Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Molecular Diagnostics

Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling

British Journal of Cancer (2024)Cite this article

Subjects

Abstract

Background

There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery.

Methods

We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues.

Results

We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues.

Conclusions

Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Blood glycopeptide biomarkers identify people with benign and malignant tumors.
Fig. 2: Circulating fucosylated tri- and tetra-antennary N-glycopeptide markers are associated with late-stage EOC.
Fig. 3: Fucosylated tri- and tetra-antennary N-glycopeptide markers are increased in metastatic EOC tissues.
Fig. 4: Putative drivers of cancer-induced glycosylation programs in circulating and tumor glycoproteins.

Similar content being viewed by others

Data availability

Glycoproteomic data are available at ftp://massive.ucsd.edu/v07/MSV000094219/

References

  1. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48.

    Article  PubMed  Google Scholar 

  2. Lheureux S, Gourley C, Vergote I, Oza AM. Epithelial ovarian cancer. Lancet. 2019;393:1240–53.

    Article  PubMed  Google Scholar 

  3. Matulonis UA, Sood AK, Fallowfield L, Howitt BE, Sehouli J, Karlan BY. Ovarian cancer. Nat Rev Dis Prim. 2016;2:1–22.

    Google Scholar 

  4. Lu KH. Screening for ovarian cancer in asymptomatic women. JAMA. 2018;319:557.

    Article  PubMed  Google Scholar 

  5. Bullock B, Larkin L, Turker L, Stampler K. Management of the adnexal mass: considerations for the family medicine physician. Front Med. 2022;9:913549.

    Article  Google Scholar 

  6. Felder M, Kapur A, Gonzalez-Bosquet J, Horibata S, Heintz J, Albrecht R, et al. MUC16 (CA125): tumor biomarker to cancer therapy, a work in progress. Mol Cancer. 2014;13:129.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Duffy MJ, Bonfrer JM, Kulpa J, Rustin GJS, Soletormos G, Torre GC. CA125 in ovarian cancer: European Group on Tumor Markers guidelines for clinical use. Int J Gynecol Cancer J Int Gynecol Cancer Soc. 2005;15:679–91.

    Article  CAS  Google Scholar 

  8. Charkhchi P, Cybulski C, Gronwald J, Wong FO, Narod SA, Akbari MR. CA125 and ovarian cancer: a comprehensive review. Cancers. 2020;12:3730.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Dochez V, Caillon H, Vaucel E, Dimet J, Winer N, Ducarme G. Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review. J Ovarian Res. 2019;12:28.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Skates SJ. Ovarian cancer screening: development of the Risk of Ovarian Cancer Algorithm (ROCA) and ROCA screening trials. Int J Gynecol Cancer. 2012;22:S24–6.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Javdekar R, Maitra N. Risk of Malignancy Index (RMI) in evaluation of adnexal mass. J Obstet Gynecol India. 2015;65:117–21.

    Article  Google Scholar 

  12. Montagnana M, Danese E, Ruzzenente O, Bresciani V, Nuzzo T, Gelati M, et al. The ROMA (Risk of Ovarian Malignancy Algorithm) for estimating the risk of epithelial ovarian cancer in women presenting with pelvic mass: is it really useful? Clin Chem Lab Med. 2011;49:521–5.

    Article  CAS  PubMed  Google Scholar 

  13. Yurkovetsky ZR, Linkov FY, E Malehorn D, Lokshin AE. Multiple biomarker panels for early detection of ovarian cancer. Future Oncol. 2006;2:733–41.

    Article  CAS  PubMed  Google Scholar 

  14. McIntosh M, Anderson G, Drescher C, Hanash S, Urban N, Brown P. Ovarian cancer early detection claims are biased. Clin Cancer Res. 2008;14:7574–7574.

    Article  PubMed  Google Scholar 

  15. Coates RJ, Kolor K, Stewart SL, Richardson LC. Diagnostic markers for ovarian cancer screening: not ready for routine clinical use. Clin Cancer Res. 2008;14:7575–6.

    Article  PubMed  Google Scholar 

  16. Check E. Running before we can walk? Nature. 2004;429:496–7.

    Article  CAS  PubMed  Google Scholar 

  17. Bristow RE, Smith A, Zhang Z, Chan DW, Crutcher G, Fung ET. Ovarian malignancy risk stratification of the adnexal mass using a multivariate index assay. Gynecol Oncol. 2013;128:252–9.

    Article  PubMed  Google Scholar 

  18. Ueland FR, Desimone CP, Seamon LG, Miller RA, Goodrich S, Podzielinski I, et al. Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors. Obstet Gynecol. 2011;117:1289.

    Article  PubMed  Google Scholar 

  19. Lertkhachonsuk AA, Buranawongtrakoon S, Lekskul N, Rermluk N, Wee-Stekly WW, Charakorn C. Serum CA19-9, CA-125 and CEA as tumor markers for mucinous ovarian tumors. J Obstet Gynaecol Res. 2020;46:2287–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hilger WS, Magrina JF, Magtibay PM. Laparoscopic management of the adnexal mass. Clin Obstet Gynecol. 2006;49:535.

