Literature DB >> 26417340

Biomarker: the universe of chemically induced gene expression alterations in human hepatocyte.

Seddik Hammad1, Hassan Ahmed2.   

Abstract

Entities:  

Year:  2014        PMID: 26417340      PMCID: PMC4462829     

Source DB:  PubMed          Journal:  EXCLI J        ISSN: 1611-2156            Impact factor:   4.068


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In a recently published article Grinberg et al. (2014[9]) analysed gene expression alterations induced by 148 compounds in cultivated human hepatocytes. The high number of analyzed compounds allowed a comprehensive study of the key features of chemically up or downregulated genes. The authors revealed four key features that are of high interest for further studies in this field of toxicogenomics. First, a stereotypical stress response has been observed. When hepatocytes are exposed at close to cytotoxic concentrations, they respond with a very similar pattern of deregulated genes for different compounds. This stereotypical response can be differentiated from more specific gene expressions alterations that are induced only by individual or small numbers of compounds. Second, approximately 20 % of the chemically altered genes overlap with genes whose expression is deregulated in human liver disease, such as steatosis or fibrosis. Third, the numbers of biological functions of the chemically altered genes are limited. Although more than 2000 genes are up or downregulated they mostly can be assigned to the categories xenobiotic, energy and lipid metabolism, inflammation and immune response, protein modification, cytoskeletal organisation, stress response and DNA repair. Finally Grinberg et al. (2014[9]) describe a set of ‘unstable baseline genes’, whose expression is already altered by the hepatocyte isolation and cultivation process. Therefore, these genes should be interpreted with caution. Currently, identification of biomarkers of toxicity is an intensively studied field of research (Kolisetty et al., 2013[15]; Song et al., 2013[23]; Black and Read, 2013[2]; Pavanello and Lotti, 2012[20]; Kim et al., 2012[14]; Park et al., 2011[19]; Delaney et al., 2005[4]; Angerer et al., 1998[1]; Usuda et al., 1998[25]). Within this field, gene expression analyses are particularly popular, because of the possibility of genome-wide analyses (Van Kesteren et al., 2013[26]; Jennings et al., 2012[13]; Drasdo et al., 2014[5]; Hrach et al., 2011[12]; Guo et al., 2008[10]; Page et al., 2007[18]; Hammad et al., 2013[11]). For example, identification of compounds inducing developmental neurotoxicity has been made possible based on gene expression analysis of differentiating stem cells (Weng et al., 2014[28]; Zimmer et al., 2014[29]; Waldmann et al. 2014[27]; Leist et al., 2013[17]; Krug et al., 2013[16]; Powers et al., 2013[21]; Bolt, 2013[3]). Much research has been invested into the development and optimization of in vitro systems (Frey et al., 2014[6]; Theocharis et al., 1994[24]; Godoy and Bolt, 2012[7]; Schug et al., 2013[22]; Godoy et al., 2009[8]). Toxicogenomics will be particularly helpful to further develop these systems and define to which degree they correctly predict expression responses in vivo. Although a high number of studies have been published in the field of toxicogenomics, they usually only comprise a relatively small number of compounds. The study of Grinberg et al. (2014[9]) is the first that includes genome-wide expression data of more than 100 compounds and therefore is able to derive general principles how the universe of chemically altered gene is organized. The study together with the supplemental toxicotranscriptomics directory offers a valuable source for an optimal choice of candidate genes for biomarker evaluation studies.
  28 in total

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Authors:  Jeanine L Page; Mary C Johnson; Katy M Olsavsky; Steven C Strom; Helmut Zarbl; Curtis J Omiecinski
Journal:  Toxicol Sci       Date:  2007-02-27       Impact factor: 4.849

2.  Test systems of developmental toxicity: state-of-the art and future perspectives.

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Journal:  Arch Toxicol       Date:  2013-12       Impact factor: 5.153

3.  Development of an in vitro liver toxicity prediction model based on longer term primary rat hepatocyte culture.

Authors:  J Hrach; S O Mueller; P Hewitt
Journal:  Toxicol Lett       Date:  2011-07-23       Impact factor: 4.372

4.  Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

Authors:  Olivier Frey; Patrick M Misun; David A Fluri; Jan G Hengstler; Andreas Hierlemann
Journal:  Nat Commun       Date:  2014-06-30       Impact factor: 14.919

5.  Urinary biomarkers monitoring for experimental fluoride nephrotoxicity.

Authors:  K Usuda; K Kono; T Dote; K Nishiura; K Miyata; H Nishiura; M Shimahara; K Sugimoto
Journal:  Arch Toxicol       Date:  1998       Impact factor: 5.153

6.  Extracellular matrix modulates sensitivity of hepatocytes to fibroblastoid dedifferentiation and transforming growth factor beta-induced apoptosis.

Authors:  Patricio Godoy; Jan G Hengstler; Iryna Ilkavets; Christoph Meyer; Anastasia Bachmann; Alexandra Müller; Gregor Tuschl; Stefan O Mueller; Steven Dooley
Journal:  Hepatology       Date:  2009-06       Impact factor: 17.425

7.  Suppression of interleukin-1 beta and tumour necrosis factor-alpha biosynthesis by cadmium in in vitro activated human peripheral blood mononuclear cells.

Authors:  S E Theocharis; V L Souliotis; P G Panayiotidis
Journal:  Arch Toxicol       Date:  1994       Impact factor: 5.153

8.  Human embryonic stem cell-derived test systems for developmental neurotoxicity: a transcriptomics approach.

Authors:  Anne K Krug; Raivo Kolde; John A Gaspar; Eugen Rempel; Nina V Balmer; Kesavan Meganathan; Kinga Vojnits; Mathurin Baquié; Tanja Waldmann; Roberto Ensenat-Waser; Smita Jagtap; Richard M Evans; Stephanie Julien; Hedi Peterson; Dimitra Zagoura; Suzanne Kadereit; Daniel Gerhard; Isaia Sotiriadou; Michael Heke; Karthick Natarajan; Margit Henry; Johannes Winkler; Rosemarie Marchan; Luc Stoppini; Sieto Bosgra; Joost Westerhout; Miriam Verwei; Jaak Vilo; Andreas Kortenkamp; Jürgen Hescheler; Ludwig Hothorn; Susanne Bremer; Christoph van Thriel; Karl-Heinz Krause; Jan G Hengstler; Jörg Rahnenführer; Marcel Leist; Agapios Sachinidis
Journal:  Arch Toxicol       Date:  2012-11-21       Impact factor: 5.153

9.  Design principles of concentration-dependent transcriptome deviations in drug-exposed differentiating stem cells.

Authors:  Tanja Waldmann; Eugen Rempel; Nina V Balmer; André König; Raivo Kolde; John Antonydas Gaspar; Margit Henry; Jürgen Hescheler; Agapios Sachinidis; Jörg Rahnenführer; Jan G Hengstler; Marcel Leist
Journal:  Chem Res Toxicol       Date:  2014-01-21       Impact factor: 3.739

10.  Profiling of drugs and environmental chemicals for functional impairment of neural crest migration in a novel stem cell-based test battery.

Authors:  B Zimmer; G Pallocca; N Dreser; S Foerster; T Waldmann; J Westerhout; S Julien; K H Krause; C van Thriel; J G Hengstler; A Sachinidis; S Bosgra; M Leist
Journal:  Arch Toxicol       Date:  2014-04-02       Impact factor: 5.153

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