Skip to main content

Advertisement

SpringerLink
Log in

Levels of plasma glycan-binding auto-IgG biomarkers improve the accuracy of prostate cancer diagnosis

  • Published:
Molecular and Cellular Biochemistry Aims and scope Submit manuscript

Abstract

Strategies to improve the early diagnosis of prostate cancer will provide opportunities for earlier intervention. The blood-based prostate-specific antigen (PSA) assay is widely used for prostate cancer diagnosis but specificity of the assay is not satisfactory. An algorithm based on serum levels of PSA combined with other serum biomarkers may significantly improve prostate cancer diagnosis. Plasma glycan-binding IgG/IgM studies suggested that glycan patterns differ between normal and tumor cells. We hypothesize that in prostate cancer glycoproteins or glycolipids are secreted from tumor tissues into the blood and induce auto-immunoglobulin (Ig) production. A 24-glycan microarray and a 5-glycan subarray were developed using plasma samples obtained from 35 prostate cancer patients and 54 healthy subjects to identify glycan-binding auto-IgGs. Neu5Acα2-8Neu5Acα2-8Neu5Acα (G81)-binding auto-IgG was higher in prostate cancer samples and, when levels of G81-binding auto-IgG and growth differentiation factor-15 (GDF-15 or NAG-1) were combined with levels of PSA, the prediction rate of prostate cancer increased from 78.2% to 86.2% than with PSA levels alone. The G81 glycan-binding auto-IgG fraction was isolated from plasma samples using G81 glycan-affinity chromatography and identified by N-terminal sequencing of the 50 kDa heavy chain variable region of the IgG. G81 glycan-binding 25 kDa fibroblast growth factor-1 (FGF1) fragment was also identified by N-terminal sequencing. Our results demonstrated that a multiplex diagnostic combining G81 glycan-binding auto-IgG, GDF-15/NAG-1 and PSA (≥ 2.1 ng PSA/ml for cancer) increased the specificity of prostate cancer diagnosis by 8%. The multiplex assessment could improve the early diagnosis of prostate cancer thereby allowing the prompt delivery of prostate cancer treatment.

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
Fig. 4

Similar content being viewed by others

References

  1. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D, Bray F (2012) Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN. Int J Cancer 136(5):E359–E386. https://doi.org/10.1002/ijc.29210

    Article  CAS  Google Scholar 

  2. Adhyam M, Gupta AKA (2012) Review on the clinical utility of PSA in cancer prostate. Indian J Surg Oncol 3(2):120–129. https://doi.org/10.1007/s13193-012-0142-6

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kawakami J, Siemens DR, Nickel JC (2004) Prostatitis and prostate cancer: implications for prostate cancer screening. Urology 64:1075. https://doi.org/10.1016/j.urology.2004.07.017

    Article  PubMed  Google Scholar 

  4. Masahiko N, Hisanori K, Tomihiro T, Oyama R, Imanaka K, Yoshizawa K (2016) Association of early PSA decline and time to PSA progression in abiraterone acetate-treated metastatic castration-resistant prostate cancer; a post-hoc analysis of Japanese phase 2 trials. BMC Urol 16(1):27. https://doi.org/10.1186/s12894-016-0148-4

    Article  CAS  Google Scholar 

  5. Lerner L, Tao J, Liu Q, Nicoletti R, Feng B, Krieger B, Mazsa E, Siddiquee Z, Wang R, Huang L, Shen L, Lin J, Vigano A, Chiu MI, Weng Z, Winston W, Weiler S, Gyuris J (2016) MAP3K11/GDF15 axis is a critical driver of cancer cachexia. J Cachexia Sarcopenia Muscle 7(4):467–482. https://doi.org/10.1002/jcsm.12077

    Article  PubMed  Google Scholar 

  6. Campbell CT, Gulley JL, Oyelaran O, Hodge JW, Schlom J, Gildersleeve JC (2013) Serum antibodies to blood group A predict survival on PROSTVAC-VF. Clin Cancer Res 19(5):1290–1299. https://doi.org/10.1158/1078-0432.CCR-12-2478

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Griffin ME, Hsieh-Wilson LC (2016) Glycan engineering for cell and developmental biology. Cell Chem Biol 23(1):108–121. https://doi.org/10.1016/j.chembiol.2015.12.007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Muthana SM, Gulley JL, Hodge JW, Schlom J, Gildersleeve JC (2015) ABO blood type correlates with survival on prostate cancer vaccine therapy. Oncotarget 6(31):32244–32256. https://doi.org/10.18632/oncotarget.4993

    Article  PubMed  PubMed Central  Google Scholar 

  9. Ohyama C, Hosono M, Nitta K, Oh-eda M, Yoshikawa K, Habuchi T, Arai Y, Fukuda M (2004) Carbohydrate structure and differential binding of prostate specific antigen to Maackia amurensis lectin between prostate cancer and benign prostate hypertrophy. Glycobiology 14(8):671–679. https://doi.org/10.1093/glycob/cwh071

