Decoding the glycoproteome: a new frontier for biomarker discovery in cancer.

Biomarker Cancer Glycoproteomics Screening

Journal

Journal of hematology & oncology
ISSN: 1756-8722
Titre abrégé: J Hematol Oncol
Pays: England
ID NLM: 101468937

Informations de publication

Date de publication:
22 Mar 2024
Historique:
received: 02 12 2023
accepted: 04 03 2024
medline: 22 3 2024
pubmed: 22 3 2024
entrez: 22 3 2024
Statut: epublish

Résumé

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

Identifiants

pubmed: 38515194
doi: 10.1186/s13045-024-01532-x
pii: 10.1186/s13045-024-01532-x
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

12

Informations de copyright

© 2024. The Author(s).

Références

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49.
pubmed: 33538338 doi: 10.3322/caac.21660
Raufaste-Cazavieille V, Santiago R, Droit A. Multi-omics analysis: Paving the path toward achieving precision medicine in cancer treatment and immuno-oncology. Front Mol Biosci. 2022;9:962743.
pubmed: 36304921 pmcid: 9595279 doi: 10.3389/fmolb.2022.962743
Rifai N, Gillette MA, Carr SA. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nat Biotechnol. 2006;24:971–83.
pubmed: 16900146 doi: 10.1038/nbt1235
Hanash SM, Pitteri SJ, Faca VM. Mining the plasma proteome for cancer biomarkers. Nature. 2008;452:571–9.
pubmed: 18385731 doi: 10.1038/nature06916
Palmirotta R, Lovero D, Cafforio P, Felici C, Mannavola F, Pellè E, et al. Liquid biopsy of cancer: a multimodal diagnostic tool in clinical oncology. Ther Adv Med Oncol. 2018;10:1758835918794630.
pubmed: 30181785 pmcid: 6116068 doi: 10.1177/1758835918794630
Alix-Panabières C, Pantel K. Liquid biopsy: from discovery to clinical application. Cancer Discov. 2021;11:858–73.
pubmed: 33811121 doi: 10.1158/2159-8290.CD-20-1311
Ignatiadis M, Sledge GW, Jeffrey SS. Liquid biopsy enters the clinic - implementation issues and future challenges. Nat Rev Clin Oncol. 2021;18:297–312.
pubmed: 33473219 doi: 10.1038/s41571-020-00457-x
Ding Z, Wang N, Ji N, Chen Z-S. Proteomics technologies for cancer liquid biopsies. Mol Cancer. 2022;21:53.
pubmed: 35168611 pmcid: 8845389 doi: 10.1186/s12943-022-01526-8
Cohen JD, Li L, Wang Y, Thoburn C, Afsari B, Danilova L, et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science. 2018;359:926–30.
pubmed: 29348365 pmcid: 6080308 doi: 10.1126/science.aar3247
Ohtsubo K, Marth JD. Glycosylation in cellular mechanisms of health and disease. Cell. 2006;126:855–67.
pubmed: 16959566 doi: 10.1016/j.cell.2006.08.019
Schjoldager KT, Narimatsu Y, Joshi HJ, Clausen H. Global view of human protein glycosylation pathways and functions. Nat Rev Mol Cell Biol. 2020;21:729–49.
pubmed: 33087899 doi: 10.1038/s41580-020-00294-x
Fuster MM, Esko JD. The sweet and sour of cancer: glycans as novel therapeutic targets. Nat Rev Cancer. 2005;5:526–42.
pubmed: 16069816 doi: 10.1038/nrc1649
Pinho SS, Reis CA. Glycosylation in cancer: mechanisms and clinical implications. Nat Rev Cancer. 2015;15:540–55.
pubmed: 26289314 doi: 10.1038/nrc3982
Carvalho S, Catarino TA, Dias AM, Kato M, Almeida A, Hessling B, et al. Preventing E-cadherin aberrant N-glycosylation at Asn-554 improves its critical function in gastric cancer. Oncogene. 2016;35:1619–31.
pubmed: 26189796 doi: 10.1038/onc.2015.225
Taniguchi N, Kizuka Y. Glycans and Cancer. 2015. p. 11–51.
Rodrigues JG, Balmaña M, Macedo JA, Poças J, Fernandes Â, de-Freitas-Junior JCM, et al. Glycosylation in cancer: selected roles in tumour progression, immune modulation and metastasis. Cell Immunol. 2018;333:46–57.
pubmed: 29576316 doi: 10.1016/j.cellimm.2018.03.007
Ignatiadis M, Lee M, Jeffrey SS. Circulating tumor cells and circulating tumor DNA: challenges and opportunities on the path to clinical utility. Clin Cancer Res. 2015;21:4786–800.
pubmed: 26527805 doi: 10.1158/1078-0432.CCR-14-1190
Dang DK, Park BH. Circulating tumor DNA: current challenges for clinical utility. J Clin Invest. 2022;132:1–10.
doi: 10.1172/JCI154941
Alix-Panabières C, Pantel K. Challenges in circulating tumour cell research. Nat Rev Cancer. 2014;14:623–31.
pubmed: 25154812 doi: 10.1038/nrc3820
Dai J, Su Y, Zhong S, Cong L, Liu B, Yang J, et al. Exosomes: key players in cancer and potential therapeutic strategy. Signal Transduct Target Ther. 2020;5:145.
pubmed: 32759948 pmcid: 7406508 doi: 10.1038/s41392-020-00261-0
Merker JD, Oxnard GR, Compton C, Diehn M, Hurley P, Lazar AJ, et al. Circulating tumor DNA analysis in patients with cancer: American Society of Clinical Oncology and College of American Pathologists joint review. J Clin Oncol. 2018;36:1631–41.
pubmed: 29504847 doi: 10.1200/JCO.2017.76.8671
Cree IA, Deans Z, Ligtenberg MJL, Normanno N, Edsjö A, Rouleau E, et al. Guidance for laboratories performing molecular pathology for cancer patients. J Clin Pathol. 2014;67:923–31.
pubmed: 25012948 doi: 10.1136/jclinpath-2014-202404
Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, et al. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer. 2017;17:223–38.
pubmed: 28233803 doi: 10.1038/nrc.2017.7
Zhou J, Kulasinghe A, Bogseth A, O’Byrne K, Punyadeera C, Papautsky I. Isolation of circulating tumor cells in non-small-cell-lung-cancer patients using a multi-flow microfluidic channel. Microsyst Nanoeng. 2019;5:8.
