Open AccessIn silico identification of EP400 and TIA1 as critical transcription factors involved in human hepatocellular carcinoma relapse
Author(s) -
Weiguo Hong,
Yan Hu,
Zhijiang Fan,
Rong Gao,
Ruihua Yang,
Jingfeng Bi,
Jun Hou
Publication year - 2019
Publication title -
oncology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 54
eISSN - 1792-1082
pISSN - 1792-1074
DOI - 10.3892/ol.2019.11171
Subject(s) - biology , transcription factor , oncogene , hepatocellular carcinoma , in silico , cancer research , human protein atlas , cancer , molecular medicine , gene , computational biology , cell cycle , bioinformatics , genetics , protein expression
Hepatocellular carcinoma (HCC) is the second leading cause of cancer-associated mortality worldwide. Transcription factors (TFs) are crucial proteins that regulate gene expression during cancer progression; however, the roles of TFs in HCC relapse remain unclear. To identify the TFs that drive HCC relapse, the present study constructed co-expression network and identified the Tan module the most relevant to HCC relapse. Numerous hub TFs (highly connected) were subsequently obtained from the Tan module according to the intra-module connectivity and the protein-protein interaction network connectivity. Next, E1A-binding protein p400 (EP400) and TIA1 cytotoxic granule associated RNA binding protein (TIA1) were identified as hub TFs differentially connected between the relapsed and non-relapsed subnetworks. In addition, zinc finger protein 143 (ZNF143) and Yin Yang 1 (YY1) were also identified by using the plugin iRegulon in Cytoscape as master upstream regulatory elements, which could potentially regulate expression of the genes and TFs of the Tan module, respectively. The Kaplan-Meier (KM) curves obtained from KMplot and Gene Expression Profiling Interactive Analysis tools confirmed that the high expression of EP400 and TIA1 were significantly associated with shorter relapse-free survival and disease-free survival of patients with HCC. Furthermore, the KM curves from the UALCAN database demonstrated that high EP400 expression significantly reduced the overall survival of patients with HCC. EP400 and TIA1 may therefore serve as potential prognostic and therapeutic biomarkers.