Skip to main content

Advertisement

Log in

Biomarkers for Drug-Induced Renal Damage and Nephrotoxicity—An Overview for Applied Toxicology

  • Review Article
  • Theme: Biomarkers of Drug-Induced Organ Toxicity
  • Published:
The AAPS Journal Aims and scope Submit manuscript

Abstract

The detection of acute kidney injury (AKI) and the monitoring of chronic kidney disease (CKD) is becoming more important in industrialized countries. Because of the direct relation of kidney damage to the increasing age of the population, as well as the connection to other diseases like diabetes mellitus and congestive heart failure, renal diseases/failure has increased in the last decades. In addition, drug-induced kidney injury, especially of patients in intensive care units, is very often a cause of AKI. The need for diagnostic tools to identify drug-induced nephrotoxicity has been emphasized by the ICH-regulated agencies. This has lead to multiple national and international projects focusing on the identification of novel biomarkers to enhance drug development. Several parameters related to AKI or CKD are known and have been used for several decades. Most of these markers deliver information only when renal damage is well established, as is the case for serum creatinine. The field of molecular toxicology has spawned new options of the detection of nephrotoxicity. These new developments lead to the identification of urinary protein biomarkers, including Kim-1, clusterin, osteopontin or RPA-1, and other transcriptional biomarkers which enable the earlier detection of AKI and deliver further information about the area of nephron damage or the underlying mechanism. These biomarkers were mainly identified and qualified in rat but also for humans, several biomarkers have been described and now have to be validated. This review will give an overview of traditional and novel tools for the detection of renal damage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

REFERENCES

  1. Frost & Sullivan (2007) Rang, HP (eds). Drug discovery and development. Churchill Livingstone: Elsevier

  2. Werner M, Costa MJ, Mitchell LG, Nayar R. Nephrotoxicity of xenobiotics. Clin Chim Acta. 1995;237(1–2):107–54.

    Article  PubMed  CAS  Google Scholar 

  3. Devarajan P. Novel biomarkers for the early prediction of acute kidney injury. Cancer Therapy. 2005;3:477–88.

    Google Scholar 

  4. Dieterle F, Sistare F, Goodsaid F, Papaluca M, Ozer JS, Webb CP, et al. Renal biomarker qualification submission: a dialog between the FDA-EMEA and Predictive Safety Testing Consortium. Nat Biotechnol. 2010;28(5):455–62.

    Article  PubMed  CAS  Google Scholar 

  5. Delanghe JR, Speeckaert MM. Creatinine determination according to Jaffe—what does it stand for? NDT Plus. 2011;4(2):83–6.

    Article  Google Scholar 

  6. Bateman JC, Barberio JR, Grice P, Klopp CT, Pierpont H. Fatal complications of intensive antibiotic therapy in patients with neoplastic disease. AMA Arch Intern Med. 1952;90(6):763–73.

    PubMed  CAS  Google Scholar 

  7. Pfaller W, Gstraunthaler G. Nephrotoxicity testing in vitro—what we know and what we need to know. Environ Health Perspect. 1998;106 Suppl 2:559–69.

    Article  PubMed  CAS  Google Scholar 

  8. Schrier RW. Blood urea nitrogen and serum creatinine: not married in heart failure. Circ Heart Fail. 2008;1(1):2–5.

    Article  PubMed  CAS  Google Scholar 

  9. Sanderson IR, Walker WA. Development of the gastrointestinal tract. 1st ed. Ontario, Canada: B.C. Decker; 1999.

    Google Scholar 

  10. Urashima M, Toyoda S, Nakano T, Matsuda S, Kobayashi N, Kitajima H, et al. BUN/Cr ratio as an index of gastrointestinal bleeding mass in children. J Pediatr Gastroenterol Nutr. 1992;15(1):89–92.

    Article  PubMed  CAS  Google Scholar 

  11. Berk L, Rana S. Hypovolemia and dehydration in the oncology patient. J Support Oncol. 2006;4(9):447–54. discussion 55–7.