pubmed: 31057935 pmcid: 6387977 doi: 10.1038/s41378-019-0045-6
Deng Z, Wu S, Wang Y, Shi D. Circulating tumor cell isolation for cancer diagnosis and prognosis. EBioMedicine. 2022;83:104237.
pubmed: 36041264 pmcid: 9440384 doi: 10.1016/j.ebiom.2022.104237
Sarioglu AF, Aceto N, Kojic N, Donaldson MC, Zeinali M, Hamza B, et al. A microfluidic device for label-free, physical capture of circulating tumor cell clusters. Nat Methods. 2015;12:685–91.
pubmed: 25984697 pmcid: 4490017 doi: 10.1038/nmeth.3404
Bronkhorst AJ, Ungerer V, Holdenrieder S. Early detection of cancer using circulating tumor DNA: biological, physiological and analytical considerations. Crit Rev Clin Lab Sci. 2019;57:253–69.
pubmed: 31865831 doi: 10.1080/10408363.2019.1700902
Ramazi S, Zahiri J. Posttranslational modifications in proteins: resources, tools and prediction methods. Database. 2021;2021:baab012.
pubmed: 33826699 pmcid: 8040245 doi: 10.1093/database/baab012
Silva MLS. Capitalizing glycomic changes for improved biomarker-based cancer diagnostics. Explor Target Antitumor Ther. 2023;4:366–95.
pubmed: 37455827 pmcid: 10344901 doi: 10.37349/etat.2023.00140
Walsh G. Post-translational modifications of protein biopharmaceuticals. Drug Discov Today. 2010;15:773–80.
pubmed: 20599624 doi: 10.1016/j.drudis.2010.06.009
Drake PM, Cho W, Li B, Prakobphol A, Johansen E, Anderson NL, et al. Sweetening the pot: adding glycosylation to the biomarker discovery equation. Clin Chem. 2010;56:223–36.
pubmed: 19959616 doi: 10.1373/clinchem.2009.136333
Trbojević-Akmačić I, Lageveen-Kammeijer GSM, Heijs B, Petrović T, Deriš H, Wuhrer M, et al. High-throughput glycomic methods. Chem Rev. 2022;122:15865–913.
pubmed: 35797639 pmcid: 9614987 doi: 10.1021/acs.chemrev.1c01031
Schwarz F, Aebi M. Mechanisms and principles of N-linked protein glycosylation. Curr Opin Struct Biol. 2011;21:576–82.
pubmed: 21978957 doi: 10.1016/j.sbi.2011.08.005
Schiel JE. Glycoprotein analysis using mass spectrometry: unraveling the layers of complexity. Anal Bioanal Chem. 2012;404:1141–9.
pubmed: 22733248 doi: 10.1007/s00216-012-6185-2
Ruhaak LR, Xu G, Li Q, Goonatilleke E, Lebrilla CB. Mass spectrometry approaches to glycomic and glycoproteomic analyses. Chem Rev. 2018;118:7886–930.
pubmed: 29553244 pmcid: 7757723 doi: 10.1021/acs.chemrev.7b00732
Levery SB, Steentoft C, Halim A, Narimatsu Y, Clausen H, Vakhrushev SY. Advances in mass spectrometry driven O-glycoproteomics. Biochim Biophys Acta. 2015;1850:33–42.
pubmed: 25284204 doi: 10.1016/j.bbagen.2014.09.026
Banazadeh A, Veillon L, Wooding KM, Zabet-Moghaddam M, Mechref Y. Recent advances in mass spectrometric analysis of glycoproteins. Electrophoresis. 2017;38:162–89.
pubmed: 27757981 doi: 10.1002/elps.201600357
Tamara S, Franc V, Heck AJR. A wealth of genotype-specific proteoforms fine-tunes hemoglobin scavenging by haptoglobin. Proc Natl Acad Sci U S A. 2020;117:15554–64.
pubmed: 32561649 pmcid: 7355005 doi: 10.1073/pnas.2002483117
Oh MJ, Lee SH, Kim U, An HJ. In-depth investigation of altered glycosylation in human haptoglobin associated cancer by mass spectrometry. Mass Spectrom Rev. 2023;42:496–518.
pubmed: 34037272 doi: 10.1002/mas.21707
Fujimura T, Shinohara Y, Tissot B, Pang P-C, Kurogochi M, Saito S, et al. Glycosylation status of haptoglobin in sera of patients with prostate cancer vs. benign prostate disease or normal subjects. Int J Cancer. 2008;122:39–49.
pubmed: 17803183 doi: 10.1002/ijc.22958
Turner GA. Haptoglobin: a potential reporter molecule for glycosylation changes in disease. Adv Exp Med Biol. 1995;1995(376):231–8.
doi: 10.1007/978-1-4615-1885-3_25
Dall’Olio F, Chiricolo M,. Sialyltransferases in cancer. Glycoconj J. 2001;18:841–50.
pubmed: 12820717 doi: 10.1023/A:1022288022969
Noda K, Miyoshi E, Uozumi N, Yanagidani S, Ikeda Y, Gao C, et al. Gene expression of alpha1-6 fucosyltransferase in human hepatoma tissues: a possible implication for increased fucosylation of alpha-fetoprotein. Hepatology. 1998;28:944–52.
pubmed: 9755230 doi: 10.1002/hep.510280408
Liu Y-C, Yen H-Y, Chen C-Y, Chen C-H, Cheng P-F, Juan Y-H, et al. Sialylation and fucosylation of epidermal growth factor receptor suppress its dimerization and activation in lung cancer cells. Proc Natl Acad Sci U S A. 2011;108:11332–7.
pubmed: 21709263 pmcid: 3136320 doi: 10.1073/pnas.1107385108
Potapenko IO, Haakensen VD, Lüders T, Helland A, Bukholm I, Sørlie T, et al. Glycan gene expression signatures in normal and malignant breast tissue; possible role in diagnosis and progression. Mol Oncol. 2010;4:98–118.
pubmed: 20060370 doi: 10.1016/j.molonc.2009.12.001
Hiraiwa N, Yabuta T, Yoritomi K, Hiraiwa M, Tanaka Y, Suzuki T, et al. Transactivation of the fucosyltransferase VII gene by human T-cell leukemia virus type 1 Tax through a variant cAMP-responsive element. Blood. 2003;101:3615–21.
