A comprehensive multi-omics analysis identifies a robust scoring system for cancer-associated fibroblasts and intervention targets in colorectal cancer

• DOI: 10.1007/s00432-023-05548-7
• Publication Date: 2024-03-13T08:32:07Z
• Authors: Feng Wang; Zhenlin Li; Tianlei Xu; Qian Zhang; Tianyi Ma; Sijia Li; Xiaohui Wang
• Keywords: Hematology

Abstract Background Cancer-associated fibroblasts (CAF) play a critical role in promoting tumor growth, metastasis, and immune evasion. While numerous studies have investigated CAF, there remains paucity of research on their clinical application colorectal cancer (CRC). Methods In this study, we collected differentially expressed genes between CAF normal (NF) from previous CRC studies, utilized machine learning analysis to differentiate two distinct subtypes CRC. To enable practical application, CAF-related (CAFGs) scoring system was developed based multivariate Cox regression. We then conducted functional enrichment analysis, Kaplan–Meier plot, consensus molecular (CMS) classification, Tumor Immune Dysfunction Exclusion (TIDE) algorithm investigate the relationship CAFGs various biological mechanisms, prognostic value, microenvironment, response checkpoint blockade (ICB) therapy. Moreover, single-cell transcriptomics proteomics analyses been employed validate significance system-related molecules identity function CAF. Results unveiled significant distinctions status prognosis not only clusters, but also across high low groups. Specifically, patients cluster 2 or with scores exhibited higher markers were enriched for pathways such as epithelial–mesenchymal transition (EMT) angiogenesis. addition, score identified risk index correlated poor overall survival (OS), progression-free (PFS), disease-free (DFS), recurrence-free (RFS). High observed advanced stages, CMS4, well lymphatic invasion. Furthermore, elevated CAFG signified suppressive microenvironment characterized by upregulation programmed death-ligand 1 (PD-L1), T-cell dysfunction, exclusion, TIDE score. And can lower rates under ICB Notably, several related function, FSTL1 , IGFBP7 FBN1 . Conclusion constructed robust using multiple cohorts. that could be potential intervention targets patients.