    PubMed  Google Scholar 

  12. Walid MS. Blood urea nitrogen/creatinine ratio in rhabdomyolysis. Indian J Nephrol. 2008;18(4):173–4.

    Article  PubMed  CAS  Google Scholar 

  13. Mendelssohn DC, Barrett BJ, Brownscombe LM, Ethier J, Greenberg DE, Kanani SD, et al. Elevated levels of serum creatinine: recommendations for management and referral. CMAJ. 1999;161(4):413–7.

    PubMed  CAS  Google Scholar 

  14. Sibai BM, Stella CL. Diagnosis and management of atypical preeclampsia-eclampsia. Am J Obstet Gynecol. 2009;200(5):481. e1-7.

    Article  PubMed  Google Scholar 

  15. Martin Jr JN, May WL, Magann EF, Terrone DA, Rinehart BK, Blake PG. Early risk assessment of severe preeclampsia: admission battery of symptoms and laboratory tests to predict likelihood of subsequent significant maternal morbidity. Am J Obstet Gynecol. 1999;180(6 Pt 1):1407–14.

    Article  PubMed  Google Scholar 

  16. Grossman RA, Hamilton RW, Morse BM, Penn AS, Goldberg M. Nontraumatic rhabdomyolysis and acute renal failure. N Engl J Med. 1974;291(16):807–11.

    Article  PubMed  CAS  Google Scholar 

  17. Uchida K, Gotoh A. Measurement of cystatin-C and creatinine in urine. Clin Chim Acta. 2002;323(1–2):121–8.

    Article  PubMed  CAS  Google Scholar 

  18. Bokenkamp A, Domanetzki M, Zinck R, Schumann G, Byrd D, Brodehl J. Cystatin C—a new marker of glomerular filtration rate in children independent of age and height. Pediatrics. 1998;101(5):875–81.

    Article  PubMed  CAS  Google Scholar 

  19. Fliser D, Ritz E. Serum cystatin C concentration as a marker of renal dysfunction in the elderly. Am J Kidney Dis. 2001;37(1):79–83.

    PubMed  CAS  Google Scholar 

  20. Aardema MJ, MacGregor JT. Toxicology and genetic toxicology in the new era of "toxicogenomics": impact of "-omics" technologies. Mutat Res. 2002;499(1):13–25.

    Article  PubMed  CAS  Google Scholar 

  21. Edwards SW, Preston RJ. Systems biology and mode of action based risk assessment. Toxicol Sci. 2008;106(2):312–8.

    Article  PubMed  CAS  Google Scholar 

  22. Zidek N, Hellmann J, Kramer PJ, Hewitt PG. Acute hepatotoxicity: a predictive model based on focused illumina microarrays. Toxicol Sci. 2007;99(1):289–302.

    Article  PubMed  CAS  Google Scholar 

  23. Amin RP, Vickers AE, Sistare F, Thompson KL, Roman RJ, Lawton M, et al. Identification of putative gene based markers of renal toxicity. Environ Health Perspect. 2004;112(4):465–79.

    Article  PubMed  CAS  Google Scholar 

  24. Kramer JA, Pettit SD, Amin RP, Bertram TA, Car B, Cunningham M, et al. Overview on the application of transcription profiling using selected nephrotoxicants for toxicology assessment. Environ Health Perspect. 2004;112(4):460–4.

    Article  PubMed  CAS  Google Scholar 

  25. Thompson KL, Afshari CA, Amin RP, Bertram TA, Car B, Cunningham M, et al. Identification of platform-independent gene expression markers of cisplatin nephrotoxicity. Environ Health Perspect. 2004;112(4):488–94.

    Article  PubMed  CAS  Google Scholar 

  26. Mattes WB, Pettit SD, Sansone SA, Bushel PR, Waters MD. Database development in toxicogenomics: issues and efforts. Environ Health Perspect. 2004;112(4):495–505.

    Article  PubMed  CAS  Google Scholar 

  27. Ozer JS, Dieterle F, Troth S, Perentes E, Cordier A, Verdes P, et al. A panel of urinary biomarkers to monitor reversibility of renal injury and a serum marker with improved potential to assess renal function. Nat Biotechnol. 2010;28(5):486–94.

