Hepatocellular carcinoma (HCC) is one of the global leading lethal tumors. Pyroptosis has recently been defined as an inflammatory programmed cell death, which is closely linked to cancer progression. However, the significance of pyroptosis-related genes (PRGs) in the prognosis of HCC remains elusive.
RNA sequencing (RNA-seq) data of HCC cases and their corresponding clinical information were collected from the Cancer Genome Atlas (TCGA) database, and differential PRGs were explored. The prognostic PRGs were analyzed with univariate COX regression and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to build a prognostic model in the TCGA training cohort. The predictive model was further validated in the TCGA test cohort and ICGC validation cohort. Differential gene function and associated pathway analysis were performed by Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG). Single-sample gene set enrichment analysis (ssGSEA) was used to identify distinct immune cell infiltration. The mRNA and protein expression of prognostic PRGs was examined by quantitative RT-qPCR and immunohistochemistry.
We identified 46 PRGs that were differentially expressed between normal and HCC tissues in a TCGA cohort, and HCC patients could be well categorized into two clusters associated with distinct survival rates based on expression levels of the PRGs. A three-PRG prognostic model comprising
The three-PRG signature (CHMP4A, HMGB1, and PLK1) could act as an independent factor to predict the prognosis of HCC patients, which would shed light upon a potent therapeutic strategy for HCC treatment.