Genome Medicine最新文献

{"title":"High genetic relatedness between multidrug resistant bacteria before and after the 2022 invasion of Ukraine.","authors":"Francois Lebreton, Viacheslav Kondratiuk, Valentyn Kovalchuk, Niels Pfennigwerth, Ting L Luo, Brendan T Jones, Nadiia Fomina, Frieder Fuchs, Jörg B Hans, Jessica Eisfeld, Ana Ong, Sören Gatermann, Jason W Bennett, Patrick Mc Gann","doi":"10.1186/s13073-025-01500-1","DOIUrl":"10.1186/s13073-025-01500-1","url":null,"abstract":"<p><strong>Background: </strong>The Russian invasion of Ukraine in 2022 has placed extraordinary pressure on hospitals there. One consequence of this has been the alarming increase in infections caused by multi-drug resistant organisms (MDROs), both within Ukraine and among the Ukrainian diaspora. The original source of these MDROs remains obscure although nosocomial origin is suspected. Here, we analyzed a collection of Acinetobacter baumannii and Pseudomonas aeruginosa collected from Ukraine before and after the invasion to glean a greater understanding of their relationship and origins.</p><p><strong>Methods: </strong>Genomic analysis was conducted on 167 A. baumannii and 93 P. aeruginosa cultured from 223 Ukrainian patients hospitalized in Ukraine or other European countries. Fifty-three isolates were cultured between 2014 and 2021, prior to the invasion, and the remaining 207 after.</p><p><strong>Results: </strong>Highly genetically related extensively-drug resistant (XDR) clones were identified that spanned the pre- and post-invasion periods. For A. baumannii, isolates encompassed three sequence types (STs), including carbapenemase-producing strains from ST-2 (bla_OXA-23) and ST-78 (bla_OXA-72), as well as ST-400 carrying the ESBL bla_GES-11. For P. aeruginosa, isolates encompassed three STs: ST-773 carrying bla_NDM-1, ST-1047 carrying bla_IMP-1, and ST-244. For all, the mobile genetic elements associated with carbapenemase carriage were fully characterized. Notably, post-invasion ST-773 and ST-1047 P. aeruginosa had a signature of host adaptation with multiple loss-of-function mutations in the quorum-sensing regulator LasR, known to modulate immune responses and provide survival advantages in animal models of infection.</p><p><strong>Conclusions: </strong>XDR epidemic clones circulating in Ukraine and across Europe since 2022 share a close genetic relationship to historical strains from Ukraine. In some cases, direct links to medical facilities within Ukraine can be inferred. These data suggest that surveillance efforts should focus on tracking nosocomial transmission within Ukrainian hospitals while infection control efforts are being disrupted by the ongoing Russian invasion.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"74"},"PeriodicalIF":10.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12220160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539928","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":"Understanding how gene-disease relationships can impact clinical utility: adaptations and challenges in hereditary cancer testing.","authors":"Jennifer Herrera-Mullar, Carolyn Horton, Amybeth Weaver, Meghan Towne, Jennifer M Huang, Grace E VanNoy, Steven M Harrison, Bess Wayburn","doi":"10.1186/s13073-025-01499-5","DOIUrl":"10.1186/s13073-025-01499-5","url":null,"abstract":"<p><strong>Background: </strong>Defining gene-disease relationships (GDRs) influences the clinical utility of hereditary cancer predisposition (HCP) multigene panel testing (MGPT) results, as variant classification relies directly on gene-disease characterization. GDR characterization for HCP is challenging due to disease prevalence, incomplete penetrance, and heterogeneity. There is insufficient data showing how gene-disease validity (GDV) scores of HCP genes affect variant classification and how GDV scores change over time. Though these issues determine the results of HCP-MGPT, their impact on short- and long-term clinical utility has not been explored in-depth.</p><p><strong>Methods: </strong>Using an evidence-based GDV framework, genes were classified into five standardized GDV categories at the time of panel addition. We curated changes in GDV scores and classifications for HCP-MGPT over 7 years. The corresponding impact on the frequency of positive and variant of uncertain significance (VUS) results was evaluated by GDV score.</p><p><strong>Results: </strong>Positive results were most common in Definitive evidence genes (31.5%), with none in Limited evidence genes (0%). Genes with Definitive GDRs (n = 42) remained Definitive, while most genes with Strong (6/10, 60%) and Moderate (19/24, 80%) GDRs changed categories, 8 (23.5%) of which received a clinically significant GDR downgrade. GDRs associated with low-moderate risk of breast cancer were significantly more likely to be downgraded compared to GDRs associated with rarer, high-penetrance specific phenotypes (p < 0.0001). Downgrades for all GDRs were due to new published data and updates to the GDV framework (77%, 10/13), with 23% (3/13) due to framework updates alone. Including Limited evidence genes on MGPT increased the VUS frequency by 13.7% percentage points.