    Article  CAS  PubMed  Google Scholar 

  10. Tang X, Mahajan SS, Nguyen LT, Béliveau F, Leduc R, Simon JA, Vasioukhin V (2014) Targeted inhibition of cell-surface serine protease Hepsin blocks prostate cancer bone metastasis. Oncotarget 5(5):1352–1362. https://doi.org/10.18632/oncotarget.1817

    Article  PubMed  PubMed Central  Google Scholar 

  11. Totten SM, Adusumilli R, Kullolli M, Tanimoto C, Brooks JD, Mallick P, Pitteri SJ (2018) Multi-lectin affinity chromatography and quantitative proteomic analysis reveal differential glycoform levels between prostate cancer and benign prostatic hyperplasia Sera. Sci Rep 8(1):6509. https://doi.org/10.1038/s41598-018-24270-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Wang CC, Huang YL, Ren CT, Lin CW, Hung JT, Yu JC, Yu AL, Wu CY, Wong CH (2008) Glycan microarray of Globo H and related structures for quantitative analysis of breast cancer. Proc Natl Acad Sci USA 105(33):11661–11666. https://doi.org/10.1073/pnas.0804923105

    Article  PubMed  Google Scholar 

  13. Meany DL, Zhang Z, Sokoll LJ, Zhang H, Chan DW (2009) Glycoproteomics for prostate cancer detection: changes in serum PSA glycosylation patterns. J Proteome Res 8:613–619. https://doi.org/10.1021/pr8007539

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wang X, Yu J, Sreekumar A, Varambally S, Shen R, Giacherio D, Mehra R, Montie JE, Pienta KJ, Sanda MG, Kantoff PW, Rubin MA, Wei JT, Ghosh D, Chinnaiyan AM (2005) Autoantibody signatures in prostate cancer. N Engl J Med 353(12):1224–1235. https://doi.org/10.1056/NEJMoa051931

    Article  CAS  PubMed  Google Scholar 

  15. Seurynck-Servoss SL, White AM, Baird CL, Rodland KD, Zangar RC (2007) Evaluation of surface chemistries for antibody microarrays. Anal Biochem 371(1):105–115. https://doi.org/10.1016/j.ab.2007.07.010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Horninger W, Cheli CD, Babaian RJ, Fritsche HA, Lepor H, Taneja SS, Childs S, Stamey TA, Sokoll LJ, Chan DW, Brawer MK, Partin AW, Bartsch G (2002) Complexed prostate-specific antigen for early detection of prostate cancer in men with serum prostate-specific antigen levels of 2 to 4 nanograms per milliliter. Urology 60(4 Suppl 1):31–35. https://doi.org/10.1016/s0090-4295(02)01693-x

    Article  PubMed  Google Scholar 

  17. Liu X, Tang J, Fei X, Li QY (2015) Prostate-specific antigen (PSA) density and free to total PSA ratio in diagnosing prostate cancer with prostate-specific antigen levels of 4.0 ng/ml or less. Iran J Public Health 44(11):1466–1472

    PubMed  PubMed Central  Google Scholar 

  18. Bruzzese F, Hägglöf C, Leone A, Sjöberg E, Roca MS, Kiflemariam S, Sjöblom T, Hammarsten P, Egevad L, Bergh A, Ostman A, Budillon A, Augsten M (2014) Local and systemic protumorigenic effects of cancer-associated fibroblast-derived GDF15. Cancer Res 74(13):3408–3417. https://doi.org/10.1158/0008-5472.CAN-13-2259

    Article  CAS  PubMed  Google Scholar 

  19. Vaňhara P, Hampl A, Kozubík A, Souček K (2012) Growth/differentiation factor-15: prostate cancer suppressor or promoter? Prostate Cancer Prostatic Dis 15(4):320–328. https://doi.org/10.1038/pcan.2012.6

    Article  CAS  PubMed  Google Scholar 

  20. Bauskin AR, Brown DA, Kuffner T, Johnen H, Luo XW, Hunter M, Breit SN (2006) Role of macrophage inhibitory cytokine-1 in tumorigenesis and diagnosis of cancer. Cancer Res 66(10):4983–4986. https://doi.org/10.1158/0008-5472.CAN-05-4067

    Article  CAS  PubMed  Google Scholar 

  21. Brown DA, Stephan C, Ward RL, Law M, Hunter M, Bauskin AR, Amin J, Jung K, Diamandis EP, Hampton GM, Russell PJ, Giles GG, Breit SN (2006) Measurement of serum levels of macrophage inhibitory cytokine 1 combined with prostate-specific antigen improves prostate cancer diagnosis. Clin Cancer Res 12:89–96. https://doi.org/10.1158/1078-0432.CCR-05-1331

