Skip to main content

Advertisement

SpringerLink
Log in

Glycosylation in cancer: its application as a biomarker and recent advances of analytical techniques

  • Original Article
  • Published:
Glycoconjugate Journal Aims and scope Submit manuscript

Abstract

Despite significant worldwide investment in research, cancer remains one of the most common cause of death in the world. Early detection and reliable diagnosis are the keys to effectively treating cancer and improving the long-term survival of cancer patients. Therefore, there is an urgent need to develop a single, non-invasive biomarker with high sensitivity and specificity. Aberrant glycosylation is well defined as a hallmark of cancer and represents a promising source of potential biomarkers. Tumor-associated carbohydrate epitopes have long been detected by using monoclonal antibodies and lectins. Recent advances in analytical technologies allow us to analyze cancer-specific glycoforms on a target protein in a variety of clinical samples. A number of glycan analysis techniques, such as lectin-based detection methods and mass spectrometry combined with various types of chromatography, have been developed to establish novel glycoform-specific cancer biomarkers. Several glycan-based cancer biomarkers are already in clinical use. The aim of this review is to outline the role of glycan as a cancer biomarker and to summarize the current status and the potential for contribution of the serum glycoproteome to cancer diagnostics, monitoring, and prognostics.

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. Sung, H., Ferlay, J., Siegel, R.L., Laversanne, M., Soerjomataram, I., Jemal, A., Bray, F.: Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 71(3), 209–249 (2021). https://doi.org/10.3322/caac.21660

    Article  PubMed  Google Scholar 

  2. Ludwig, J.A., Weinstein, J.N.: Biomarkers in cancer staging, prognosis and treatment selection. Nat. Rev. Cancer 5(11), 845–856 (2005). https://doi.org/10.1038/nrc1739

    Article  CAS  PubMed  Google Scholar 

  3. Chia, J., Goh, G., Bard, F.: Short O-GalNAc glycans: regulation and role in tumor development and clinical perspectives. Biochim. Biophys. Acta. 1860(8), 1623–1639 (2016). https://doi.org/10.1016/j.bbagen.2016.03.008

    Article  CAS  PubMed  Google Scholar 

  4. Steentoft, C., Vakhrushev, S.Y., Joshi, H.J., Kong, Y., Vester-Christensen, M.B., Schjoldager, K.T., Lavrsen, K., Dabelsteen, S., Pedersen, N.B., Marcos-Silva, L., Gupta, R., Bennett, E.P., Mandel, U., Brunak, S., Wandall, H.H., Levery, S.B., Clausen, H.: Precision mapping of the human O-GalNAc glycoproteome through SimpleCell technology. EMBO J. 32(10), 1478–1488 (2013). https://doi.org/10.1038/emboj.2013.79

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Clerc, F., Reiding, K.R., Jansen, B.C., Kammeijer, G.S., Bondt, A., Wuhrer, M.: Human plasma protein N-glycosylation. Glycoconj. J. 33(3), 309–343 (2016). https://doi.org/10.1007/s10719-015-9626-2

    Article  CAS  PubMed  Google Scholar 

  6. Reily, C., Stewart, T.J., Renfrow, M.B., Novak, J.: Glycosylation in health and disease. Nat. Rev. Nephrol. 15(6), 346–366 (2019). https://doi.org/10.1038/s41581-019-0129-4

    Article  PubMed  PubMed Central  Google Scholar 

  7. Hakomori, S., Jeanloz, R.W.: Isolation of a glycolipid containing fucose, galactose, glucose, and glucosamine from human cancerous tissue. The J. biol. chem. 239, Pc3606–3607 (1964)

  8. Hakomori, S.: Aberrant glycosylation in tumors and tumor-associated carbohydrate antigens. Adv. Cancer Res. 52, 257–331 (1989). https://doi.org/10.1016/s0065-230x(08)60215-8

    Article  CAS  PubMed  Google Scholar 

  9. Hakomori, S., Kannagi, R.: Glycosphingolipids as tumor-associated and differentiation markers. J. Natl. Cancer Inst. 71(2), 231–251 (1983)

    CAS  PubMed  Google Scholar 

  10. Pinho, S.S., Reis, C.A.: Glycosylation in cancer: mechanisms and clinical implications. Nat. Rev. Cancer 15(9), 540–555 (2015). https://doi.org/10.1038/nrc3982

    Article  CAS  PubMed  Google Scholar 

  11. Hakomori, S.: Tumor malignancy defined by aberrant glycosylation and sphingo(glyco)lipid metabolism. Cancer Res. 56(23), 5309–5318 (1996)

    CAS  PubMed  Google Scholar 

  12. Handa, K., Hakomori, S.I.: Carbohydrate to carbohydrate interaction in development process and cancer progression. Glycoconj. J. 29(8–9), 627–637 (2012). https://doi.org/10.1007/s10719-012-9380-7

    Article  CAS  PubMed  Google Scholar 

  13. Julien, S., Bobowski, M., Steenackers, A., Le Bourhis, X., Delannoy, P.: How Do Gangliosides Regulate RTKs Signaling? Cells 2(4), 751–767 (2013). https://doi.org/10.3390/cells2040751

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Hakomori, S.I., Cummings, R.D.: Glycosylation effects on cancer development. Glycoconj. J. 29(8–9), 565–566 (2012). https://doi.org/10.1007/s10719-012-9448-4

    Article  CAS  PubMed  Google Scholar 

  15. Hakomori, S.I., Handa, K.: GM3 and cancer. Glycoconj. J. 32(1–2), 1–8 (2015). https://doi.org/10.1007/s10719-014-9572-4

    Article  CAS  PubMed  Google Scholar 

  16. Bremer, E.G., Schlessinger, J., Hakomori, S.: Ganglioside-mediated modulation of cell growth. Specific effects of GM3 on tyrosine phosphorylation of the epidermal growth factor receptor. The J. biol. chem. 261(5), 2434–2440 (1986)