pubmed: 12506041 doi: 10.1182/blood-2002-07-2301
Matsuura N, Narita T, Hiraiwa N, Hiraiwa M, Murai H, Iwase T, et al. Gene expression of fucosyl- and sialyl-transferases which synthesize sialyl Lewisx, the carbohydrate ligands for E-selectin, in human breast cancer. Int J Oncol. 1998;12:1157–64.
pubmed: 9538143
Holmes EH, Hakomori S, Ostrander GK. Synthesis of type 1 and 2 lacto series glycolipid antigens in human colonic adenocarcinoma and derived cell lines is due to activation of a normally unexpressed beta 1–3N-acetylglucosaminyltransferase. J Biol Chem. 1987;262:15649–58.
pubmed: 2960671 doi: 10.1016/S0021-9258(18)47776-9
Guo H, Nagy T, Pierce M. Post-translational glycoprotein modifications regulate colon cancer stem cells and colon adenoma progression in Apc(min/+) mice through altered Wnt receptor signaling. J Biol Chem. 2014;289:31534–49.
pubmed: 25274627 pmcid: 4223351 doi: 10.1074/jbc.M114.602680
Yoshimura M, Nishikawa A, Ihara Y, Taniguchi S, Taniguchi N. Suppression of lung metastasis of B16 mouse melanoma by N-acetylglucosaminyltransferase III gene transfection. Proc Natl Acad Sci U S A. 1995;92:8754–8.
pubmed: 7568011 pmcid: 41045 doi: 10.1073/pnas.92.19.8754
Niu L, Geyer PE, Wewer Albrechtsen NJ, Gluud LL, Santos A, Doll S, et al. Plasma proteome profiling discovers novel proteins associated with non-alcoholic fatty liver disease. Mol Syst Biol. 2019;15:e8793.
pubmed: 30824564 pmcid: 6396370 doi: 10.15252/msb.20188793
Wang G, Li J, Bojmar L, Chen H, Li Z, Tobias GC, et al. Tumour extracellular vesicles and particles induce liver metabolic dysfunction. Nature. 2023;618:374–82.
pubmed: 37225988 pmcid: 10330936 doi: 10.1038/s41586-023-06114-4
Jiao Y, Xu P, Shi H, Chen D, Shi H. Advances on liver cell-derived exosomes in liver diseases. J Cell Mol Med. 2021;25:15–26.
pubmed: 33247543 doi: 10.1111/jcmm.16123
Zhu J, Wu J, Yin H, Marrero J, Lubman DM. Mass spectrometric N-glycan analysis of haptoglobin from patient serum samples using a 96-well plate format. J Proteome Res. 2015;14:4932–9.
pubmed: 26448449 pmcid: 4636918 doi: 10.1021/acs.jproteome.5b00662
Mehta A, Herrera H, Block T. Glycosylation and liver cancer. Adv Cancer Res. 2015;126:257–79.
pubmed: 25727150 pmcid: 4634841 doi: 10.1016/bs.acr.2014.11.005
Zhu J, Warner E, Parikh ND, Lubman DM. Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches. Mass Spectrom Rev. 2019;38:265–90.
pubmed: 30472795 doi: 10.1002/mas.21583
Čaval T, Lin Y-H, Varkila M, Reiding KR, Bonten MJM, Cremer OL, et al. Glycoproteoform profiles of individual patients’ plasma alpha-1-antichymotrypsin are unique and extensively remodeled following a septic episode. Front Immunol. 2020;11:608466.
pubmed: 33519818 doi: 10.3389/fimmu.2020.608466
Keser T, Tijardović M, Gornik I, Lukić E, Lauc G, Gornik O, et al. High-throughput and site-specific N-glycosylation analysis of human alpha-1-acid glycoprotein offers a great potential for new biomarker discovery. Mol Cell Proteomics. 2021;20:100044.
pubmed: 33493676 pmcid: 7950198 doi: 10.1074/mcp.RA120.002433
Virág D, Kremmer T, Lőrincz K, Kiss N, Jobbágy A, Bozsányi S, et al. Altered glycosylation of human alpha-1-acid glycoprotein as a biomarker for malignant melanoma. Molecules. 2021;26:6003.
pubmed: 34641547 pmcid: 8513036 doi: 10.3390/molecules26196003
Yokobori T, Yazawa S, Asao T, Nakazawa N, Mogi A, Sano R, et al. Fucosylated α1-acid glycoprotein as a biomarker to predict prognosis following tumor immunotherapy of patients with lung cancer. Sci Rep. 2019;9:14503.
pubmed: 31601857 pmcid: 6787216 doi: 10.1038/s41598-019-51021-2
Yazawa S, Takahashi R, Yokobori T, Sano R, Mogi A, Saniabadi AR, et al. Fucosylated glycans in α1-acid glycoprotein for monitoring treatment outcomes and prognosis of cancer patients. PLoS ONE. 2016;11:e0156277.
pubmed: 27295180 pmcid: 4905682 doi: 10.1371/journal.pone.0156277
Doherty M, Theodoratou E, Walsh I, Adamczyk B, Stöckmann H, Agakov F, et al. Plasma N-glycans in colorectal cancer risk. Sci Rep. 2018;8:8655.
pubmed: 29872119 pmcid: 5988698 doi: 10.1038/s41598-018-26805-7
de Vroome SW, Holst S, Girondo MR, van der Burgt YEM, Mesker WE, Tollenaar RAEM, et al. Serum N-glycome alterations in colorectal cancer associate with survival. Oncotarget. 2018;9:30610–23.
pubmed: 30093973 pmcid: 6078140 doi: 10.18632/oncotarget.25753
Dotz V, Wuhrer M. N-glycome signatures in human plasma: associations with physiology and major diseases. FEBS Lett. 2019;593:2966–76.
pubmed: 31509238 doi: 10.1002/1873-3468.13598
Pickering C, Aiyetan P, Xu G, Mitchell A, Rice R, Najjar YG, et al. Plasma glycoproteomic biomarkers identify metastatic melanoma patients with reduced clinical benefit from immune checkpoint inhibitor therapy. Front Immunol. 2023;14:1187332.
