A gene expression biomarker for predictive toxicology to identify chemical modulators of NF-κB

The nuclear factor-kappa B (NF-kappa B) is a transcription factor with important roles in inflammation, immune response, and oncogenesis. Dysregulation of NF-kappa B signaling is associated with inflammation and certain cancers. We developed a gene expression biomarker predictive of NF-kappa B modulation and used the biomarker to screen a large compendia of gene expression data. The biomarker consists of 108 genes responsive to tumor necrosis factor a in the absence but not the presence of I kappa B, an inhibitor of NF-kappa B. Using a set of 450 profiles from cells treated with immunomodulatory factors with known NF-kappa B activity, the balanced accuracy for prediction of NF-kappa B activation was > 90%. The biomarker was used to screen a microarray compendium consisting of 12,061 microarray comparisons from human cells exposed to 2,672 individual chemicals to identify chemicals that could cause toxic effects through NF-kappa B. There were 215 and 49 chemicals that were identified as putative or known NF-kappa B activators or suppressors, respectively. NF-kappa B activators were also identified using two high-throughput screening assays; 165 out of the similar to 3,800 chemicals (ToxCast assay) and 55 out of similar to 7,500 unique compounds (Tox21 assay) were identified as potential activators. A set of 32 chemicals not previously associated with NF-kappa B activation and which partially overlapped between the different screens were selected for validation in wild-type and NFKB1-null HeLa cells. Using RT-qPCR and targeted RNA-Seq, 31 of the 32 chemicals were confirmed to be NF-kappa B activators. These results comprehensively identify a set of chemicals that could cause toxic effects through NF-kappa B.

Automated summary

NF-kappa B is a crucial transcription factor involved in inflammation, immune response, and oncogenesis. A gene expression biomarker predictive of NF-kappa B modulation was developed and used to screen a large dataset, identifying a set of potential chemicals that could cause toxic effects through NF-kappa B.