  17. Yoon, S.J., Nakayama, K., Hikita, T., Handa, K., Hakomori, S.I.: Epidermal growth factor receptor tyrosine kinase is modulated by GM3 interaction with N-linked GlcNAc termini of the receptor. Proc. Natl. Acad. Sci. U.S.A. 103(50), 18987–18991 (2006). https://doi.org/10.1073/pnas.0609281103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kawashima, N., Yoon, S.J., Itoh, K., Nakayama, K.: Tyrosine kinase activity of epidermal growth factor receptor is regulated by GM3 binding through carbohydrate to carbohydrate interactions. J. Biol. Chem. 284(10), 6147–6155 (2009). https://doi.org/10.1074/jbc.M808171200

    Article  CAS  PubMed  Google Scholar 

  19. Varki, A., Kannagi, R., Toole, B., Stanley, P.: Glycosylation Changes in Cancer. In: rd, Varki, A., Cummings, R.D., Esko, J.D., Stanley, P., Hart, G.W., Aebi, M., Darvill, A.G., Kinoshita, T., Packer, N.H., Prestegard, J.H., Schnaar, R.L., Seeberger, P.H. (eds.): Essentials of Glycobiology. pp. 597–609. Cold Spring Harbor Laboratory Press Copyright 2015–2017 by The Consortium of Glycobiology Editors, La Jolla, California. All rights reserved., Cold Spring Harbor (NY) (2015)

  20. Taniguchi, N., Honke, K., Fukuda, M.: Handbook of Glycosyltransferases and Related Genes. In. Springer, Tokyo, (2002)

  21. Huang, Y.F., Aoki, K., Akase, S., Ishihara, M., Liu, Y.S., Yang, G., Kizuka, Y., Mizumoto, S., Tiemeyer, M., Gao, X.D., Aoki-Kinoshita, K.F., Fujita, M.: Global mapping of glycosylation pathways in human-derived cells. Dev. Cell. 56(8), 1195–1209 e1197 (2021). https://doi.org/10.1016/j.devcel.2021.02.023

  22. Kizuka, Y., Taniguchi, N.: Enzymes for N-Glycan Branching and Their Genetic and Nongenetic Regulation in Cancer. Biomolecules 6(2) (2016). https://doi.org/10.3390/biom6020025

  23. Noda, K., Miyoshi, E., Uozumi, N., Gao, C.X., Suzuki, K., Hayashi, N., Hori, M., Taniguchi, N.: High expression of alpha-1-6 fucosyltransferase during rat hepatocarcinogenesis. Int. J. Cancer 75(3), 444–450 (1998). https://doi.org/10.1002/(sici)1097-0215(19980130)75:3%3c444::aid-ijc19%3e3.0.co;2-8

    Article  CAS  PubMed  Google Scholar 

  24. Chen, C.Y., Jan, Y.H., Juan, Y.H., Yang, C.J., Huang, M.S., Yu, C.J., Yang, P.C., Hsiao, M., Hsu, T.L., Wong, C.H.: Fucosyltransferase 8 as a functional regulator of nonsmall cell lung cancer. Proc. Natl. Acad. Sci. U.S.A. 110(2), 630–635 (2013). https://doi.org/10.1073/pnas.1220425110

    Article  PubMed  Google Scholar 

  25. Honma, R., Kinoshita, I., Miyoshi, E., Tomaru, U., Matsuno, Y., Shimizu, Y., Takeuchi, S., Kobayashi, Y., Kaga, K., Taniguchi, N., Dosaka-Akita, H.: Expression of fucosyltransferase 8 is associated with an unfavorable clinical outcome in non-small cell lung cancers. Oncology 88(5), 298–308 (2015). https://doi.org/10.1159/000369495

    Article  CAS  PubMed  Google Scholar 

  26. Potapenko, I.O., Haakensen, V.D., Luders, T., Helland, A., Bukholm, I., Sorlie, T., Kristensen, V.N., Lingjaerde, O.C., Borresen-Dale, A.L.: Glycan gene expression signatures in normal and malignant breast tissue; possible role in diagnosis and progression. Mol. Oncol. 4(2), 98–118 (2010). https://doi.org/10.1016/j.molonc.2009.12.001

    Article  CAS  PubMed  Google Scholar 

  27. Saldova, R., Fan, Y., Fitzpatrick, J.M., Watson, R.W., Rudd, P.M.: Core fucosylation and alpha2-3 sialylation in serum N-glycome is significantly increased in prostate cancer comparing to benign prostate hyperplasia. Glycobiology 21(2), 195–205 (2011). https://doi.org/10.1093/glycob/cwq147

    Article  CAS  PubMed  Google Scholar 

  28. Wang, X., Chen, J., Li, Q.K., Peskoe, S.B., Zhang, B., Choi, C., Platz, E.A., Zhang, H.: Overexpression of alpha (1,6) fucosyltransferase associated with aggressive prostate cancer. Glycobiology 24(10), 935–944 (2014). https://doi.org/10.1093/glycob/cwu051

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhang, Z., Wuhrer, M., Holst, S.: Serum sialylation changes in cancer. Glycoconj. J. 35(2), 139–160 (2018). https://doi.org/10.1007/s10719-018-9820-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lasky, L.A.: Selectin-carbohydrate interactions and the initiation of the inflammatory response. Annu. Rev. Biochem. 64, 113–139 (1995). https://doi.org/10.1146/annurev.bi.64.070195.000553

    Article  CAS  PubMed  Google Scholar 

  31. Brockhausen, I., Stanley, P.: O-GalNAc Glycans. In: rd, Varki, A., Cummings, R.D., Esko, J.D., Stanley, P., Hart, G.W., Aebi, M., Darvill, A.G., Kinoshita, T., Packer, N.H., Prestegard, J.H., Schnaar, R.L., Seeberger, P.H. (eds.) Essentials of Glycobiology. pp. 113–123. Cold Spring Harbor Laboratory Press

  32. Oliveira-Ferrer, L., Legler, K., Milde-Langosch, K.: Role of protein glycosylation in cancer metastasis. Semin. Cancer Biol. 44, 141–152 (2017). https://doi.org/10.1016/j.semcancer.2017.03.002

    Article  CAS  PubMed  Google Scholar 

  33. Huang, M.J., Hu, R.H., Chou, C.H., Hsu, C.L., Liu, Y.W., Huang, J., Hung, J.S., Lai, I.R., Juan, H.F., Yu, S.L., Wu, Y.M., Huang, M.C.: Knockdown of GALNT1 suppresses malignant phenotype of hepatocellular carcinoma by suppressing EGFR signaling. Oncotarget 6(8), 5650–5665 (2015). https://doi.org/10.18632/oncotarget.3117

