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Network analyses identify liver-specific targets for treating liver diseases.

Journal article
Authors Sunjae Lee
Cheng Zhang
Zhengtao Liu
Martina Klevstig
Bani Mukhopadhyay
Mattias Bergentall
Resat Cinar
Marcus Ståhlman
Natasha Sikanic
Joshua K Park
Sumit Deshmukh
Azadeh M Harzandi
Tim Kuijpers
Morten Grøtli
Simon J Elsässer
Brian D Piening
Michael Snyder
Ulf Smith
Jens Nielsen
Fredrik Bäckhed
George Kunos
Mathias Uhlen
Jan Boren
Adil Mardinoglu
Published in Molecular systems biology
Volume 13
Issue 8
ISSN 1744-4292
Publication year 2017
Published at Department of Chemistry and Molecular Biology
Institute of Medicine, Department of Molecular and Clinical Medicine
Language en
Links dx.doi.org/10.15252/msb.20177703
www.ncbi.nlm.nih.gov/entrez/query.f...
Subject categories Clinical Medicine

Abstract

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.

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