ArticleThe Kaohsiung journal of medical sciences2016
Bioinformatics microarray analysis and identification of gene expression profiles associated with cirrhotic liver.
Article in The Kaohsiung journal of medical sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comparative Transcriptome Analysis of Hens' Livers in Conventional Cage vs. Cage-Free Egg Production Systems.Veterinary medicine international · 2025Article
- Secreted folate receptor γ drives fibrogenesis in metabolic dysfunction-associated steatohepatitis by amplifying TGFβ signaling in hepatic stellate cells.Science translational medicine · 2023Article
- Article
- Differentially Expressed Genes in Response to a Squalene-Supplemented Diet Are Accurate Discriminants of Porcine Non-Alcoholic Steatohepatitis.International journal of molecular sciences · 2023Article
- Differences of core genes in liver fibrosis and hepatocellular carcinoma: Evidence from integrated bioinformatics and immunohistochemical analysis.World journal of gastrointestinal oncology · 2022Article
- Network Modeling Approaches and Applications to Unravelling Non-Alcoholic Fatty Liver Disease.Genes · 2019Review
- The putative tumour suppressor protein Latexin is secreted by prostate luminal cells and is downregulated in malignancy.Scientific reports · 2019Article
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Authors and funding
6 authors.
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Abstract
Cirrhosis is the endpoint of liver fibrosis that is accompanied by limited regeneration capacity and complications and is the ultimate cause of death in many patients. Despite this, few studies have thoroughly looked at the gene expression profiles in the cirrhotic liver. Hence, this study aims to identify the genes that were differentially expressed in the cirrhotic liver and to explore the putative related signaling pathway and interaction networks. The gene expression profiles of cirrhotic livers and noncirrhotic livers were examined and compared using microarray gene analysis. Proteins encoded by the differentially expressed genes were analyzed for functional clustering and signaling pathway involvement using MetaCore bioinformatics analyses. The Gene Ontology analysis as well as the Kyoto encyclopedia of Genes and Genomes pathway analysis were also performed. A total of 213 significant genes were differentially expressed at more than a two-fold change in cirrhotic livers as compared to noncirrhotic livers. Of these, 105 upregulated genes and 63 downregulated genes were validated through MetaCore bioinformatics analyses. The signaling pathways and major functions of proteins encoded by these differentially expressed genes were further analyzed; results showed that the cirrhotic liver has a unique gene expression pattern related to inflammatory reaction, immune response, and cell growth, and is potentially cancer related. Our findings suggest that the microarray analysis may provide clues to the molecular mechanisms of liver cirrhosis for future experimental studies. However, further exploration of areas regarding therapeutic strategy might be possible to support metabolic activity, decrease inflammation, or enhance regeneration for liver cirrhosis.
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