    Article  PubMed  PubMed Central  Google Scholar 

  34. Springer, G.F., Desai, P.R., Banatwala, I.: Blood group MN antigens and precursors in normal and malignant human breast glandular tissue. J. Natl. Cancer Inst. 54(2), 335–339 (1975)

    CAS  PubMed  Google Scholar 

  35. Springer, G.F., Murthy, M.S., Desai, P.R., Scanlon, E.F.: Breast cancer patient’s cell-mediated immune response to Thomsen-Friedenreich (T) antigen. Cancer 45(12), 2949–2954 (1980). https://doi.org/10.1002/1097-0142(19800615)45:12%3c2949::aid-cncr2820451210%3e3.0.co;2-l

    Article  CAS  PubMed  Google Scholar 

  36. Osako, M., Yonezawa, S., Siddiki, B., Huang, J., Ho, J.J., Kim, Y.S., Sato, E.: Immunohistochemical study of mucin carbohydrates and core proteins in human pancreatic tumors. Cancer 71(7), 2191–2199 (1993). https://doi.org/10.1002/1097-0142(19930401)71:7%3c2191::aid-cncr2820710705%3e3.0.co;2-x

    Article  CAS  PubMed  Google Scholar 

  37. Laack, E., Nikbakht, H., Peters, A., Kugler, C., Jasiewicz, Y., Edler, L., Hossfeld, D.K., Schumacher, U.: Lectin histochemistry of resected adenocarcinoma of the lung: helix pomatia agglutinin binding is an independent prognostic factor. Am. J. Pathol. 160(3), 1001–1008 (2002). https://doi.org/10.1016/s0002-9440(10)64921-8

    Article  PubMed  PubMed Central  Google Scholar 

  38. Itzkowitz, S.H., Bloom, E.J., Lau, T.S., Kim, Y.S.: Mucin associated Tn and sialosyl-Tn antigen expression in colorectal polyps. Gut 33(4), 518–523 (1992). https://doi.org/10.1136/gut.33.4.518

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Cao, Y., Karsten, U.R., Liebrich, W., Haensch, W., Springer, G.F., Schlag, P.M.: Expression of Thomsen-Friedenreich-related antigens in primary and metastatic colorectal carcinomas. A reevaluation. Cancer 76(10), 1700–1708 (1995). https://doi.org/10.1002/1097-0142(19951115)76:10%3c1700::aid-cncr2820761005%3e3.0.co;2-z

    Article  CAS  PubMed  Google Scholar 

  40. Langkilde, N.C., Wolf, H., Clausen, H., Kjeldsen, T., Orntoft, T.F.: Nuclear volume and expression of T-antigen, sialosyl-Tn-antigen, and Tn-antigen in carcinoma of the human bladder. Relation to tumor recurrence and progression. Cancer 69(1), 219–227 (1992).

  41. Hamada, S., Furumoto, H., Kamada, M., Hirao, T., Aono, T.: High expression rate of Tn antigen in metastatic lesions of uterine cervical cancers. Cancer Lett. 74(3), 167–173 (1993). https://doi.org/10.1016/0304-3835(93)90239-6

    Article  CAS  PubMed  Google Scholar 

  42. Hirao, T., Sakamoto, Y., Kamada, M., Hamada, S., Aono, T.: Tn antigen, a marker of potential for metastasis of uterine cervix cancer cells. Cancer 72(1), 154–159 (1993). https://doi.org/10.1002/1097-0142(19930701)72:1%3c154::aid-cncr2820720129%3e3.0.co;2-c

    Article  CAS  PubMed  Google Scholar 

  43. Kakeji, Y., Tsujitani, S., Mori, M., Maehara, Y., Sugimachi, K.: Helix pomatia agglutinin binding activity is a predictor of survival time for patients with gastric carcinoma. Cancer 68(11), 2438–2442 (1991). https://doi.org/10.1002/1097-0142(19911201)68:11%3c2438::aid-cncr2820681119%3e3.0.co;2-#

    Article  CAS  PubMed  Google Scholar 

  44. David, L., Nesland, J.M., Clausen, H., Carneiro, F., Sobrinho-Simoes, M.: Simple mucin-type carbohydrate antigens (Tn, sialosyl-Tn and T) in gastric mucosa, carcinomas and metastases. APMIS Suppl. 27, 162–172 (1992)

    CAS  PubMed  Google Scholar 

  45. Therkildsen, M.H., Mandel, U., Christensen, M., Dabelsteen, E.: Simple mucin-type Tn and sialosyl-Tn carbohydrate antigens in salivary gland carcinomas. Cancer 72(4), 1147–1154 (1993). https://doi.org/10.1002/1097-0142(19930815)72:4%3c1147::aid-cncr2820720403%3e3.0.co;2-a

    Article  CAS  PubMed  Google Scholar 

  46. Roxby, D.J., Pfeiffer, M.B., Morley, A.A., Kirkland, M.A.: Expression of the Tn antigen in myelodysplasia, lymphoma, and leukemia. Transfusion 32(9), 834–838 (1992). https://doi.org/10.1046/j.1537-2995.1992.32993110755.x

    Article  CAS  PubMed  Google Scholar 

  47. Kufe, D.W.: Mucins in cancer: function, prognosis and therapy. Nat. Rev. Cancer 9(12), 874–885 (2009). https://doi.org/10.1038/nrc2761

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Hollingsworth, M.A., Swanson, B.J.: Mucins in cancer: protection and control of the cell surface. Nat. Rev. Cancer 4(1), 45–60 (2004). https://doi.org/10.1038/nrc1251

    Article  CAS  PubMed  Google Scholar 

  49. Kudelka, M.R., Ju, T., Heimburg-Molinaro, J., Cummings, R.D.: Simple sugars to complex disease–mucin-type O-glycans in cancer. Adv. Cancer Res. 126, 53–135 (2015). https://doi.org/10.1016/bs.acr.2014.11.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Almeida, A., Kolarich, D.: The promise of protein glycosylation for personalised medicine. Biochim. Biophys. Acta 1860(8), 1583–1595 (2016). https://doi.org/10.1016/j.bbagen.2016.03.012