pubmed: 37388743 pmcid: 10302726 doi: 10.3389/fimmu.2023.1187332
Desai K, Gupta S, May FP, Xu G, Shaukat A, Hommes DW, et al. Early detection of advanced adenomas and colorectal carcinoma by serum glycoproteome profiling. Gastroenterology. 2024;166:194-197.e2.
pubmed: 37769953 doi: 10.1053/j.gastro.2023.09.034
Chen M, Ren AH, Prassas I, Soosaipillai A, Lim B, Fraser DD, et al. Plasma protein profiling by proximity extension assay technology reveals novel biomarkers of traumatic brain injury—a pilot study. J Appl Lab Med. 2021;6:1165–78.
pubmed: 33778875 doi: 10.1093/jalm/jfab004
Wik L, Nordberg N, Broberg J, Björkesten J, Assarsson E, Henriksson S, et al. Proximity extension assay in combination with next-generation sequencing for high-throughput proteome-wide analysis. Mol Cell Proteomics. 2021;20:100168.
pubmed: 34715355 pmcid: 8633680 doi: 10.1016/j.mcpro.2021.100168
Pietzner M, Wheeler E, Carrasco-Zanini J, Kerrison ND, Oerton E, Koprulu M, et al. Synergistic insights into human health from aptamer- and antibody-based proteomic profiling. Nat Commun. 2021;12:6822.
pubmed: 34819519 pmcid: 8613205 doi: 10.1038/s41467-021-27164-0
Dwek MV, Jenks A, Leathem AJC. A sensitive assay to measure biomarker glycosylation demonstrates increased fucosylation of prostate specific antigen (PSA) in patients with prostate cancer compared with benign prostatic hyperplasia. Clin Chim Acta. 2010;411:1935–9.
pubmed: 20708609 doi: 10.1016/j.cca.2010.08.009
Bojar D, Meche L, Meng G, Eng W, Smith DF, Cummings RD, et al. A useful guide to lectin binding: machine-learning directed annotation of 57 unique lectin specificities. ACS Chem Biol. 2022;17:2993–3012.
pubmed: 35084820 pmcid: 9679999 doi: 10.1021/acschembio.1c00689
De Leoz MLA, Duewer DL, Fung A, Liu L, Yau HK, Potter O, et al. NIST interlaboratory study on glycosylation analysis of monoclonal antibodies: comparison of results from diverse analytical methods. Mol Cell Proteomics. 2020;19:11–30.
pubmed: 31591262 doi: 10.1074/mcp.RA119.001677
Shajahan A, Heiss C, Ishihara M, Azadi P. Glycomic and glycoproteomic analysis of glycoproteins-a tutorial. Anal Bioanal Chem. 2017;409:4483–505.
pubmed: 28585084 pmcid: 5498624 doi: 10.1007/s00216-017-0406-7
Kailemia MJ, Park D, Lebrilla CB. Glycans and glycoproteins as specific biomarkers for cancer. Anal Bioanal Chem. 2017;409:395–410.
pubmed: 27590322 doi: 10.1007/s00216-016-9880-6
Melmer M, Stangler T, Premstaller A, Lindner W. Comparison of hydrophilic-interaction, reversed-phase and porous graphitic carbon chromatography for glycan analysis. J Chromatogr A. 2011;1218:118–23.
pubmed: 21122866 doi: 10.1016/j.chroma.2010.10.122
Ruhaak LR, Deelder AM, Wuhrer M. Oligosaccharide analysis by graphitized carbon liquid chromatography-mass spectrometry. Anal Bioanal Chem. 2009;394:163–74.
pubmed: 19247642 doi: 10.1007/s00216-009-2664-5
Zhang C, Ye Z, Xue P, Shu Q, Zhou Y, Ji Y, et al. Evaluation of different N-glycopeptide enrichment methods for N-glycosylation sites mapping in mouse brain. J Proteome Res. 2016;15:2960–8.
pubmed: 27480293 doi: 10.1021/acs.jproteome.6b00098
Liu Z, Xu M, Zhang W, Miao X, Wang PG, Li S, et al. Recent development in hydrophilic interaction liquid chromatography stationary materials for glycopeptide analysis. Anal Methods. 2022;14:4437–48.
pubmed: 36300821 doi: 10.1039/D2AY01369J
Balaguer E, Neusüss C. Glycoprotein characterization combining intact protein and glycan analysis by capillary electrophoresis-electrospray ionization-mass spectrometry. Anal Chem. 2006;78:5384–93.
pubmed: 16878873 doi: 10.1021/ac060376g
Lingg N, Zhang P, Song Z, Bardor M. The sweet tooth of biopharmaceuticals: importance of recombinant protein glycosylation analysis. Biotechnol J. 2012;7:1462–72.
pubmed: 22829536 doi: 10.1002/biot.201200078
Han L, Costello CE. Mass spectrometry of glycans. Biochemistry (Mosc). 2013;78:710–20.
pubmed: 24010834 doi: 10.1134/S0006297913070031
Song E, Pyreddy S, Mechref Y. Quantification of glycopeptides by multiple reaction monitoring liquid chromatography/tandem mass spectrometry. Rapid Commun Mass Spectrom. 2012;26:1941–54.
pubmed: 22847692 pmcid: 3673029 doi: 10.1002/rcm.6290
van der Burgt Y, Wuhrer M. The role of clinical glyco(proteo)mics in precision medicine. Mol Cell Proteomics. 2023;22:100565.
pubmed: 37169080 pmcid: 10326703 doi: 10.1016/j.mcpro.2023.100565
Varki A, Cummings R, Esko JD. Essentials of Glycobiology. 2022.
