneous sub-cohort of advanced stage (3 and 4) patients only.</p><p><strong>Conclusions: </strong>Overall, we demonstrate the potential for using longitudinal outcomes in cancer genetic studies to complement traditional survival-based analyses, and to enable systematic identification of candidate gene-treatment interactions for future validation.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13523221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148271277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DISCERN: inferring drug sensitivity from single-cell transcriptomes using cell-type-specific genetic interaction networks.","authors":"Mingyue Liu, Yu Tian, Yuchao Jia, Jiewei Zhang, Xi Yi, Shaocong Sang, Nan Zhang, Kaidong Liu, Yunyi Peng, Yuncong Wang, Xin Li, Bo Chen, Haihai Liang, Yunyan Gu","doi":"10.1186/s13073-026-01688-w","DOIUrl":"10.1186/s13073-026-01688-w","url":null,"abstract":"<p><strong>Background: </strong>Genetic interactions, including synthetic lethality (SL) and synthetic viability (SV), are crucial for understanding tumor-specific vulnerabilities and mechanisms of drug resistance. However, predicting drug response at single-cell resolution based on SL and SV remains challenging.</p><p><strong>Methods: </strong>Here, we construct a large-scale atlas of cell-type-specific SL and SV networks across 14 human cancers using scRNA-seq datasets. Based on this atlas, we develop DISCERN (Drug response Inference from Single-Cell gEnetic inteRactioNs), a novel computational framework designed to infer single-cell drug sensitivity by utilizing malignant cell-specific genetic interactions. We also establish CellGIdb, an interactive portal that provides the cell-type-specific genetic interaction networks.</p><p><strong>Results: </strong>We reconstruct cell-type-specific genetic interaction networks across cancers, revealing both shared and distinct patterns among cell types. Notably, SL and SV interactions derived from malignant cells and T cells exhibit prognostic value and correlate with response to immunotherapy. DISCERN effectively infers tumor cell-specific drug sensitivity in scRNA-seq datasets from lung and breast cancers. DISCERN demonstrates improved predictive performance compared with existing computational methods. CellGIdb provides user-friendly analytical tools to facilitate the exploration of genetic interactions' roles in drug response and immunotherapy.</p><p><strong>Conclusions: </strong>Collectively, this study provides a comprehensive atlas and a novel computational framework, DISCERN, for interpreting drug responses in the context of genetic interactions at single-cell resolution. The publicly available CellGIdb ( https://biodata.hrbmu.edu.cn/CellGIdb/index.html ) resource will support further exploration of cell-type-specific vulnerabilities in cancer therapy.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13505051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148264289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic health archetypes identified in disease-free adults enable risk assessment for diverse chronic diseases.","authors":"Xiangyang Zhang, Weizhen Yan, Xianliang Fan, Peng Zhang, Yan Gao, Yuanzhe Wang, Hong Shen, Changjing Cai, Shan Zeng, Jiang Zhu","doi":"10.1186/s13073-026-01696-w","DOIUrl":"10.1186/s13073-026-01696-w","url":null,"abstract":"<p><strong>Background: </strong>The prevention of common chronic diseases is hampered by the lack of tools to identify at-risk individuals. The plasma proteome could enable a systems-level assessment of health, but its clinical translation is limited by platform-specific biases and a focus on single diseases.</p><p><strong>Methods: </strong>We aimed to develop and validate a clinically deployable proteomic classifier for multi-system risk prediction. Using data from 11,900 disease-free adults, we defined five ProteoHealth Archetypes (PHAs) via unsupervised learning. Critically, we trained a classifier using paired protein ratios to ensure robustness across measurement platforms.</p><p><strong>Results: </strong>The ratio-based classifier successfully transferred PHA signatures in an internal validation cohort (n = 3,570) and, importantly, in three external cohorts profiled by different technologies (SomaScan and mass spectrometry). Each PHA exhibited distinct, highly reproducible risks for developing cardiometabolic, inflammatory/immune, neurovascular, and psychiatric diseases. Individuals in high-risk archetypes experienced significantly steeper declines in survival. Genome-wide association analyses identified loci associated with PHA liability, and two-sample Mendelian randomisation produced effect directions consistent with the observational disease association. The differential proteomes and enriched pathways aligned with the specific disease profiles of each archetype.