Dataset Information

Key pathways and genes in hepatitis B virus-related liver inflammation: Expression profiling and bioinformatics analysis.

ABSTRACT: Chronic hepatitis B virus infection has become a major public health issue worldwide, which can lead to liver inflammation, fibrosis, and hepatocellular carcinoma. According to the inflammation activity, liver tissues can be divided into 5 grades (G0-G4). However, the mechanism of the development of liver inflammation remains unclear. In our study, expression profiling by microarray and bioinformatics technology was used to systemically identify differentially expressed genes (DEGs) between low grades (G0-G1) and high (G2-G4) grades of liver inflammation. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and protein-protein interaction network construction were performed for further identification of the key functions, pathways, and hub genes that might play important roles in the inflammation development. A total of 1982 DEGs were identified, consisting of 1220 downregulated genes and 762 upregulated genes. GO analysis revealed the DEGs were mainly enriched in GO terms that related to neutrophil activation and degranulation. MAPK1, ITGA2, CDK2, TGFB1, CDKN2A, MTOR, IL6, PCNA, OAS2, and EP300 were hub genes that had the highest centricity and might be potential markers for inflammation development. This study identified the differentially expressed genes between different grades of inflammation, which would enlighten the study that focuses on the mechanism of liver inflammation development.

SUBMITTER: Zhao JY

PROVIDER: S-EPMC9410593 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Key pathways and genes in hepatitis B virus-related liver inflammation: Expression profiling and bioinformatics analysis.

Zhao Jing-Yuan JY Zhong Zhao-Zhong ZZ Zhao Li-Yun LY Li Wen W

Medicine 20220801 34

Chronic hepatitis B virus infection has become a major public health issue worldwide, which can lead to liver inflammation, fibrosis, and hepatocellular carcinoma. According to the inflammation activity, liver tissues can be divided into 5 grades (G0-G4). However, the mechanism of the development of liver inflammation remains unclear. In our study, expression profiling by microarray and bioinformatics technology was used to systemically identify differentially expressed genes (DEGs) between low ...[more]

PMID: 36042612

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Project description:BackgroundLiver fibrosis is often a consequence of chronic liver injury, and has the potential to progress to cirrhosis and liver cancer. Despite being an important human disease, there are currently no approved anti-fibrotic drugs. In this study, we aim to identify the key genes and pathways governing the pathophysiological processes of liver fibrosis, and to screen therapeutic anti-fibrotic agents.MethodsExpression profiles were downloaded from the Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) were identified by R packages (Affy and limma). Gene functional enrichments of each dataset were performed on the DAVID database. Protein-protein interaction (PPI) network was constructed by STRING database and visualized in Cytoscape software. The hub genes were explored by the CytoHubba plugin app and validated in another GEO dataset and in a liver fibrosis cell model by quantitative real-time PCR assay. The Connectivity Map L1000 platform was used to identify potential anti-fibrotic agents.ResultsWe integrated three fibrosis datasets of different disease etiologies, incorporating a total of 70 severe (F3-F4) and 116 mild (F0-F1) fibrotic tissue samples. Gene functional enrichment analyses revealed that cell cycle was a pathway uniquely enriched in a dataset from those patients infected by hepatitis B virus (HBV), while the immune-inflammatory response was enriched in both the HBV and hepatitis C virus (HCV) datasets, but not in the nonalcoholic fatty liver disease (NAFLD) dataset. There was overlap between these three datasets; 185 total shared DEGs that were enriched for pathways associated with extracellular matrix constitution, platelet-derived growth-factor binding, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling. In the PPI network, 25 hub genes were extracted and deemed to be essential genes for fibrogenesis, and the expression trends were consistent with GSE14323 (an additional dataset) and liver fibrosis cell model, confirming the relevance of our findings. Among the 10 best matching anti-fibrotic agents, Zosuquidar and its corresponding gene target ABCB1 might be a novel anti-fibrotic agent or therapeutic target, but further work will be needed to verify its utility.ConclusionsThrough this bioinformatics analysis, we identified that cell cycle is a pathway uniquely enriched in HBV related dataset and immune-inflammatory response is clearly enriched in the virus-related datasets. Zosuquidar and ABCB1 might be a novel anti-fibrotic agent or target.

Dataset Information

Key pathways and genes in hepatitis B virus-related liver inflammation: Expression profiling and bioinformatics analysis.

Publications

Key pathways and genes in hepatitis B virus-related liver inflammation: Expression profiling and bioinformatics analysis.

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