    Article  CAS  PubMed  Google Scholar 

  51. Adamczyk, B., Tharmalingam, T., Rudd, P.M.: Glycans as cancer biomarkers. Biochim. Biophys. Acta 1820(9), 1347–1353 (2012). https://doi.org/10.1016/j.bbagen.2011.12.001

    Article  CAS  PubMed  Google Scholar 

  52. Hashim, O.H., Jayapalan, J.J., Lee, C.S.: Lectins: an effective tool for screening of potential cancer biomarkers. Peer J. 5,(2017)

  53. Ambrosi, M., Cameron, N.R., Davis, B.G.: Lectins: tools for the molecular understanding of the glycocode. Org. Biomol. Chem. 3(9), 1593–1608 (2005). https://doi.org/10.1039/b414350g

    Article  CAS  PubMed  Google Scholar 

  54. Gornik, O., Lauc, G.: Enzyme linked lectin assay (ELLA) for direct analysis of transferrin sialylation in serum samples. Clin. Biochem. 40(9–10), 718–723 (2007). https://doi.org/10.1016/j.clinbiochem.2007.01.010

    Article  CAS  PubMed  Google Scholar 

  55. Reusch, D., Haberger, M., Maier, B., Maier, M., Kloseck, R., Zimmermann, B., Hook, M., Szabo, Z., Tep, S., Wegstein, J., Alt, N., Bulau, P., Wuhrer, M.: Comparison of methods for the analysis of therapeutic immunoglobulin G Fc-glycosylation profiles–part 1: separation-based methods. MAbs 7(1), 167–179 (2015). https://doi.org/10.4161/19420862.2014.986000

    Article  CAS  PubMed  Google Scholar 

  56. Yu, A., Zhao, J., Peng, W., Banazadeh, A., Williamson, S.D., Goli, M., Huang, Y., Mechref, Y.: Advances in mass spectrometry-based glycoproteomics. Electrophoresis 39(24), 3104–3122 (2018). https://doi.org/10.1002/elps.201800272

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Stadlmann, J., Pabst, M., Kolarich, D., Kunert, R., Altmann, F.: Analysis of immunoglobulin glycosylation by LC-ESI-MS of glycopeptides and oligosaccharides. Proteomics 8(14), 2858–2871 (2008). https://doi.org/10.1002/pmic.200700968

    Article  CAS  PubMed  Google Scholar 

  58. Huffman, J.E., Pučić-Baković, M., Klarić, L., Hennig, R., Selman, M.H., Vučković, F., Novokmet, M., Krištić, J., Borowiak, M., Muth, T., Polašek, O., Razdorov, G., Gornik, O., Plomp, R., Theodoratou, E., Wright, A.F., Rudan, I., Hayward, C., Campbell, H., Deelder, A.M., Reichl, U., Aulchenko, Y.S., Rapp, E., Wuhrer, M., Lauc, G.: Comparative performance of four methods for high-throughput glycosylation analysis of immunoglobulin G in genetic and epidemiological research. Molecular & cellular proteomics : MCP 13(6), 1598–1610 (2014). https://doi.org/10.1074/mcp.M113.037465

    Article  CAS  PubMed Central  Google Scholar 

  59. van der Burgt, Y.E.M., Siliakus, K.M., Cobbaert, C.M., Ruhaak, L.R.: HILIC-MRM-MS for Linkage-Specific Separation of Sialylated Glycopeptides to Quantify Prostate-Specific Antigen Proteoforms. J. Proteome Res. (2020). https://doi.org/10.1021/acs.jproteome.0c00050

    Article  PubMed  PubMed Central  Google Scholar 

  60. Kammeijer, G.S.M., Jansen, B.C., Kohler, I., Heemskerk, A.A.M., Mayboroda, O.A., Hensbergen, P.J., Schappler, J., Wuhrer, M.: Sialic acid linkage differentiation of glycopeptides using capillary electrophoresis - electrospray ionization - mass spectrometry. Sci. Rep. 7(1), 3733 (2017). https://doi.org/10.1038/s41598-017-03838-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Kammeijer, G.S.M., Nouta, J., de la Rosette, J., de Reijke, T.M., Wuhrer, M.: An In-Depth Glycosylation Assay for Urinary Prostate-Specific Antigen. Anal. Chem. 90(7), 4414–4421 (2018). https://doi.org/10.1021/acs.analchem.7b04281

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Selman, M.H., Hoffmann, M., Zauner, G., McDonnell, L.A., Balog, C.I., Rapp, E., Deelder, A.M., Wuhrer, M.: MALDI-TOF-MS analysis of sialylated glycans and glycopeptides using 4-chloro-α-cyanocinnamic acid matrix. Proteomics 12(9), 1337–1348 (2012). https://doi.org/10.1002/pmic.201100498

    Article  CAS  PubMed  Google Scholar 

  63. Kolarich, D., Jensen, P.H., Altmann, F., Packer, N.H.: Determination of site-specific glycan heterogeneity on glycoproteins. Nat. Protoc. 7(7), 1285–1298 (2012). https://doi.org/10.1038/nprot.2012.062

    Article  CAS  PubMed  Google Scholar 

  64. Reusch, D., Haberger, M., Falck, D., Peter, B., Maier, B., Gassner, J., Hook, M., Wagner, K., Bonnington, L., Bulau, P., Wuhrer, M.: Comparison of methods for the analysis of therapeutic immunoglobulin G Fc-glycosylation profiles-Part 2: Mass spectrometric methods. MAbs 7(4), 732–742 (2015). https://doi.org/10.1080/19420862.2015.1045173

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Glaskin, R.S., Khatri, K., Wang, Q., Zaia, J., Costello, C.E.: Construction of a Database of Collision Cross Section Values for Glycopeptides, Glycans, and Peptides Determined by IM-MS. Anal. Chem. 89(8), 4452–4460 (2017). https://doi.org/10.1021/acs.analchem.6b04146

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Manz, C., Pagel, K.: Glycan analysis by ion mobility-mass spectrometry and gas-phase spectroscopy. Curr. Opin. Chem. Biol. 42, 16–24 (2018). https://doi.org/10.1016/j.cbpa.2017.10.021

    Article  CAS  PubMed  Google Scholar 

  67. Lanucara, F., Holman, S.W., Gray, C.J., Eyers, C.E.: The power of ion mobility-mass spectrometry for structural characterization and the study of conformational dynamics. Nat. Chem. 6(4), 281–294 (2014). https://doi.org/10.1038/nchem.1889

