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Mining a human transcriptome database for chemical modulators of NRF2
Author(s) -
John P. Rooney,
Brian N. Chorley,
Steven Hiemstra,
Steven Wink,
Xuting Wang,
Douglas A. Bell,
Bob van de Water,
J. Christopher Corton
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0239367
Subject(s) - biomarker , transcriptome , microarray analysis techniques , microarray , gene expression , gene expression profiling , dna microarray , gene , toxicogenomics , biology , gene knockdown , biomarker discovery , computational biology , hmox1 , proteomics , genetics , biochemistry , heme , heme oxygenase , enzyme
Nuclear factor erythroid-2 related factor 2 (NRF2) encoded by the NFE2L2 gene is a transcription factor critical for protecting cells from chemically-induced oxidative stress. We developed computational procedures to identify chemical modulators of NRF2 in a large database of human microarray data. A gene expression biomarker was built from statistically-filtered gene lists derived from microarray experiments in primary human hepatocytes and cancer cell lines exposed to NRF2-activating chemicals (oltipraz, sulforaphane, CDDO-Im) or in which the NRF2 suppressor Keap1 was knocked down by siRNA. Directionally consistent biomarker genes were further filtered for those dependent on NRF2 using a microarray dataset from cells after NFE2L2 siRNA knockdown. The resulting 143-gene biomarker was evaluated as a predictive tool using the correlation-based Running Fisher algorithm. Using 59 gene expression comparisons from chemically-treated cells with known NRF2 activating potential, the biomarker gave a balanced accuracy of 93%. The biomarker was comprised of many well-known NRF2 target genes ( AKR1B10 , AKR1C1 , NQO1 , TXNRD1 , SRXN1 , GCLC , GCLM ), 69% of which were found to be bound directly by NRF2 using ChIP-Seq. NRF2 activity was assessed across ~9840 microarray comparisons from ~1460 studies examining the effects of ~2260 chemicals in human cell lines. A total of 260 and 43 chemicals were found to activate or suppress NRF2, respectively, most of which have not been previously reported to modulate NRF2 activity. Using a NRF2-responsive reporter gene in HepG2 cells, we confirmed the activity of a set of chemicals predicted using the biomarker. The biomarker will be useful for future gene expression screening studies of environmentally-relevant chemicals.

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