    Article  PubMed  CAS  Google Scholar 

  28. Vaidya VS, Ozer JS, Dieterle F, Collings FB, Ramirez V, Troth S, et al. Kidney injury molecule-1 outperforms traditional biomarkers of kidney injury in preclinical biomarker qualification studies. Nat Biotechnol. 2010;28(5):478–85.

    Article  PubMed  CAS  Google Scholar 

  29. Rached E, Hoffmann D, Blumbach K, Weber K, Dekant W, Mally A. Evaluation of putative biomarkers of nephrotoxicity after exposure to ochratoxin a in vivo and in vitro. Toxicol Sci. 2008;103(2):371–81.

    Article  PubMed  CAS  Google Scholar 

  30. Vaidya VS, Ford GM, et al. A rapid urine test for early detection of kidney injury. Kidney Int. 2009;76(1):108–14.

    Article  PubMed  CAS  Google Scholar 

  31. Alexopoulos LG, Saez-Rodriguez J, Espelin CW. High-throughput protein-based technologies and computational models for drug development, efficacy, and toxicity. In: Ekins S, Xu JJ, editors. Drug efficacy, safety, and biologics discovery: emerging technologies and tools. Hoboken, NJ, USA: Wiley; 2008.

    Google Scholar 

  32. Jantos-Siwy J, Schiffer E, Brand K, Schumann G, Rossing K, Delles C, et al. Quantitative urinary proteome analysis for biomarker evaluation in chronic kidney disease. J Proteome Res. 2009;8(1):268–81.

    Article  PubMed  CAS  Google Scholar 

  33. Mischak H, Delles C, Klein J, Schanstra JP. Urinary proteomics based on capillary electrophoresis-coupled mass spectrometry in kidney disease: discovery and validation of biomarkers, and clinical application. Adv Chronic Kidney Dis. 2010;17(6):493–506.

    Article  PubMed  Google Scholar 

  34. Zangvil E. Compugen, Ltd. Pharmacogenomics. 2007;8(10):1461–3.

    Article  PubMed  Google Scholar 

  35. Thukral SK, Nordone PJ, Hu R, Sullivan L, Galambos E, Fitzpatrick VD, et al. Prediction of nephrotoxicant action and identification of candidate toxicity-related biomarkers. Toxicol Pathol. 2005;33(3):343–55.

    Article  PubMed  CAS  Google Scholar 

  36. Ebbels TM, Keun HC, Beckonert OP, Bollard ME, Lindon JC, Holmes E, et al. Prediction and classification of drug toxicity using probabilistic modeling of temporal metabolic data: the consortium on metabonomic toxicology screening approach. J Proteome Res. 2007;6(11):4407–22.

    Article  PubMed  CAS  Google Scholar 

  37. Boudonck KJ, Mitchell MW, Nemet L, Keresztes L, Nyska A, Shinar D, et al. Discovery of metabolomics biomarkers for early detection of nephrotoxicity. Toxicol Pathol. 2009;37(3):280–92.

    Article  PubMed  CAS  Google Scholar 

  38. Saal S, Harvey SJ. MicroRNAs and the kidney: coming of age. Curr Opin Nephrol Hypertens. 2009;18(4):317–23.

    Article  PubMed  CAS  Google Scholar 

  39. Melkonyan HS, Feaver WJ, Meyer E, Scheinker V, Shekhtman EM, Xin Z, et al. Transrenal nucleic acids: from proof of principle to clinical tests. Ann N Y Acad Sci. 2008;1137:73–81.

    Article  PubMed  CAS  Google Scholar 

  40. Simpson RJ, Lim JW, Moritz RL, Mathivanan S. Exosomes: proteomic insights and diagnostic potential. Expert Rev Proteomics. 2009;6(3):267–83.

    Article  PubMed  CAS  Google Scholar 

  41. Bhatt K, Zhou L, Mi QS, Huang S, She JX, Dong Z. MicroRNA-34a is induced via p53 during cisplatin nephrotoxicity and contributes to cell survival. Mol Med. 2010;16(9–10):409–16.

    PubMed  CAS  Google Scholar 

  42. Han WK, Bailly V, Abichandani R, Thadhani R, Bonventre JV. Kidney Injury Molecule-1 (KIM-1): a novel biomarker for human renal proximal tubule injury. Kidney Int. 2002;62(1):237–44.

