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Network analyses identify liver-specific targets for treating liver diseases
KTH, Centra, Science for Life Laboratory, SciLifeLab.ORCID-id: 0000-0002-6428-5936
KTH, Centra, Science for Life Laboratory, SciLifeLab.
KTH, Centra, Science for Life Laboratory, SciLifeLab.
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2017 (engelsk)Inngår i: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co-expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC), we investigated the liver-specific genes co-expressed with fatty acid synthase (FASN). CN analyses predicted that inhibition of these liver-specific genes decreases FASN expression. Experiments in human cancer cell lines, mouse liver samples, and primary human hepatocytes validated our predictions by demonstrating functional relationships between these liver genes, and showing that their inhibition decreases cell growth and liver fat content. In conclusion, we identified liver-specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenesis, such as PKLR, patatin-like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.

sted, utgiver, år, opplag, sider
John Wiley & Sons, 2017.
Emneord [en]
co-expression; co-regulation; HCC; metabolism; NAFLD
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-248643DOI: 10.15252/msb.20177703ISI: 000426043900001OAI: oai:DiVA.org:kth-248643DiVA, id: diva2:1303458
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QC 20190425

Tilgjengelig fra: 2019-04-09 Laget: 2019-04-09 Sist oppdatert: 2020-03-04bibliografisk kontrollert

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Lee, SunjaeZhang, ChengLiu, ZhengtaoSikanic, NatasaDeshmukh, SumitHarzandi, Azadeh M.Kuijpers, TimNielsen, JensUhlén, MathiasMardinoglu, Adil
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