SMOC2 high myofibroblastic cancer-associated fibroblast drives primary cilia-associated tumor microenvironment remodeling and poor prognosis in gastric cancer.

IF 6.3 2区 医学 Q1 ONCOLOGY
Qiqi Xu, Changjiang Yang, Jingyuan Ning, Yunze Niu, Xuesong Zhao, Long Zhao, Caihong Wang, Shan Wang, Yingjiang Ye, Zhanlong Shen
{"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}
引用次数: 0

Abstract

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 SMOC2 high mCAFs represents a potential therapeutic strategy for patients with high-PCS gastric cancer.

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
目的:由于肿瘤微环境的异质性,晚期胃癌的免疫治疗效果有限。原发性纤毛,微管为基础的细胞器,参与肿瘤进展,在胃癌中仍未充分探讨。本研究旨在确定原发性纤毛亚型,并建立个性化治疗策略的预后特征。方法:整合来自1500多个胃癌样本的大量转录组学数据,以确定不同的原发性纤毛亚型。使用包含十种算法的多机器学习生存框架建立了初级纤毛表型相关特征(PCS)。通过多个独立队列验证PCS的预后预测价值和免疫治疗反应预测能力。单细胞RNA测序分析鉴定与高pcs表型相关的细胞群体。采用因果加权基因共表达网络分析(WGCNA)确定驱动因素,然后通过细胞培养实验和异种移植模型进行功能验证。结果:在所有队列中确定并验证了两种不同的原发性纤毛亚型,C2患者的总生存率明显低于C1患者。PCS在预后和免疫治疗反应方面显示出强大的预测价值,与现有模型相比,在多个验证队列中具有更高的准确性。高pcs患者肿瘤纯度降低,基质细胞浸润增加,免疫治疗反应差。单细胞分析显示,成纤维细胞具有最高的PCS评分,并鉴定出一种新的分泌模块化钙结合蛋白2 (SMOC2)高肌成纤维细胞癌症相关成纤维细胞(mCAF)群体是高PCS表型的关键驱动因素。功能实验证实,SMOC2敲低可显著抑制胃癌细胞的增殖、迁移和侵袭,促进mcaf向炎性癌相关成纤维细胞(iCAF)转化。结论:PCS可作为胃癌患者预后的可靠生物标志物。此外,靶向SMOC2高mCAFs是高pcs胃癌患者的潜在治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
9.80%
发文量
1726
审稿时长
4.5 months
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信