Literature DB >> 15805072

Prediction of nephrotoxicant action and identification of candidate toxicity-related biomarkers.

Sushil K Thukral1, Paul J Nordone, Rong Hu, Leah Sullivan, Eric Galambos, Vincent D Fitzpatrick, Laura Healy, Michael B Bass, Mary E Cosenza, Cynthia A Afshari.   

Abstract

A vast majority of pharmacological compounds and their metabolites are excreted via the urine, and within the complex structure of the kidney,the proximal tubules are a main target site of nephrotoxic compounds. We used the model nephrotoxicants mercuric chloride, 2-bromoethylamine hydrobromide, hexachlorobutadiene, mitomycin, amphotericin, and puromycin to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. Male Sprague-Dawley rats were dosed via intraperitoneal injection once daily for mercuric chloride and amphotericin (up to 7 doses), while a single dose was given for all other compounds. Animals were exposed to 2 different doses of these compounds and kidney tissues were collected on day 1, 3, and 7 postdosing. Gene expression profiles were generated from kidney RNA using 17K rat cDNA dual dye microarray and analyzed in conjunction with histopathology. Analysis of gene expression profiles showed that the profiles clustered based on similarities in the severity and type of pathology of individual animals. Further, the expression changes were indicative of tubular toxicity showing hallmarks of tubular degeneration/regeneration and necrosis. Use of gene expression data in predicting the type of nephrotoxicity was then tested with a support vector machine (SVM)-based approach. A SVM prediction module was trained using 120 profiles of total profiles divided into four classes based on the severity of pathology and clustering. Although mitomycin C and amphotericin B treatments did not cause toxicity, their expression profiles were included in the SVM prediction module to increase the sample size. Using this classifier, the SVM predicted the type of pathology of 28 test profiles with 100% selectivity and 82% sensitivity. These data indicate that valid predictions could be made based on gene expression changes from a small set of expression profiles. A set of potential biomarkers showing a time- and dose-response with respect to the progression of proximal tubular toxicity were identified. These include several transporters (Slc21a2, Slc15, Slc34a2), Kim 1, IGFbp-1, osteopontin, alpha-fibrinogen, and Gstalpha.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15805072     DOI: 10.1080/01926230590927230

Source DB:  PubMed          Journal:  Toxicol Pathol        ISSN: 0192-6233            Impact factor:   1.902


  23 in total

Review 1.  Toxicogenomics in drug discovery and drug development: potential applications and future challenges.

Authors:  Tin Oo Khor; Sherif Ibrahim; Ah-Ng Tony Kong
Journal:  Pharm Res       Date:  2006-08       Impact factor: 4.200

Review 2.  Mass spectrometry based proteomics in urine biomarker discovery.

Authors:  Dan Theodorescu; Harald Mischak
Journal:  World J Urol       Date:  2007-08-17       Impact factor: 4.226

Review 3.  Use of transcriptomics in understanding mechanisms of drug-induced toxicity.

Authors:  Yuxia Cui; Richard S Paules
Journal:  Pharmacogenomics       Date:  2010-04       Impact factor: 2.533

4.  High-resolution proteome/peptidome analysis of peptides and low-molecular-weight proteins in urine.

Authors:  Harald Mischak; Bruce A Julian; Jan Novak
Journal:  Proteomics Clin Appl       Date:  2007-07-10       Impact factor: 3.494

Review 5.  Blood transcriptomics: applications in toxicology.

Authors:  Pius Joseph; Christina Umbright; Rajendran Sellamuthu
Journal:  J Appl Toxicol       Date:  2013-03-01       Impact factor: 3.446

6.  Mechanisms of acute kidney injury induced by experimental Lonomia obliqua envenomation.

Authors:  Markus Berger; Lucélia Santi; Walter O Beys-da-Silva; Fabrício Marcus Silva Oliveira; Marcelo Vidigal Caliari; John R Yates; Maria Aparecida Ribeiro Vieira; Jorge Almeida Guimarães
Journal:  Arch Toxicol       Date:  2014-05-06       Impact factor: 5.153

7.  Metabolomics for the early detection of cisplatin-induced nephrotoxicity.

Authors:  Takeshi Ezaki; Shin Nishiumi; Takeshi Azuma; Masaru Yoshida
Journal:  Toxicol Res (Camb)       Date:  2017-08-29       Impact factor: 3.524

8.  Performance of urinary and gene expression biomarkers in detecting the nephrotoxic effects of melamine and cyanuric acid following diverse scenarios of co-exposure.

Authors:  Omari Bandele; Luísa Camacho; Martine Ferguson; Renate Reimschuessel; Cynthia Stine; Thomas Black; Nicholas Olejnik; Zachary Keltner; Michael Scott; Gonçalo Gamboa da Costa; Robert Sprando
Journal:  Food Chem Toxicol       Date:  2012-09-26       Impact factor: 6.023

9.  Genomic-derived markers for early detection of calcineurin inhibitor immunosuppressant-mediated nephrotoxicity.

Authors:  Yuxia Cui; Qihong Huang; James Todd Auman; Brian Knight; Xidong Jin; Kerry T Blanchard; Jeff Chou; Supriya Jayadev; Richard S Paules
Journal:  Toxicol Sci       Date:  2011-08-24       Impact factor: 4.849

10.  Kidney injury molecule-1 expression in transplant biopsies is a sensitive measure of cell injury.

Authors:  P L Zhang; L I Rothblum; W K Han; T M Blasick; S Potdar; J V Bonventre
Journal:  Kidney Int       Date:  2007-12-26       Impact factor: 10.612

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.