ANTXR1 as a potential prognostic biomarker for hepatitis B virus-related hepatocellular carcinoma identified by a weighted gene correlation network analysis

Tao Si; Xuejian Ning; Haihui Chen; Zhengguo Hu; Linglu Dun; Na Zheng; Ping Huang; Liu Yang; Ping Yi

doi:10.21037/jgo-21-764

ANTXR1 as a potential prognostic biomarker for hepatitis B virus-related hepatocellular carcinoma identified by a weighted gene correlation network analysis

J Gastrointest Oncol. 2021 Dec;12(6):3079-3092. doi: 10.21037/jgo-21-764.

Authors

Tao Si^#¹, Xuejian Ning^#¹, Haihui Chen¹, Zhengguo Hu¹, Linglu Dun², Na Zheng², Ping Huang¹, Liu Yang¹, Ping Yi²

Affiliations

¹ Department of Oncology, Liuzhou Traditional Chinese Medical Hospital, Liuzhou, China.
² Department of Neurology Laboratory, Liuzhou Traditional Chinese Medical Hospital, Liuzhou, China.

^# Contributed equally.

Abstract

Background: With high incidence and mortality rates, hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors worldwide. Chronic hepatitis B virus (HBV) infection is a leading cause of HCC, especially for Asians and blacks. However, the molecular mechanisms underlying HBV-related HCC are unclear. This study sought to identify novel prognostic biomarkers and explore the potential pathogenesis of HBV-related HCC.

Methods: The gene expression profiles and corresponding clinical information of HCC from The Cancer Genome Atlas Liver Hepatocellular Carcinoma data set were analyzed by a weighted gene co-expression network analysis. Correlations between the co-expression modules and clinical traits were calculated. Next, key modules associated with HBV infection were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted for the genes in the key modules. The hub genes were identified based on the protein-protein interaction (PPI) network via the Cytoscape. Finally, an overall survival (OS) analysis was performed.

Results: The two modules (i.e., the brown and yellow modules) most relevant to HBV infection were constructed. A functional enrichment analysis revealed that the genes in the two modules were mainly enriched in HCC-related pathways, such as the phosphatidylinositol-3-kinase and protein kinase B signaling pathway, focal adhesion, human papillomavirus infection, the Rap1 signaling pathway, and the cyclic guanosine monophosphate-dependent protein kinase (cGMP-PKG) signaling pathway. Ten hub genes [i.e., COL3A1, ANTXR1, COL14A1, THBS2, ADAMTS2, AEBP1, PRELP, EMILIN1, DCN and PODN] in the brown module, and 10 hub genes [i.e., USP34, SEC24C, ZNF770, STAG1, TSTD2, PKD1P6, CCNK, GFT2I, NT5C2 and SMG6] in the yellow module were identified. Among the hub genes, ANTXR1 (Anthrax-toxin receptor 1) was significantly correlated with HBV-related HCC patients' OS.

Conclusions: ANTXR1 represents a potential therapeutic target for HBV-related HCC. This study offers novel insights into the molecular mechanisms of HBV-induced tumorigenesis, which needs to be further validated by basic experiments and large-scale cohort studies.

Keywords: ANTXR1; TEM8; Weighted gene correlation network analysis; hepatitis B virus (HBV); hepatocellular carcinoma (HCC).