Abstract 782: A network approach to study the effect of chemical exposures on gene regulatory system in rats

Exposure to environmental chemicals during early development may increase the risk of developing breast cancer later in life. In this context, we are interested in characterizing which microRNA (miRNA) and mRNA expressions change in a coherent manner across the lifespan, and whether the co-expression pattern is affected by environmental exposures. miRNAs contribute to tumor progression via the regulation of post-transcriptional gene expressions. Thus, information on different interaction patterns among miRNAs and mRNAs measured in mammary tissues from chemical exposed vs. non-exposed rats can cast light on how chemical exposures may alter mammary gland development. Specifically, we consider three common environmental chemicals: diethyl phthalate (DEP), methyl paraben (MPB) and triclosan (TCS). Female Sprague-Dawley rats were treated with these chemicals at four windows of susceptibility (prenatal, neonatal, prepubertal and pubertal) respectively with oral doses shown to produce urinary metabolite levels similar to those measured in US population. We implemented a new algorithm, Joint Random Forest (JRF), for simultaneous estimation of multiple related networks to characterize co-expression patterns among mRNAs and miRNAs. JRF is designed to borrow information across different treatment conditions, so that regulatory relationships shared across conditions can be detected with increased power, while those specific to each condition can be detected with fewer false positives. We focused on 1403 mRNAs and 283 miRNAs with larger variability across rats, and derived four co-expression networks of these mRNAs/miRNAs for each environmental chemical treatment plus a control group. Overall we observed a substantial loss of connectivity in networks of chemical exposed groups (DEP: 1813 edges, MPB: 1539 edges and TCS: 1013 edges) compared to that of the control group (2641 edges). Interestingly, despite the overall loss of connectivity in networks of chemical exposed groups, some microRNAs such as rno-miR-126b (MIMAT0017843) and rno-miR-3596b (MIMAT0017871) showed many connecting edges in networks of chemical exposed groups but zero in that of the control group. In particular, rno-miR-3596b is a member of the Let-7 family which is well known to regulate self-renewal and tumorigenicity in breast cancer cells. Findings like this can lead to better understanding of how chemical exposures could alter gene regulatory activities. Our study also demonstrates the great potent