Inferring transcription factor activity from microarray data reveals novel targets for toxicological investigations.

Area of Science:

• Toxicology
• Molecular Biology
• Genomics

Background:

• Transcription factors (TFs) regulate gene expression and are crucial for understanding responses to chemical exposure.
• Current low-throughput methods limit the analysis of TF activity to a few entities, hindering comprehensive toxicological investigations.
• High-throughput approaches are needed to identify novel mechanistic and predictive TF targets.

Purpose of the Study:

• To infer the activity of multiple TFs in primary human hepatocytes exposed to various chemicals.
• To evaluate TF activity profiles for predicting toxicological outcomes like carcinogenicity and drug-induced liver injury (DILI).
• To identify known and novel TFs involved in chemical-induced toxicity.

Main Methods:

• Utilized publicly available microarray data from human hepatocytes exposed to hundreds of chemicals.
• Applied multiple correspondence analysis to evaluate TF activity profiles.
• Analyzed TF activity patterns at different chemical doses and exposure times (2h and 24h).

Main Results:

• Specific chemical exposure conditions (low dose, 24h) revealed TF signatures indicative of carcinogenicity, potentially linked to DNA damage.
• Early exposure (2h) and high doses clustered chemicals associated with diverse forms of DILI.
• Identified known TFs (e.g., AhR, NFE2L2, NF-κB, PPARG) and novel TFs (e.g., FOXM1, IRF1, E2F4, SMADs, KLF5) associated with toxicological responses.

Conclusions:

• The study presents a novel mechanistic approach to assess TF activity during chemical exposure.
• Inferred TF activities provide insights into genotoxic carcinogenesis and DILI mechanisms.
• This high-throughput method enhances the identification of TFs relevant to chemical toxicity assessment.