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Background: Autophagy regulates many cell functions related to cancer, ranging from cell proliferation and angiogenesis to metabolism. Due to the close relationship between autophagy and tumors, we investigated the predictive value of autophagy-related genes. Methods: Data from patients with hepatocellular carcinoma were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. A regression analysis of differentially expressed genes was performed. Based on a prognostic model, patients were divided into a high-risk or low-risk group. Kaplan-Meier survival analyses of patients were conducted. The immune landscapes, as determined using single-sample gene set enrichment analysis (ssGSEA), exhibited different patterns in the two groups. The prognostic model was verified using the ICGC database and clinical data from patients collected at Zhongnan Hospital. Based on the results of multivariate Cox regression analysis, 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/inosine monophosphate (IMP) cyclohydrolase (ATIC) had the largest hazard ratio, and thus we studied the effect of ATIC on autophagy and tumor progression by performing in vitro and in vivo experiments. Results: Fifty-eight autophagy-related genes were differentially expressed (false discovery rate (FDR)<0.05, log2 fold change (logFC)>1); 23 genes were related to the prognosis of patients. A prognostic model based on 12 genes (ATG10, ATIC, BIRC5, CAPN10, FKBP1A, GAPDH, HDAC1, PRKCD, RHEB, SPNS1, SQSTM1 and TMEM74) was constructed. A significant difference in survival rate was observed between the high-risk group and low-risk group distinguished by the model (P<0.001). The model had good predictive power (area under the curve (AUC)>0.7). Risk-related genes were related to the terms type II IFN response, MHC class I (P<0.001) and HLA (P<0.05). ATIC was confirmed to inhibit autophagy and promote the proliferation, invasion and metastasis of liver cancer cells through the AKT/Forkhead box subgroup O3 (FOXO3) signaling pathway in vitro and in vivo. Conclusions: The prediction model effectively predicts the survival time of patients with liver cancer. The risk score reflects the immune cell features and immune status of patients. ATIC inhibits autophagy and promotes the progression of liver cancer through the AKT/FOXO3 signaling pathway.
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