    Article  PubMed  CAS  Google Scholar 

  43. Rosen S, Heyman S. Concerns about KIM-1 as a urinary biomarker for acute tubular necrosis (ATN). Kidney Int. 2003;63(5):1955.

    Article  PubMed  Google Scholar 

  44. Dyrskjot L, Ostenfeld MS, Bramsen JB, Silahtaroglu AN, Lamy P, Ramanathan R, et al. Genomic profiling of microRNAs in bladder cancer: miR-129 is associated with poor outcome and promotes cell death in vitro. Cancer Res. 2009;69(11):4851–60.

    Article  PubMed  CAS  Google Scholar 

  45. Waters MD, Fostel JM. Toxicogenomics and systems toxicology: aims and prospects. Nat Rev Genet. 2004;5(12):936–48.

    Article  PubMed  CAS  Google Scholar 

  46. Colle A, Tavera C, Laurent P, Leung-Tack J, Girolami JP. Direct radioimmunoassay of rat cystatin C: increased urinary excretion of this cysteine proteases inhibitor during chromate nephropathy. J Immunoassay. 1990;11(2):199–214.

    Article  PubMed  CAS  Google Scholar 

  47. Conti M, Moutereau S, Zater M, Lallali K, Durrbach A, Manivet P, et al. Urinary cystatin C as a specific marker of tubular dysfunction. Clin Chem Lab Med. 2006;44(3):288–91.

    Article  PubMed  CAS  Google Scholar 

  48. Dieterle F, Perentes E, Cordier A, Roth DR, Verdes P, Grenet O, et al. Urinary clusterin, cystatin C, beta2-microglobulin and total protein as markers to detect drug-induced kidney injury. Nat Biotechnol. 2010;28(5):463–9.

    Article  PubMed  CAS  Google Scholar 

  49. Schaefer L, Gilge U, Heidland A, Schaefer RM. Urinary excretion of cathepsin B and cystatins as parameters of tubular damage. Kidney Int Suppl. 1994;47:S64–7.

    PubMed  CAS  Google Scholar 

  50. Vaidya VS, Waikar SS, Ferguson MA, Collings FB, Sunderland K, Gioules C, et al. Urinary biomarkers for sensitive and specific detection of acute kidney injury in humans. Clin Transl Sci. 2008;1(3):200–8.

    Article  PubMed  CAS  Google Scholar 

  51. Ichimura T, Asseldonk EJ, Humphreys BD, Gunaratnam L, Duffield JS, Bonventre JV. Kidney injury molecule-1 is a phosphatidylserine receptor that confers a phagocytic phenotype on epithelial cells. J Clin Invest. 2008;118(5):1657–68.

    Article  PubMed  CAS  Google Scholar 

  52. Liangos O, Perianayagam MC, Vaidya VS, Han WK, Wald R, Tighiouart H, et al. Urinary N-acetyl-beta-(d)-glucosaminidase activity and kidney injury molecule-1 level are associated with adverse outcomes in acute renal failure. J Am Soc Nephrol. 2007;18(3):904–12.

    Article  PubMed  CAS  Google Scholar 

  53. Prozialeck WC, Vaidya VS, Liu J, Waalkes MP, Edwards JR, Lamar PC, et al. Kidney injury molecule-1 is an early biomarker of cadmium nephrotoxicity. Kidney Int. 2007;72(8):985–93.

    Article  PubMed  CAS  Google Scholar 

  54. Sieber M, Hoffmann D, Adler M, Vaidya VS, Clement M, Bonventre JV, et al. Comparative analysis of novel noninvasive renal biomarkers and metabonomic changes in a rat model of gentamicin nephrotoxicity. Toxicol Sci. 2009;109(2):336–49.

    Article  PubMed  CAS  Google Scholar 

  55. van Timmeren MM, Vaidya VS, van Ree RM, Oterdoom LH, de Vries AP, Gans RO, et al. High urinary excretion of kidney injury molecule-1 is an independent predictor of graft loss in renal transplant recipients. Transplantation. 2007;84(12):1625–30.

