Qiqi Xu, Changjiang Yang, Jingyuan Ning, Yunze Niu, Xuesong Zhao, Long Zhao, Caihong Wang, Shan Wang, Yingjiang Ye, Zhanlong Shen
{"title":"SMOC2高肌成纤维细胞癌相关成纤维细胞驱动原发性纤毛相关肿瘤微环境重塑和不良预后","authors":"Qiqi Xu, Changjiang Yang, Jingyuan Ning, Yunze Niu, Xuesong Zhao, Long Zhao, Caihong Wang, Shan Wang, Yingjiang Ye, Zhanlong Shen","doi":"10.21147/j.issn.1000-9604.2025.04.12","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Advanced gastric cancer remains highly refractory to therapy, with limited immunotherapy efficacy due to tumor microenvironment heterogeneity. Primary cilia, microtubule-based organelles involved in tumor progression, remain insufficiently explored in gastric cancer. This study aimed to define primary cilia subtypes and establish prognostic signatures for personalized treatment strategies.</p><p><strong>Methods: </strong>Bulk transcriptomic data from over 1,500 gastric cancer samples were integrated to define distinct primary cilia subtypes. A primary ciliary phenotype-associated signature (PCS) was established using a multi-machine learning survival framework incorporating ten algorithms. The prognostic predictive value and immunotherapy response prediction capability of PCS were validated across multiple independent cohorts. Single-cell RNA sequencing analysis was performed to identify cellular populations associated with high-PCS phenotype. Causal weighted gene co-expression network analysis (WGCNA) was employed to identify driving factors, followed by functional validation through cell culture experiments and xenograft models.</p><p><strong>Results: </strong>Two distinct primary cilia subtypes were identified and validated across all cohorts, with C2 patients exhibiting significantly worse overall survival compared to C1 patients. PCS demonstrated robust predictive value for both prognosis and immunotherapy response, with superior accuracy compared to existing models across multiple validation cohorts. High-PCS patients showed reduced tumor purity, increased stromal cell infiltration, and poor response to immunotherapy. Single-cell analysis revealed that fibroblasts had the highest PCS scores and identified a novel secreted modular calcium-binding protein 2 (<i>SMOC2</i>)<sup>high</sup> myofibroblastic cancer-associated fibroblast (mCAF) population as the key driver of high-PCS phenotype. Functional experiments confirmed that <i>SMOC2</i> knockdown significantly suppressed gastric cancer cell proliferation, migration, and invasion, while promoting mCAF-to-inflammatory cancer-associated fibroblasts (iCAF) transition.</p><p><strong>Conclusions: </strong>PCS serves as a robust prognostic biomarker for gastric cancer patients. Additionally, targeting <i>SMOC2</i> <sup>high</sup> mCAFs represents a potential therapeutic strategy for patients with high-PCS gastric cancer.</p>","PeriodicalId":9882,"journal":{"name":"Chinese Journal of Cancer Research","volume":"37 4","pages":"603-623"},"PeriodicalIF":6.3000,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12444353/pdf/","citationCount":"0","resultStr":"{\"title\":\"<i>SMOC2</i> <sup>high</sup> myofibroblastic cancer-associated fibroblast drives primary cilia-associated tumor microenvironment remodeling and poor prognosis in gastric cancer.\",\"authors\":\"Qiqi Xu, Changjiang Yang, Jingyuan Ning, Yunze Niu, Xuesong Zhao, Long Zhao, Caihong Wang, Shan Wang, Yingjiang Ye, Zhanlong Shen\",\"doi\":\"10.21147/j.issn.1000-9604.2025.04.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Advanced gastric cancer remains highly refractory to therapy, with limited immunotherapy efficacy due to tumor microenvironment heterogeneity. Primary cilia, microtubule-based organelles involved in tumor progression, remain insufficiently explored in gastric cancer. This study aimed to define primary cilia subtypes and establish prognostic signatures for personalized treatment strategies.</p><p><strong>Methods: </strong>Bulk transcriptomic data from over 1,500 gastric cancer samples were integrated to define distinct primary cilia subtypes. A primary ciliary phenotype-associated signature (PCS) was established using a multi-machine learning survival framework incorporating ten algorithms. The prognostic predictive value and immunotherapy response prediction capability of PCS were validated across multiple independent cohorts. Single-cell RNA sequencing analysis was performed to identify cellular populations associated with high-PCS phenotype. Causal weighted gene co-expression network analysis (WGCNA) was employed to identify driving factors, followed by functional validation through cell culture experiments and xenograft models.