Linking Coregulated Gene Modules with Polycyclic Aromatic Hydrocarbon-Related Cancer Risk in the 3D Human Bronchial Epithelium

Abstract

Exposure to polycyclic aromatic hydrocarbons (PAHs) often occurs as complex chemical mixtures, which are linked to numerous adverse health outcomes in humans, with cancer as the greatest concern. The cancer risk associated with PAH exposures is commonly evaluated using the relative potency factor (RPF) approach, which estimates PAH mixture carcinogenic potential based on the sum of relative potency estimates of individual PAHs, compared to benzo­[a]­pyrene (BAP), a reference carcinogen. The present study evaluates molecular mechanisms related to PAH cancer risk through integration of transcriptomic and bioinformatic approaches in a 3D human bronchial epithelial cell model. Genes with significant differential expression from human bronchial epithelium exposed to PAHs were analyzed using a weighted gene coexpression network analysis (WGCNA) two-tiered approach: first to identify gene sets comodulated to RPF and second to link genes to a more comprehensive list of regulatory values, including inhalation-specific risk values. Over 3000 genes associated with processes of cell cycle regulation, inflammation, DNA damage, and cell adhesion processes were found to be comodulated with increasing RPF with pathways for cell cycle S phase and cytoskeleton actin identified as the most significantly enriched biological networks correlated to RPF. In addition, comodulated genes were linked to additional cancer-relevant risk values, including inhalation unit risks, oral cancer slope factors, and cancer hazard classifications from the World Health Organization’s International Agency for Research on Cancer (IARC). These gene sets represent potential biomarkers that could be used to evaluate cancer risk associated with PAH mixtures. Among the values tested, RPF values and IARC categorizations shared the most similar responses in positively and negatively correlated gene modules. Together, we demonstrated a novel manner of integrating gene sets with chemical toxicity equivalence estimates through WGCNA to understand potential mechanisms.

Wildfires and extracellular vesicles: Exosomal MicroRNAs as mediators of cross-tissue cardiopulmonary responses to biomass smoke

“…At 24 h post-exposure, a total of 376, 8, 8, and 30 mRNAs were identified with significant differential expression associated with flaming peat, flaming red oak, smoldering peat, and smoldering red oak, respectively ( Table A.7 ). These gene counts are notably in range of previous inhalation toxicology research evaluating complex air pollutant exposures ( Chang et al 2021 ; Rager et al 2011a ).…”

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

“…We find that pathways involved in cardiopulmonary function, carcinogenesis, and hormone signaling were altered in response to these wildfire-relevant exposure scenarios. Trainees are lastly pointed to additional resources, including further information on -omics and systems biology, as well as additional research examples that have evaluated -omic alterations occurring in relation to the environment and involved in disease ( Smeester et al, 2011 ; Lu et al, 2014 ; Rager et al, 2016 ; Chappell and Rager, 2017 ; Balik-Meisner et al, 2018 ; Chappell et al, 2019 ; Manuck et al, 2021b ; Chang et al, 2021 ). The importance of this module lies in the training of systems biology concepts and analysis of -omics data, including RNA sequencing data, which are becoming increasingly standard molecular endpoints used in the evaluation of exposure-induced biological responses and disease etiologies.…”

A Framework for Cumulative Risk Assessment: Exploring the Carcinogenic Effects of Chemical Mixtures

“…Organoid models, which may also be used in the screening approach, are well suited for testing how chemical mixtures affect cancer-relevant pathways or biomarkers. 7,8 The authors also recommend experimental designs. For studying poorly understood cancers, they suggest starting with singlecompound testing in an in vivo or in vitro screen, followed by highthroughput testing of multiple ratios of two chemicals along a single predicted response plane.…”