Zhang Lei, Xu Chao, Wang Si-Han, Ge Qin-Wen, Wang Xiao-Wei, Xiao Pan, Yao Qing-Hua
Department of Integrated Chinese and Western Medicine, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China.
The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
Front Genet. 2022 Nov 25;13:1054152. doi: 10.3389/fgene.2022.1054152. eCollection 2022.
Cancer-associated fibroblasts (CAFs) play an important role in the tumorigenesis, immunosuppression and metastasis of colorectal cancer (CRC), and can predict poor prognosis in patients with CRC. The present study aimed to construct a CAFs-related prognostic signature for CRC. The clinical information and corresponding RNA data of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The Estimation of STromal and Immune cells in MAlignant Tumor tissues (ESTIMATES) and xCell methods were applied to evaluate the tumor microenvironment infiltration from bulk gene expression data. Weighted gene co-expression network analysis (WGCNA) was used to construct co-expression modules. The key module was identified by calculating the module-trait correlations. The univariate Cox regression and least absolute shrinkage operator (LASSO) analyses were combined to develop a CAFs-related signature for the prognostic model. Moreover, pRRophetic and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to predict chemosensitivity and immunotherapy response. Human Protein Atlas (HPA) databases were employed to evaluate the protein expressions. ESTIMATES and xCell analysis showed that high CAFs infiltration was associated with adverse prognoses. A twenty-gene CAFs-related prognostic signature (CAFPS) was established in the training cohort. Kaplan-Meier survival analyses reveled that CRC patients with higher CAFs risk scores were associated with poor prognosis in each cohort. Univariate and multivariate Cox regression analyses verified that CAFPS was as an independent prognostic factor in predicting overall survival, and a nomogram was built for clinical utility in predicting CRC prognosis. Patients with higher CAFs risk scores tended to not respond to immunotherapy, but were more sensitive to five conventional chemotherapeutic drugs. In summary, the CAFPS could serve as a robust prognostic indicator in CRC patients, which might help to optimize risk stratification and provide a new insight into individual treatments for CRC.
癌症相关成纤维细胞(CAFs)在结直肠癌(CRC)的肿瘤发生、免疫抑制和转移中起重要作用,并且可以预测CRC患者的不良预后。本研究旨在构建一个与CAFs相关的CRC预后特征。从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)下载了CRC患者的临床信息和相应的RNA数据。应用肿瘤组织中基质和免疫细胞估计(ESTIMATES)和xCell方法从大量基因表达数据评估肿瘤微环境浸润。加权基因共表达网络分析(WGCNA)用于构建共表达模块。通过计算模块-性状相关性确定关键模块。将单变量Cox回归和最小绝对收缩算子(LASSO)分析相结合,开发用于预后模型的与CAFs相关的特征。此外,利用pRRophetic和肿瘤免疫功能障碍与排除(TIDE)算法预测化疗敏感性和免疫治疗反应。使用人类蛋白质图谱(HPA)数据库评估蛋白质表达。ESTIMATES和xCell分析表明,高CAFs浸润与不良预后相关。在训练队列中建立了一个包含20个基因的与CAFs相关的预后特征(CAFPS)。Kaplan-Meier生存分析显示,在每个队列中,CAFs风险评分较高的CRC患者预后较差。单变量和多变量Cox回归分析证实,CAFPS是预测总生存的独立预后因素,并构建了列线图用于临床预测CRC预后。CAFs风险评分较高的患者往往对免疫治疗无反应,但对五种传统化疗药物更敏感。总之,CAFPS可作为CRC患者强有力的预后指标,这可能有助于优化风险分层,并为CRC的个体化治疗提供新的见解。