Wohlgemuth J, Karas M, Eichhorn T, Hendriks R, Andrecht S. Quantitative site-specific analysis of protein glycosylation by LC-MS using different glycopeptide-enrichment strategies. Anal Biochem. 2009;395:178–88.
pubmed: 19699707 doi: 10.1016/j.ab.2009.08.023
Goumenou A, Delaunay N, Pichon V. Recent advances in lectin-based affinity sorbents for protein glycosylation studies. Front Mol Biosci. 2021;8:746822.
pubmed: 34778373 pmcid: 8585745 doi: 10.3389/fmolb.2021.746822
Hong Q, Ruhaak LR, Stroble C, Parker E, Huang J, Maverakis E, et al. A method for comprehensive glycosite-mapping and direct quantitation of serum glycoproteins. J Proteome Res. 2015;14:5179–92.
pubmed: 26510530 pmcid: 4670571 doi: 10.1021/acs.jproteome.5b00756
Ongay S, Boichenko A, Govorukhina N, Bischoff R. Glycopeptide enrichment and separation for protein glycosylation analysis. J Sep Sci. 2012;35:2341–72.
pubmed: 22997027 doi: 10.1002/jssc.201200434
Xue Y, Xie J, Fang P, Yao J, Yan G, Shen H, et al. Study on behaviors and performances of universal N-glycopeptide enrichment methods. Analyst. 2018;143:1870–80.
pubmed: 29557479 doi: 10.1039/C7AN02062G
Huang Y, Nie Y, Boyes B, Orlando R. Resolving isomeric glycopeptide glycoforms with hydrophilic interaction chromatography (HILIC). J Biomol Tech. 2016;27:98–104.
pubmed: 27582638 pmcid: 4972402 doi: 10.7171/jbt.16-2703-003
Mookherjee A, Guttman M. Bridging the structural gap of glycoproteomics with ion mobility spectrometry. Curr Opin Chem Biol. 2018;42:86–92.
pubmed: 29202341 doi: 10.1016/j.cbpa.2017.11.012
Makrydaki E, Kotidis P, Polizzi KM, Kontoravdi C. Hitting the sweet spot with capillary electrophoresis: advances in N-glycomics and glycoproteomics. Curr Opin Biotechnol. 2021;71:182–90.
pubmed: 34438131 doi: 10.1016/j.copbio.2021.07.013
Macklin A, Khan S, Kislinger T. Recent advances in mass spectrometry based clinical proteomics: applications to cancer research. Clin Proteomics. 2020;17:17.
pubmed: 32489335 pmcid: 7247207 doi: 10.1186/s12014-020-09283-w
Ye Z, Vakhrushev SY. The role of data-independent acquisition for glycoproteomics. Mol Cell Proteomics. 2021;20:100042.
pubmed: 33372048 pmcid: 8724878 doi: 10.1074/mcp.R120.002204
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.
pubmed: 29207246 doi: 10.1021/acs.jproteome.7b00541
Goossens N, Nakagawa S, Sun X, Hoshida Y. Cancer biomarker discovery and validation. Transl Cancer Res. 2015;4:256–69.
pubmed: 26213686
Kirwan A, Utratna M, O’Dwyer ME, Joshi L, Kilcoyne M. Glycosylation-based serum biomarkers for cancer diagnostics and prognostics. Biomed Res Int. 2015;2015:1–16.
doi: 10.1155/2015/490531
Li F, Li C, Wang M, Webb GI, Zhang Y, Whisstock JC, et al. GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome. Bioinformatics. 2015;31:1411–9.
pubmed: 25568279 doi: 10.1093/bioinformatics/btu852
Sato T, Furukawa K, Greenwalt DE, Kobata A. Most bovine milk fat globule membrane glycoproteins contain asparagine-linked sugar chains with GalNAc beta 1–>4GlcNAc groups. J Biochem. 1993;114:890–900.
pubmed: 8138548 doi: 10.1093/oxfordjournals.jbchem.a124273
FDA Center for Devices and Radiological Health. AFP-L3% Immunological Test Systems - Class II Special Controls Guidance Document for Industry and FDA Staff. 2005 Oct.
Kim H, Kim K, Jin J, Park J, Yu SJ, Yoon J-H, et al. Measurement of glycosylated alpha-fetoprotein improves diagnostic power over the native form in hepatocellular carcinoma. PLoS ONE. 2014;9:e110366.
pubmed: 25310463 pmcid: 4195728 doi: 10.1371/journal.pone.0110366
Li D, Mallory T, Satomura S. AFP-L3: a new generation of tumor marker for hepatocellular carcinoma. Clin Chim Acta. 2001;313:15–9.
pubmed: 11694234 doi: 10.1016/S0009-8981(01)00644-1
Choi J, Kim G, Han S, Lee W, Chun S, Lim Y. Longitudinal assessment of three serum biomarkers to detect very early-stage hepatocellular carcinoma. Hepatology. 2019;69:1983–94.
pubmed: 30153338 doi: 10.1002/hep.30233
Dunbar C, Kushnir MM, Yang YK. Glycosylation profiling of the neoplastic biomarker alpha fetoprotein through intact mass protein analysis. J Proteome Res. 2023;22:226–34.
pubmed: 36541409 doi: 10.1021/acs.jproteome.2c00656
Zhou J-M, Wang T, Zhang K-H. AFP-L3 for the diagnosis of early hepatocellular carcinoma: a meta-analysis. Medicine. 2021;100:e27673.
pubmed: 34713864 pmcid: 8556013 doi: 10.1097/MD.0000000000027673
Valmu L, Alfthan H, Hotakainen K, Birken S, Stenman U-H. Site-specific glycan analysis of human chorionic gonadotropin beta-subunit from malignancies and pregnancy by liquid chromatography–electrospray mass spectrometry. Glycobiology. 2006;16:1207–18.
pubmed: 16880503 doi: 10.1093/glycob/cwl034
Elliott MM, Kardana A, Lustbader JW, Cole LA. Carbohydrate and peptide structure of the alpha- and beta-subunits of human chorionic gonadotropin from normal and aberrant pregnancy and choriocarcinoma. Endocrine. 1997;7:15–32.
pubmed: 9449027 doi: 10.1007/BF02778058
Terävä J, Tiainen L, Lamminmäki U, Kellokumpu-Lehtinen P-L, Pettersson K, Gidwani K. Lectin nanoparticle assays for detecting breast cancer-associated glycovariants of cancer antigen 15–3 (CA15-3) in human plasma. PLoS ONE. 2019;14:e0219480.
pubmed: 31344060 pmcid: 6658058 doi: 10.1371/journal.pone.0219480
Choi JW, Moon B-I, Lee JW, Kim HJ, Jin Y, Kim H-J. Use of CA15-3 for screening breast cancer: an antibody-lectin sandwich assay for detecting glycosylation of CA15-3 in sera. Oncol Rep. 2018;40:145–54.
pubmed: 29749490 pmcid: 6059737
Chen W, Zhang Z, Zhang S, Zhu P, Ko JK-S, Yung KK-L. MUC1: structure, function, and clinic application in epithelial cancers. Int J Mol Sci. 2021;22:6567.
