Identify and validate the genes linked to mitochondrial quality control in colorectal cancer

Mitochondrial quality control (MQC) dysregulation occurs during the development and progression of colorectal cancer (CRC). In this study, we examined MQC-related genes (MQC-RGs) as prognostic markers in CRC. Public CRC datasets and literature-curated MQC-RGs were used to generate single-sample gene set enrichment analysis (ssGSEA)-based MQC scores. Weighted gene co-expression network analysis (WGCNA) was used to identify correlated genes, which were subsequently filtered through differential expression analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression to build and validate a prognostic signature. Mechanisms were investigated through gene set enrichment analysis, immune infiltration analysis, immune therapeutic response prediction, drug prediction/sensitivity analyses, and RT-qPCR. The prognostic genes GIMAP1, SIGLEC1, FCGR2B, C1orf162, VSIG4, P2RY13, and SLAMF1 were identified using an MQC-linked immune co-expression module. The seven-gene risk model stratified patients into groups with significantly different survival outcomes and showed modest time-dependent discriminatory performance. However, adding the risk score to clinical factors did not improve overall discrimination (C-index: 0.785 vs. 0.789; ΔC-index = − 0.004). Enrichment analysis indicated that high-risk CRC cases were markedly enriched in the focal adhesion pathway. Immune cell infiltration levels varied significantly across 20 immune cell types between the distinct risk groups. The prognostic genes broadly exhibited positive correlations with multiple infiltrating immune cell types, including regulatory T cells ( p < 0.001). Patients in the high-risk group demonstrated increased immune barrier function, more severe T-cell dysfunction, and greater overall potential for immune evasion. In addition, four putative therapeutic drugs were predicted based on the prognostic genes. The high-risk cohort showed greater predicted sensitivity to a Trk kinase inhibitor and an IGF1R inhibitor. RT-qPCR analysis revealed a marked decrease in the expression levels of GIMAP1, FCGR2B, and VSIG4 in CRC samples. We identified a seven-gene signature transcriptionally linked to MQC activity in CRC, providing important insight into its potential prognostic and immunological relevance in this disease.