    Article  CAS  PubMed  Google Scholar 

  68. Abrahams, J.L., Taherzadeh, G., Jarvas, G., Guttman, A., Zhou, Y., Campbell, M.P.: Recent advances in glycoinformatic platforms for glycomics and glycoproteomics. Curr. Opin. Struct. Biol. 62, 56–69 (2019). https://doi.org/10.1016/j.sbi.2019.11.009

    Article  CAS  PubMed  Google Scholar 

  69. Ye, Z., Mao, Y., Clausen, H., Vakhrushev, S.Y.: Glyco-DIA: a method for quantitative O-glycoproteomics with in silico-boosted glycopeptide libraries. Nat. Methods 16(9), 902–910 (2019). https://doi.org/10.1038/s41592-019-0504-x

    Article  CAS  PubMed  Google Scholar 

  70. Fuzery, A.K., Levin, J., Chan, M.M., Chan, D.W.: Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges. Clin. Proteomics 10(1), 13 (2013). https://doi.org/10.1186/1559-0275-10-13

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Chinen, A.B., Guan, C.M., Ferrer, J.R., Barnaby, S.N., Merkel, T.J., Mirkin, C.A.: Nanoparticle Probes for the Detection of Cancer Biomarkers, Cells, and Tissues by Fluorescence. Chem. Rev. 115(19), 10530–10574 (2015). https://doi.org/10.1021/acs.chemrev.5b00321

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Romano, G.: Tumor markers currently utilized in cancer care. Maters. Methods 5 (2015). https://doi.org/10.13070/mm.en.5.1456

  73. Kirwan, A., Utratna, M., O’Dwyer, M.E., Joshi, L., Kilcoyne, M.: Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics. Biomed. Res. Int. 2015,(2015)

  74. Dixit, C.K., Kadimisetty, K., Otieno, B.A., Tang, C., Malla, S., Krause, C.E., Rusling, J.F.: Electrochemistry-based approaches to low cost, high sensitivity, automated, multiplexed protein immunoassays for cancer diagnostics. Analyst 141(2), 536–547 (2016). https://doi.org/10.1039/c5an01829c

    Article  CAS  PubMed  Google Scholar 

  75. Magnani, J.L., Nilsson, B., Brockhaus, M., Zopf, D., Steplewski, Z., Koprowski, H., Ginsburg, V.: A monoclonal antibody-defined antigen associated with gastrointestinal cancer is a ganglioside containing sialylated lacto-N-fucopentaose II. J. Biol. Chem. 257(23), 14365–14369 (1982)

    Article  CAS  Google Scholar 

  76. Ballehaninna, U.K., Chamberlain, R.S.: Serum CA 19–9 as a Biomarker for Pancreatic Cancer-A Comprehensive Review. Indian J. Surg. Oncol. 2(2), 88–100 (2011). https://doi.org/10.1007/s13193-011-0042-1

    Article  PubMed  PubMed Central  Google Scholar 

  77. Andrén-Sandberg, A.: CA 50 and CA 19–9 in serum as tumor markers for pancreatic cancer: a review of the literature. Acta Chir. Scand. Suppl. 549, 75–81 (1989)

    PubMed  Google Scholar 

  78. Swiderska, M., Choromańska, B., Dąbrowska, E., Konarzewska-Duchnowska, E., Choromańska, K., Szczurko, G., Myśliwiec, P., Dadan, J., Ladny, J.R., Zwierz, K.: The diagnostics of colorectal cancer. Contemporary oncology (Poznan, Poland) 18(1), 1–6 (2014). https://doi.org/10.5114/wo.2013.39995

    Article  CAS  Google Scholar 

  79. Galli, C., Basso, D., Plebani, M.: CA 19–9: handle with care. Clin. Chem. Lab. Med. 51(7), 1369–1383 (2013). https://doi.org/10.1515/cclm-2012-0744

    Article  CAS  PubMed  Google Scholar 

  80. López Vélez, M., Martínez Martínez, F.: Study of serum antioxidant capacity and relation with CA 19–9 and PSA in patients with gastrointestinal tract and prostate tumors. Clin. Biochem. 44(13), 1121–1127 (2011). https://doi.org/10.1016/j.clinbiochem.2011.06.082

    Article  CAS  PubMed  Google Scholar 

  81. Kato, K., Taniguchi, M., Kawakami, T., Nagase, A., Matsuda, M., Onodea, K., Yamaguchi, H., Higuchi, M., Furukawa, H.: Gastric Cancer with a Very High Serum CA 19–9 Level. Case Rep. Gastroenterol. 5(1), 258–261 (2011). https://doi.org/10.1159/000327984

    Article  PubMed  PubMed Central  Google Scholar 

  82. Musto, A., Grassetto, G., Marzola, M.C., Rampin, L., Chondrogiannis, S., Maffione, A.M., Colletti, P.M., Perkins, A.C., Fagioli, G., Rubello, D.: Management of epithelial ovarian cancer from diagnosis to restaging: an overview of the role of imaging techniques with particular regard to the contribution of 18F-FDG PET/CT. Nucl. Med. Commun. 35(6), 588–597 (2014). https://doi.org/10.1097/mnm.0000000000000091

    Article  CAS  PubMed  Google Scholar 

  83. Díaz-Padilla, I., Razak, A.R., Minig, L., Bernardini, M.Q., María Del Campo, J.: Prognostic and predictive value of CA-125 in the primary treatment of epithelial ovarian cancer: potentials and pitfalls. Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico 14(1), 15–20 (2012). https://doi.org/10.1007/s12094-012-0756-8

    Article  CAS  Google Scholar 

  84. Brooks, M.: Breast cancer screening and biomarkers. Methods in molecular biology (Clifton, N.J.) 472, 307–321 (2009). https://doi.org/10.1007/978-1-60327-492-0_13

  85. Hayes, D.F., Sekine, H., Ohno, T., Abe, M., Keefe, K., Kufe, D.W.: Use of a murine monoclonal antibody for detection of circulating plasma DF3 antigen levels in breast cancer patients. J. Clin. Investig. 75(5), 1671–1678 (1985). https://doi.org/10.1172/jci111875