pubmed: 34207342 pmcid: 8234110 doi: 10.3390/ijms22126567
Scarà S, Bottoni P, Scatena R. CA 19–9: biochemical and clinical aspects. Adv Exp Med Biol. 2015;867:247–60.
pubmed: 26530370 doi: 10.1007/978-94-017-7215-0_15
Canney PA, Wilkinson PM, James RD, Moore M. CA19-9 as a marker for ovarian cancer: alone and in comparison with CA125. Br J Cancer. 1985;52:131–3.
pubmed: 2410004 pmcid: 1977182 doi: 10.1038/bjc.1985.161
Duffy MJ. CA 19–9 as a marker for gastrointestinal cancers: a review. Ann Clin Biochem. 1998;35(Pt 3):364–70.
pubmed: 9635101 doi: 10.1177/000456329803500304
Bayoumy S, Hyytiä H, Leivo J, Talha SM, Huhtinen K, Poutanen M, et al. Glycovariant-based lateral flow immunoassay to detect ovarian cancer-associated serum CA125. Commun Biol. 2020;3:460.
pubmed: 32826955 pmcid: 7442799 doi: 10.1038/s42003-020-01191-x
Chen K, Gentry-Maharaj A, Burnell M, Steentoft C, Marcos-Silva L, Mandel U, et al. Microarray Glycoprofiling of CA125 improves differential diagnosis of ovarian cancer. J Proteome Res. 2013;12:1408–18.
pubmed: 23360124 doi: 10.1021/pr3010474
Akita K, Yoshida S, Ikehara Y, Shirakawa S, Toda M, Inoue M, et al. Different levels of sialyl-Tn antigen expressed on MUC16 in patients with endometriosis and ovarian cancer. Int J Gynecol Cancer. 2012;22:531–8.
pubmed: 22367369 doi: 10.1097/IGC.0b013e3182473292
Zhao Q, Zhan T, Deng Z, Li Q, Liu Y, Yang S, et al. Glycan analysis of colorectal cancer samples reveals stage-dependent changes in CEA glycosylation patterns. Clin Proteomics. 2018;15:9.
pubmed: 29507546 pmcid: 5834848 doi: 10.1186/s12014-018-9182-4
Pont L, Kuzyk V, Benavente F, Sanz-Nebot V, Mayboroda OA, Wuhrer M, et al. Site-specific N-linked glycosylation analysis of human carcinoembryonic antigen by sheathless capillary electrophoresis-tandem mass spectrometry. J Proteome Res. 2021;20:1666–75.
pubmed: 33560857 pmcid: 8023805 doi: 10.1021/acs.jproteome.0c00875
Gebauer F, Wicklein D, Horst J, Sundermann P, Maar H, Streichert T, et al. Carcinoembryonic antigen-related cell adhesion molecules (CEACAM) 1, 5 and 6 as biomarkers in pancreatic cancer. PLoS ONE. 2014;9:e113023.
pubmed: 25409014 pmcid: 4237406 doi: 10.1371/journal.pone.0113023
Zhang X, Han X, Zuo P, Zhang X, Xu H. CEACAM5 stimulates the progression of non-small-cell lung cancer by promoting cell proliferation and migration. J Int Med Res. 2020;48:300060520959478.
pubmed: 32993395
Beauchemin N, Arabzadeh A. Carcinoembryonic antigen-related cell adhesion molecules (CEACAMs) in cancer progression and metastasis. Cancer Metastasis Rev. 2013;32:643–71.
pubmed: 23903773 doi: 10.1007/s10555-013-9444-6
Hayes JH, Barry MJ. Screening for prostate cancer with the prostate-specific antigen test. JAMA. 2014;311:1143.
pubmed: 24643604 doi: 10.1001/jama.2014.2085
Thompson IM. Operating characteristics of prostate-specific antigen in men with an initial PSA level of 3.0 ng/mL or lower. JAMA. 2005;294:66.
pubmed: 15998892 doi: 10.1001/jama.294.1.66
Gilgunn S, Conroy PJ, Saldova R, Rudd PM, O’Kennedy RJ. Aberrant PSA glycosylation—a sweet predictor of prostate cancer. Nat Rev Urol. 2013;10:99–107.
pubmed: 23318363 doi: 10.1038/nrurol.2012.258
Meany DL, Zhang Z, Sokoll LJ, Zhang H, Chan DW. Glycoproteomics for prostate cancer detection: changes in serum PSA glycosylation patterns. J Proteome Res. 2009;8:613–9.
pubmed: 19035787 pmcid: 2997339 doi: 10.1021/pr8007539
Peracaula R. Altered glycosylation pattern allows the distinction between prostate-specific antigen (PSA) from normal and tumor origins. Glycobiology. 2003;13:457–70.
pubmed: 12626390 doi: 10.1093/glycob/cwg041
Prakash S, Robbins Ph. Glycotyping of prostate specific antigen. Glycobiology. 2000;10:173–6.
pubmed: 10642608 doi: 10.1093/glycob/10.2.173
Wang C, Höti N, Lih T-SM, Sokoll LJ, Zhang R, Zhang Z, et al. Development of a glycoproteomic strategy to detect more aggressive prostate cancer using lectin-immunoassays for serum fucosylated PSA. Clin Proteomics. 2019;16:1–18.
pubmed: 30622446 pmcid: 6317216 doi: 10.1186/s12014-019-9234-4
Ferrer-Batallé M, Llop E, Ramírez M, Aleixandre R, Saez M, Comet J, et al. Comparative study of blood-based biomarkers, α2,3-sialic acid PSA and PHI, for high-risk prostate cancer detection. Int J Mol Sci. 2017;18:845.
pubmed: 28420168 pmcid: 5412429 doi: 10.3390/ijms18040845
Ishikawa T, Yoneyama T, Tobisawa Y, Hatakeyama S, Kurosawa T, Nakamura K, et al. An automated micro-total immunoassay system for measuring cancer-associated α2,3-linked sialyl N-glycan-carrying prostate-specific antigen may improve the accuracy of prostate cancer diagnosis. Int J Mol Sci. 2017;18:470.
pubmed: 28241428 pmcid: 5344002 doi: 10.3390/ijms18020470
Yoneyama T, Ohyama C, Hatakeyama S, Narita S, Habuchi T, Koie T, et al. Measurement of aberrant glycosylation of prostate specific antigen can improve specificity in early detection of prostate cancer. Biochem Biophys Res Commun. 2014;448:390–6.
