Network analyses identify liver-specific targets for treating liver diseases
Journal article, 2017
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.
metabolism
NAFLD
co-regulation
co-expression
HCC
Author
SangWook Lee
Royal Institute of Technology (KTH)
C. Zhang
Royal Institute of Technology (KTH)
Z. T. Liu
Royal Institute of Technology (KTH)
M. Klevstig
Sahlgrenska University Hospital
B. Mukhopadhyay
NIAAA
Mattias Bergentall
Sahlgrenska University Hospital
R. Cinar
NIAAA
Marcus Ståhlman
Sahlgrenska University Hospital
Natasha Sikanic
Royal Institute of Technology (KTH)
Joshua K. Park
NIAAA
Sumit Deshmukh
Royal Institute of Technology (KTH)
Azadeh M. Harzandi
Royal Institute of Technology (KTH)
Tim Kuijpers
Royal Institute of Technology (KTH)
Morten Grötli
University of Gothenburg
Simon J. Elsässer
Karolinska Institutet
B. D. Piening
Stanford University
M. Snyder
Stanford University
U. Smith
Sahlgrenska University Hospital
Jens B Nielsen
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Fredrik Bäckhed
Sahlgrenska University Hospital
G. Kunos
NIAAA
Mathias Uhlen
Royal Institute of Technology (KTH)
Jan Borén
Sahlgrenska University Hospital
Adil Mardinoglu
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Molecular Systems Biology
17444292 (eISSN)
Vol. 13 8 938Subject Categories
Cell Biology
DOI
10.15252/msb.20177703