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Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation

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Mining toxicogenomic data for dose-responsive pathways: implications in advancing next-generation risk assessment.

A Rasim Barutcu¹, Michael B Black¹, Andy Nong¹

¹ScitoVation LLC, Durham, NC, United States.

Frontiers in Toxicology

|December 4, 2023

Summary

Unbiased transcriptomic analysis reveals dose-responsive toxicity pathways and points of departure, improving chemical risk assessment. This systems-toxicology approach complements targeted methods for comprehensive evaluation.

Keywords:

BMD modeling NAM dose response toxicogenomics (Tgx)transcriptomics

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Area of Science:

Toxicology
Bioinformatics
Computational Biology

Background:

Targeted toxicity pathway investigation aids biomarker discovery.
Unbiased, systems-level transcriptomic analysis offers a complementary perspective.
Systematic implementation of unbiased transcriptomic approaches remains underdeveloped.

Purpose of the Study:

To demonstrate the power of an integrated bioinformatic approach for analyzing transcriptomic data.
To identify dose-responsive molecular changes, biological pathways, and points of departure in an untargeted manner.
To evaluate the utility of systems-toxicology for improving chemical risk assessment.

Main Methods:

Re-analysis of publicly available MCF7 cell TempO-seq data for 44 ToxCast chemicals.
Integrated bioinformatic workflow: differential expression, gene set enrichment, benchmark dose modeling, network visualization.
Comparison with original study's gene signature approach and ToxCast high-throughput screening (HTS) assays.

Main Results:

Identified dose-responsive molecular changes and perturbed biological pathways.
Benchmark dose modeling based on pathways recapitulated apical endpoints' points of departure.
Revealed additional perturbed mechanisms missed by single endpoint analyses.

Conclusions:

Systems-toxicology provides multifaceted insights into chemical exposure effects.
Unbiased, data-driven techniques are crucial alongside targeted methods for comprehensive toxicity evaluation.
Integrating omics assays with bioinformatics enhances chemical risk assessment and supports New Approach Methodologies (NAMs).