Integrate bulk RNA and single-cell sequencing to identify prognostic genes associated with dietary restriction and circadian rhythm in colorectal cancer and conduct experimental verification

Colorectal cancer (CRC) is an aggressive malignancy with a poor prognosis. Recent research has focused on the impact of dietary restriction (DR) and circadian rhythm (CR) on cancer; however, the roles of DR-related genes (DRRGs) and CR-related genes (CRRGs) in CRC remain poorly understood. Bulk RNA and single-cell sequencing data for CRC were retrieved from public databases, while DRRGs and CRRGs were compiled from existing literature. Prognostic genes were identified through univariate Cox regression and machine learning approaches. A prognostic risk model and a clinically applicable nomogram were developed. Differences in functional pathways, tumor microenvironment characteristics, and drug sensitivities were analyzed between the high-risk cohort (HRC) and the low-risk cohort (LRC). The expression of prognostic genes was assessed at the single-cell level and validated in clinical samples. Five prognostic genes, namely SOCS3, MMP3, SLC3A1, FABP4, and SERPINE1, were identified. Both the model and nomogram demonstrated strong predictive power. LRC was primarily associated with DNA replication pathways, whereas HRC exhibited higher ESTIMATE, immune, stromal, and TIDE scores, with significant differences across 24 immune cell types. Sensitivity to 61 drugs was observed in HRC, while 56 drugs were sensitive to LRC. Single-cell analysis highlighted fibroblasts as key cells, with dynamic expression of FABP4 and SOCS3 during differentiation. With the exception of SERPINE1, prognostic genes showed differential expression in clinical samples. The risk model effectively predicts CRC prognosis and emphasizes the prognostic relevance of DRRGs and CRRGs, offering novel insights for personalized CRC therapy.