Skip to main content
SpringerLink
Log in

Detection of renal allograft dysfunction with characteristic protein fingerprint by serum proteomic analysis

  • Urology – Original Paper
  • Published:
International Urology and Nephrology Aims and scope Submit manuscript

Abstract

This study aimed to diagnose renal allograft dysfunction with specific biomarkers by serum proteomic analysis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and bioinformatics (support vector machine and leave-one cross validation) were used to analyze serum proteome. Enrolled patients included 38 biopsy-proved acute rejection (BPAR), 10 acute tubular necrosis (ATN), 24 subclinical rejection (SCR) and 29 stable control recipients verified by protocol biopsy. A characteristic protein profile can be detected in each renal allograft dysfunction group. BPAR patients were differentiated from stable patients with markers of 9710.1, 4971, 6675.5, 8563.8, 6709.2, 9319 and 4476.7 Da with high sensitivity and specificity. ATN can be clearly distinguished from BPAR and stable control. Subclinical rejection differentiated from stable control with markers of 9193.1, 2759.1, 8464.6 Da. The independent blind test yielded with high specificity and sensitivity for each group. Serum proteome analysis by SELDI-TOF MS combined with bioinformatics in renal allograft dysfunction is valuable and promising. Specific markers were detected in each group. Identification of these proteins may prove useful as diagnostic markers for allograft dysfunction and better to elucidate the mechanism of acute rejection.

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

Access this article

Log in via an institution

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. Nankivell BJ, Chapman JR (2006) Chronic allograft nephropathy: current concepts and future directions. Transplantation 815:643–654

    Article  Google Scholar 

  2. Cornell LD, Colvin RB (2005) Chronic allograft nephropathy. Curr Opin Nephrol Hypertens 143:229–234

    Article  Google Scholar 

  3. Schwarz A et al (2005) Risk factors for chronic allograft nephropathy after renal transplantation: a protocol biopsy study. Kidney Int 671:341–348

    Article  Google Scholar 

  4. Colvin RB (2003) Chronic allograft nephropathy. N Engl J Med 34924:2288–2290

    Article  Google Scholar 

  5. Choi BS et al (2005) Clinical significance of an early protocol biopsy in living-donor renal transplantation: ten-year experience at a single center. Am J Transplant 56:1354–1360

    Article  Google Scholar 

  6. Shishido S et al (2003) The impact of repeated subclinical acute rejection on the progression of chronic allograft nephropathy. J Am Soc Nephrol 144:1046–1052

    Article  Google Scholar 

  7. Strom TB (2005) Rejection–more than the eye can see. N Engl J Med 35322:2394–2396

    Article  Google Scholar 

  8. Jianghua C et al (2005) C4d as a significant predictor for humoral rejection in renal allografts. Clin Transplant 196:785–791

    Article  Google Scholar 

  9. Chen JH, Wang RD, wu JY (2004) The impact of early vascular rejection on late rejection in 1062 cadaveric renal transplant. J Am Soc Nephrol 15:812

    Article  Google Scholar 

  10. Wu JY et al (2004) Improved clinical outcomes in Chinese renal allograft recipients receiving lower dose immunosuppressants. Transplantation 785:713–718

    Article  Google Scholar 

  11. Muthukumar T et al (2005) Messenger RNA for FOXP3 in the urine of renal-allograft recipients. N Engl J Med 35322:2342–2351

    Article  Google Scholar 

  12. Wittke S et al (2005) Detection of acute tubulointerstitial rejection by proteomic analysis of urinary samples in renal transplant recipients. Am J Transplant 510:2479–2488

    Article  Google Scholar 

  13. Flechner SM et al (2004) Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes. Am J Transplant 49:1475–1489

    Article  Google Scholar 

  14. Sarwal M et al (2003) Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. N Engl J Med 3492:125–138

    Article  Google Scholar 

  15. Rai AJ et al (2005) Analysis of human proteome organization plasma proteome project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers. Proteomics 513:3467–3474

    Article  Google Scholar 

  16. Tolson J et al (2004) Serum protein profiling by SELDI mass spectrometry: detection of multiple variants of serum amyloid alpha in renal cancer patients. Lab Invest 847:845–856

    Article  Google Scholar 

  17. Issaq HJ et al (2003) SELDI-TOF MS for diagnostic proteomics. Anal Chem 757:148A–155A

    Google Scholar 

  18. Fung E et al (2003) The use of SELDI ProteinChip array technology in renal disease research. Methods Mol Med 86:295–312

    PubMed  CAS  Google Scholar 

  19. Xu WH et al (2006) Preoperatively molecular staging with CM10 ProteinChip and SELDI-TOF-MS for colorectal cancer patients. J Zhejiang Univ Sci B 73:235–240

    Article  Google Scholar 

  20. Yu JK et al (2005) An integrated approach utilizing proteomics and bioinformatics to detect ovarian cancer. J Zhejiang Univ Sci B 64:227–231

    Article  Google Scholar 

  21. Chen YD et al (2004) Artificial neural networks analysis of surface-enhanced laser desorption/ionization mass spectra of serum protein pattern distinguishes colorectal cancer from healthy population. Clin Cancer Res 1024:8380–8385

    Article  Google Scholar 

  22. Mao Y et al (2008) Diagnosis of renal allograft subclinical rejection by urine protein fingerprint analysis. Transpl Immunol 183:255–259

    Article  Google Scholar 

  23. Schaub S et al (2004) Proteomic-based detection of urine proteins associated with acute renal allograft rejection. J Am Soc Nephrol 151:219–227

    Article  Google Scholar 

  24. O’Riordan E et al (2004) Bioinformatic analysis of the urine proteome of acute allograft rejection. J Am Soc Nephrol 1512:3240–3248

    Article  Google Scholar 

  25. Racusen LC, Halloran PF, Solez K (2004) Banff 2003 meeting report: new diagnostic insights and standards. Am J Transplant 410:1562–1566

    Article  Google Scholar 

  26. O’Riordan E, Goligorsky MS (2005) Emerging studies of the urinary proteome: the end of the beginning? Curr Opin Nephrol Hypertens 146:579–585

    Article  Google Scholar 

  27. Clarke W et al (2003) Characterization of renal allograft rejection by urinary proteomic analysis. Ann Surg 2375:660–664 discussion 664–665

    Google Scholar 

  28. Somorjai RL, Dolenko B, Baumgartner R (2003) Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: curses, caveats, cautions. Bioinformatics 1912:1484–1491

    Article  Google Scholar 

  29. Byvatov E, Schneider G (2003) Support vector machine applications in bioinformatics. Appl Bioinformatics 22:67–77

    Google Scholar 

  30. Furey TS et al (2000) Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 1610:906–914

    Article  Google Scholar 

  31. Wang JX et al (2006) Application of serum protein fingerprint in diagnosis of papillary thyroid carcinoma. Proteomics 619:5344–5349

    Article  Google Scholar 

  32. Nankivell BJ et al (2003) The natural history of chronic allograft nephropathy. N Engl J Med 34924:2326–2333

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the National High Technology Research and Development Program of China (863 Program, 2006AA02A248), Key Projects in the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period (2008BAI60B04), Major projects of Zhejiang Science and Technology Department(2008C13026-2).

Author information

Authors and Affiliations

  1. The Kidney Disease Center, The First Affiliated Hospital of Medical College, Zhejiang University, 79 Qingchun Road, Hangzhou, China

    Minmin Wang, Qiu Jin, Haiyan Tu, Youying Mao, Ying Chen, Zhangfei Shou, Qiang He, Jianyong Wu & Jianghua Chen

  2. Kidney Disease Immunology Laboratory, The Third Grade Laboratory, State Administration of Traditional Chinese Medicine, Hangzhou, China

    Youying Mao, Ying Chen, Zhangfei Shou, Qiang He, Jianyong Wu & Jianghua Chen

  3. Key Laboratory of Multiple Organ Transplantation, Ministry of Health, Hangzhou, China

    Zhangfei Shou, Qiang He, Jianyong Wu & Jianghua Chen

  4. Cancer Institute, Zhejiang University, Hangzhou, China

    Jiekai Yu & Shu Zheng

Authors
  1. Minmin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qiu Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haiyan Tu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Youying Mao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jiekai Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ying Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Zhangfei Shou
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Qiang He
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jianyong Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Shu Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jianghua Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jianghua Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, M., Jin, Q., Tu, H. et al. Detection of renal allograft dysfunction with characteristic protein fingerprint by serum proteomic analysis. Int Urol Nephrol 43, 1009–1017 (2011). https://doi.org/10.1007/s11255-011-9962-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11255-011-9962-5

Keywords

Search

Navigation