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

Authors :
Lee S
Zhang C
Liu Z
Klevstig M
Mukhopadhyay B
Bergentall M
Cinar R
Ståhlman M
Sikanic N
Park JK
Deshmukh S
Harzandi AM
Kuijpers T
Grøtli M
Elsässer SJ
Piening BD
Snyder M
Smith U
Nielsen J
Bäckhed F
Kunos G
Uhlen M
Boren J
Mardinoglu A
Source :
Molecular systems biology [Mol Syst Biol] 2017 Aug 21; Vol. 13 (8), pp. 938. Date of Electronic Publication: 2017 Aug 21.
Publication Year :
2017

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.<br /> (© 2017 The Authors. Published under the terms of the CC BY 4.0 license.)

Details

Language :
English
ISSN :
1744-4292
Volume :
13
Issue :
8
Database :
MEDLINE
Journal :
Molecular systems biology
Publication Type :
Academic Journal
Accession number :
28827398
Full Text :
https://doi.org/10.15252/msb.20177703