</p><p><strong>Conclusions: </strong>Positive and VUS results varied by GDV category, and Limited evidence genes did not contribute to diagnostic yield. No Limited evidence genes in the category for ≥ 3 years (n = 8) were upgraded, indicating that including these genes on HCP-MGPT provides limited long-term clinical utility. Our data highlight that GDV assessment for HCP requires robust evidence and must account for variable disease penetrance and elevated prevalence in the population. Balancing the availability of a comprehensive gene menu and transparency surrounding clinical utility of novel genes will maximize identification of high-risk patients while reducing the risk of misdiagnosis through clinical false-positive results.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"73"},"PeriodicalIF":10.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12220650/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539979","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":"The CXCL16/CXCR6 axis is linked to immune effector cell-associated neurotoxicity in chimeric antigen receptor (CAR) T cell therapy.","authors":"I-Na Lu, Louisa Müller-Miny, Carolin Krekeler, Phyllis Fung-Yi Cheung, Georgia Antonopoulou, Astrid Jeibmann, Andreas Schulte-Mecklenbeck, Kornelius Kerl, Simon Call, Christian Reicherts, Annalen Bleckmann, Matthias Stelljes, Georg Lenz, Heinz Wiendl, Gerd Meyer Zu Hörste, Oliver M Grauer","doi":"10.1186/s13073-025-01498-6","DOIUrl":"10.1186/s13073-025-01498-6","url":null,"abstract":"<p><strong>Background: </strong>Immune effector cell-associated neurotoxicity syndrome (ICANS) is a common and potentially life-threatening complication of chimeric antigen receptor (CAR) T cell therapy. The underlying mechanisms of ICANS remain incompletely understood and are unlikely to be explained by cytokine excess alone.</p><p><strong>Methods: </strong>We analyzed paired peripheral blood and cerebrospinal fluid (CSF) samples from CAR T cell-treated patients who developed ICANS (n = 11) within 5-21 days post-infusion. ICANS severity was graded as follows: grade 1 (n = 3), grade 2 (n = 4), grade 3 (n = 1), and grade 4 (n = 3). Control samples were obtained from patients with idiopathic intracranial hypertension, functional neurological disorders, and multiple sclerosis. We employed single-cell RNA sequencing (scRNA-seq) and flow cytometry to profile immune cell populations and performed multi-modal spatial transcriptomics and immunofluorescence on postmortem choroid plexus and brain tissue from a patient with fatal grade 4 ICANS.</p><p><strong>Results: </strong>We identified a distinct population of proliferating, cytotoxic T cells characterized by CXCR6 expression, enriched in CD4 + CAR T cells and predominantly localized in ICANS CSF. These CXCR6 + T cells were largely absent from control CSF samples. Spatial mapping of postmortem brain tissue revealed widespread infiltration of myeloid cells and a striking spatial association between CXCR6 + T cells and CXCL16-expressing myeloid cells in both the choroid plexus and brain parenchyma. Notably, CSF levels of CXCL16 positively correlated with ICANS severity across the cohort, from grade 1 to grade 4.</p><p><strong>Conclusions: </strong>Our findings implicate the CXCL16/CXCR6 axis in the recruitment of cytotoxic CAR CD4 + T cells to the central nervous system (CNS) during ICANS. This interaction may be linked to neuroinflammatory processes and severity stratification in ICANS pathogenesis. These results provide a mechanistic rationale for exploring CXCL16/CXCR6 as a potential biomarker and therapeutic target in CAR T cell-associated neurotoxicity.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"71"},"PeriodicalIF":10.4,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12210444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144527625","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":"Plasma microRNA signatures of aging and their links to health outcomes and mortality: findings from a population-based cohort study.","authors":"Lieke M Kuiper, Michelle M J Mens, Julia W Wu, Jaap Goudsmit, Yuan Ma, Liming Liang, Albert Hofman, Trudy Voortman, M Arfan Ikram, Jeroen G J van Rooij, Joyce B J van Meurs, Mohsen Ghanbari","doi":"10.1186/s13073-025-01437-5","DOIUrl":"10.1186/s13073-025-01437-5","url":null,"abstract":"<p><strong>Background: </strong>MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as a biological aging indicator and their associations with health outcomes using population-level data.