Exploring Autophagy-Related Gene Expression in Hepatocellular Carcinoma via TCGA, GEPIA2, and HPA Databases: Implications for Prognosis.

Objective: This study aimed to identify autophagy-related genes (ARGs) with prognostic significance in hepatocellular carcinoma (HCC) using bioinformatics and survival analysis. Materials and Methods: ARGs were sourced from multiple references, including the Human Autophagy Database (HADb), relevant literatures, the Gene Set Enrichment Analysis (GSEA), and a final list was confirmed after eliminating duplicate entries. Differential expression analysis between normal and tumor tissues relied on data from The Cancer Genome Atlas (TCGA). Subsequently, the univariate and multivariate Cox regression analysis, along with the Kaplan-Meier survival analysis, were conducted to identify survival-associated genes. These findings were cross-validated using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database and the Human Protein Atlas (HPA) database. Furthermore, expression levels of randomly selected ARGs were validated in HCC and normal cell lines using Real-time quantitative PCR (RT-qPCR), confirming bioinformatics findings. Results: 41 ARGs were pinpointed. The bioinformatics analysis revealed elevated expression levels of these genes in HCC tissues compared to normal tissues. Notably, mRNA expression levels of ARGs were markedly higher in the tumor tissue samples than in the normal liver tissue samples. This observation was corroborated by data from the GEPIA2 and HPA databases, except for Conclusion: This study showed that the 41 obtained ARGs, such as