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Mutagenicity and Carcinogenicity

Mutagenicity and Carcinogenicity

Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...

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Classifying polycyclic aromatic hydrocarbons by carcinogenic potency using in vitro biosignatures.

Yvonne Chang¹, Celine Thanh Thu Huynh¹, Kelley M Bastin¹

¹Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA.

Toxicology in Vitro : an International Journal Published in Association with BIBRA

|September 5, 2020

Summary

Evaluating complex chemical mixtures like polycyclic aromatic hydrocarbons (PAHs) is challenging. A new human cell model using gene expression successfully predicts PAH carcinogenicity, improving chemical risk assessment.

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Published on: December 19, 2019

Area of Science:

Toxicology
Systems Biology
Chemical Risk Assessment

Background:

Assessing the carcinogenic potential of chemical mixtures, such as polycyclic aromatic hydrocarbons (PAHs), presents significant challenges in risk assessment.
Previous work established a mouse model using systems biology data to predict tumor outcomes following chemical exposure.

Purpose of the Study:

To translate a predictive classification model for chemical carcinogenicity from a mouse model to a human in vitro system.
To utilize 3D human bronchial epithelial cells (HBEC) to classify PAHs based on their carcinogenic potency using chemical-specific bioactivity profiles.

Main Methods:

Gene expression profiles were analyzed from HBEC exposed to carcinogenic and non-carcinogenic PAHs.
Pathway-based gene sets were evaluated for classification accuracy.
Bayesian integration combined posterior probabilities from the best-performing gene sets to create a multi-gene set classifier.
Transcriptional benchmark dose modeling was applied to benzo[a]pyrene (BAP).

Main Results:

A classifier integrating four gene sets (aryl hydrocarbon receptor signaling, epithelial mesenchymal transition regulation, angiogenesis regulation, and cell cycle G2-M) accurately classified PAHs by carcinogenic potency.
Gene sets most sensitive to BAP regulation differed from those that best classified overall PAH carcinogenicity.
This suggests BAP's mode of action may not represent all PAHs.

Conclusions:

Systems toxicology approaches, analyzing global gene expression, are valuable for carcinogenic hazard assessment.
The developed human in vitro model demonstrates utility in predicting PAH carcinogenicity.
Current assumptions regarding BAP carcinogenicity reflecting overall PAH carcinogenicity may need re-evaluation.