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Updated: Dec 8, 2025

Cell Type-specific Gene Expression Profiling in the Mouse Liver
Published on: September 17, 2019
Screening and evaluation of key genes in contributing to pathogenesis of hepatic fibrosis based on microarray data
Furong Wu1, Lijuan Ning1, Ran Zhou1
1Department of Pharmacy, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, People's Republic of China.
Background:
Hepatic fibrosis (HF), which is characterized by the excessive accumulation of extracellular matrix (ECM) in the liver, usually progresses to liver cirrhosis and then death. To screen differentially expressed (DE) long non-coding RNAs (lncRNAs) and mRNAs, explore their potential functions to elucidate the underlying mechanisms of HF.
Methods:
The microarray of GSE80601 was downloaded from the Gene Expression Omnibus database, which is based on the GPL1355 platform. Screening for the differentially expressed LncRNAs and mRNAs was conducted between the control and model groups. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the biological functions and pathways of the DE mRNAs. Additionally, the protein-protein interaction (PPI) network was delineated. In addition, utilizing the Weighted Gene Co-expression Network Analysis (WGCNA) package and Cytoscape software, we constructed lncRNA-mRNA weighted co-expression networks.
Results:
A total of 254 significantly differentially expressed lncRNAs and 472 mRNAs were identified. GO and KEGG analyses revealed that DE mRNAs regulated HF by participating in the GO terms of metabolic process, inflammatory response, response to wounding and oxidation-reduction. DE mRNAs were also significantly enriched in the pathways of ECM-receptor interaction, PI3K-Akt signaling pathway, focal adhesion (FA), retinol metabolism and metabolic pathways. Moreover, 24 lncRNAs associated with 40 differentially expressed genes were observed in the modules of lncRNA-mRNA weighted co-expression network.
Conclusions:
This study revealed crucial information on the molecular mechanisms of HF and laid a foundation for subsequent genes validation and functional studies, which could contribute to the development of novel diagnostic markers and provide new therapeutic targets for the clinical treatment of HF.
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