    Article  CAS  PubMed  Google Scholar 

  22. Stephan C, Xu C, Brown DA, Breit SN, Michael A, Nakamura T, Diamandis EP, Meyer H, Cammann H, Jung K (2006) Three new serum markers for prostate cancer detection within a percent free PSA-based artificial neural network. Prostate 66(6):651–659. https://doi.org/10.1002/pros.20381

    Article  CAS  PubMed  Google Scholar 

  23. Jiang T, Su C, Ren S, Cappuzzo F, Rocco G, Palmer JD, van Zandwijk N, Blackhall F, Le X, Pennell NA, Zhou C (2018) A consensus on the role of osimertinib in non-small cell lung cancer from the AME Lung Cancer Collaborative Group. J Thorac Dis 10(7):3909–3921. https://doi.org/10.21037/jtd.2018.07.61

    Article  PubMed  PubMed Central  Google Scholar 

  24. Tysarowski A, Nasierowska-Guttmejer A (2018) Quality and practical aspects of pathological and molecular diagnostics in metastatic colorectal cancer (mCRC). Contemp Oncol (Pozn) 22(2):75–85. https://doi.org/10.5114/wo.2018.77047

    Article  CAS  Google Scholar 

  25. Reuschenbach M, von Knebel DM, Wentzensen N (2009) A systematic review of humoral immune responses against tumor antigens. Cancer Immunol Immunother 58(10):1535–1544. https://doi.org/10.1007/s00262-009-0733-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sauer U (2017) Analytical protein microarrays: advancements towards clinical applications. Sensors 17(2):256. https://doi.org/10.3390/s17020256

    Article  CAS  Google Scholar 

  27. Srinivasan S, Clements JA, Batra J (2016) Single nucleotide polymorphisms in clinics: fantasy or reality for cancer? Crit Rev Clin Lab Sci 53(1):29–39. https://doi.org/10.3109/10408363.2015.1075469

    Article  CAS  PubMed  Google Scholar 

  28. He XX, Du S, Gao SQ, Chen JY, Cao RJ, Xing ZK, Kazim ARS, Yu HL, Zheng QC, Zhu XJ (2018) Humanization of fibroblast growth factor 1 single-chain antibody and validation for its antitumorigenic efficacy in breast cancer and glioma cells. J Cell Mol Med 22(6):3259–3263. https://doi.org/10.1111/jcmm.13547

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Li J, Chen H, Li X, Wang L, Gao A, Zhang P, Lin W, Gao W, Yang D, Guo X, Liu J, Dang Q, Sun Y (2017) Co-expression of podoplanin and fibroblast growth factor 1 predicts poor prognosis in patients with lung squamous cell carcinoma. Mol Med Rep 16(2):1643–1652. https://doi.org/10.3892/mmr.2017.6830

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Udayakumar TS, Nagle RB, Bowden GT (2004) Fibroblast growth factor-1 transcriptionally induces membrane type-1 matrix metalloproteinase expression in prostate carcinoma cell line. Prostate 58(1):66–75. https://doi.org/10.1002/pros.10293

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This study was supported by NIH/NCI SBIR Phase I Grant, CA159721 (HK).

Author information

Authors and Affiliations

  1. Detroit R&D, Inc., 2727 Second Ave. Suite 4113, Detroit, MI, USA

    Julia Matzenbacher dos Santos, Aby Joiakim, David J. Kaplan, David A. Putt & Hyesook Kim

  2. Department of Education, Health and Human Performance, Fairmont State University, Fairmont, WV, USA

    Julia Matzenbacher dos Santos

  3. Department of Chemical Engineering, University of Arkansas, Fayetteville, AR, USA

    German Perez Bakovic & Shannon L. Servoss

  4. Henry Ford Health System, Detroit, MI, USA

    Benjamin A. Rybicki

  5. Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA

    Alan A. Dombkowski

Authors
  1. Julia Matzenbacher dos Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aby Joiakim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David J. Kaplan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David A. Putt
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. German Perez Bakovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shannon L. Servoss
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Benjamin A. Rybicki
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Alan A. Dombkowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Hyesook Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hyesook Kim.

Ethics declarations

Conflict of interest

Benjamin A. Rybicki, German Perez Bakovic and Shannon L. Servoss declare that they have no competing interests. Hyesook Kim is the president of Detroit R&D, Inc. and has a commercial interest. David J. Kaplan, Aby Joiakim, Julia M. Santos and David A. Putt also work for Detroit R&D, Inc. Alan A. Dombkowski is a board member for Detroit R&D, Inc.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

dos Santos, J.M., Joiakim, A., Kaplan, D.J. et al. Levels of plasma glycan-binding auto-IgG biomarkers improve the accuracy of prostate cancer diagnosis. Mol Cell Biochem 476, 13–22 (2021). https://doi.org/10.1007/s11010-020-03876-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11010-020-03876-7

Keywords

Search

Navigation