Clustering of Hepatotoxins Based on Mechanism of Toxicity Using Gene Expression Profiles

Waring, Jeffrey F.; Jolly, Robert A.; Ciurlionis, Rita; Lum, Pek Yee; Præstgaard, Jens; Morfitt, David C.; Buratto, Bruno; Roberts, Chris; Schadt, Eric E.; Ulrich, Roger G.

doi:10.1006/taap.2001.9243

Cited by 361 publications

(161 citation statements)

References 48 publications

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“…On the other hand, the repressed genes classified into this process were only SMUG1 in the TCE treatment and RAD23B in the DMN and TCE treatments. Furthermore, CDKN1A (p21/Waf1), which has been reported to be associated with cell cycle arrest following DNA damage [Waring et al, 2001;Lee et al, 2006], was upregulated with 3.5-and 2.5-folds in the DMN and TPA treatments, respectively.…”

Section: Genes Altered By Model Chemical Exposuresmentioning

confidence: 99%

Comparison of gene expression profiles in HepG2 cells exposed to arsenic, cadmium, nickel, and three model carcinogens for investigating the mechanisms of metal carcinogenesis

Kawata

Shimazaki

Okabe

2008

Environ and Mol Mutagen

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Carcinogenesis is an important chronic toxicity of metals and metalloids, although their mechanisms of action are still unclear. Comparison of gene expression patterns induced by carcinogenic metals, metalloids, and model carcinogens would give an insight into understanding of their carcinogenic mechanisms. In this study, we examined the gene expression alteration in human hepatoma cell line, HepG2, after exposing to two metals (cadmium and nickel), a metalloid (arsenic), and three model carcinogenic chemicals N-dimethylnitrosoamine (DMN), 12-O-tetradecanoylphorbol-13-acetate (TPA), and tetrachloroethylene (TCE) using DNA microarrays with 8,795 human genes. Of the genes altered by As, Cd, and Ni exposures, 31-55% were overlapped with those altered by three model carcinogenic chemical exposures in our experiments. In particular, the metals and metalloid shared certain characteristics with TPA and TCE in remarkable upregulations of the genes associated with progression of cell cycle, which might play a central role in As, Cd, and Ni carcinogenesis. This characteristic of gene expression alteration was partially counteracted by intracellular accumulation of vitamin C in Asexposed cells, whereas the number of cell-cycle associated genes was increased in Cd-and Niexposed cells. In our experimental conditions, ROS might have an accelerative effect on the cell proliferation mechanisms of As, but have an inhibitory effect on those of other two heavy metals. Furthermore, based on the results of Q-PCR, the oncogene PTTG1, which was upregulated by all carcinogenic chemical exposures in the array experiments, might be a useful biomarker for evaluation of the carcinogenesis of inorganic carcinogens. Environ. Mol. Mutagen. 50:46-59, 2009.

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Section: Genes Altered By Model Chemical Exposuresmentioning

confidence: 99%

Comparison of gene expression profiles in HepG2 cells exposed to arsenic, cadmium, nickel, and three model carcinogens for investigating the mechanisms of metal carcinogenesis

Kawata

Shimazaki

Okabe

2008

Environ and Mol Mutagen

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“…In medicine, initial studies proved that classification of cancer types was possible based on their gene expression profile (2), leading to the development of microarray based tests that are now used clinically to predict cancer prognosis (3). Toxicological studies have also shown the ability to classify chemicals and predict their mode of toxicity on the basis of their gene expression profiles (4).…”

Section: Introductionmentioning

confidence: 99%

Gene Expression Profiling in Daphnia magna, Part II: Validation of a Copper Specific Gene Expression Signature with Effluent from Two Copper Mines in California

Poynton

Zuzow

Loguinov

et al. 2008

Environ. Sci. Technol.

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Genomic technologies show great potential for classifying disease states and toxicological impacts from exposure to chemicals into functional categories. In environmental monitoring, the ability to classify field samples and predict the pollutants present in these samples could contribute to monitoring efforts and the diagnosis of contaminated sites. Using gene expression analysis, we challenged our custom Daphnia magna cDNA microarray to determine the presence of a specific metal toxicant in blinded field samples collected from two copper mines in California. We compared the gene expression profiles from our field samples to previously established expression profiles for Cu, Cd, and Zn. The expression profiles from the Cu-containing field samples clustered with the laboratory-exposed Cu-specific gene expression profiles and included genes previously identified as copper biomarkers, verifying that gene expression analysis can predict environmental exposure to a specific pollutant. In addition, our study revealed that upstream field samples containing undetectable levels of Cu caused the differential expression of only a few genes, lending support for the concept of a no observed transcriptional effect level (NOTEL). If confirmed by further studies, the NOTEL may play an important role in discriminating polluted and nonpolluted sites in future monitoring efforts.

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“…M essenger RNA samples are often pooled in a microarray experiment out of necessity (1,2) or in an effort to reduce the effects of biological variation (3)(4)(5)(6). The idea behind the latter motivation is that differences due to subject-to-subject variation will be minimized, making substantive features easier to find (7)(8)(9)(10)(11)(12)(13).…”

mentioning

confidence: 99%

On the utility of pooling biological samples in microarray experiments

Kendziorski

Irizarry

Chen

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

444

377

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Over 15% of the data sets catalogued in the Gene Expression Omnibus Database involve RNA samples that have been pooled before hybridization. Pooling affects data quality and inference, but the exact effects are not yet known because pooling has not been systematically studied in the context of microarray experiments. Here we report on the results of an experiment designed to evaluate the utility of pooling and the impact on identifying differentially expressed genes. We find that inference for most genes is not adversely affected by pooling, and we recommend that pooling be done when fewer than three arrays are used in each condition. For larger designs, pooling does not significantly improve inferences if few subjects are pooled. The realized benefits in this case do not outweigh the price paid for loss of individual specific information. Pooling is beneficial when many subjects are pooled, provided that independent samples contribute to multiple pools.

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Clustering of Hepatotoxins Based on Mechanism of Toxicity Using Gene Expression Profiles

Cited by 361 publications

References 48 publications

Comparison of gene expression profiles in HepG2 cells exposed to arsenic, cadmium, nickel, and three model carcinogens for investigating the mechanisms of metal carcinogenesis

Comparison of gene expression profiles in HepG2 cells exposed to arsenic, cadmium, nickel, and three model carcinogens for investigating the mechanisms of metal carcinogenesis

Gene Expression Profiling in Daphnia magna, Part II: Validation of a Copper Specific Gene Expression Signature with Effluent from Two Copper Mines in California

On the utility of pooling biological samples in microarray experiments

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