</p><p><strong>Conclusions: </strong>PHAs provide an externally transferable, mechanistically interpretable map of baseline proteomic health that forecasts multisystem disease and survival, offering a scalable substrate for prevention, risk communication, and biomarker-guided stratification.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13505149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148264266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From aging to Alzheimer's disease: concordant brain DNA methylation changes in late life.","authors":"David Lukacsovich, Juan I Young, Lissette Gomez, Michael A Schmidt, Wei Zhang, Brian W Kunkle, Xi Steven Chen, Eden R Martin, Lily Wang","doi":"10.1186/s13073-026-01698-8","DOIUrl":"10.1186/s13073-026-01698-8","url":null,"abstract":"<p><strong>Background: </strong>Aging is the strongest risk factor for Alzheimer's disease (AD), but the molecular connections between aging and AD remain unclear. DNA methylation (DNAm) is implicated in both processes.</p><p><strong>Methods: </strong>We conducted a meta-analysis of DNAm in prefrontal cortex from two independent postmortem cohorts: the Religious Orders Study and Memory and Aging Project (ROSMAP) and Brains for Dementia Research (BDR). Age-associated CpG sites were identified using cohort-specific linear models adjusted for neuronal proportion, sex, and batch, followed by meta-analysis. We computed epigenetic age acceleration in brain samples as delta-age (DNAmAge - chronological age), and compared clinically diagnosed AD with cognitively unimpaired participants. Functional analyses included genomic feature enrichment, pathway analysis, brain-blood DNAm correlation, and colocalization with genome-wide association study (GWAS) loci. Prognostic relevance of age-associated CpGs was tested in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset using Cox proportional hazards models for disease progression.</p><p><strong>Results: </strong>We identified 3264 CpG sites associated with aging; most were hypermethylated and enriched in promoters and CpG islands, and involved genes related to immune regulation and metabolism. Comparison with AD neuropathology-associated methylation showed substantial overlap, with nearly all shared CpGs and regions showing concordant directional changes. Cortical epigenetic age acceleration was higher in ROSMAP participants with clinical AD than in cognitively unimpaired individuals after covariates adjustment, and this association persisted when the cortical clock was restricted to the aging-associated CpGs identified here, suggesting that acceleration in AD is attributable to age-related CpGs. Several CpGs showed significant brain-blood methylation correlations or were linked to AD GWAS risk loci through colocalization analyses. In ADNI, among 33 candidate CpGs selected for concordant aging- and AD-associated changes in cortex and significant brain-blood methylation correlations, baseline methylation at one CpG (cg10752406 in AZU1 promoter) was associated with progression at a 5% false discovery rate after covariate adjustment.</p><p><strong>Conclusions: </strong>Aging-associated DNAm changes in prefrontal cortex overlap with AD neuropathology-related changes and are involved in accelerated epigenetic aging in clinical AD. Our study provides valuable insights into the epigenetic landscape of aging and its implications for AD.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13505181/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148264305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Circulating DNA reveals nucleosome occupancy patterns that are associated with nucleosome-DNA affinity and are affected in cancer.","authors":"Marianne Richaud, Ekaterina Pisareva, Paul Burgat, Alain R Thierry, Jacques Colinge","doi":"10.1186/s13073-026-01697-9","DOIUrl":"10.1186/s13073-026-01697-9","url":null,"abstract":"<p><strong>Background: </strong>The study of cell-free circulating DNA (cirDNA) fragments (fragmentomics) from liquid biopsies has received increasing attention to detect biomarkers. CirDNA found in blood plasma originates from cells in diverse tissues with a predominance for hematopoietic cells. CirDNA fragments are associated with nucleosomes which protect them against DNAse degradation.</p><p><strong>Methods: </strong>The genomic positions of CirDNA fragments originating from different cohorts of healthy individual and cancer patients were obtained from the public database FinaleDB. Various bioinformatic and statistical analyses were conducted on these fragments.