Profiles of Acetylation Regulation Genes Contribute to Malignant Progression and Have a Clinical Prognostic Impact on Liver Cancer.

Abstract

Background Several studies have demonstrated that acetylation was involved in the process of liver cancer. This study aimed to establish an effective predictive prognostic model using acetylation regulation genes in liver cancer. Methods Two datasets were downloaded from the Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database. Differentially expressed acetylation regulation genes were identified in the TCGA-LIHC dataset, and then, Gene Ontology (GO) functional annotation analysis was used to investigate the molecular mechanism. After grouping the patients into clusters based on consensus clustering, we explored the correlation between clusters and clinical characteristics. A risk model was constructed by the least absolute shrinkage and selection operator (LASSO) regression analysis to calculate the risk score. Patients were divided into high-risk and low-risk groups according to the risk score using the acetylation regulation genes. Data downloaded from LIRI-JP were used for external validation. Univariate and multivariate Cox regressions were performed to identify independent risk factors. A prognostic nomogram was constructed according to the TCGA-LIHC dataset. The effect of HDAC11 expression on the proliferation and migration of liver cancer was detected by the CCK-8 method and cell scratch test, respectively. Results Eleven of 29 acetylation regulation genes were identified as upregulated differentially expressed genes. Go enrichment analysis showed that they were involved in “protein and histone deacylation and deacetylation.” Patients were categorized into two clusters according to the expression of 29 acetylation regulation genes. Compared with cluster 2, cluster 1 correlated with shorter overall survival (OS) and higher expression. Stage, T stage, grade, gender, age, and follow-up state were significantly different between two clusters. Pathways involved in DNA repair were significantly enriched in cluster 1. The risk score was calculated by HDAC1, HDAC2, HDAC4, HDAC11, HAT1, and SIRT6. Patients in the high-risk group had a worse prognosis in both datasets. Risk score was not only an independent prognostic marker but could also predict the clinicopathological features of liver cancer. A nomogram containing risk score, T stage, and M stage was built to predict overall survival. After transfection with HDAC11 overexpression plasmid, the proliferation ability of HepG2 cells increased, while the migration ability had no change. Conclusions Our findings suggested that acetylation regulation genes contribute to malignant progression and have a clinical prognostic impact on liver cancer.