Purpose: Autophagy has a critical involvement in the initiation and progression of various cancers, including colorectal cancer (CRC). The feasibility of using autophagy-related genes as prognostic tools for CRC patients is yet to be determined.
Methods: We gathered RNA sequencing data and clinical details for colorectal cancer (CRC) from TCGA as our training set and used the GSE39582 dataset from the GEO database for validation. Autophagy-related genes (ARGs) were obtained from the Human Autophagy Database. Using the R limma package, we identified differentially expressed ARGs (DAGs) in TCGA's CRC samples. Prognostic DAGs signatures were established via Cox and LASSO Cox regression analyses. CRC patients were divided into high-risk and low-risk groups based on median risk scores, with their prognosis assessed through Kaplan-Meier, ROC, and calibration curve analyses. The CIBERSORT algorithms were employed to examine the association between immune status and the signature. Immunohistochemistry assays were conducted to evaluate the prognostic significance of these DAGs in CRC samples.
Results: Our study developed a signature consisting of 11 key prognostic DAGs (CANX, NRG1, WIPI1, EIF2AK3, WDR45, PELP1, ULK1, WIPI2, DAPK1, ULK3, MAP1LC3C), revealing that high-risk patients had markedly reduced overall survival compared to low-risk ones. This signature, independently predictive after adjusting for clinical factors, was validated using the GSE39582 dataset and showed a strong correlation with immune status in TCGA CRC samples.
Conclusion: The autophagy-related signature independently predicts CRC prognosis and guides immunotherapy strategies.