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Identification of Potential Chemical Carcinogens in Compendia of Gene Expression Profiles
Citation:
Corton, C. Identification of Potential Chemical Carcinogens in Compendia of Gene Expression Profiles. sot, san antonio, Tx, March 12 - 15, 2018.
Impact/Purpose:
This talk will cover the use of gene expression biomarkers to assist in interpreting the gene expression changes observed in high throughput transcriptomic studies.
Description:
Chemicals induce cancer through partially characterized adverse outcome pathways (AOPs) that include molecular initiating events (MIEs) and downstream key events (KEs). Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. We developed computational strategies to identify chemicals in large microarray compendia that activate MIEs/KEs. Predictive biomarkers were built from profiles of knockdown or overexpression of the transcription factor (TF) and through selection of genes consistently regulated by chemicals known to modulate the TF. Gene expression profiles were compared to biomarkers using a correlation-based method which determines the significance of the overlapping gene expression allowing for prediction of modulation of that MIE/KE. The predictive biomarkers accurately identify chemicals that modulate a number of MIEs (genotoxicity assessed using p53-dependent genes, the endocrine disruptor targets estrogen receptor (ER) and androgen receptor (AR), as well as xenobiotic receptors aryl hydrocarbon receptor (AhR), constitutive activated/androstane receptor (CAR), peroxisome proliferator-activated receptor a (PPARa)) or downstream KEs (cell proliferation and oxidative stress (assessed indirectly through Nrf2 activation)). A number of examples will be given of applications of our approach including screening in 1) ER positive breast MCF-7 cells, 2) AR positive prostate LAPC-4 cells, and 3) human primary hepatocytes. Our screen identified many unique chemicals previously unknown to affect these pathways. In the MCF-7 compendium of 1153 unique compounds, 75 compounds were found to activate ERa and 39 suppressed ERa. ERa activators included those that are known ERa agonists as well as previously unrecognized activators. Chemicals were identified that increased cell proliferation in MCF-7 cells either dependent or independent of ER activation. Our approach highlights the value of using transcript profiling to identify chemicals that have the potential to cause cancer. This does not represent US EPA policy.