Core liver homeostatic co-expression networks are preserved but respond to perturbations in an organism and disease specific manner

Published: 9 May 2022| Version 2 | DOI: 10.17632/sfng2h249n.2
Contributors:
Saeed Esmaili,
,

Description

Summary: We used WGCNA and module preservation analyse on liver transcriptomic data of mice (GSE148080), human MAFLD/MeSH (GSE126848), and human liver cancer (hepatocellular carcinoma [HCC]). The liver cancer dataset includes: A) TCGA, LIHC_US; B) ICGC datasets (LIRI_JP, LICA_FR). We defined a core homeostatic system within the liver that are preserved between all these models. We found module-eigengene QTLs for some of the modules that were predictive of patients survival. The framework presented in the original paper (Core liver homeostatic co-expression networks are preserved but respond to perturbations in an organism and disease specific manner) can be used to understand homeostasis at systems levels in pre-clinical models and in humans.

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Institutions

University of Sydney, Westmead Institute for Medical Research

Categories

Systems Biology, Homeostasis, Liver Cancer, Fatty Liver, Cancer Systems Biology, Cancer Network

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