Literature DB >> 24197968

Discovery of characteristic molecular signatures for the simultaneous prediction and detection of environmental pollutants.

Mi-Kyung Song1, Han-Seam Choi, Yong-Keun Park, Jae-Chun Ryu.   

Abstract

Gene expression data may be very promising for the classification of toxicant types, but the development and application of transcriptomic-based gene classifiers for environmental toxicological applications are lacking compared to the biomedical sciences. Also, simultaneous classification across a set of toxicant types has not been investigated extensively. In the present study, we determined the transcriptomic response to three types of ubiquitous toxicants exposure in two types of human cell lines (HepG2 and HL-60), which are useful in vitro human model for evaluation of toxic substances that may affect human hepatotoxicity (e.g., polycyclic aromatic hydrocarbon [PAH] and persistent organic pollutant [POP]) and human leukemic myelopoietic proliferation (e.g., volatile organic compound [VOC]). The findings demonstrate characteristic molecular signatures that facilitated discrimination and prediction of the toxicant type. To evaluate changes in gene expression levels after exposure to environmental toxicants, we utilized 18 chemical substances; nine PAH toxicants, six VOC toxicants, and three POP toxicants. Unsupervised gene expression analysis resulted in a characteristic molecular signature for each toxicant group, and combination analysis of two separate multi-classifications indicated 265 genes as surrogate markers for predicting each group of toxicants with 100 % accuracy. Our results suggest that these expression signatures can be used as predictable and discernible surrogate markers for detection and prediction of environmental toxicant exposure. Furthermore, this approach could easily be extended to screening for other types of environmental toxicants.

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Year:  2013        PMID: 24197968     DOI: 10.1007/s11356-013-2198-4

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  44 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2001-12-11       Impact factor: 11.205

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8.  Identification of molecular signatures predicting the carcinogenicity of polycyclic aromatic hydrocarbons (PAHs).

Authors:  Mi-Kyung Song; Mee Song; Han-Seam Choi; Youn-Jung Kim; Yong-Keun Park; Jae-Chun Ryu
Journal:  Toxicol Lett       Date:  2012-05-01       Impact factor: 4.372

9.  From genomics to chemical genomics: new developments in KEGG.

Authors:  Minoru Kanehisa; Susumu Goto; Masahiro Hattori; Kiyoko F Aoki-Kinoshita; Masumi Itoh; Shuichi Kawashima; Toshiaki Katayama; Michihiro Araki; Mika Hirakawa
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

10.  Discrimination of carcinogens by hepatic transcript profiling in rats following 28-day administration.

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Journal:  Cancer Inform       Date:  2009-11-13
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  1 in total

1.  Comparative Analysis of Transcriptional Responses to Genotoxic and Non-Genotoxic Agents in the Blood Cell Model TK6 and the Liver Model HepaRG.

Authors:  Katrin Kreuzer; Heike Sprenger; Albert Braeuning
Journal:  Int J Mol Sci       Date:  2022-03-22       Impact factor: 5.923

  1 in total

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