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Bioinformatics microarray analysis and identification of gene expression profiles associated with cirrhotic liver

  • Kun Ming Chan*
  • , Tsung Han Wu
  • , Ting Jung Wu
  • , Hong Shiue Chou
  • , Ming Chin Yu
  • , Wei Chen Lee
  • *Corresponding author for this work
  • Chang Gung Memorial Hospital
  • Chang Gung University

Research output: Contribution to journalJournal Article peer-review

10 Scopus citations

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.

Original languageEnglish
Pages (from-to)165-176
Number of pages12
JournalKaohsiung Journal of Medical Sciences
Volume32
Issue number4
DOIs
StatePublished - 01 04 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Kaohsiung Medical University. Published by Elsevier Taiwan LLC.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Bioinformatics
  • Gene profiles
  • Liver
  • Liver cirrhosis
  • Microarray analysis

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