    Article  PubMed  Google Scholar 

  56. Wang EJ, Snyder RD, Fielden MR, Smith RJ, Gu YZ. Validation of putative genomic biomarkers of nephrotoxicity in rats. Toxicology. 2008;246(2–3):91–100.

    Article  PubMed  CAS  Google Scholar 

  57. Zhou Y, Vaidya VS, Brown RP, Zhang J, Rosenzweig BA, Thompson KL, et al. Comparison of kidney injury molecule-1 and other nephrotoxicity biomarkers in urine and kidney following acute exposure to gentamicin, mercury, and chromium. Toxicol Sci. 2008;101(1):159–70.

    Article  PubMed  CAS  Google Scholar 

  58. Chen N, Aleksa K, Woodland C, Rieder M, Koren G. N-Acetylcysteine prevents ifosfamide-induced nephrotoxicity in rats. Br J Pharmacol. 2008;153(7):1364–72.

    Article  PubMed  CAS  Google Scholar 

  59. Gatanaga H, Tachikawa N, Kikuchi Y, Teruya K, Genka I, Honda M, et al. Urinary beta2-microglobulin as a possible sensitive marker for renal injury caused by tenofovir disoproxil fumarate. AIDS Res Hum Retroviruses. 2006;22(8):744–8.

    Article  PubMed  CAS  Google Scholar 

  60. Hofstra JM, Deegens JK, Willems HL, Wetzels JF. Beta-2-microglobulin is superior to N-acetyl-beta-glucosaminidase in predicting prognosis in idiopathic membranous nephropathy. Nephrol Dial Transplant. 2008;23(8):2546–51.

    Article  PubMed  CAS  Google Scholar 

  61. Morel G, Ban M, Bonnet P, Zissu D, Brondeau MT. Effect of beta-naphthoflavone and phenobarbital on the nephrotoxicity of chlorotrifluoroethylene and 1,1-dichloro-2,2-difluoroethylene in the rat. J Appl Toxicol. 2005;25(2):153–65.

    Article  PubMed  CAS  Google Scholar 

  62. Schaub S, Wilkins JA, Antonovici M, Krokhin O, Weiler T, Rush D, et al. Proteomic-based identification of cleaved urinary beta2-microglobulin as a potential marker for acute tubular injury in renal allografts. Am J Transplant. 2005;5(4 Pt 1):729–38.

    Article  PubMed  CAS  Google Scholar 

  63. Zhu G, Xiang X, Chen X, Wang L, Hu H, Weng S. Renal dysfunction induced by long-term exposure to depleted uranium in rats. Arch Toxicol. 2009;83(1):37–46.

    Article  PubMed  CAS  Google Scholar 

  64. Kern W, Braess J, Kaufmann CC, Wilde S, Schleyer E, Hiddemann W. Microalbuminuria during cisplatin therapy: relation with pharmacokinetics and implications for nephroprotection. Anticancer Res. 2000;20(5C):3679–88.

    PubMed  CAS  Google Scholar 

  65. Vallon V. The proximal tubule in the pathophysiology of the diabetic kidney. Am J Physiol Regul Integr Comp Physiol. 2011;300(5):R1009–22.

    Article  PubMed  Google Scholar 

  66. Arici M, Chana R, Lewington A, Brown J, Brunskill NJ. Stimulation of proximal tubular cell apoptosis by albumin-bound fatty acids mediated by peroxisome proliferator activated receptor-gamma. J Am Soc Nephrol. 2003;14(1):17–27.

    Article  PubMed  CAS  Google Scholar 

  67. Russo LM, Sandoval RM, McKee M, Osicka TM, Collins AB, Brown D, et al. The normal kidney filters nephrotic levels of albumin retrieved by proximal tubule cells: retrieval is disrupted in nephrotic states. Kidney Int. 2007;71(6):504–13.

    Article  PubMed  CAS  Google Scholar 

  68. Gautier JC, Riefke B, Walter J, Kurth P, Mylecraine L, Guilpin V, et al. Evaluation of novel biomarkers of nephrotoxicity in two strains of rat treated with Cisplatin. Toxicol Pathol. 2010;38(6):943–56.

