Identification of pivotal genes and crucial pathways in liver fibrosis through WGCNA analysis

Article type: Research Article

Authors: Zhang, Xibing^{a; b} | Yang, Fuli^c | Han, Lei^d | Su, Qiuming^{a; b} | Gao, Yang^{a; b} | Wu, Ruichao^{a; b} | Wang, Duo^{a; b} | Li, Wang^{a; b} | Zheng, Kepu^{a; b} | Liu, Fang^{e; *} | Ran, Jianghua^{a; b; *}

Affiliations: [a] Department of Hepatopancreatobiliary and Vascular Surgery, The Affiliated Calmette Hospital of Kunming Medical University, The First People’s Hospital of Kunming, Yunnan, China | [b] Yunnan Organ Transplantation Research Institute, The Affiliated Calmette Hospital of Kunming Medical University, The First People’s Hospital of Kunming, Kunming, Yunnan, China | [c] Department of Pathology, The Affiliated Calmette Hospital of Kunming Medical University, The First People’s Hospital of Kunming, Kunming, Yunnan, China | [d] Department of Hepatobiliary Surgery, Changzhi People’s Hospital, Changzhi, Shanxi, China | [e] Department of Endocrinology, The Affiliated Calmette Hospital of Kunming Medical University, The First People’s Hospital of Kunming, Kunming, Yunnan, China

Correspondence: [*] Corresponding authors: Fang Liu, Department of Endocrinology, The Affiliated Calmette Hospital of Kunming Medical University, The First People’s Hospital of Kunming, Kunming, Yunnan, China. E-mail: liufang@kmmu.edu.cn. Jianghua Ran, Department of Hepatopancreatobiliary and Vascular Surgery, The Affiliated Calmette Hospital of Kunming Medical University, The First People’s Hospital of Kunming, Kunming, Yunnan, China. E-mail: ranjianghua@kmmu.edu.cn.

Abstract: BACKGROUND: Liver fibrosis is a progressive liver disease with increasing incidence, yet its underlying pathogenic mechanisms remain incompletely understood. OBJECTIVE: This study aims to explore potential therapeutic targets for liver fibrosis using weighted gene co-expression network analysis (WGCNA) and experimental validation. METHODS: We retrieved the microarray data (GSE174099) from the GEO database and performed differential expression analysis and WGCNA to identify co-expression modules associated with liver fibrosis. A module with the highest correlation to liver fibrosis was selected for further analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to investigate the biological functions and signaling pathways of the identified genes. Protein-protein interaction (PPI) networks were constructed using the STRING database. The correlation between core genes and immune cells was analyzed with the CIBERSORT algorithm. Additionally, pathological and molecular biology experiments were performed to validate the expression levels of core genes in liver tissue, including HE and Masson staining, immunohistochemistry, RT-qPCR, and Western blotting. RESULTS: We identified a total of 86 intersecting genes from the differential expression analysis and WGCNA. GO enrichment analysis revealed that these genes were involved in processes such as cellular response to cAMP, collagen-containing extracellular matrix, and G protein-coupled receptor binding. KEGG pathway analysis highlighted the involvement of these genes in pathways like Cell Adhesion Molecules and the PI3K-Akt signaling pathway. Using Cytoscape software, we identified four core genes: Cftr, Cldn4, Map2, and Spp1. Pathological examinations showed that the experimental group exhibited significant fibrous tissue proliferation compared to the control group. Immunohistochemistry, RT-qPCR, and Western blotting analyses confirmed that these core genes were significantly upregulated in the experimental group (P< 0.05). CONCLUSION: This study identified four key genes (Cftr, Cldn4, Map2, Spp1) that are significantly associated with liver fibrosis. These genes are upregulated in liver fibrosis and could potentially as biomarkers for diagnosis and targets for therapeutic interventions.

Keywords: Liver fibrosis, WGCNA, protein-protein interaction, signal transduction, gene expression

DOI: 10.3233/THC-241142

Journal: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-18, 2024