</p><p><strong>Results: </strong>Two distinct primary cilia subtypes were identified and validated across all cohorts, with C2 patients exhibiting significantly worse overall survival compared to C1 patients. PCS demonstrated robust predictive value for both prognosis and immunotherapy response, with superior accuracy compared to existing models across multiple validation cohorts. High-PCS patients showed reduced tumor purity, increased stromal cell infiltration, and poor response to immunotherapy. Single-cell analysis revealed that fibroblasts had the highest PCS scores and identified a novel secreted modular calcium-binding protein 2 (<i>SMOC2</i>)<sup>high</sup> myofibroblastic cancer-associated fibroblast (mCAF) population as the key driver of high-PCS phenotype. Functional experiments confirmed that <i>SMOC2</i> knockdown significantly suppressed gastric cancer cell proliferation, migration, and invasion, while promoting mCAF-to-inflammatory cancer-associated fibroblasts (iCAF) transition.</p><p><strong>Conclusions: </strong>PCS serves as a robust prognostic biomarker for gastric cancer patients. Additionally, targeting <i>SMOC2</i> <sup>high</sup> mCAFs represents a potential therapeutic strategy for patients with high-PCS gastric cancer.</p>\",\"PeriodicalId\":9882,\"journal\":{\"name\":\"Chinese Journal of Cancer Research\",\"volume\":\"37 4\",\"pages\":\"603-623\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12444353/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chinese Journal of Cancer Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21147/j.issn.1000-9604.2025.04.12\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Journal of Cancer Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21147/j.issn.1000-9604.2025.04.12","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
SMOC2high myofibroblastic cancer-associated fibroblast drives primary cilia-associated tumor microenvironment remodeling and poor prognosis in gastric cancer.
Objective: Advanced gastric cancer remains highly refractory to therapy, with limited immunotherapy efficacy due to tumor microenvironment heterogeneity. Primary cilia, microtubule-based organelles involved in tumor progression, remain insufficiently explored in gastric cancer. This study aimed to define primary cilia subtypes and establish prognostic signatures for personalized treatment strategies.
Methods: Bulk transcriptomic data from over 1,500 gastric cancer samples were integrated to define distinct primary cilia subtypes. A primary ciliary phenotype-associated signature (PCS) was established using a multi-machine learning survival framework incorporating ten algorithms. The prognostic predictive value and immunotherapy response prediction capability of PCS were validated across multiple independent cohorts. Single-cell RNA sequencing analysis was performed to identify cellular populations associated with high-PCS phenotype. Causal weighted gene co-expression network analysis (WGCNA) was employed to identify driving factors, followed by functional validation through cell culture experiments and xenograft models.
Results: Two distinct primary cilia subtypes were identified and validated across all cohorts, with C2 patients exhibiting significantly worse overall survival compared to C1 patients. PCS demonstrated robust predictive value for both prognosis and immunotherapy response, with superior accuracy compared to existing models across multiple validation cohorts. High-PCS patients showed reduced tumor purity, increased stromal cell infiltration, and poor response to immunotherapy. Single-cell analysis revealed that fibroblasts had the highest PCS scores and identified a novel secreted modular calcium-binding protein 2 (SMOC2)high myofibroblastic cancer-associated fibroblast (mCAF) population as the key driver of high-PCS phenotype. Functional experiments confirmed that SMOC2 knockdown significantly suppressed gastric cancer cell proliferation, migration, and invasion, while promoting mCAF-to-inflammatory cancer-associated fibroblasts (iCAF) transition.
Conclusions: PCS serves as a robust prognostic biomarker for gastric cancer patients. Additionally, targeting SMOC2high mCAFs represents a potential therapeutic strategy for patients with high-PCS gastric cancer.
期刊介绍:
Chinese Journal of Cancer Research (CJCR; Print ISSN: 1000-9604; Online ISSN:1993-0631) is published by AME Publishing Company in association with Chinese Anti-Cancer Association.It was launched in March 1995 as a quarterly publication and is now published bi-monthly since February 2013.
CJCR is published bi-monthly in English, and is an international journal devoted to the life sciences and medical sciences. It publishes peer-reviewed original articles of basic investigations and clinical observations, reviews and brief communications providing a forum for the recent experimental and clinical advances in cancer research. This journal is indexed in Science Citation Index Expanded (SCIE), PubMed/PubMed Central (PMC), Scopus, SciSearch, Chemistry Abstracts (CA), the Excerpta Medica/EMBASE, Chinainfo, CNKI, CSCI, etc.