    Article  PubMed  CAS  Google Scholar 

  69. Yu Y, Jin H, Holder D, Ozer JS, Villarreal S, Shughrue P, et al. Urinary biomarkers trefoil factor 3 and albumin enable early detection of kidney tubular injury. Nat Biotechnol. 2010;28(5):470–7.

    Article  PubMed  CAS  Google Scholar 

  70. Venkat KK. Proteinuria and microalbuminuria in adults: significance, evaluation, and treatment. South Med J. 2004;97(10):969–79.

    Article  PubMed  CAS  Google Scholar 

  71. Peterson PA, Evrin PE, Berggard I. Differentiation of glomerular, tubular, and normal proteinuria: determinations of urinary excretion of beta-2-macroglobulin, albumin, and total protein. J Clin Invest. 1969;48(7):1189–98.

    Article  PubMed  CAS  Google Scholar 

  72. Shihabi ZK, Konen JC, O’Connor ML. Albuminuria vs urinary total protein for detecting chronic renal disorders. Clin Chem. 1991;37(5):621–4.

    PubMed  CAS  Google Scholar 

  73. Madsen J, Nielsen O, Tornoe I, Thim L, Holmskov U. Tissue localization of human trefoil factors 1, 2, and 3. J Histochem Cytochem. 2007;55(5):505–13.

    Article  PubMed  CAS  Google Scholar 

  74. Taupin D, Podolsky DK. Trefoil factors: initiators of mucosal healing. Nat Rev Mol Cell Biol. 2003;4(9):721–32.

    Article  PubMed  CAS  Google Scholar 

  75. Debata PR, Panda H, Supakar PC. Altered expression of trefoil factor 3 and cathepsin l gene in rat kidney during aging. Biogerontology. 2007;8(1):25–30.

    Article  PubMed  CAS  Google Scholar 

  76. Dvergsten J, Manivel JC, Correa-Rotter R, Rosenberg ME. Expression of clusterin in human renal diseases. Kidney Int. 1994;45(3):828–35.

    Article  PubMed  CAS  Google Scholar 

  77. Hidaka S, Kranzlin B, Gretz N, Witzgall R. Urinary clusterin levels in the rat correlate with the severity of tubular damage and may help to differentiate between glomerular and tubular injuries. Cell Tissue Res. 2002;310(3):289–96.

    Article  PubMed  CAS  Google Scholar 

  78. Ishii A, Sakai Y, Nakamura A. Molecular pathological evaluation of clusterin in a rat model of unilateral ureteral obstruction as a possible biomarker of nephrotoxicity. Toxicol Pathol. 2007;35(3):376–82.

    Article  PubMed  CAS  Google Scholar 

  79. Shannan B, Seifert M, Boothman DA, Tilgen W, Reichrath J. Clusterin and DNA repair: a new function in cancer for a key player in apoptosis and cell cycle control. J Mol Histol. 2006;37(5–7):183–8.

    Article  PubMed  CAS  Google Scholar 

  80. Price SA, Davies D, Rowlinson R, Copley CG, Roche A, Falkenberg FW, et al. Characterization of renal papillary antigen 1 (RPA-1), a biomarker of renal papillary necrosis. Toxicol Pathol. 2010;38(3):346–58.

    Article  PubMed  CAS  Google Scholar 

  81. Hildebrand H, Rinke M, Schluter G, Bomhard E, Falkenberg FW. Urinary antigens as markers of papillary toxicity. II: Application of monoclonal antibodies for the determination of papillary antigens in rat urine. Arch Toxicol. 1999;73(4–5):233–45.

    Article  PubMed  CAS  Google Scholar 

  82. Shaw M. Cell-specific biomarkers in renal medicine and research. Methods Mol Biol. 2010;641:271–302.

    Article  PubMed  CAS  Google Scholar 

  83. Lu Q, Lu C, Zhou GP, Zhang W, Xiao H, Wang XR. MicroRNA-221 silencing predisposed human bladder cancer cells to undergo apoptosis induced by TRAIL. Urol Oncol. 2009;28(6):635–41.