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Donepudi, M.S., Kondapalli, K., Amos, S.J., Venkanteshan, P.: Breast cancer statistics and markers. J. Cancer Res. Ther. 10(3), 506–511 (2014). https://doi.org/10.4103/0973-1482.137927

    Article  PubMed  Google Scholar 

  87. Farghaly, S.A.: Tumor markers in gynecologic cancer. Gynecol. Obstet. Invest. 34(2), 65–72 (1992). https://doi.org/10.1159/000292728

    Article  CAS  PubMed  Google Scholar 

  88. Wang, X.F., Wu, Y.H., Wang, M.S., Wang, Y.S.: CEA, AFP, CA125, CA153 and CA199 in malignant pleural effusions predict the cause. Asian Pacific journal of cancer prevention : APJCP 15(1), 363–368 (2014). https://doi.org/10.7314/apjcp.2014.15.1.363

    Article  PubMed  Google Scholar 

  89. Shu, J., Li, C.G., Liu, Y.C., Yan, X.C., Xu, X., Huang, X.E., Cao, J., Li, Y., Lu, Y.Y., Wu, X.Y., Liu, J., Xiang, J.: Comparison of serum tumor associated material (TAM) with conventional biomarkers in cancer patients. Asian Pacific journal of cancer prevention : APJCP 13(5), 2399–2403 (2012). https://doi.org/10.7314/apjcp.2012.13.5.2399

    Article  PubMed  Google Scholar 

  90. Duffy, M.J.: Serum tumor markers in breast cancer: are they of clinical value? Clin. Chem. 52(3), 345–351 (2006). https://doi.org/10.1373/clinchem.2005.059832

    Article  CAS  PubMed  Google Scholar 

  91. Goonewardene, T.I., Hall, M.R., Rustin, G.J.: Management of asymptomatic patients on follow-up for ovarian cancer with rising CA-125 concentrations. Lancet Oncol. 8(9), 813–821 (2007). https://doi.org/10.1016/s1470-2045(07)70273-5

    Article  PubMed  Google Scholar 

  92. Breborowicz, J., Mackiewicz, A., Breborowicz, D.: Microheterogeneity of alpha-fetoprotein in patient serum as demonstrated by lectin affino-electrophoresis. Scand. J. Immunol. 14(1), 15–20 (1981). https://doi.org/10.1111/j.1365-3083.1981.tb00179.x

    Article  CAS  PubMed  Google Scholar 

  93. Nakagawa, T., Uozumi, N., Nakano, M., Mizuno-Horikawa, Y., Okuyama, N., Taguchi, T., Gu, J., Kondo, A., Taniguchi, N., Miyoshi, E.: Fucosylation of N-glycans regulates the secretion of hepatic glycoproteins into bile ducts. J. Biol. Chem. 281(40), 29797–29806 (2006). https://doi.org/10.1074/jbc.M605697200

    Article  CAS  PubMed  Google Scholar 

  94. Nakagawa, T., Moriwaki, K., Terao, N., Nakagawa, T., Miyamoto, Y., Kamada, Y., Miyoshi, E.: Analysis of polarized secretion of fucosylated alpha-fetoprotein in HepG2 cells. J. Proteome Res. 11(5), 2798–2806 (2012). https://doi.org/10.1021/pr201154k

    Article  CAS  PubMed  Google Scholar 

  95. Li, D., Mallory, T., Satomura, S.: AFP-L3: a new generation of tumor marker for hepatocellular carcinoma. Clin. Chim. Acta 313(1–2), 15–19 (2001). https://doi.org/10.1016/s0009-8981(01)00644-1

    Article  CAS  PubMed  Google Scholar 

  96. Miyoshi, E., Moriwaki, K., Terao, N., Tan, C.C., Terao, M., Nakagawa, T., Matsumoto, H., Shinzaki, S., Kamada, Y.: Fucosylation is a promising target for cancer diagnosis and therapy. Biomolecules 2(1), 34–45 (2012). https://doi.org/10.3390/biom2010034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Wong, R.J., Ahmed, A., Gish, R.G.: Elevated alpha-fetoprotein: differential diagnosis - hepatocellular carcinoma and other disorders. Clin. Liver Dis. 19(2), 309–323 (2015). https://doi.org/10.1016/j.cld.2015.01.005

    Article  PubMed  Google Scholar 

  98. Shiraki, K., Takase, K., Tameda, Y., Hamada, M., Kosaka, Y., Nakano, T.: A clinical study of lectin-reactive alpha-fetoprotein as an early indicator of hepatocellular carcinoma in the follow-up of cirrhotic patients. Hepatology (Baltimore, Md.) 22(3), 802–807 (1995).

  99. Siegel, R.L., Miller, K.D., Fuchs, H.E., Jemal, A.: Cancer Statistics, 2021. CA Cancer J. Clin. 71(1), 7–33 (2021). https://doi.org/10.3322/caac.21654

    Article  PubMed  Google Scholar 

  100. Stephan, C., Ralla, B., Jung, K.: Prostate-specific antigen and other serum and urine markers in prostate cancer. Biochim. Biophys. Acta 1846(1), 99–112 (2014). https://doi.org/10.1016/j.bbcan.2014.04.001

    Article  CAS  PubMed  Google Scholar 

  101. Wallner, L.P., Jacobsen, S.J.: Prostate-specific antigen and prostate cancer mortality: a systematic review. Am. J. Prev. Med. 45(3), 318–326 (2013). https://doi.org/10.1016/j.amepre.2013.04.015

    Article  PubMed  Google Scholar 

  102. Schröder, F.H., Hugosson, J., Roobol, M.J., Tammela, T.L.J., Zappa, M., Nelen, V., Kwiatkowski, M., Lujan, M., Määttänen, L., Lilja, H., Denis, L.J., Recker, F., Paez, A., Bangma, C.H., Carlsson, S., Puliti, D., Villers, A., Rebillard, X., Hakama, M., Stenman, U.-H., Kujala, P., Taari, K., Aus, G., Huber, A., van der Kwast, T.H., van Schaik, R.H.N., de Koning, H.J., Moss, S.M., Auvinen, A.: Screening and prostate cancer mortality: results of the European Randomised Study of Screening for Prostate Cancer (ERSPC) at 13 years of follow-up. The Lancet 384(9959), 2027–2035 (2014). https://doi.org/10.1016/s0140-6736(14)60525-0

