Application of cDNA microarray technology to in vitro toxicology and the selection of genes for a real-time RT-PCR-based screen for oxidative stress in Hep-G2 cells.

Large-scale analysis of gene expression using cDNA microarrays promises the rapid detection of the mode of toxicity for drugs and other chemicals. cDNA microarrays were used to examine chemically induced alterations of gene expression in HepG2 cells exposed to a diverse group of toxicants at an equitoxic exposure concentration. The treatments were ouabain (43 microM), lauryl sulfate (260 microM), dimethylsulfoxide (1.28 M), cycloheximide (62.5 microM), tolbutamide (12.8 mM), sodium fluoride (3 mM), diethyl maleate (1.25 mM), buthionine sulfoximine (30 mM), potassium bromate (2.5 mM), sodium selenite (30 microM), alloxan (130 mM), adriamycin (40 microM), hydrogen peroxide (4 mM), and heat stress (45 degrees C x 30 minutes). Patterns of gene expression were correlated with morphologic and biochemical indicators of toxicity. Gene expression responses were characteristically different for each treatment. Patterns of expression were consistent with cell cycle arrest, DNA damage, diminished protein synthesis, and oxidative stress. Based upon these results, we concluded that gene expression changes provide a useful indicator of oxidative stress, as assessed by the GSH:GSSG ratio. Under the conditions of this cell culture test system, oxidative stress upregulated 5 genes, HMOX1, p21(waf1/cip1), GCLM, GR, TXNR1 while downregulating CYP1A1 and TOPO2A. Primers and probes for these genes were incorporated into the design of a 7-gene plate for RT-PCR. The plate design permitted statistical analysis and allowed clear discrimination between chemicals inducing oxidative vs nonoxidative stress. A simple oxidative stress score (0-1), based on the responses by the 7 genes (including p-value) on the RT-PCR plate, was correlated with the GSH:GSSG ratio using linear regression and ranking (Pearson product) procedures. These analyses yielded correlation coefficients of 0.74 and 0.87, respectively, for the treatments tested (when 1 outlier was excluded), indicating a good correlation between the biochemical and transcriptional measures of oxidative stress. We conclude that it is essential to measure the mechanism of interest directly in the test system being used when assessing gene expression as a tool for toxicology. Tables 1-15, referenced in this paper, are not printed in this issue of Toxicologic Pathology. They are available as downloadable text files at http://taylorandfrancis.metapress.com/openurl.asp?genre=journal&issn=0192-6233. To access them, click on the issue link for 30(4), then select this article. A download option appears at the bottom of this abstract. In order to access the full article online, you must either have an individual subscription or a member subscription accessed through www.toxpath.org.