pubmed: 24814705 doi: 10.1016/j.bbrc.2014.04.107
Kaya T, Kaneko T, Kojima S, Nakamura Y, Ide Y, Ishida K, et al. 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 GalNAcβ1–4GlcNAc-linked prostate-specific antigen for prostate cancer diagnosis. Anal Chem. 2015;87:1797–803.
pubmed: 25546230 doi: 10.1021/ac503735e
Llop E, Ferrer-Batallé M, Barrabés S, Guerrero PE, Ramírez M, Saldova R, et al. Improvement of prostate cancer diagnosis by detecting PSA glycosylation-specific changes. Theranostics. 2016;6:1190–204.
pubmed: 27279911 pmcid: 4893645 doi: 10.7150/thno.15226
Fujita K, Hatano K, Tomiyama E, Hayashi Y, Matsushita M, Tsuchiya M, et al. Serum core-type fucosylated prostate-specific antigen index for the detection of high-risk prostate cancer. Int J Cancer. 2021;148:3111–8.
pubmed: 33594666 doi: 10.1002/ijc.33517
Yoneyama T, Tobisawa Y, Kaneko T, Kaya T, Hatakeyama S, Mori K, et al. Clinical significance of the Lacdi <scp>NA</scp> c-glycosylated prostate-specific antigen assay for prostate cancer detection. Cancer Sci. 2019;110:2573–89.
pubmed: 31145522 pmcid: 6676104 doi: 10.1111/cas.14082
Leymarie N, Griffin PJ, Jonscher K, Kolarich D, Orlando R, McComb M, et al. Interlaboratory study on differential analysis of protein glycosylation by mass spectrometry: the ABRF glycoprotein research multi-institutional study 2012. Mol Cell Proteomics. 2013;12:2935–51.
pubmed: 23764502 pmcid: 3790302 doi: 10.1074/mcp.M113.030643
Saeland E, Belo AI, Mongera S, van Die I, Meijer GA, van Kooyk Y. Differential glycosylation of MUC1 and CEACAM5 between normal mucosa and tumour tissue of colon cancer patients. Int J Cancer. 2012;131:117–28.
pubmed: 21823122 doi: 10.1002/ijc.26354
van Gisbergen KPJM, Aarnoudse CA, Meijer GA, Geijtenbeek TBH, van Kooyk Y. Dendritic cells recognize tumor-specific glycosylation of carcinoembryonic antigen on colorectal cancer cells through dendritic cell-specific intercellular adhesion molecule-3–grabbing nonintegrin. Cancer Res. 2005;65:5935–44.
pubmed: 15994972 doi: 10.1158/0008-5472.CAN-04-4140
Kufe DW. Mucins in cancer: function, prognosis and therapy. Nat Rev Cancer. 2009;9:874–85.
pubmed: 19935676 pmcid: 2951677 doi: 10.1038/nrc2761
Rangel-Angarita V, Malaker SA. Mucinomics as the Next Frontier of Mass Spectrometry. ACS Chem Biol. 2021;16:1866–83.
pubmed: 34319686 doi: 10.1021/acschembio.1c00384
Malaker SA, Riley NM, Shon DJ, Pedram K, Krishnan V, Dorigo O, et al. Revealing the human mucinome. Nat Commun. 2022;13:3542.
pubmed: 35725833 pmcid: 9209528 doi: 10.1038/s41467-022-31062-4
Malaker SA, Pedram K, Ferracane MJ, Bensing BA, Krishnan V, Pett C, et al. The mucin-selective protease StcE enables molecular and functional analysis of human cancer-associated mucins. Proc Natl Acad Sci. 2019;116:7278–87.
pubmed: 30910957 pmcid: 6462054 doi: 10.1073/pnas.1813020116
Kletter D, Cao Z, Bern M, Haab B. Determining lectin specificity from glycan array data using motif segregation and glycosearch software. Curr Protoc Chem Biol. 2013;5:157–69.
pubmed: 23839995 pmcid: 4041489 doi: 10.1002/9780470559277.ch130028
Kim H, Park S, Jeong IG, Song SH, Jeong Y, Kim C-S, et al. Noninvasive precision screening of prostate cancer by urinary multimarker sensor and artificial intelligence analysis. ACS Nano. 2021;15:4054–65.
pubmed: 33296173 doi: 10.1021/acsnano.0c06946
Yurkovetsky Z, Skates S, Lomakin A, Nolen B, Pulsipher T, Modugno F, et al. Development of a multimarker assay for early detection of ovarian cancer. J Clin Oncol. 2010;28:2159–66.
pubmed: 20368574 pmcid: 2860434 doi: 10.1200/JCO.2008.19.2484
Füzéry AK, Levin J, Chan MM, Chan DW. Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges. Clin Proteomics. 2013;10:13.
pubmed: 24088261 pmcid: 3850675 doi: 10.1186/1559-0275-10-13
Ou F-S, Michiels S, Shyr Y, Adjei AA, Oberg AL. Biomarker discovery and validation: statistical considerations. J Thorac Oncol. 2021;16:537–45.
pubmed: 33545385 pmcid: 8012218 doi: 10.1016/j.jtho.2021.01.1616
Delafield DG, Li L. Recent advances in analytical approaches for glycan and glycopeptide quantitation. Mol Cell Proteomics. 2021;20:100054.
pubmed: 32576592 pmcid: 8724918 doi: 10.1074/mcp.R120.002095
Yin H, Zhu J. Methods for quantification of glycopeptides by liquid separation and mass spectrometry. Mass Spectrom Rev. 2023;42:887–917.
pubmed: 35099083 doi: 10.1002/mas.21771
Hong Q, Lebrilla CB, Miyamoto S, Ruhaak LR. Absolute quantitation of immunoglobulin g and its glycoforms using multiple reaction monitoring. Anal Chem. 2013;85:8585–93.
pubmed: 23944609 doi: 10.1021/ac4009995
Krishnan S, Shimoda M, Sacchi R, Kailemia MJ, Luxardi G, Kaysen GA, et al. HDL glycoprotein composition and site-specific glycosylation differentiates between clinical groups and affects IL-6 secretion in lipopolysaccharide-stimulated monocytes. Sci Rep. 2017;7:43728.
pubmed: 28287093 pmcid: 5347119 doi: 10.1038/srep43728
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.