</p><p><strong>Methods: </strong>We quantified plasma expression levels of 2083 extracellular microRNAs using targeted RNA-sequencing in 2684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge-a composite score of age and nine multi-system blood biomarkers-the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets.</p><p><strong>Results: </strong>We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (n_training = 1158, n_test = 772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (n_validation = 754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with 10-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge.</p><p><strong>Conclusions: </strong>This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with the potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"70"},"PeriodicalIF":10.4,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188677/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495837","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":"Correction: Integrated proteotranscriptomics of breast cancer reveals globally increased protein-mRNA concordance associated with subtypes and survival.","authors":"Wei Tang, Ming Zhou, Tiffany H Dorsey, DaRue A Prieto, Xin W Wang, Eytan Ruppin, Timothy D Veenstra, Stefan Ambs","doi":"10.1186/s13073-025-01495-9","DOIUrl":"10.1186/s13073-025-01495-9","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"69"},"PeriodicalIF":10.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12186356/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484098","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":"Longitudinal analysis of genetic and environmental interplay in human metabolic profiles and the implication for metabolic health.","authors":"Jing Wang, Alberto Zenere, Xingyue Wang, Göran Bergström, Fredrik Edfors, Mathias Uhlén, Wen Zhong","doi":"10.1186/s13073-025-01492-y","DOIUrl":"10.1186/s13073-025-01492-y","url":null,"abstract":"<p><strong>Background: </strong>Understanding how genetics and environmental factors shape human metabolic profiles is crucial for advancing metabolic health. Variability in metabolic profiles, influenced by genetic makeup, lifestyle, and environmental exposures, plays a critical role in disease susceptibility and progression.</p><p><strong>Methods: </strong>We conducted a two-year longitudinal study involving 101 clinically healthy individuals aged 50 to 65, integrating genomics, metabolomics, lipidomics, proteomics, clinical measurements, and lifestyle questionnaire data from repeat sampling. We evaluated the influence of both external and internal factors, including genetic predispositions, lifestyle factors, and physiological conditions, on individual metabolic profiles. Additionally, we developed an integrative metabolite-protein network to analyze protein-metabolite associations under both genetic and environmental regulations.</p><p><strong>Results: </strong>Our findings highlighted the significant role of genetics in determining metabolic variability, identifying 22 plasma metabolites as genetically predetermined. Environmental factors such as seasonal variation, weight management, smoking, and stress also significantly influenced metabolite levels. The integrative metabolite-protein network comprised 5,649 significant protein-metabolite pairs and identified 87 causal metabolite-protein associations under genetic regulation, validated by showing a high replication rate in an independent cohort. This network revealed stable and unique protein-metabolite profiles for each individual, emphasizing metabolic individuality. Notably, our results demonstrated the importance of plasma proteins in capturing individualized metabolic variabilities. Key proteins related to individual metabolic profiles were identified and validated in the UK Biobank, showing great potential for metabolic risk assessment.</p><p><strong>Conclusions: </strong>Our study provides longitudinal insights into how genetic and environmental factors shape human metabolic profiles, revealing unique and stable individual metabolic profiles. Plasma proteins emerged as key indicators for capturing the variability in human metabolism and assessing metabolic risks. These findings offer valuable tools for personalized medicine and the development of diagnostics for metabolic diseases.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"68"},"PeriodicalIF":10.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12172340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144316704","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":"PhenoDP: leveraging deep learning for phenotype-based case reporting, disease ranking, and symptom recommendation.","authors":"Baole Wen, Sheng Shi, Yi Long, Yanan Dang, Weidong Tian","doi":"10.1186/s13073-025-01496-8","DOIUrl":"10.1186/s13073-025-01496-8","url":null,"abstract":"<p><strong>Background: </strong>Current phenotype-based diagnostic tools often struggle with accurate disease prioritization due to incomplete phenotypic data and the complexity of rare disease presentations. Additionally, they lack the ability to generate patient-centered clinical insights or recommend further symptoms for differential diagnosis.