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Network analyses identify liver-specific targets for treating liver diseases

Research output: Contribution to journalArticle

Sunjae Lee, Cheng Zhang, Zhengtao Liu, Martina Klevstig, Bani Mukhopadhyay, Mattias Bergentall, Resat Cinar, Marcus Stahlman, Natasha Sikanic, Joshua K. Park, Sumit Deshmukh, Azadeh M. Harzandi, Tim Kuijpers, Morten Grotli, Simon J. Elsasser, Brian D. Piening, Michael Snyder, Ulf Smith, Jens Nielsen, Fredrik Backhed & 4 more George Kunos, Mathias Uhlen, Jan Boren, Adil Mardinoglu

Original languageEnglish
JournalMolecular Systems Biology
Volume13
Issue number8
Early online date21 Aug 2017
DOIs
Publication statusPublished - Aug 2017

King's Authors

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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