An aging-related gene signature to predict the prognosis of hepatocellular carcinoma

Abstract

Aging increases the susceptibility of various diseases, including hepatocellular carcinoma (HCC). This study aimed to establish an aging-related prognostic model for HCC and to investigate the role of aging-related genes in HCC progression. Transcriptome and clinical information of HCC cases were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Aging-related prognostic genes were identified through univariate Cox regression analysis, protein-protein interaction analysis, and least absolute shrinkage and selection operator (LASSO) analysis. An aging-related risk signature was then constructed, including LDHA, MMP12, ATAD3A, CD8A, TPI1, CST3, and TPM1. The risk score was inversely associated with the overall survival of patients with HCC and correlated well with known prognostic factors. The area under the curve of 1-, 3-, and 5-year survival in the training dataset was 0.83, 0.83, and 0.84, respectively. Univariate and multivariate cox regression analysis verified that the aging-related risk signature independently predicted the overall survival in HCC. To increase the clinical utility of the prognostic model, a nomogram was developed by incorporating the risk score with key clinical features. Finally, single-cell transcriptomes of HCC were analyzed to elucidate the expression pattern of the prognostic genes across different tissues, pathologic stages, and cell types. Collectively, the aging-related prognostic model shed light on HCC pathogenesis and held potential for optimizing the management of HCC.