    Article  Google Scholar 

  103. Harvey, P., Basuita, A., Endersby, D., Curtis, B., Iacovidou, A., Walker, M.: A systematic review of the diagnostic accuracy of prostate specific antigen. BMC Urol 9, 14 (2009). https://doi.org/10.1186/1471-2490-9-14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Catalona, W.J., Partin, A.W., Slawin, K.M., Brawer, M.K., Flanigan, R.C., Patel, A., Richie, J.P., deKernion, J.B., Walsh, P.C., Scardino, P.T., Lange, P.H., Subong, E.N., Parson, R.E., Gasior, G.H., Loveland, K.G., Southwick, P.C.: Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial. JAMA 279(19), 1542–1547 (1998)

    Article  CAS  Google Scholar 

  105. Mistry, K., Cable, G.: Meta-analysis of prostate-specific antigen and digital rectal examination as screening tests for prostate carcinoma. J. Am. Board Fam. Pract. 16(2), 95–101 (2003). https://doi.org/10.3122/jabfm.16.2.95

    Article  PubMed  Google Scholar 

  106. Carter, H.B., Albertsen, P.C., Barry, M.J., Etzioni, R., Freedland, S.J., Greene, K.L., Holmberg, L., Kantoff, P., Konety, B.R., Murad, M.H., Penson, D.F., Zietman, A.L.: Early detection of prostate cancer: AUA Guideline. J. Urol. 190(2), 419–426 (2013). https://doi.org/10.1016/j.juro.2013.04.119

    Article  PubMed  PubMed Central  Google Scholar 

  107. Loeb, S., Sanda, M.G., Broyles, D.L., Shin, S.S., Bangma, C.H., Wei, J.T., Partin, A.W., Klee, G.G., Slawin, K.M., Marks, L.S., van Schaik, R.H., Chan, D.W., Sokoll, L.J., Cruz, A.B., Mizrahi, I.A., Catalona, W.J.: The prostate health index selectively identifies clinically significant prostate cancer. J. Urol. 193(4), 1163–1169 (2015). https://doi.org/10.1016/j.juro.2014.10.121

    Article  PubMed  Google Scholar 

  108. Wang, W., Wang, M., Wang, L., Adams, T.S., Tian, Y., Xu, J.: Diagnostic ability of %p2PSA and prostate health index for aggressive prostate cancer: a meta-analysis. Sci. Rep. 4, 5012 (2014). https://doi.org/10.1038/srep05012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Wei, J.T., Feng, Z., Partin, A.W., Brown, E., Thompson, I., Sokoll, L., Chan, D.W., Lotan, Y., Kibel, A.S., Busby, J.E., Bidair, M., Lin, D.W., Taneja, S.S., Viterbo, R., Joon, A.Y., Dahlgren, J., Kagan, J., Srivastava, S., Sanda, M.G.: Can urinary PCA3 supplement PSA in the early detection of prostate cancer? J. Clin. Oncol. 32(36), 4066–4072 (2014). https://doi.org/10.1200/JCO.2013.52.8505

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Schmid, M., Hansen, J., Chun, F.K.: Urinary Prostate Cancer Antigen 3 as a Tumour Marker: Biochemical and Clinical Aspects. Adv. Exp. Med. Biol. 867, 277–289 (2015). https://doi.org/10.1007/978-94-017-7215-0_17

    Article  CAS  PubMed  Google Scholar 

  111. Vlaeminck-Guillem, V., Ruffion, A., Andre, J., Devonec, M., Paparel, P.: Urinary prostate cancer 3 test: toward the age of reason? Urology 75(2), 447–453 (2010). https://doi.org/10.1016/j.urology.2009.03.046

    Article  PubMed  Google Scholar 

  112. Duffy, M.J.: Biomarkers for prostate cancer: prostate-specific antigen and beyond. Clin. Chem. Lab. Med. (2019). https://doi.org/10.1515/cclm-2019-0693

    Article  Google Scholar 

  113. A. Rice, M., Stoyanova, T.: Biomarkers for Diagnosis and Prognosis of Prostate Cancer. (2019). https://doi.org/10.5772/intechopen.79726

  114. Gilgunn, S., Conroy, P.J., Saldova, R., Rudd, P.M., O’Kennedy, R.J.: Aberrant PSA glycosylation–a sweet predictor of prostate cancer. Nat. Rev. Urol. 10(2), 99–107 (2013). https://doi.org/10.1038/nrurol.2012.258

    Article  CAS  PubMed  Google Scholar 

  115. Scott, E., Munkley, J.: Glycans as Biomarkers in Prostate Cancer. Int. J. Mol. Sci. 20(6) (2019). https://doi.org/10.3390/ijms20061389

  116. Hatakeyama, S., Yoneyama, T., Tobisawa, Y., Ohyama, C.: Recent progress and perspectives on prostate cancer biomarkers. Int. J. Clin. Oncol 22(2), 214–221 (2017). https://doi.org/10.1007/s10147-016-1049-y

    Article  CAS  PubMed  Google Scholar 

  117. Vermassen, T., Speeckaert, M.M., Lumen, N., Rottey, S., Delanghe, J.R.: Glycosylation of prostate specific antigen and its potential diagnostic applications. Clin. Chim. Acta 413(19–20), 1500–1505 (2012). https://doi.org/10.1016/j.cca.2012.06.007

    Article  CAS  PubMed  Google Scholar 

  118. Li, Q.K., Chen, L., Ao, M.H., Chiu, J.H., Zhang, Z., Zhang, H., Chan, D.W.: Serum fucosylated prostate-specific antigen (PSA) improves the differentiation of aggressive from non-aggressive prostate cancers. Theranostics 5(3), 267–276 (2015). https://doi.org/10.7150/thno.10349