</p><p><strong>Results: </strong>By mapping a large ensemble of well-positioned nucleosomes (WPNs), we found that nucleosome occupancy was associated with histone-DNA affinity, as evidenced by codon usage bias and differences in cirDNA fragment sizes. Moreover, nucleosome occupancy was different in healthy and cancer samples, thus allowing developing a high-performance machine learning approach for cancer detection (specificity and sensitivity > 0.95 for seven cancer types). Cancer influenced nucleosome occupancy in a global manner, although distinct cancer types retained specific features. WPN occupancy at transcription factor binding sites revealed shared, pan-cancer regulation of transcriptional programs involved in hematopoietic cell differentiation and neutrophil biology, the main cirDNA sources.</p><p><strong>Conclusions: </strong>This work provides new fundamental insights into cirDNA and DNA sequence using cirDNA as a physical readout. It also bares translational significance by disclosing a new high-performance strategy for cancer detection from liquid biopsies.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13495171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148239222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetically supported drug target prioritization for rare diseases.","authors":"Robert Chen, Áine Duffy, Matthew Mort, David N Cooper, Ghislain Rocheleau, Daniel M Jordan, Ron Do","doi":"10.1186/s13073-026-01671-5","DOIUrl":"10.1186/s13073-026-01671-5","url":null,"abstract":"<p><p>RareGPS is a machine-learning framework prioritizing drug targets for rare and uncommon diseases, integrating 11 genetic, clinical, and experimental evidence sources. It uses the full distribution of genetic associations across allele-frequency bins in an allelic-series model. Across 161 phenotypes, RareGPS outperforms existing resources for predicting drug indications and clinical trial progression; top 1% targets show 58-fold higher likelihood of advancing from nonindicated to phase IV and 8-fold from phase I to IV versus the middle 50%. We validated RareGPS using prescriptome analyses in two million patients and an independent literature evaluation tool (AMELIE). We publish predictions for 3,021,965 gene-phenotype pairs.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"18 1","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13255270/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148224479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infiltrating monocyte-derived macrophages does not survive long term in stroke brain despite their dominance in the acute ischemic core and myeloid derived IGF-1 play dichotomous roles in stroke recovery.","authors":"Hongli Ma, Nicolas Hugues, Kirsten Voice, Joshua Peter, Aleksandr Taranov, Christina Thapa, Krishna Roskin, Yu Luo","doi":"10.1186/s13073-026-01687-x","DOIUrl":"10.1186/s13073-026-01687-x","url":null,"abstract":"<p><strong>Background: </strong>Ischemic stroke elicits a strong neuroinflammatory response characterized by activation of microglia and infiltration of monocytes-derived macrophages (iMM), which have been speculated to have differential functions in stroke. However, because the gene expression profiles of microglia and iMM overlap in the injured brain, distinguishing these two cell populations has posed a challenge for the field.</p><p><strong>Methods: </strong>Using a recently characterized microglia-specific TMEM119^CreER-Ai14 tdTomato reporter mouse model and single cell RNA sequencing (scRNA-seq) analysis, we prelabeled microglia in the brain prior to stroke, enabling detailed characterization of the transcriptomic and spatial distributions of microglia vs. iMM across different stages of post-stroke. ScRNA-seq findings were validated through immunohistochemistry, RNAscope, and animal models.</p><p><strong>Results: </strong>Here, we report that microglia and iMM are enriched at distinct locations and exhibit differential temporal dynamics in the stroke brain. Our genetic tracing data reveals that iMM does not survive in the chronic stroke brain past 30 days in our model. Additionally, scRNA-seq further revealed distinct transcriptomic states between microglia and iMM at D7 and D14 in the stroke brain. Genetic tracing also allowed us to identify novel markers for activated microglia vs. iMM in the acute stroke brain such as Gm21188. Finally, our data also showed that Igf1 is up-regulated in both microglia and iMM after stroke. Cx3cr1^ERT2 Igf1^fl/fl mediated myeloid-specific Igf1 gene deletion at 5-9 Days after stroke lead to decreased CD8⁺ T-cell infiltration in the stroke brain. Functionally, myeloid specific Igf1 iKO mice show expedited sensorimotor function recovery but worsened anxiety-like behavior.</p><p><strong>Conclusions: </strong>In summary, Tmem119^CreER-Ai14 tdTomato reporter mouse line is a useful tool for the field to clearly delineate the cellular dynamics and transcriptomic profiles of microglia vs. iMM in a variety of central nervous system pathological conditions, which could have broad implications beyond stroke studies. Moreover, we have characterized novel subtypes and markers for activated microglia and iMM, as well as a possible novel role for myeloid cell-derived IGF-1 in driving T-cell infiltration and/or survival in the post-stroke brain. This study provides valuable insights for future investigations aimed at modulating microglia vs. iMM to promote stroke resolution and functional recovery in vivo.