RESUMO
Autophagy affects the development, progression, and prognosis of various cancers including pancreatic cancer. To develop an autophagy-related prognostic model of pancreatic cancer, we systematically analyzed gene expression profile from The Cancer Genome Atlas and Genotype-Tissue Expression. Ten autophagy-relevant genes with potential prognostic values were identified, based on which a prognostic model was constructed. We divided patients into a high- and a low-risk group with this model. Time-dependent receiver operating characteristic and Kaplan-Meier curves were conducted to evaluate the accuracy of the model. The Area Under Curvevalues of this model at 12, 18, and 24 months were 0.76, 0.73, and 0.78, respectively. The model was further validated in two Gene Expression Omnibus datasets. Gene set enrichment analysis and Cibersort were applied to analyze immune infiltration patterns and immune checkpoint blockade (ICB) molecules. The expression of ICB molecules, such as PD-L1 and PD1, presented significant correlation with the risk score. In conclusion, the risk score model established herein has been proved to be robust for evaluating the prognosis of pancreatic cancer and facilitate to improve the efficacy of ICB.
