Abstract
Potassium channel-related genes (PCRGs) play an important role in hepatocellular
carcinoma (HCC) development, recurrence, and immunotherapy tolerance. We aimed
to develop a new prognostic model associated with PCRGs that can be used for
prognosis and immunotherapy prediction in HCC patients. The transcriptional
profiles and clinical data related to HCC were obtained from The Cancer Genome
Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially
expressed PCRGs were identified using the “edgeR” package. Prognostic model
associated with PCRGs were constructed using univariate analysis, least absolute
shrinkage and selection operator (LASSO), and multivariate regression analysis.
The prognostic value of the model was evaluated through Kaplan–Meier (K–M)
survival analysis and receiver operating characteristic (ROC) curves.
Additionally, the tumor immune microenvironment was assessed using single sample
gene set enrichment analysis (ssGSEA) and the CIBERSORT algorithm. Finally,
potential drugs targeting signature genes were predicted. We successfully
constructed a prognostic signature based on PCRGs, and the prognostic results
were superior in the low-risk group. The nomogram demonstrated satisfactory
predictive performance in estimating overall survival (OS) in HCC patients. The
results of immune cell infiltration and predictions of immunotherapy response
revealed that the low-risk group exhibited a more favorable response to
immunotherapy. In addition, signature gene expression was significantly
correlated with antitumor drug sensitivity. In conclusion, the characteristics
of PCRGs serve as valuable tools for accurately assessing the prognosis and
tumor microenvironment of HCC patients. Additionally, PCRGs markers can
facilitate precision therapy in HCC management.
Keywords
hepatocellular carcinoma - potassium channel-related genes - immunotherapy - prognosis