Identification of the entosis-related prognostic signature and tumour microenvironment in hepatocellular carcinoma on the basis of bioinformatics analysis and experimental validation

Liver cancer ranks among the deadliest cancers worldwide. Entosis, a recently uncovered method of cell death, has not yet been fully explored for its relevance to HCC. A bioinformatics analysis was performed to determine the expression and mutational landscapes of Entosis-related genes (ERGs). A subset of differentially expressed Entosis-related genes (DEERGs) was generated. A risk model for entosis was subsequently constructed employing LASSO and Cox regression methodologies. The correlations among ERGs, genes associated with risk, the developed risk model, and the immune context of the tumour were explored. Furthermore, the study investigated the varying drug sensitivities between high-risk and slight-risk patient groups. The expression patterns of four pivotal risk genes were delineated via qRT‒PCR and WB. A prognostic model comprising four DEERGs (KIF18A, SPP1, LCAT and TRIB3) was developed. The ability of this model to predict the survival outcomes of patients with HCC was confirmed through receiver operating characteristic curve analysis. Patients were grouped according to their risk assessments, revealing that the low-risk population demonstrated a more favourable survival outcome than did the high-risk population. The high-risk population presented reduced tumour stroma, immune and ESTIMATE scores, along with an increased proportion of cancer stem cells and tumour mutation burden. Additionally, a connection between the risk model and the responsiveness of various chemotherapy drugs as well as the efficacy of immunotherapies in patients was noted. These findings provide significant guidance for the development of targeted clinical treatment strategies. qRT‒PCR and WB analysis revealed that the gene expression of KIF18A and SPP1 were elevated in HCCLM3 cells compared with that in THLE2 cells; whereas, the expression level of LCAT and TIRB3 was decreased. The four genes KIF18A, SPP1, LCAT and TRIB3 could effectively predict the survival prognosis of patients with liver cancer. KIF18A and SPP1 were elevated in HCC tissues compared with that in THLE2 cells.