AUTHOR=Chen Xingte , Wang Lei , Hong Liang , Su Zhixiong , Zhong Xiaohong , Zhou Han , Zhang Xueqing , Wu Junxin , Shao Lingdong 

TITLE=Identification of Aging-Related Genes Associated With Clinical and Prognostic Features of Hepatocellular Carcinoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.661988

DOI=10.3389/fgene.2021.661988

ISSN=1664-8021

ABSTRACT=Background: Aging is a well-studied concept, but no studies have comprehensively analyzed the association between aging-related genes (AGs) and hepatocellular carcinoma (HCC) prognosis. 
Methods: Interaction gene candidates were selected from differentially expressed genes and prognostic genes in The Cancer Genome Atlas (TCGA) database. A gene risk score was established using the least absolute shrinkage and selection operator (LASSO) regression analysis for overall survival prediction, which was validated using the data from the International Cancer Genome Consortium (ICGC) database. Functional analysis was also conducted using gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis, and immune, microenvironment, and tumor stemness analyses. 
Results: Initially, 72 AGs were screened from TCGA as differentially expressed genes between normal and tumor tissues and as genes associated with HCC prognosis. Then, seven AGs were identified using the LASSO regression analysis. A risk score was constructed in the training set with the seven AGs (POLA1, CDK1, SOCS2, HDAC1, MAPT, RAE1, and EEF1E1) and was validated in the ICGC set (P < 0.05). Patients with high risk scores also had lower tumor differentiation, higher stage, and worse prognosis (all P<0.05). The risk score was also confirmed by multivariate Cox regression analyses in both TCGA and ICGC sets (all P<0.05) to be an independent prognostic factor for HCC. Further analysis showed that a high risk score was correlated with the downregulation of metabolism and tumor immunity.
Conclusion: Based on the current data, we conclude that this risk score could be used as a predictive biomarker for HCC and provide clues for the individualized treatment of HCC patients.