{"title":"The Impact of SF3B1 Mutations on the Tumor Microenvironment and Response to Immunotherapy","authors":"Kyung-Jin Cho, Byungho Lim","doi":"10.1002/cam4.72318","DOIUrl":null,"url":null,"abstract":"<p>Cancer genomes shape the immune landscape within the tumor microenvironment (TME), thereby influencing host antitumor immunity. Identifying somatic mutations that modulate the TME is critical for selecting patients most likely to benefit from immunotherapy. Here, by integrating a transcriptome-based predictive model with comprehensive genomic analyses, we identified <i>SF3B1</i> splicing factor mutations associated with the response to immune checkpoint inhibitors (ICIs). We systematically evaluated the effects of <i>SF3B1</i> mutations on the TME and ICI response through <i>in silico</i>, in vitro, and in vivo approaches. Comparative analyses of patient genotypes, together with loss- and gain-of-function studies, revealed that <i>SF3B1</i> mutations drive transcriptional reprogramming that enhances ICI responsiveness. To validate these findings in vivo, we established a syngeneic mouse model using immune-resistant B16F10 melanoma cells. SF3B1-mutant tumors, compared with wild-type counterparts, exhibited TME features and immune profiles indicative of an enhanced antitumor immune response, including increased proportions of CD4<sup>+</sup> and CD8<sup>+</sup> T cells and dendritic cells, accompanied by the upregulation of immune effectors. Consistently, mice bearing SF3B1-mutant tumors demonstrated significantly greater tumor regression following anti-PD-1 treatment compared with their wild-type counterparts. These findings establish <i>SF3B1</i> mutations as predictive biomarkers for guiding rational immunotherapy selection in cancer patients.</p>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620285/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cam4.72318","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Cancer genomes shape the immune landscape within the tumor microenvironment (TME), thereby influencing host antitumor immunity. Identifying somatic mutations that modulate the TME is critical for selecting patients most likely to benefit from immunotherapy. Here, by integrating a transcriptome-based predictive model with comprehensive genomic analyses, we identified SF3B1 splicing factor mutations associated with the response to immune checkpoint inhibitors (ICIs). We systematically evaluated the effects of SF3B1 mutations on the TME and ICI response through in silico, in vitro, and in vivo approaches. Comparative analyses of patient genotypes, together with loss- and gain-of-function studies, revealed that SF3B1 mutations drive transcriptional reprogramming that enhances ICI responsiveness. To validate these findings in vivo, we established a syngeneic mouse model using immune-resistant B16F10 melanoma cells. SF3B1-mutant tumors, compared with wild-type counterparts, exhibited TME features and immune profiles indicative of an enhanced antitumor immune response, including increased proportions of CD4+ and CD8+ T cells and dendritic cells, accompanied by the upregulation of immune effectors. Consistently, mice bearing SF3B1-mutant tumors demonstrated significantly greater tumor regression following anti-PD-1 treatment compared with their wild-type counterparts. These findings establish SF3B1 mutations as predictive biomarkers for guiding rational immunotherapy selection in cancer patients.
期刊介绍:
Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas:
Clinical Cancer Research
Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations
Cancer Biology:
Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery.
Cancer Prevention:
Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach.
Bioinformatics:
Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers.
Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.