Identification of a pyroptosis-related gene prognostic signature in patients with hepatocellular carcinoma.

BACKGROUND

Pyroptosis has been recently identified as a hallmark of cancer biology; however, the potential of pyroptosis-related genes (PRGs) as prognostic markers has not been fully elucidated in hepatocellular carcinoma (HCC). The aim of this study was to develop a PRG-associated risk signature for prediction prognosis in patients with HCC.

METHODS

We identified 35 PRGs from the published literature, and pyroptosis subtypes were identified through bioinformatics methods. The risk score model was established by applying least absolute shrinkage and selection operator (LASSO) Cox regression method in The Cancer Genome Atlas (TCGA) cohort and validated in International Cancer Genome Consortium (ICGC) datasets. Additionally, immune infiltration, enriched pathways, and genomic alterations were compared between the high- and low-risk score subgroups. Finally, a nomogram containing the pyroptosis risk score and other prognosis-related clinical factors was developed for predicting the overall survival of patients with HCC.

RESULTS

Based on the expression profile of PRGs, we determined two pyroptosis-related subtypes (cluster A and cluster B) of HCC associated with different immune characteristics and significantly different prognoses. The risk score model showed that upregulation of and was associated with poor overall survival (OS), while high expression of was associated with good prognosis. Compared with group with a lower risk score, the group with a high risk score had worse prognosis (P<0.001) and a high level of immune cell infiltration. Functional analysis indicated that the highly expressed genes in the high-risk group were mainly enriched in various signaling pathways, while the genes with low expression in the high-risk group were mainly enriched in different biochemical metabolic translations. Genomic alterations in high-risk and low-risk populations suggested that mutations in the gene are highly associated with pyroptosis in patients with HCC. A nomogram including risk score and TNM stage demonstrated good prognostic ability in predicting 1-year, 3-year, and 5-year OS.

CONCLUSIONS

We developed and verified a prognostic risk model based on PRGs for patients with HCC, which may provide a robust tool for predicting outcomes in this setting.