Exploring the prognostic value of N4-acetylcytosine- modified genes in colorectal cancer using transcriptomics combined with single-cell data

Background Colorectal cancer (CRC) is a malignant tumor of the colon or rectal mucosal epithelial cells. Emerging evidence indicates that N4-acetylcytosine (ac4C) modification potentially contributes to disease pathogenesis and progression, yet the underlying molecular mechanisms warrant further investigation. Elucidating ac4C-associated prognostic biomarkers and their regulatory networks in colorectal cancer (CRC) represents a critical research priority. Methods A cross-analysis was performed between differentially expressed genes (DEGs) identified between CRC and control samples and N4-acetylcytosine modification-related genes (ac4CMRGs) to identify candidate genes. Prognostic gene candidates were identified through univariate Cox proportional hazards regression coupled with Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. These candidates were subsequently integrated to develop a risk stratification model, enabling classification of CRC specimens into high-risk group (HRG) versus low-risk group (LRG). Comparative analyses encompassed pathway enrichment profiles, immune infiltration landscapes, and chemotherapeutic response patterns between risk stratifications. Single-cell resolution analysis was employed to delineate pivotal cell populations, complemented by intercellular communication networks and differentiation trajectory inference. Results Transcriptomic profiling revealed 12,998 differentially expressed genes, yielding 7 ac4C-related prognostic signatures (CCNF, TKT, SIX2, SEZ6L2, CLU, DMPK, TNNT1) for risk model construction. Pathway enrichment demonstrated HRG predominance in focal adhesion-associated processes, whereas LRG exhibited ribosomal pathway activation. Six distinct immune cell subsets displayed differential infiltration between risk categories. Epithelial, endothelial, fibroblastic, and smooth muscle compartments emerged as critical regulators during CRC advancement, manifesting dynamic expression trajectories of the 7-gene signature across cellular differentiation continua. Conclusion This study obtained seven prognostic genes (such as CCNF, TKT) and four key cell types, providing new insights into potential therapeutic strategies for CRC.