Identification of Key Genes and Pathways Associated with Hepatosplenic T-Cell Lymphoma (HSTCL) by Bioinformatics Analysis

BACKGROUND Prognosis of Hepatosplenic T-Cell Lymphoma (HSTCL) is very poor, while the molecular mechanism of this disease has rarely been investigated and remains mysterious. The aim of the study is to screen differentially expressed genes (DEGs) of patients with HSTCL and normal controls, explore the pathogenesis, and provide guidance for the gene diagnosis and precise treatment of HSTCL. METHODS The genetic chip data GSE57520 of HSTCL was searched from the GEO database, and the quality control and DEGs screening were performed through BART online tools. In addition, FunRich software was used to perform gene enrichment and pathway analysis on the screened DEGs. Subsequently protein interaction network (PPI) was constructed via the STRING database and analyzed using the visual module of Cytoscape software. RESULTS A total of 4,759 DEGs were obtained, including 2,501 up-regulated genes and 2,258 down-regulated genes (p < 0.05). The analysis of gene ontology (GO) showed that DEGs in cytology component (CC) mainly involved cytoplasm, nucleus, plasma membrane, Golgi apparatus, lysosome, and endoplasmic reticulum. Besides, DEGs in molecular function (MF) mainly included transcription factor activity, catalytic activity, transporter activity, transcription regulator activity, receptor signaling pathway complex, receptor activity. Moreover, DEGs in biological processes (BP) are mainly involved in base regulation, transport, energy pathways, metabolism, protein metabolism, and apoptosis. The results of the Kyoto Gene and Genome Encyclopedia (KEGG) analysis showed that the DEGs mainly include TRAIL, Beta1 integrin, integrin family, proteoglycan, S1P, and ErbB. Combined with Cytoscape software cytoHubba plug-in, protein interaction network (PPI) analysis showed that KIF20A, DLGAP5, PBK, TOP2A, ASPM, NEK2, KIF14, and DEPDC1B were the most abundant core genes. Module analysis showed that the three gene modules with the highest scores were mainly related to mitosis, epithelial cell adhesion and signal transduction, and the process of DNA damage. CONCLUSIONS The DEGs of HSTCL patients versus healthy control groups were obtained through a variety of bioinformatics methods. KIF20A and DLGAP5 may become potential therapeutic targets for HSTCL. Also, the most abundant signaling pathway in DEGs was the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) - related pathway. Besides, related genes and expression characteristics of HSTCL pathogenesis were reanalyzed from distinctive perspectives, which might provide specific diagnostic markers and targeted therapy for HSTCL.