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Pihikova, D., Kasak, P., Kubanikova, P., Sokol, R., Tkac, J.: Aberrant sialylation of a prostate-specific antigen: Electrochemical label-free glycoprofiling in prostate cancer serum samples. Anal. Chim. Acta 934, 72–79 (2016). https://doi.org/10.1016/j.aca.2016.06.043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Ishikawa, T., Yoneyama, T., Tobisawa, Y., Hatakeyama, S., Kurosawa, T., Nakamura, K., Narita, S., Mitsuzuka, K., Duivenvoorden, W., Pinthus, J.H., Hashimoto, Y., Koie, T., Habuchi, T., Arai, Y., Ohyama, C.: An Automated Micro-Total Immunoassay System for Measuring Cancer-Associated alpha2,3-linked Sialyl N-Glycan-Carrying Prostate-Specific Antigen May Improve the Accuracy of Prostate Cancer Diagnosis. Int. J. Mol. Sci. 18(2) (2017). https://doi.org/10.3390/ijms18020470

  121. Hatano, K., Yoneyama, T., Hatakeyama, S., Tomiyama, E., Tsuchiya, M., Nishimoto, M., Yoshimura, K., Miyoshi, E., Uemura, H., Ohyama, C., Nonomura, N., Fujita, K.: Simultaneous analysis of serum alpha2,3-linked sialylation and core-type fucosylation of prostate-specific antigen for the detection of high-grade prostate cancer. Br. J. Cancer (2021). https://doi.org/10.1038/s41416-021-01637-x

    Article  PubMed  Google Scholar 

  122. Kaya, T., Kaneko, T., Kojima, S., Nakamura, Y., Ide, Y., Ishida, K., Suda, Y., Yamashita, K.: High-sensitivity immunoassay with surface plasmon field-enhanced fluorescence spectroscopy using a plastic sensor chip: application to quantitative analysis of total prostate-specific antigen and GalNAcbeta1-4GlcNAc-linked prostate-specific antigen for prostate cancer diagnosis. Anal. Chem. 87(3), 1797–1803 (2015). https://doi.org/10.1021/ac503735e

    Article  CAS  PubMed  Google Scholar 

  123. Yoneyama, T., Ohyama, C., Hatakeyama, S., Narita, S., Habuchi, T., Koie, T., Mori, K., Hidari, K.I., Yamaguchi, M., Suzuki, T., Tobisawa, Y.: Measurement of aberrant glycosylation of prostate specific antigen can improve specificity in early detection of prostate cancer. Biochem. Biophys. Res. Commun. 448(4), 390–396 (2014). https://doi.org/10.1016/j.bbrc.2014.04.107

    Article  CAS  PubMed  Google Scholar 

  124. Haga, Y., Uemura, M., Baba, S., Inamura, K., Takeuchi, K., Nonomura, N., Ueda, K.: Identification of Multisialylated LacdiNAc Structures as Highly Prostate Cancer Specific Glycan Signatures on PSA. Anal. Chem. 91(3), 2247–2254 (2019). https://doi.org/10.1021/acs.analchem.8b04829

    Article  CAS  PubMed  Google Scholar 

  125. Hirano, K., Matsuda, A., Shirai, T., Furukawa, K.: Expression of LacdiNAc groups on N-glycans among human tumors is complex. Biomed. Res. Int. 2014,(2014)

  126. Fukushima, K., Satoh, T., Baba, S., Yamashita, K.: alpha1,2-Fucosylated and beta-N-acetylgalactosaminylated prostate-specific antigen as an efficient marker of prostatic cancer. Glycobiology 20(4), 452–460 (2010). https://doi.org/10.1093/glycob/cwp197

    Article  CAS  PubMed  Google Scholar 

  127. Machado, E., Kandzia, S., Carilho, R., Altevogt, P., Conradt, H.S., Costa, J.: N-Glycosylation of total cellular glycoproteins from the human ovarian carcinoma SKOV3 cell line and of recombinantly expressed human erythropoietin. Glycobiology 21(3), 376–386 (2011). https://doi.org/10.1093/glycob/cwq170

    Article  CAS  PubMed  Google Scholar 

  128. Peracaula, R., Royle, L., Tabares, G., Mallorqui-Fernandez, G., Barrabes, S., Harvey, D.J., Dwek, R.A., Rudd, P.M., de Llorens, R.: Glycosylation of human pancreatic ribonuclease: differences between normal and tumor states. Glycobiology 13(4), 227–244 (2003). https://doi.org/10.1093/glycob/cwg019

    Article  CAS  PubMed  Google Scholar 

  129. Barrabés, S., Llop, E., Ferrer-Batallé, M., Ramírez, M., Aleixandre, R.N., Perry, A.S., de Llorens, R., Peracaula, R.: Analysis of urinary PSA glycosylation is not indicative of high-risk prostate cancer. Clin. Chim. Acta 470, 97–102 (2017). https://doi.org/10.1016/j.cca.2017.05.009

    Article  CAS  PubMed  Google Scholar 

  130. Jia, G., Dong, Z., Sun, C., Wen, F., Wang, H., Guo, H., Gao, X., Xu, C., Xu, C., Yang, C., Sun, Y.: Alterations in expressed prostate secretion-urine PSA N-glycosylation discriminate prostate cancer from benign prostate hyperplasia. Oncotarget 8(44), 76987–76999 (2017). https://doi.org/10.18632/oncotarget.20299

    Article  PubMed  PubMed Central  Google Scholar 

  131. Drake, R.R., Jones, E.E., Powers, T.W., Nyalwidhe, J.O.: Altered glycosylation in prostate cancer. Adv. Cancer Res. 126, 345–382 (2015). https://doi.org/10.1016/bs.acr.2014.12.001

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was partly supported by JSPS KAKENHI (Grant number JP19K06553 to Y.H. and Grant number JP26710007 to K.U.).

Author information

Authors and Affiliations

  1. Cancer Proteomics Group, Cancer Precision Medicine Center, Japanese Foundation for Cancer Research, Tokyo, 135-8550, Japan

    Yoshimi Haga & Koji Ueda

Authors
  1. Yoshimi Haga
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Koji Ueda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoshimi Haga.

Ethics declarations

Conflict of interests

K.U. serves as a consultant of LSI Medience Corporation. Y.H. has no conflict of interest.

Additional information

Publisher's Note

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

This article belongs to the Topical Collection: Tribute to Professor Sen-itiroh Hakomori

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Haga, Y., Ueda, K. Glycosylation in cancer: its application as a biomarker and recent advances of analytical techniques. Glycoconj J 39, 303–313 (2022). https://doi.org/10.1007/s10719-022-10043-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10719-022-10043-1

Keywords

Search

Navigation