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Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

Luisier, Raphaelle and Unterberger, Elif and Goodman, Jay and Schwarz, Michael and Moggs, Jonathan and Terranova, Remi and van Nimwegen, Erik (2014) Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion. Nucleic Acid Research (NAR).

Abstract

Gene regulatory interactions underlying the early
stages of non-genotoxic carcinogenesis are poorly
understood. Here, we have identified key candidate
regulators of phenobarbital (PB)-mediated mouse
liver tumorigenesis, a well-characterized model of
non-genotoxic carcinogenesis, by applying a new
computational modeling approach to a comprehensive
collection of in vivo gene expression studies.
We have combined our previously developed motif
activity response analysis (MARA), which models
gene expression patterns in terms of computationally
predicted transcription factor binding sites with
singular value decomposition (SVD) of the inferred
motif activities, to disentangle the roles that
different transcriptional regulators play in specific
biological pathways of tumor promotion.
Furthermore, transgenic mouse models enabled us
to identify which of these regulatory activities was
downstream of constitutive androstane receptor
and b-catenin signaling, both crucial components
of PB-mediated liver tumorigenesis. We propose
novel roles for E2F and ZFP161 in PB-mediated hepatocyte
proliferation and suggest that PB-mediated
suppression of ESR1 activity contributes to the development
of a tumor-prone environment. Our study
shows that combining MARA with SVD allows for
automated identification of independent transcription
regulatory programs within a complex in vivo
tissue environment and provides novel mechanistic
insights into PB-mediated hepatocarcinogenesis.

Item Type: Article
Date Deposited: 13 Oct 2015 13:13
Last Modified: 13 Oct 2015 13:13
URI: https://oak.novartis.com/id/eprint/11322

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