Identification and Validation of Hub Genes Associated With Hepatocellular Carcinoma Via Integrated Bioinformatics Analysis

• Published in: Frontiers in oncology Vol. 11; p. 614531
• Main Authors: Wang, Sumei, Song, Zuoli, Tan, Bing, Zhang, Jinjuan, Zhang, Jiandong, Liu, Shuye
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 30-06-2021
• Subjects: biomarker; GEO; hepatocellular carcinoma; Oncology; TCGA; weighted gene co-expression network analysis
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2021.614531

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, with high morbidity and mortality, yet its molecular mechanisms of tumorigenesis are still unclear. In this study, gene expression profile of GSE62232 was downloaded from the Gene Expression Omnibus (GEO). The RNA-seq expression data and relative clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. The datasets were analyzed by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the overlapping genes. Then, we performed a functional enrichment analysis to understand the potential biological functions of these co-expression genes. Finally, we constructed the protein-protein interaction (PPI) analysis combined with survival analysis. MARCO, CLEC4M, FCGR2B, LYVE1, TIMD4, STAB2, CFP, CLEC4G, CLEC1B, FCN2, FCN3 and FOXO1 were identified as the candidate hub genes using the CytoHubba plugin of Cytoscape. Based on survival analysis, the lower expression of FCN3 and FOXO1 were associated with worse overall survival (OS) in HCC patients. Furthermore, the expression levels of FCN3 and FOXO1 were validated by the Human Protein Atlas (HPA) database and the qRT-PCR. In summary, our findings contribute new ideas for the precise early diagnosis, clinical treatment and prognosis of HCC in the future.