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13474826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148217524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"circVDJ-seq for T cell clonotype detection in single-cell and spatial multi-omics.","authors":"Izabela Plumbom, Benedikt Obermayer, Raphael Raspe, Anna Pascual-Reguant, Ilan Theurillat, Tancredi Massimo Pentimalli, Yu-Hsin Hsieh, Marine Gil, Carola Dietrich, Michaela Seeger-Zografakis, Claudia Quedenau, Jeannine Wilde, Caroline Braeuning, Cornelius Fischer, Markus Schuelke, Volkhard Seitz, Leif S Ludwig, Angelika Eggert, Nikolaus Rajewsky, Tatiana Borodina, Dieter Beule, Janine Altmueller, Helena Radbruch, Anja Erika Hauser, Thomas Conrad","doi":"10.1186/s13073-026-01691-1","DOIUrl":"10.1186/s13073-026-01691-1","url":null,"abstract":"<p><p>Monitoring T cell repertoires in human tissues provides important insights into immune response mechanisms in cancer, infectious diseases, and autoimmunity. However, retrieving VDJ information from single-cell and spatial transcriptomics workflows with 3'-barcoding of cDNA remains resource-intensive or requires specialized sequencing equipment. Here, we introduce circVDJ-seq for simplified and cost-efficient T cell receptor (TCR) profiling from 3'-directed workflows like single-cell or single-nucleus RNA sequencing, ATAC + RNA multi-omics, and spatial transcriptomics. Application of circVDJ-seq to freshly resected neuroblastomas and postmortem lymph nodes affected by pneumonia or COVID-19 reveals distinct immune microenvironments and T cell clonality patterns, highlighting broad utility across diverse clinical contexts.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13255474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148217454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial genetic evolution and phenotypic plasticity in triple-negative breast cancer.","authors":"Ruoxi Hong, Pin Wu, Yuyue Qiu, Shichen Dong, Yuhan Huang, Kaping Lee, Huifang Wang, Mei Li, Cuijuan Zhang, Feng Ye, Shanlan Mo, Siming Xue, Wei Wu, Zheng Hu, Weimin Zhang, Qimin Zhan, Guibo Li, Shusen Wang","doi":"10.1186/s13073-026-01684-0","DOIUrl":"10.1186/s13073-026-01684-0","url":null,"abstract":"<p><strong>Background: </strong>The interplay between genotype and phenotype in shaping spatial heterogeneity and metastatic evolution in triple-negative breast cancer (TNBC) remains poorly understood.</p><p><strong>Methods: </strong>Here, we developed a pathology-guided geospatial genomic and transcriptomic sequencing workflow (pGeo-G&T-seq) and applied it to TNBC specimens from primary tumors and matched metastatic sites. Using laser capture microdissection (LCM) we isolated mRNA and gDNA for whole-exome sequencing, whole-genome sequencing and whole-transcriptome sequencing to analyze spatial genomic heterogeneity and transcriptomic plasticity. Findings were further evaluated using independent bulk transcriptomic, single-cell immunotherapy, and spatial transcriptomic TNBC datasets.</p><p><strong>Results: </strong>The analysis unveiled spatial intratumoral heterogeneity at genomic and transcriptomic levels characterized by distinct spatial patterns of \"decay\" or \"uniformity\", demonstrating regional clonal expansion and genetic mosaicism, including heterogeneity in driver alterations and molecular subtypes. Notably, we identified a previously uncharacterized oxidative phosphorylation (OXPHOS)-associated transcriptional state associated with poor prognosis and features of limited immunotherapy responsiveness in single-cell cohorts. Intriguingly, genetic ancestry was associated with relatively stable transcriptional programs in a subset of cases. Furthermore, phylogenetically closely related clones from primary tumors and lymph node metastases shared convergent biological processes, suggesting that phenotypic traits may be partially retained during metastatic colonization.</p><p><strong>Conclusions: </strong>These findings support a model in which genetic evolution and phenotypic retention contribute to the spatial heterogeneity and metastatic progression of TNBC. More broadly, our pathology-guided spatial multi-omics framework enables the dissection of genotype-phenotype coupling in intact tissue, while the identification of an OXPHOS-associated transcriptional program may inform biologically guided patient stratification and generate hypotheses for future therapeutic studies.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13474512/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148217502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}