Role of telomere maintenance genes as a predictive biomarker for colorectal cancer immunotherapy response and prognosis - Zhikai Wang; Chunyan Zhao; Yifen Huang; Chong Li (Biomolecules & Biomedicine)
Colorectal cancer (CRC) represents a significant global health challenge. Although telomere maintenance plays a crucial role in tumorigenesis, the prognostic value and immunotherapeutic relevance of telomere maintenance genes (TMGs) in CRC remain poorly understood. In this study, relevant data were retrieved from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. TMG scores were calculated using the single-sample gene set enrichment analysis (ssGSEA) method, and TMGs associated with prognosis were subsequently identified. TCGA-CRC samples were classified into subtypes via consensus clustering (ConsensusClusterPlus). A risk prediction model was then constructed using univariate and Lasso Cox regression analyses. Survival analysis was performed using Kaplan–Meier curves generated with the survival package. Key genes were validated in vitro using cellular models. Immune cell infiltration was evaluated through ssGSEA, TIMER, and MCP-Counter tools, and chemotherapy responses were predicted using the pRRophetic package. From 28 prognosis-related TMGs, two distinct CRC subtypes were established, with subtype C1 demonstrating more favorable clinical outcomes. Additionally, a risk model incorporating seven TMG-related genes (CDC25C, CXCL1, RTL8C, FABP4, ITLN1, MUC12, and ERI1) was developed for CRC prognosis. Differential mRNA expression levels of these genes were confirmed between CRC cell lines and normal control cells. Furthermore, silencing MUC12 suppressed CRC cell migration and invasion in vitro. Importantly, CRC patients classified as low-risk exhibited superior responses to immunotherapy, whereas high-risk patients showed increased sensitivity to conventional anti-cancer treatments. This study represents the first systematic evaluation of TMGs in CRC prognosis and immunotherapy, providing novel insights that could inform personalized therapeutic strategies.