    Article  PubMed  Google Scholar 

  21. Schuueler J, Trimbos J, Hermans J. The yield of surgical staging in presumed early stage ovarian cancer. Int J Gynecol Cancer. 1998;8:95–102.

    Article  Google Scholar 

  22. Young RC, Decker DG, Wharton JT, Piver MS, Sindelar WF, Edwards BK. Staging laparotomy in early ovarian cancer. JAMA. 1983;250:3072–6.

    Article  CAS  PubMed  Google Scholar 

  23. Alley WR, Vasseur JA, Goetz JA, Svoboda M, Mann BF, Matei DE, et al. N-linked glycan structures and their expressions change in the blood sera of ovarian cancer patients. J Proteome Res. 2012;11:2282–300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Miyamoto S, Stroble CD, Taylor S, Hong Q, Lebrilla CB, Leiserowitz GS, et al. Multiple reaction monitoring for the quantitation of serum protein glycosylation profiles: application to ovarian cancer. J Proteome Res. 2018;17:222–33.

    Article  CAS  PubMed  Google Scholar 

  25. Ruhaak LR, Kim K, Stroble C, Taylor SL, Hong Q, Miyamoto S, et al. Protein-specific differential glycosylation of immunoglobulins in serum of ovarian cancer patients. J Proteome Res. 2016;15:1002–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Saldova R, Wormald MR, Dwek RA, Rudd PM. Glycosylation changes on serum glycoproteins in ovarian cancer may contribute to disease pathogenesis. Dis Markers. 2008;25:219–32.

    Article  CAS  PubMed  Google Scholar 

  27. Wu Z, Serie D, Xu G, Zou J. PB-Net: Automatic peak integration by sequential deep learning for multiple reaction monitoring. J Proteom. 2020;223:103820.

    Article  CAS  Google Scholar 

  28. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57:289–300.

    Article  Google Scholar 

  29. Bartha Á, Győrffy B. TNMplot.com: A web tool for the comparison of gene expression in normal, tumor and metastatic tissues. Int J Mol Sci. 2021;22:2622.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Jin Y, Wang W, Wang Q, Zhang Y, Zahid KR, Raza U, et al. Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases. Cancer Cell Int. 2022;22:156.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Duché JC, Urien S, Simon N, Malaurie E, Monnet I, Barré J. Expression of the genetic variants of human alpha-1-acid glycoprotein in cancer. Clin Biochem. 2000;33:197–202.

    Article  PubMed  Google Scholar 

  32. Čaval T, Alisson-Silva F, Schwarz F. Roles of glycosylation at the cancer cell surface: opportunities for large scale glycoproteomics. Theranostics. 2023;13:2605–15.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Blanas A, Sahasrabudhe NM, Rodríguez E, van Kooyk Y, van Vliet SJ. Fucosylated antigens in cancer: an alliance toward tumor progression, metastasis, and resistance to chemotherapy. Front Oncol. 2018;8:1–14.

    Google Scholar 

  34. Aranganathan S, Senthil K, Nalini N. A case control study of glycoprotein status in ovarian carcinoma. Clin Biochem. 2005;38:535–9.

    Article  CAS  PubMed  Google Scholar 

  35. Kohler RS, Anugraham M, López MN, Xiao C, Schoetzau A, Hettich T. Epigenetic activation of MGAT3 and corresponding bisecting GlcNAc shortens the survival of cancer patients. Oncotarget. 2016;7:51674–86.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Alix-Panabières C, Marchetti D, Lang JE. Liquid biopsy: from concept to clinical application. Sci Rep. 2023;13:21685.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Pappas L, Adalsteinsson VA, Parikh AR. The emerging promise of liquid biopsies in solid tumors. Nat Cancer. 2022;3:1420–2.

    Article  PubMed  Google Scholar 

  38. Connal S, Cameron JM, Sala A, Brennan PM, Palmer DS, Palmer JD, et al. Liquid biopsies: the future of cancer early detection. J Transl Med. 2023;21:118.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Peracaula R, Sarrats A, Rudd PM. Liver proteins as sensor of human malignancies and inflammation. PROTEOMICS – Clin Appl. 2010;4:426–31.

    Article  CAS  PubMed  Google Scholar 

  40. Suraj S, Dhar C, Srivastava S. Circulating nucleic acids: An analysis of their occurrence in malignancies (Review). Biomed Rep. 2017;6:8–14.

    Article  CAS  PubMed  Google Scholar 

  41. Dědová T, Braicu EI, Sehouli J, Blanchard V. Sialic acid linkage analysis refines the diagnosis of ovarian cancer. Front Oncol. 2019;9:261. https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.00261.

    Article  PubMed  PubMed Central  Google Scholar 

  42. An HJ, Miyamoto S, Lancaster KS, Kirmiz C, Li B, Lam KS, et al. Profiling of Glycans in serum for the discovery of potential biomarkers for ovarian cancer. J Proteome Res. 2006;5:1626–35.