    Article  PubMed  CAS  Google Scholar 

  84. Chiyomaru T, Enokida H, Kawakami K, Tatarano S, Uchida Y, Kawahara K et al. (2011) Functional role of LASP1 in cell viability and its regulation by microRNAs in bladder cancer. Urol Oncol (in press)

  85. Cao Y, Yu SL, Wang Y, Guo GY, Ding Q, An RH. MicroRNA-dependent regulation of PTEN after arsenic trioxide treatment in bladder cancer cell line T24. Tumour Biol. 2010;32(1):179–88.

    Article  PubMed  CAS  Google Scholar 

  86. Ichimi T, Enokida H, Okuno Y, Kunimoto R, Chiyomaru T, Kawamoto K, et al. Identification of novel microRNA targets based on microRNA signatures in bladder cancer. Int J Cancer. 2009;125(2):345–52.

    Article  PubMed  CAS  Google Scholar 

  87. Lodygin D, Tarasov V, Epanchintsev A, Berking C, Knyazeva T, Korner H, et al. Inactivation of miR-34a by aberrant CpG methylation in multiple types of cancer. Cell Cycle. 2008;7(16):2591–600.

    Article  PubMed  CAS  Google Scholar 

  88. Hanke M, Hoefig K, Merz H, Feller AC, Kausch I, Jocham D, et al. A robust methodology to study urine microRNA as tumor marker: microRNA-126 and microRNA-182 are related to urinary bladder cancer. Urol Oncol. 2009;28(6):655–61.

    Article  PubMed  CAS  Google Scholar 

  89. Catto JW, Miah S, Owen HC, Bryant H, Myers K, Dudziec E, et al. Distinct microRNA alterations characterize high- and low-grade bladder cancer. Cancer Res. 2009;69(21):8472–81.

    Article  PubMed  CAS  Google Scholar 

  90. Friedman JM, Liang G, Liu CC, Wolff EM, Tsai YC, Ye W, et al. The putative tumor suppressor microRNA-101 modulates the cancer epigenome by repressing the polycomb group protein EZH2. Cancer Res. 2009;69(6):2623–9.

    Article  PubMed  CAS  Google Scholar 

  91. Huang Q, Dunn 2nd RT, Jayadev S, DiSorbo O, Pack FD, Farr SB, et al. Assessment of cisplatin-induced nephrotoxicity by microarray technology. Toxicol Sci. 2001;63(2):196–207.

    Article  PubMed  CAS  Google Scholar 

  92. Ostenfeld MS, Bramsen JB, Lamy P, Villadsen SB, Fristrup N, Sorensen KD, et al. miR-145 induces caspase-dependent and -independent cell death in urothelial cancer cell lines with targeting of an expression signature present in Ta bladder tumors. Oncogene. 2010;29(7):1073–84.

    Article  PubMed  CAS  Google Scholar 

  93. Wiklund ED, Bramsen JB, Hulf T, Dyrskjot L, Ramanathan R, Hansen TB, et al. Coordinated epigenetic repression of the miR-200 family and miR-205 in invasive bladder cancer. Int J Cancer. 2011;128(6):1327–34.

    Article  PubMed  CAS  Google Scholar 

  94. Kenney PA, Wszolek MF, Rieger-Christ KM, Neto BS, Gould JJ, Harty NJ, et al. Novel ZEB1 expression in bladder tumorigenesis. BJU Int. 2010;107(4):656–63.

    Article  PubMed  Google Scholar 

  95. Adam L, Zhong M, Choi W, Qi W, Nicoloso M, Arora A, et al. miR-200 expression regulates epithelial-to-mesenchymal transition in bladder cancer cells and reverses resistance to epidermal growth factor receptor therapy. Clin Cancer Res. 2009;15(16):5060–72.

    Article  PubMed  CAS  Google Scholar 

  96. Liu W, Zabirnyk O, Wang H, Shiao YH, Nickerson ML, Khalil S, et al. miR-23b targets proline oxidase, a novel tumor suppressor protein in renal cancer. Oncogene. 2010;29(35):4914–24.

