Abstract
Given the poor prognosis of patients with hepatocellular carcinoma (HCC), it is crucial to investigate possible new biomarkers to aid in prognostication and customised treatment. Accordingly, we analysed differentially expressed anoikis- and autophagy-related genes (DE-AARGs) associated with poor outcomes in actual cases of HCC. Analysis of differentially expressed genes (DEGs) was performed based on mRNA expression patterns and clinicopathological information found in the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database. Further validation of TCGA results was performed using the International Cancer Genome Consortium database. AARGs signatures were constructed by applying Univariate COX regression and the Least Absolute Shrinkage and Selection Operator method. We identified 13 AARGs, of which 9 showed significant associations with overall survival. Three AARGs (BIRC5, MAPK3, and BAK1) were selected to establish an AARGs signature. We assessed the prognostic capacity of the AARGs signature through various statistical methods. The molecular mechanisms underpinning this phenomenon were further studied using Gene Set Enrichment Analyses (GSEA). The prognostic ability of the signature was also examined in terms of clinical characteristics, immune landscape, immune checkpoint-blocking response, stemness, and chemotherapy response. Immunohistochemical staining was used to compare the protein expression levels of AARGs between normal liver tissue and HCC tissues. The high-risk group had higher tumour staging, shorter survival time, and worse prognosis than the low-risk group. In addition, high-risk patients showed inhibition of anoikis, a high autophagy index, and a suppressed immune system. The nomogram showed a strong prognostic capability for predicting overall survival in patients with HCC. With this study, a new AARGs-based signature has been developed to reliably predict patient prognosis for HCC.