title: Identification of genomic biomarkers for concurrent diagnosis of drug-induced renal tubular injury using a large-scale toxicogenomics database.
abstract: Drug-induced renal tubular injury is one of the major concerns in preclinical safety evaluations. Toxicogenomics is becoming a generally accepted approach for identifying chemicals with potential safety problems. In the present study, we analyzed 33 nephrotoxicants and 8 non-nephrotoxic hepatotoxicants to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. The compounds were administered orally or intravenously once daily to male Sprague-Dawley rats. The animals were exposed to four different doses of the compounds, and kidney tissues were collected on days 4, 8, 15, and 29. Gene expression profiles were generated from kidney RNA by using Affymetrix GeneChips and analyzed in conjunction with the histopathological changes. We used the filter-type gene selection algorithm based on t-statistics conjugated with the SVM classifier, and achieved a sensitivity of 90% with a selectivity of 90%. Then, 92 genes were extracted as the genomic biomarker candidates that were used to construct the classifier. The gene list contains well-known biomarkers, such as Kidney injury molecule 1, Ceruloplasmin, Clusterin, Tissue inhibitor of metallopeptidase 1, and also novel biomarker candidates. Most of the genes involved in tissue remodeling, the immune/inflammatory response, cell adhesion/proliferation/migration, and metabolism were predominantly up-regulated. Down-regulated genes participated in cell adhesion/proliferation/migration, membrane transport, and signal transduction. Our classifier has better prediction accuracy than any of the well-known biomarkers. Therefore, the toxicogenomics approach would be useful for concurrent diagnosis of renal tubular injury.
authors.affiliation: Developmental Research Laboratories, Shionogi & Co., Ltd., 3-1-1, Futaba-cho, Toyonaka, Osaka, Japan.
authors.forename: Chiaki
authors.initials: C
authors.lastname: Kondo
authors.forename: Yohsuke
authors.initials: Y
authors.lastname: Minowa
authors.forename: Takeki
authors.initials: T
authors.lastname: Uehara
authors.forename: Yasushi
authors.initials: Y
authors.lastname: Okuno
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Nakatsu
authors.forename: Atsushi
authors.initials: A
authors.lastname: Ono
authors.forename: Toshiyuki
authors.initials: T
authors.lastname: Maruyama
authors.forename: Ikuo
authors.initials: I
authors.lastname: Kato
authors.forename: Jyoji
authors.initials: J
authors.lastname: Yamate
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Yamada
authors.forename: Yasuo
authors.initials: Y
authors.lastname: Ohno
authors.forename: Tetsuro
authors.initials: T
authors.lastname: Urushidani
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000032:analysis*; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions; D005544:Forecasting; D007674:Kidney Diseases / Q000139:chemically induced* / Q000235:genetics* / Q000473:pathology; D007684:Kidney Tubules / Q000378:metabolism* / Q000473:pathology; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis; D051381:Rats; D017207:Rats, Sprague-Dawley; D043922:Toxicogenetics / Q000145:classification / Q000379:methods*
chemical_list: D015415:Biomarkers