Comprehensive Bioinformatics Analysis and Machine Learning of TTK as a Transhepatic Arterial Chemoembolization Resistance Target in Hepatocellular Carcinoma.

Abstract

Transhepatic arterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC). However, a significant proportion of patients are non-responders or poor responders to TACE. Therefore, our aim is to identify the targets of TACE responders or non-responders. GSE104580 was utilized to identify differentially expressed genes (DEGs) in TACE responders and non-responders. Following the protein-protein interaction (PPI) analysis, hub genes were identified using the MCC and MCODE plugins in Cytoscape software, as well as LASSO regression analysis. Gene set enrichment analysis (GSEA) was performed to investigate potential mechanisms. Subsequently, the hub genes were validated using data from The Cancer Genome Atlas (TCGA), the Cancer Cell Line Encyclopedia (CCLE), and The Human Protein Atlas (HPA) database. To evaluate the clinical significance of the hub genes, Kaplan-Meier (KM) survival and Cox regression analysis were employed. A total of 375 DEGs were identified, with 126 remaining following PPI analysis, and TTK, a dual-specificity protein kinase associated with cell proliferation, was ultimately identified as the hub gene through multiple screening methods. Data analysis from TCGA, CCLE, and HPA databases revealed elevated TTK expression in HCC tissues. GSEA indicated that the cell cycle, farnesoid X receptor pathway, PPAR pathway, FOXM1 pathway, E2F pathway, and ferroptosis could be potential mechanisms for TACE non-responders. Analysis of immune cell infiltration showed a significant correlation between TTK and Th2 cells. KM and Cox analysis suggested that HCC patients with high TTK expression had a worse prognosis. TTK may play a pivotal role in HCC patients' response to TACE therapy and could be linked to the prognosis of these patients.