A gene expression signature that predicts the future onset of drug-induced renal tubular toxicity

被引:70
作者
Fielden, MR
Eynon, BP
Natsoulis, G
Jarnagin, K
Banas, D
Kolaja, KL
机构
[1] Iconix Pharmaceut Inc, Mountain View, CA 94043 USA
[2] Expt Pathol Labs, Herndon, VA USA
关键词
biomarkers; toxicogenomics; renal; genomics; microarray; preclinical research and development;
D O I
10.1080/01926230500321213
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
One application of genomics in drug safety assessment is the identification of biomarkers to predict compound toxicity before it is detected using traditional approaches, such as histopathology. However, many genomic approaches have failed to demonstrate superiority to traditional methods, have not been appropriately validated on external samples, or have been derived using small data sets, thus raising concerns of their general applicability. Using kidney gene expression profiles from male SD rats treated with 64 nephrotoxic or non-nephrotoxic compound treatments, a gene signature consisting of only 35 genes was derived to predict the future development of renal tubular degeneration weeks before it appears histologically following short-term test compound administration. By comparison, histopathology or clinical chemistry fails to predict the future development of tubular degeneration, thus demonstrating the enhanced sensitivity of gene expression relative to traditional approaches. In addition, the performance of the signature was validated on 21 independent compound treatments structurally distinct from the training set. The signature correctly predicted the ability of test compounds to induce tubular degeneration 76% of the time, far better than traditional approaches. This study demonstrates that genomic data can be more sensitive than traditional methods for the early prediction of compound-induced pathology in the kidney.
引用
收藏
页码:675 / 683
页数:9
相关论文
共 23 条
[1]   Identification of putative gene-based markers of renal toxicity [J].
Amin, RA ;
Vickers, AE ;
Sistare, F ;
Thompson, KL ;
Roman, RJ ;
Lawton, M ;
Kramer, J ;
Hamadeh, HK ;
Collins, J ;
Grissom, S ;
Bennett, L ;
Tucker, CJ ;
Wild, S ;
Kind, C ;
Oreffo, V ;
Davis, JW ;
Curtiss, S ;
Naciff, JM ;
Cunningham, M ;
Tennant, R ;
Stevens, J ;
Car, B ;
Bertram, TA ;
Afsharil, CA .
ENVIRONMENTAL HEALTH PERSPECTIVES, 2004, 112 (04) :465-479
[2]   Albumin induces NF-κB expression in human proximal tubule-derived cells (IHKE-1) [J].
Drumm, K ;
Bauer, B ;
Freudinger, R ;
Gekle, M .
CELLULAR PHYSIOLOGY AND BIOCHEMISTRY, 2002, 12 (04) :187-196
[3]  
ELGHAOUI L, 2003, UCBCSD031279 EECS
[4]   Development of a large-scale chemogenomics database to improve drug candidate selection and to understand mechanisms of chemical toxicity and action [J].
Ganter, B ;
Tugendreich, S ;
Pearson, CI ;
Ayanoglu, E ;
Baumhueter, S ;
Bostian, KA ;
Brady, L ;
Browne, LJ ;
Calvin, JT ;
Day, GJ ;
Breckenridge, N ;
Dunlea, S ;
Eynon, BP ;
Furness, LM ;
Ferng, J ;
Fielden, MR ;
Fujimoto, SY ;
Gong, L ;
Hu, C ;
Idury, R ;
Judo, MSB ;
Kolaja, KL ;
Lee, MD ;
McSorley, C ;
Minor, JM ;
Nair, RV ;
Natsoulis, G ;
Nguyen, P ;
Nicholson, SM ;
Pham, H ;
Roter, AH ;
Sun, DX ;
Tan, SQ ;
Thode, S ;
Tolley, AM ;
Vladimirova, A ;
Yang, J ;
Zhou, ZM ;
Jarnagin, K .
JOURNAL OF BIOTECHNOLOGY, 2005, 119 (03) :219-244
[5]  
Hamadeh HK, 2002, TOXICOL SCI, V67, P219, DOI 10.1093/toxsci/67.2.219
[6]   Methapyrilene toxicity: Anchorage of pathologic observations to gene expression alterations [J].
Hamadeh, HK ;
Knight, BL ;
Haugen, AC ;
Sieber, S ;
Amin, RP ;
Bushel, PR ;
Stoll, R ;
Blanchard, K ;
Jayadev, S ;
Tennant, RW ;
Cunningham, ML ;
Afshari, CA ;
Paules, RS .
TOXICOLOGIC PATHOLOGY, 2002, 30 (04) :470-482
[7]   Diclofenac induced in vivo nephrotoxicity may involve oxidative stress-mediated massive genomic DNA fragmentation and apoptotic cell death [J].
Hickey, EJ ;
Raje, RR ;
Redd, VE ;
Gross, SM ;
Ray, SD .
FREE RADICAL BIOLOGY AND MEDICINE, 2001, 31 (02) :139-152
[8]  
Kocaoglu Sukran, 1997, Archivum Immunologiae et Therapiae Experimentalis, V45, P73
[9]  
LAU SS, 1984, J PHARMACOL EXP THER, V230, P360
[10]   Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures [J].
Natsoulis, G ;
El Ghaoui, L ;
Lanckriet, GRG ;
Tolley, AM ;
Leroy, F ;
Dunlea, S ;
Eynon, BP ;
Pearson, CI ;
Tugendreich, S ;
Jarnagin, K .
GENOME RESEARCH, 2005, 15 (05) :724-736