Identification of a pyroptosis-related long noncoding RNA signature for determining the prognosis and immune status of hepatocellular carcinoma patients.

BACKGROUND

Despite improvements in cancer screening and diagnosis, hepatocellular carcinoma (HCC) is still diagnosed at an advanced stage, and the prognosis is worse than that of early HCC patients. Therefore, better molecular markers and therapeutic targets in HCC are required.

OBJECTIVES

We investigated the predictive value of pyroptosis-related long noncoding RNAs (lncRNAs) in HCC and the effects of these lncRNAs on the immune microenvironment of HCC.

MATERIAL AND METHODS

RNA sequencing data of HCC patients were extracted from The Cancer Genome Atlas (TCGA) database to identify differentially expressed pyroptosis-related lncRNAs related to overall survival (OS). A model was established to verify the character of pyroptosis-associated lncRNAs in the tumor microenvironment, and their prognostic value was evaluated.

RESULTS

A total of 721 PR lncRNAs were identified based on the analysis of the TCGA database. Univariate Cox analysis revealed 37 survival-related PRlncRNAs with prognostic values. As a result of least absolute shrinkage and selection operator (LASSO) regression analysis, 'ELFN-AS1', AC099850.3, AC073389.3, 'HPN-AS1', AC009283.1, and AL139289.1 showed prognostic value. Kaplan-Meier analysis indicated that the OS of the high-risk set was worse than those of the low-risk set in both the training and testing cohorts. Univariate and multivariate analyses revealed that the risk score was a better independent prognostic factor than the stage. The precision of the lncRNA signature was confirmed using receiver operating characteristic curve (ROC) analysis. Immuneand metabolism-related pathways were enriched in both the lowand high-risk groups. Gene set enrichment analysis suggested that the identified lncRNAs regulate HCC tumorigenesis and prognosis by modulating metabolism. Various algorithms were used to confirm the significant differences in immune cells between these 2 groups.

CONCLUSIONS

These findings could contribute to the development and validation of favorable biomarkers, improve the prognosis and survival of HCC, and help in developed individualized treatment plans for HCC.