    Article  CAS  PubMed  Google Scholar 

  43. Hua S, Williams CC, Dimapasoc LM, Ro GS, Ozcan S, Miyamoto S, et al. Isomer-specific chromatographic profiling yields highly sensitive and specific potential N-glycan biomarkers for epithelial ovarian cancer. J Chromatogr A. 2013;1279:58–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kim K, Ruhaak LR, Nguyen UT, Taylor SL, Dimapasoc L, Williams C. Evaluation of glycomic profiling as a diagnostic biomarker for epithelial ovarian cancer. Cancer Epidemiol Biomark Prev. 2014;23:611–21.

    Article  CAS  Google Scholar 

  45. Horita S, Nomura Y, Sato Y, Shimamura T, Iwata S, Nomura N. High-resolution crystal structure of the therapeutic antibody pembrolizumab bound to the human PD-1. Sci Rep. 2016;6:35297.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Abbott KL, Lim JM, Wells L, Benigno BB, McDonald JF, Pierce M. Identification of candidate biomarkers with cancer-specific glycosylation in the tissue and serum of endometrioid ovarian cancer patients by glycoproteomic analysis. Proteomics 2010;10:470–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Biskup K, Braicu EI, Sehouli J, Tauber R, Blanchard V. The ascites N-glycome of epithelial ovarian cancer patients. J Proteom. 2017;157:33–9.

    Article  CAS  Google Scholar 

  48. Anugraham M, Jacob F, Nixdorf S, Everest-Dass AV, Heinzelmann-Schwarz V, Packer NH. Specific glycosylation of membrane proteins in epithelial ovarian cancer cell lines: glycan structures reflect gene expression and DNA methylation status*. Mol Cell Proteom. 2014;13:2213–32.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank all the colleagues at InterVenn Biosciences, in particular Ranjan Bhadra for sample management, Cassie Xu for establishing protocols to analyze mRNA sequencing data, and Hector Huang, Robert Cheng, Itati Hundal and Gregg Czerwieniec for support with mass spectrometry analysis. We are grateful to Carlito Lebrilla for reviewing the manuscript and providing feedback.

Funding

This study was funded by InterVenn Bioscience. FJ was supported by the Swiss Cancer Research foundation (project number KFS-5389-08-2021-R).

Author information

Author notes

  1. These authors contributed equally: Chirag Dhar, Prasanna Ramachandran, Gege Xu.

Authors and Affiliations

  1. InterVenn Biosciences, South San Francisco, CA, USA

    Chirag Dhar, Prasanna Ramachandran, Gege Xu, Chad Pickering, Tomislav Čaval, Maurice Wong, Rachel Rice, Bo Zhou, Apoorva Srinivasan, Paul Aiyetan, Chih-Wei Chu, Kaitlyn Moser, Daniel Serie, Klaus Lindpaintner & Flavio Schwarz

  2. Division of Gynecologic Oncology, University of Cincinnati Cancer Center, Cincinnati, OH, USA

    Thomas J. Herzog

  3. Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Alexander Babatunde Olawaiye

  4. Ovarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland

    Francis Jacob

Authors
  1. Chirag Dhar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prasanna Ramachandran
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gege Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chad Pickering
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tomislav Čaval
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Maurice Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rachel Rice
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bo Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Apoorva Srinivasan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Paul Aiyetan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Chih-Wei Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Kaitlyn Moser
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Thomas J. Herzog
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Alexander Babatunde Olawaiye
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Francis Jacob
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Daniel Serie
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Klaus Lindpaintner
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Flavio Schwarz
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Project conceptualization: CD, DS, KL, FS. Data generation and analysis: CD, PR, GX, CP, TC, MW, RR, BZ, AS, PA, CC, FJ. Data visualization: CD, PR, CP, BZ, PA, FJ. Clinical samples acquisition: KM. Manuscript writing: CD, KL, FS. Manuscript review, editing and approval: all authors.

Corresponding author

Correspondence to Flavio Schwarz.

Ethics declarations

Competing interests

CD, PR, GX, CP, TC, MW, RR, BZ, AS, PA, CWC, KM, DS, KS and FS are or were employees of InterVenn, a company that discovers biomarkers and develops diagnostic tests. TJH received consulting fees from AZ, Caris, Clovis, Eisai, Epsilogen, Genelux, Genentech, GSK, Immunogen, J&J, Merck, Mersana, and Seagen. TJH also received support for attending meetings and/or travel from Alkermes and is on the leadership board of the GOG foundation. Additionally, TJH participated in a Data Safety Monitoring Board/Advisory Board with Corcept. ABO attended advisory board meetings for Merck, GSK, AZ, Genentech, Immunogen.

Ethics approval and consent to participate

All subjects gave written informed consent to participate. The study was approved by an institutional review board (WCG IRB 20223899 and WIRB IRB 20190246) and performed in accordance with the Declaration of Helsinki.

Additional information

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

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dhar, C., Ramachandran, P., Xu, G. et al. Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling. Br J Cancer (2024). https://doi.org/10.1038/s41416-024-02644-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41416-024-02644-4

Search

Advanced search

Quick links