Ontology highlight
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
SUBMITTER: Zhu W
PROVIDER: S-EPMC9482539 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature