Skip to main content
SpringerLink
Log in

Development of candidate biomarkers for pancreatic ductal adenocarcinoma using multiple reaction monitoring

  • Research Paper
  • Published:
Biotechnology and Bioprocess Engineering Aims and scope Submit manuscript

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the fourth most frequent cause of cancer mortality in the United States. Because CA 19-9 increases not only in PDAC, but also in benign conditions, there is urgent need for an additional PDAC biomarker. Isotope tags for relative and absolute quantification (iTRAQ) were performed using 6 pairs of PDAC and normal tissues from the same patients, to obtain preliminary PDAC-specific proteins; and verification was performed by multiple reactions monitoring (MRM), using 30 PDAC and 20 normal serum, targeting high-abundant serum proteins without any pre-preparation. As a result, 17 candidate proteins from tissue iTRAQ were verified as potential markers (AUC values > 0.7). Multivariate analysis (MA) demonstrated that a 6-marker panel, consisting of alpha-1 antitrypsin, haptoglobin beta chain, hemopexin, transferrin, zinc alpha-2 glycoprotein, and apolipoprotein A4 from the MRM result, had comparable discriminatory power versus CA 19-9. Our study demonstrated that a combination of iTRAQ on PDAC tissue and verification MRM-MA on individual serum was an efficient method for the development of PDAC multimarkers.

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

Similar content being viewed by others

References

  1. Jemal, A., R. Siegel, J. Xu, and E. Ward (2010) Cancer statistics. CA Cancer J. Clin. 60: 277–300.

    Article  Google Scholar 

  2. Jung, K. W., S. Park, H. J. Kong, Y. J. Won, Y. K. Boo, H. R. Shin, E. C. Park, and J. S. Lee (2010) Cancer statistics in Korea: Incidence, mortality and survival in 2006–2007. J. Kor. Med. Sci. 25: 1113–1121.

    Article  Google Scholar 

  3. Maitra, A. and R. H. Hruban (2008) Pancreatic cancer. Annu. Rev. Pathol. 3: 157–188.

    Article  CAS  Google Scholar 

  4. Ghaneh, P., E. Costello, and J. P. Neoptolemos (2007) Biology and management of pancreatic cancer. Gut. 56: 1134–1152.

    Article  CAS  Google Scholar 

  5. Adamek, H. E., J. Albert, H. Breer, M. Weitz, D. Schilling, and J. F. Riemann (2000) Pancreatic cancer detection with magnetic resonance cholangiopancreatography and endoscopic retrograde cholangiopancreatography: A prospective controlled study. Lancet. 356: 190–193.

    Article  CAS  Google Scholar 

  6. Porcel, J. M., M. Vives, A. Esquerda, A. Salud, B. Perez, and F. Rodriguez-Panadero (2004) Use of a panel of tumor markers (carcinoembryonic antigen, cancer antigen 125, carbohydrate antigen 15-3, and cytokeratin 19 fragments) in pleural fluid for the differential diagnosis of benign and malignant effusions. Chest. 126: 1757–1763.

    Article  Google Scholar 

  7. Robin, X., N. Turck, A. Hainard, F. Lisacek, J. C. Sanchez, and M. Muller (2009) Bioinformatics for protein biomarker panel classification: What is needed to bring biomarker panels into in vitro diagnostics? Expert. Rev. Proteomics. 6: 675–689.

    Article  CAS  Google Scholar 

  8. Ng, I. S., X. S. Zheng, B. Y. Chen, X. Q. Chi, Y. H. Lu, and C. S. Chang (2013) Proteomics approach to decipher novel genes and enzymes characterization of a bioelectricity-generating and dyedecolorizing bacterium Proteus hauseri ZMd44. Biotechnol. Bioproc. Eng. 18: 8–17.

    Article  CAS  Google Scholar 

  9. Cheng, J. S., X. M. Lv, and Y. J. Yuan (2012) Investigation of proteomic responses of Streptomyces lydicus to pitching ratios for improving streptolydigin production. Biotechnol. Bioproc. Eng. 17: 997–1007.

    Article  CAS  Google Scholar 

  10. Aggarwal, K., L. H. Choe, and K. H. Lee (2005) Quantitative analysis of protein expression using amine-specific isobaric tags in Escherichia coli cells expressing rhsA elements. Proteomics. 5: 2297–2308.

    Article  CAS  Google Scholar 

  11. Zhang, Y., A. Wolf-Yadlin, P. L. Ross, D. J. Pappin, J. Rush, D. A. Lauffenburger, and F. M. White (2005) Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules. Mol. Cell Proteomics. 4: 1240–1250.

    Article  CAS  Google Scholar 

  12. Anderson, L. and C. L. Hunter (2006) Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol. Cell Proteomics. 5: 573–588.

    CAS  Google Scholar 

  13. Kiyonami, R., A. Schoen, A. Prakash, S. Peterman, V. Zabrouskov, P. Picotti, R. Aebersold, A. Huhmer, and B. Domon (2011) Increased selectivity, analytical precision, and throughput in targeted proteomics. Mol. Cell Proteomics. 10: 1–11.

    Google Scholar 

  14. Whiteaker, J. R., C. Lin, J. Kennedy, L. Hou, M. Trute, I. Sokal, P. Yan, R. M. Schoenherr, L. Zhao, U. J. Voytovich, K. S. Kelly-Spratt, A. Krasnoselsky, P. R. Gafken, J. M. Hogan, L. A. Jones, P. Wang, L. Amon, L. A. Chodosh, P. S. Nelson, M. W. McIntosh, C. J. Kemp, and A. G. Paulovich (2011) A targeted proteomics-based pipeline for verification of biomarkers in plasma. Nat. Biotechnol. 29: 625–634.

    Article  CAS  Google Scholar 

  15. Kim, K., S. J. Kim, H. G. Yu, J. Yu, K. S. Park, I. J. Jang, and Y. Kim (2010) Verification of biomarkers for diabetic retinopathy by multiple reaction monitoring. J. Proteome Res. 9: 689–699.

    Article  CAS  Google Scholar 

  16. Chen, R., E. C. Yi, S. Donohoe, S. Pan, J. Eng, K. Cooke, D. A. Crispin, Z. Lane, D. R. Goodlett, M. P. Bronner, R. Aebersold, and T. A. Brentnall (2005) Pancreatic cancer proteome: The proteins that underlie invasion, metastasis, and immunologic escape. Gastroenterol. 129: 1187–1197.

    Article  CAS  Google Scholar 

  17. Lu, Z., L. Hu, S. Evers, J. Chen, and Y. Shen (2004) Differential expression profiling of human pancreatic adenocarcinoma and healthy pancreatic tissue. Proteomics. 4: 3975–3988.

    Article  CAS  Google Scholar 

  18. Ohuchida, K., K. Mizumoto, N. Ishikawa, K. Fujii, H. Konomi, E. Nagai, K. Yamaguchi, M. Tsuneyoshi, and M. Tanaka (2005) The role of S100A6 in pancreatic cancer development and its clinical implication as a diagnostic marker and therapeutic target. Clin. Cancer Res. 11: 7785–7793.

    Article  CAS  Google Scholar 

  19. Jin, J., Y. W. Kwon, J. S. Paek, H. J. Cho, J. Yu, J. Y. Lee, I. S. Chu, I. H. Park, Y. B. Park, H. S. Kim, and Y. Kim (2011) Analysis of differential proteomes of induced pluripotent stem cells by protein-based reprogramming of fibroblasts. J. Proteome Res. 10: 977–989.

    Article  CAS  Google Scholar 

  20. Han, D., S. Moon, H. Kim, S. E. Choi, S. J. Lee, K. S. Park, H. Jun, Y. Kang, and Y. Kim (2011) Detection of differential proteomes associated with the development of type 2 diabetes in the Zucker rat model using the iTRAQ technique. J. Proteome Res. 10: 564–577.

    Article  CAS  Google Scholar 

  21. Jin, J., Y. H. Ku, Y. Kim, K. Kim, J. Y. Lee, Y. M. Cho, H. K. Lee, and K. S. Park (2012) Differential proteome profiling using iTRAQ in microalbuminuric and normoalbuminuric type 2 diabetic patients. Exp. Diabetes Res. 2012: 168602.

    Article  Google Scholar 

  22. Matsubara, J., M. Ono, K. Honda, A. Negishi, H. Ueno, T. Okusaka, J. Furuse, K. Furuta, E. Sugiyama, Y. Saito, N. Kaniwa, J. Sawada, A. Shoji, T. Sakuma, T. Chiba, N. Saijo, S. Hirohashi, and T. Yamada (2010) Survival prediction for pancreatic cancer patients receiving gemcitabine treatment. Mol. Cell Proteomics. 9: 695–704.

    Article  CAS  Google Scholar 

  23. Kang, S. M., H. J. Sung, J. M. Ahn, J. Y. Park, S. Y. Lee, C. S. Park, and J. Y. Cho (2011) The Haptoglobin beta chain as a supportive biomarker for human lung cancers. Mol. Biosyst. 7: 1167–1175.

    Article  CAS  Google Scholar 

  24. Thompson, S., B. M. Cantwell, C. Cornell, and G. A. Turner (1991) Abnormally-fucosylated haptoglobin: A cancer marker for tumour burden but not gross liver metastasis. Br. J. Cancer. 64: 386–390.

    Article  CAS  Google Scholar 

  25. Thompson, S., E. Dargan, and G. A. Turner (1992) Increased fucosylation and other carbohydrate changes in haptoglobin in ovarian cancer. Cancer Lett. 66: 43–48.

    Article  CAS  Google Scholar 

  26. Okuyama, N., Y. Ide, M. Nakano, T. Nakagawa, K. Yamanaka, K. Moriwaki, K. Murata, H. Ohigashi, S. Yokoyama, H. Eguchi, O. Ishikawa, T. Ito, M. Kato, A. Kasahara, S. Kawano, J. Gu, N. Taniguchi, and E. Miyoshi (2006) Fucosylated haptoglobin is a novel marker for pancreatic cancer: A detailed analysis of the oligosaccharide structure and a possible mechanism for fucosylation. Int. J. Cancer. 118: 2803–2808.

    Article  CAS  Google Scholar 

  27. Wang, Z., C. Wang, X. Huang, Y. Shen, J. Shen, and K. Ying (2012) Differential proteome profiling of pleural effusions from lung cancer and benign inflammatory disease patients. Biochim. Biophys. Acta 1824: 692–700.

    Article  CAS  Google Scholar 

  28. Jou, Y. J., C. D. Lin, C. H. Lai, C. H. Chen, J. Y. Kao, S. Y. Chen, M. H. Tsai, S. H. Huang, and C. W. Lin (2010) Proteomic identification of salivary transferrin as a biomarker for early detection of oral cancer. Anal. Chim. Acta 681: 41–48.

    Article  CAS  Google Scholar 

  29. Dubois, V., L. Delort, F. Mishellany, T. Jarde, H. Billard, C. Lequeux, O. Damour, F. Penault-Llorca, M. P. Vasson, and F. Caldefie-Chezet (2010) Zinc-alpha2-glycoprotein: A new biomarker of breast cancer? Anticancer Res. 30: 2919–2925.

    CAS  Google Scholar 

  30. Dieplinger, H., D. P. Ankerst, A. Burges, M. Lenhard, A. Lingenhel, L. Fineder, H. Buchner, and P. Stieber (2009) Afamin and apolipoprotein A-IV: Novel protein markers for ovarian cancer. Cancer Epidemiol. Biomarkers Prev. 18: 1127–1133.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, 110-799, Korea

    Jiyoung Yu, Kyunggon Kim, Hyunsoo Kim & Youngsoo Kim

  2. Department of Surgery, Seoul National University College of Medicine, Seoul, 110-799, Korea

    MeeJoo Kang, Sun Whe Kim & Jin-Young Jang

Authors
  1. Jiyoung Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kyunggon Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. MeeJoo Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hyunsoo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sun Whe Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jin-Young Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Youngsoo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jin-Young Jang or Youngsoo Kim.

Additional information

These authors contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yu, J., Kim, K., Kang, M. et al. Development of candidate biomarkers for pancreatic ductal adenocarcinoma using multiple reaction monitoring. Biotechnol Bioproc E 18, 1038–1047 (2013). https://doi.org/10.1007/s12257-013-0421-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12257-013-0421-2

Keywords

Search

Navigation