Time series analysis of oxidative stress response patterns in HepG2: A toxicogenomics approach

L. Deferme*, J. J. Briede, S. M. H. Claessen, D. G. J. Jennen, R. Cavil, J. C. S. Kleinjans

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Oxidative stress plays an important role in chemically induced liver injury, however, our insight into molecular responses to different oxygen radicals is fragmentary. Since these cellular responses will differ over time, examining time-dependent changes in gene expression, and correlating these with markers for oxidative stress, may provide new insights into responses to oxidants. We used the human hepatoma cell line HepG2 to investigate the effects of oxidative stress on the transcriptome level by micro-arrays at seven time points (0.5, 1, 2, 4, 6, 8 and 24 h) following exposure to the oxidants menadione, hydrogen peroxide and tert-butyl hydroperoxide including the effects on cell cycle and apoptosis by flow cytometry, protein carbonyl formation by spectrophotometry and oxidative DNA damage by FPG-comet. In total, 3429 genes were differentially expressed, including 136 genes that were significantly modified by all oxidants. Time-dependent biological pathway analysis showed that these genes were particularly involved in inflammatory responses, cell cycle processes and glutathione signaling. These responses were confirmed and supported by phenotypic anchoring to the different cellular endpoints. In addition, using an innovative temporal analysis we established an oxidative stress-related gene expression time cluster. Altogether, this study provides new insights in temporal oxidative stress mechanisms and demonstrates sequential cellular responses that may contribute to a better hazard identification and the mechanisms of toxicological responses in the liver induced by oxidative stress.
Original languageEnglish
Pages (from-to)24-34
Publication statusPublished - 5 Apr 2013


  • Oxidative stress
  • Liver toxicity
  • HepG2 cells
  • Whole-genome gene expression
  • Phenotypical anchoring
  • Temporal gene expression profiles


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