    Article  PubMed  CAS  Google Scholar 

  97. Kort EJ, Farber L, Tretiakova M, Petillo D, Furge KA, Yang XJ, et al. The E2F3-Oncomir-1 axis is activated in Wilms’ tumor. Cancer Res. 2008;68(11):4034–8.

    Article  PubMed  CAS  Google Scholar 

  98. Gregory PA, Bert AG, Paterson EL, Barry SC, Tsykin A, Farshid G, et al. The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1. Nat Cell Biol. 2008;10(5):593–601.

    Article  PubMed  CAS  Google Scholar 

  99. Godwin JG, Ge X, Stephan K, Jurisch A, Tullius SG, Iacomini J. Identification of a microRNA signature of renal ischemia reperfusion injury. Proc Natl Acad Sci U S A. 2010;107(32):14339–44.

    Article  PubMed  CAS  Google Scholar 

  100. Agrawal R, Tran U, Wessely O. The miR-30 miRNA family regulates Xenopus pronephros development and targets the transcription factor Xlim1/Lhx1. Development. 2009;136(23):3927–36.

    Article  PubMed  CAS  Google Scholar 

  101. Kato M, Zhang J, Wang M, Lanting L, Yuan H, Rossi JJ, et al. MicroRNA-192 in diabetic kidney glomeruli and its function in TGF-beta-induced collagen expression via inhibition of E-box repressors. Proc Natl Acad Sci U S A. 2007;104(9):3432–7.

    Article  PubMed  CAS  Google Scholar 

  102. Kato M, Putta S, Wang M, Yuan H, Lanting L, Nair I, et al. TGF-beta activates Akt kinase through a microRNA-dependent amplifying circuit targeting PTEN. Nat Cell Biol. 2009;11(7):881–9.

    Article  PubMed  CAS  Google Scholar 

  103. Wang Q, Wang Y, Minto AW, Wang J, Shi Q, Li X, et al. MicroRNA-377 is up-regulated and can lead to increased fibronectin production in diabetic nephropathy. FASEB J. 2008;22(12):4126–35.

    Article  PubMed  CAS  Google Scholar 

  104. Sun H, Li QW, Lv XY, Ai JZ, Yang QT, Duan JJ, et al. MicroRNA-17 post-transcriptionally regulates polycystic kidney disease-2 gene and promotes cell proliferation. Mol Biol Rep. 2010;37(6):2951–8.

    Article  PubMed  CAS  Google Scholar 

  105. Lee SO, Masyuk T, Splinter P, Banales JM, Masyuk A, Stroope A, et al. MicroRNA15a modulates expression of the cell-cycle regulator Cdc25A and affects hepatic cystogenesis in a rat model of polycystic kidney disease. J Clin Invest. 2008;118(11):3714–24.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Philip Hewitt.

Additional information

Guest Editors: Brian Booth and Murali Ramanathan

ELECTRONIC SUPPLEMENTARY MATERIALS

Below is the link to the electronic supplementary material.

Supplementary Fig. 1

Overview of RIFLE and AKIN processes for assessing DIKI/AKI. Patients who receive renal replacement therapy (RRT) are classified as stage 3 in the AKIN schema (Cr serum creatinine, GFR glomerular filtration rate, AKI acute kidney injury; JPEG 25 kb)

High-resolution image (TIFF 4,752 kb)

Supplementary Fig. 2

The overlap of human, mouse, and rat miRNAs identified in renal tissue shows the conservation of miRNA over different species. The total number of miRNAs determined per species is shown under the name of species. Out of these, a number of 73 miRNAs were detectable in all three species. Adapted from (44) (JPEG 9 kb)

High resolution image (TIFF 541 kb)

Supplementary Table I

The five kidney damage stages discerned by the GFR (DOC 29 kb)

Supplementary Table II

An overview of international projects focused on the identification of biomarkers for the detection of nephrotoxicity using novel technologies like toxicogenomic and proteomics (DOC 32 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fuchs, T.C., Hewitt, P. Biomarkers for Drug-Induced Renal Damage and Nephrotoxicity—An Overview for Applied Toxicology. AAPS J 13, 615–631 (2011). https://doi.org/10.1208/s12248-011-9301-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1208/s12248-011-9301-x

KEY WORDS

Navigation