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Time series analysis of benzo[a]pyrene-induced transcriptome changes suggests that a network of transcription factors regulates the effects on functional gene sets

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Author: Delft, J.H.M. van · Mathijs, K. · Staal, Y.C.M. · Herwijnen, M.H.M. van · Brauers, K.J.J. · Boorsma, A. · Kleinjans, J.C.S.
Institution: TNO Kwaliteit van Leven
Source:Toxicological Sciences, 2, 117, 381-392
Identifier: 409829
Keywords: Nutrition · Biomedical Research · Carcinogen · Network · Time series · Transcription factor · Transcriptome · benzo[a]pyrene · immunoglobulin enhancer binding protein · Myc protein · serum response factor · transcription factor · transcription factor AP 1 · transcription factor E2F1 · transcriptome · amino acid metabolism · apoptosis · article · carcinogenesis · cell cycle G1 phase · cell cycle S phase · controlled study · correlation analysis · DNA adduct · DNA repair · down regulation · functional genomics · gene expression · gene regulatory network · hepatoma cell · human · human cell · lipid metabolism · named inventories, questionnaires and rating scales · proto oncogene · Short Time series Expression Miner · signal transduction · time series analysis · transcription regulation · tumor suppressor gene · upregulation


Chemical carcinogens may cause a multitude of effects inside cells, thereby affecting transcript levels of genes by direct activation of transcription factors (TF) or indirectly through the formation of DNA damage. As the temporal profiles of these responses may be profoundly different, examining time-dependent changes may provide new insights in TF networks related to cellular responses to chemical carcinogens. Therefore, we investigated in human hepatoma cells gene expression changes caused by benzo[a]pyrene at 12 time points after exposure, in relation to DNA adduct and cell cycle. Temporal profiles for functional gene sets demonstrate both early and late effects in up- and downregulation of relevant gene sets involved in cell cycle, apoptosis, DNA repair, and metabolism of amino acids and lipids. Many significant transcription regulation networks appeared to be around TF that are proto-oncogenes or tumor suppressor genes. The time series analysis tool Short Time-series Expression Miner (STEM) was used to identify time-dependent correlation of pathways, gene sets, TF networks, and biological parameters. Most correlations are with DNA adduct levels, which is an early response, and less with the later responses on G1 and S phase cells. The majority of the modulated genes in the Reactome pathways can be regulated by several of these TF, e.g., 73% by nuclear factor-kappa B and 34-42% by c-MYC, SRF, AP1, and E2F1. All these TF can also regulate one or more of the others. Our data indicate that a complex network of a few TF is responsible for the majority of the transcriptional changes induced by BaP. This network hardly changes over time, despite that the transcriptional profiles clearly alter, suggesting that also other regulatory mechanisms are involved. © The Author 2010. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.