Identification of hub genes in peripheral blood mononuclear cells for the diagnosis of hepatocellular carcinoma using a weighted gene co‑expression network analysis
- Zi Ye
- Zhirui Zeng
- Yiyi Shen
- Zubing Chen
Affiliations: Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China, Guizhou Provincial Key Laboratory of Pathogenesis & Drug Research on Common Chronic Diseases, Guizhou Medical University, Guiyang, Guizhou 550009, P.R. China, Department of Liver‑Biliary Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou 550009, P.R. China
- Published online on: May 12, 2020 https://doi.org/10.3892/etm.2020.8736
Copyright: © Ye
et al. This is an open access article distributed under the
terms of Creative
Commons Attribution License.
Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )
This article is mentioned in:
Human hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive tract that is prevalent worldwide. Improving diagnosis methods for HCC helps to improve patient survival rate. The present study aimed to identify novel HCC biomarkers for the diagnosis of HCC through analyzing gene changes on peripheral blood mononuclear cells (PBMCs) and verifying these in additional samples. The gene expression profiles GSE49515 (including 10 specimens from normal patients and 10 specimens from patients with HCC) and GSE58208 (including 5 specimens from normal patients and 10 specimens from patients with HCC) were downloaded from the online Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) in PBMCs between healthy controls and patients with HCC were identified using R software. A total of 935 DEGs, including 686 upregulated DEGs and 249 downregulated DEGs, were identified in the present study. In order to identify any internal associations, these DEGs were used to construct weighted gene co‑expression networks (WGCNA). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of genes in each module were conducted using the online database DAVID. Furthermore, hub genes with high module membership were identified in a co‑expression network and receiver operating characteristic curves were used to verify the diagnostic values of these eight hub genes. Furthermore, the expression and diagnosis value of the eight hub genes were also verified in additional samples. The results of the present study suggested that secreted protein acidic and cysteine rich(SPARC), transmembrane protein 40 (TMEM40), solute carrier family 25 member 44, formyl peptide receptor 2 (FPR2), complement C8 β chain, N‑myristoyltransferase 1, protein kinase C δ(PRKCD) and protein phosphatase, Mg2+/Mn2+ dependent 1M(PPM1M) were hub genes. SPARC, TMEM40, FPR2, PRKCD and PPM1M had prominent diagnostic value according to the results from the GEO data and the additional samples. The present study demonstrated that these hub genes may help to improve the diagnosis of HCC.