Cell-type deconvolution analysis identifies cancer-associated myofibroblast component as a poor prognostic factor in multiple cancer types

• Published in: Oncogene 2021-07, Vol.40 (28), p.4686-4694
• Main Authors: Li, Bingrui, Pei, Guangsheng, Yao, Jun, Ding, Qingqing, Jia, Peilin, Zhao, Zhongming
• Format: Article
• Language: English
• Subjects: 101/47; 38/39; 45/41; 45/61; 631/61/212/2019; 631/67/327; 631/67/69; Antineoplastic drugs; Apoptosis; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Cancer; Cancer-Associated Fibroblasts - metabolism; Cancer-Associated Fibroblasts - pathology; Cell Biology; Drug resistance; Extracellular matrix; Fibroblasts; Gene Expression Regulation, Neoplastic; Genetic aspects; Genomes; Human Genetics; Humans; Identification and classification; Inflammation; Internal Medicine; Medical prognosis; Medicine; Medicine & Public Health; Myofibroblasts - metabolism; Myofibroblasts - pathology; Neoplasms - drug therapy; Neoplasms - genetics; Neoplasms - pathology; Oncology; Patients; Prediction models; Prognosis; Survival analysis; Tumor microenvironment; Tumor Microenvironment - genetics
• ISSN: 0950-9232; 1476-5594; 1476-5594
• DOI: 10.1038/s41388-021-01870-x

Cancer-associated fibroblasts (CAFs) constitute a prominent component of the tumor microenvironment and play critical roles in cancer progression and drug resistance. Although recent studies indicate CAFs may consist of several CAF subtypes, the breadth of CAF heterogeneity and functional roles of CAF subtypes in cancer progression remain unclear. In this study, we implemented a cell-type deconvolutional approach to comprehensively characterize cell-type alternations across 18 cancer types from The Cancer Genome Atlas (TCGA). Pan-cancer survival analysis using deconvoluted CAF subtypes revealed myofibroblastic CAF (myCAF) composition as a poor prognostic factor in nine cancer types. Patients with higher myCAF compositions tend to have worse response to six antineoplastic drugs predicted by a lncRNA-based Elastic Net prediction model (LENP). In addition, integrative mutational analysis identified 14 and 413 genes associated with the differentiation degree of myCAF and inflammatory CAF (iCAF), respectively, with significant enrichment of genes involved in fibroblast and extracellular matrix (ECM)-related pathways. In summary, our findings systematically illustrated the complex roles of CAF subtypes in patient prognosis and drug response, and identified putative driver genes in CAF-subtype differentiation. These results provided novel therapeutic perspectives for targeting CAF subtypes in tumor microenvironment and arranging treatment scheme based on the CAF compositions in different cancer types.