</p><p><strong>Methods: </strong>We developed PhenoDP, a deep learning-based toolkit with three modules: Summarizer, Ranker, and Recommender. The Summarizer fine-tuned a distilled large language model to create clinical summaries from a patient's Human Phenotype Ontology (HPO) terms. The Ranker prioritizes diseases by combining information content-based, phi-based, and semantic-based similarity measures. The Recommender employs contrastive learning to recommend additional HPO terms for enhanced diagnostic accuracy.</p><p><strong>Results: </strong>PhenoDP's Summarizer produces more clinically coherent and patient-centered summaries than the general-purpose language model FlanT5. The Ranker achieves state-of-the-art diagnostic performance, consistently outperforming existing phenotype-based methods across both simulated and real-world datasets. The Recommender also outperformed GPT-4o and PhenoTips in improving diagnostic accuracy when its suggested terms were incorporated into different ranking pipelines.</p><p><strong>Conclusions: </strong>PhenoDP enhances Mendelian disease diagnosis through deep learning, offering precise summarization, ranking, and symptom recommendation. Its superior performance and open-source design make it a valuable clinical tool, with potential to accelerate diagnosis and improve patient outcomes. PhenoDP is freely available at https://github.com/TianLab-Bioinfo/PhenoDP .</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"67"},"PeriodicalIF":10.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247520","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":"Associations between HLA-II variation and antibody specificity are predicted by antigen properties.","authors":"Gabriel Innocenti, Sergio Andreu-Sánchez, Nicolai V Hörstke, Hesham Elabd, Iros Barozzi, Andre Franke, Máté Manczinger, Thomas Vogl","doi":"10.1186/s13073-025-01486-w","DOIUrl":"10.1186/s13073-025-01486-w","url":null,"abstract":"<p><strong>Background: </strong>Human leukocyte antigen class II (HLA-II) genes are highly polymorphic affecting the specificity of human antibody responses, as presentation of processed antigen peptides by HLA-II on B cells is essential for T helper cell dependent affinity maturation and class switching. The combination of high-throughput immunoassays and genome-wide association studies has recently revealed strong associations between HLA-II variants and antibody responses against specific antigens. However, factors underlying these associations remain incompletely understood.</p><p><strong>Methods: </strong>Here, we have leveraged paired data sets of SNP arrays and functional antibody epitope repertoires against 344,000 peptide antigens in 1940 individuals to mine for key determinants linking genetics and antibody specificity.</p><p><strong>Results: </strong>We show that secreted proteins and antigens presented in small modules (i.e., viruses) are significantly more frequently associated with HLA-II alleles, than membrane bound or intracellular proteins. This data suggests a model in which antibody responses against separate antigen units composed of single or few proteins dominate HLA-II associations. In contrast, the presence of manifold intracellular or membrane proteins (peptides of which could be bound by different HLA-II alleles) on bacterial cells dilutes potential associations to antibody specificities.</p><p><strong>Conclusions: </strong>Hence, genetic associations to antibody specificities are shaped by antigen intrinsic properties. Given the prominent role of HLA-II alleles in infection, autoimmune diseases, allergies, and cancer, our work provides a theoretical framework to study antigen/HLA-II risk factors in these disease settings and will fuel the design of improved immunogenetics screens.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"65"},"PeriodicalIF":10.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12131526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208402","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":"Pan-cancer analysis identifies CD155 as a promising target for CAR-T cell therapy.","authors":"Xiaohong Liu, Yue Sun, Boxu Lin, Hao Xiong, Xinyue Lu, Binghe Tan, Chenglin Zhang, Mingyao Liu, Juliang Qin, Na Zhang, Bing Du","doi":"10.1186/s13073-025-01490-0","DOIUrl":"10.1186/s13073-025-01490-0","url":null,"abstract":"<p><strong>Background: </strong>Chimeric antigen receptor T (CAR-T) cell therapy has shown remarkable success in treating hematologic malignancies. However, its efficacy against solid tumors remains limited. One of the major challenges is the lack of specific tumor antigens. Therefore, the exploration and rational selection of novel tumor targets is urgently needed. In this study, we investigate the therapeutic potential of targeting CD155 in cancer by CAR-T cells.</p><p><strong>Methods: </strong>The expression of CD155 was analyzed across various cancer types using data from The Cancer Genome Atlas (TCGA) and validated by tissue microarray analysis. The impact of CD155 on T cell mediated cytotoxicity was analyzed using CD155 over-expression or knockout tumor cells. Subsequently, second-generation CAR-T cells were constructed using either the extracellular domain (ECD) of TIGIT or an anti-CD155 scFv to evaluate their anti-tumor efficacy both in vitro and in vivo.</p><p><strong>Results: </strong>We demonstrated that CD155 is specifically overexpressed across various cancer types and that its high expression is strongly associated with poor prognosis, as revealed by data from TCGA. Consistently, CD155 is significantly upregulated in clinical tumor tissues and in numerous cancer cell lines, while it is rarely expressed in normal tissues. Furthermore, CD155 expression is also significantly increased in granulocytes derived from cancer patients compared to those from healthy donors. Functionally, high CD155 expression significantly inhibits the release of cytotoxic factors from T cells, thereby functioning as an immune checkpoint that mediates tumor immune evasion. After comparison, the scFv based anti-CD155 CAR-T cells demonstrated stronger anti-tumor activity than ECD of TIGIT based CAR-T cells. Moreover, the scFv based CAR-T cells exhibited effective anti-tumor activity against multiple CD155⁺ solid and hematologic tumors both in vitro and in different xenograft mouse models.</p><p><strong>Conclusions: </strong>Our study demonstrates that CD155 is selectively expressed in cancer cells while being rarely detected in normal tissues, and may serve as a promising pan-cancer target for CAR-T therapy. Targeting CD155 with CAR-T cells provides an effective approach to treating both solid and hematologic malignancies.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"64"},"PeriodicalIF":10.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12128359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208404","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":"The molecular impact of cigarette smoking resembles aging across tissues.","authors":"Jose Miguel Ramirez, Rogério Ribeiro, Oleksandra Soldatkina, Athos Moraes, Raquel García-Pérez, Winona Oliveros, Pedro G Ferreira, Marta Melé","doi":"10.1186/s13073-025-01485-x","DOIUrl":"10.1186/s13073-025-01485-x","url":null,"abstract":"<p><strong>Background: </strong>Tobacco smoke is the main cause of preventable mortality worldwide. Smoking increases the risk of developing many diseases and has been proposed as an aging accelerator. Yet, the molecular mechanisms driving smoking-related health decline and aging acceleration in most tissues remain unexplored.</p><p><strong>Methods: </strong>Here, we use data from the Genotype-Tissue Expression Project (GTEx) to perform a characterization of the effect of cigarette smoking across human tissues. We perform a multi-tissue analysis across 46 human tissues. Our multi-omics characterization includes analysis of gene expression, alternative splicing, DNA methylation, and histological alterations. We further analyze ex-smoker samples to assess the reversibility of these molecular alterations upon smoking cessation.</p><p><strong>Results: </strong>We show that smoking impacts tissue architecture and triggers systemic inflammation. We find that in many tissues, the effects of smoking significantly overlap those of aging. Specifically, both age and smoking upregulate inflammatory genes and drive hypomethylation at enhancers (odds ratio (OR) = 2). In addition, we observe widespread smoking-driven hypermethylation at target regions of the Polycomb repressive complex (OR = 2), which is a well-known aging effect. Smoking-induced epigenetic changes overlap causal aging CpGs, suggesting that these methylation changes may directly mediate the aging acceleration observed in smokers. Finally, we find that smoking effects that are shared with aging are more persistent over time.</p><p><strong>Conclusion: </strong>Overall, our multi-tissue and multi-omic analysis of the effects of cigarette smoking provides an extensive characterization of the impact of tobacco smoke across tissues and unravels the molecular mechanisms driving smoking-induced tissue homeostasis decline and aging acceleration.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"66"},"PeriodicalIF":10.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12131351/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208405","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}