pubmed: 26813784 pmcid: 5637400 doi: 10.1021/acs.jproteome.5b01071
Ruhaak LR, Barkauskas DA, Torres J, Cooke CL, Wu LD, Stroble C, et al. The serum immunoglobulin G glycosylation signature of gastric cancer. EuPA Open Proteom. 2015;6:1–9.
pubmed: 25685702 doi: 10.1016/j.euprot.2014.11.002
Darebna P, Novak P, Kucera R, Topolcan O, Sanda M, Goldman R, et al. Changes in the expression of N- and O-glycopeptides in patients with colorectal cancer and hepatocellular carcinoma quantified by full-MS scan FT-ICR and multiple reaction monitoring. J Proteomics. 2017;153:44–52.
pubmed: 27646713 doi: 10.1016/j.jprot.2016.09.004
Li Q, Kailemia MJ, Merleev AA, Xu G, Serie D, Danan LM, et al. Site-specific glycosylation quantitation of 50 serum glycoproteins enhanced by predictive glycopeptidomics for improved disease biomarker discovery. Anal Chem. 2019;91:5433–45.
pubmed: 30882205 doi: 10.1021/acs.analchem.9b00776
Ramachandran P, Xu G, Huang HH, Rice R, Zhou B, Lindpaintner K, et al. Serum glycoprotein markers in nonalcoholic steatohepatitis and hepatocellular carcinoma. J Proteome Res. 2022;21:1083–94.
pubmed: 35286803 pmcid: 8981307 doi: 10.1021/acs.jproteome.1c00965
Wu Z, Serie D, Xu G, Zou J. PB-Net: Automatic peak integration by sequential deep learning for multiple reaction monitoring. J Proteomics. 2020;223:103820.
pubmed: 32416316 doi: 10.1016/j.jprot.2020.103820
Pickering C, Zhou B, Xu G, Rice R, Ramachandran P, Huang H, et al. Differential peripheral blood glycoprotein profiles in symptomatic and asymptomatic COVID-19. Viruses. 2022;14:553.
pubmed: 35336960 pmcid: 8951729 doi: 10.3390/v14030553
Xi Y, Xu P. Global colorectal cancer burden in 2020 and projections to 2040. Transl Oncol. 2021;14:101174.
pubmed: 34243011 pmcid: 8273208 doi: 10.1016/j.tranon.2021.101174
Chandrasekar D, Guerrier C, Alisson-Silva F, Dhar C, Caval T, Schwarz F, et al. Warning signs from the crypt: aberrant protein glycosylation marks opportunities for early colorectal cancer detection. Clin Transl Gastroenterol. 2023;14:e00592.
pubmed: 37141103 pmcid: 10371329 doi: 10.14309/ctg.0000000000000592
Qiu Y, Patwa TH, Xu L, Shedden K, Misek DE, Tuck M, et al. Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot. J Proteome Res. 2008;7:1693–703.
pubmed: 18311904 pmcid: 2751808 doi: 10.1021/pr700706s
Pan Y, Zhang L, Zhang R, Han J, Qin W, Gu Y, et al. Screening and diagnosis of colorectal cancer and advanced adenoma by Bionic Glycome method and machine learning. Am J Cancer Res. 2021;11:3002–20.
pubmed: 34249441 pmcid: 8263652
Gu Y, Duan B, Sha J, Zhang R, Fan J, Xu X, et al. Serum IgG N-glycans enable early detection and early relapse prediction of colorectal cancer. Int J Cancer. 2023;152:536–47.
pubmed: 36121650 doi: 10.1002/ijc.34298
Takei D, Harada K, Nouso K, Miyahara K, Dohi C, Matsushita H, et al. Clinical utility of a serum glycome analysis in patients with colorectal cancer. J Gastroenterol Hepatol. 2022;37:727–33.
pubmed: 35064597 doi: 10.1111/jgh.15781
Barrow H, Guo X, Wandall HH, Pedersen JW, Fu B, Zhao Q, et al. Serum galectin-2, -4, and -8 are greatly increased in colon and breast cancer patients and promote cancer cell adhesion to blood vascular endothelium. Clin Cancer Res. 2011;17:7035–46.
pubmed: 21933892 doi: 10.1158/1078-0432.CCR-11-1462
Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer Statistics, 2023. CA Cancer J Clin. 2023;73:17–48.
pubmed: 36633525 doi: 10.3322/caac.21763
Mulshine JL, D’Amico TA. Issues with implementing a high-quality lung cancer screening program. CA Cancer J Clin. 2014;64:352–63.
pubmed: 24976072 doi: 10.3322/caac.21239
Zeng X, Hood BL, Sun M, Conrads TP, Day RS, Weissfeld JL, et al. Lung cancer serum biomarker discovery using glycoprotein capture and liquid chromatography mass spectrometry. J Proteome Res. 2010;9:6440–9.
pubmed: 20931982 pmcid: 3184639 doi: 10.1021/pr100696n
Heo S-H, Lee S-J, Ryoo H-M, Park J-Y, Cho J-Y. Identification of putative serum glycoprotein biomarkers for human lung adenocarcinoma by multilectin affinity chromatography and LC-MS/MS. Proteomics. 2007;7:4292–302.
pubmed: 17963278 doi: 10.1002/pmic.200700433
Arnold JN, Saldova R, Galligan MC, Murphy TB, Mimura-Kimura Y, Telford JE, et al. Novel glycan biomarkers for the detection of lung cancer. J Proteome Res. 2011;10:1755–64.
pubmed: 21214223 doi: 10.1021/pr101034t
Vasseur JA, Goetz JA, Alley WR, Novotny MV. Smoking and lung cancer-induced changes in N-glycosylation of blood serum proteins. Glycobiology. 2012;22:1684–708.
pubmed: 22781126 pmcid: 3486013 doi: 10.1093/glycob/cws108
Fang K, Long Q, Liao Z, Zhang C, Jiang Z. Glycoproteomics revealed novel N-glycosylation biomarkers for early diagnosis of lung adenocarcinoma cancers. Clin Proteomics. 2022;19:43.
pubmed: 36401165 pmcid: 9675222 doi: 10.1186/s12014-022-09376-8
Ahn J-M, Sung H-J, Yoon Y-H, Kim B-G, Yang WS, Lee C, et al. Integrated glycoproteomics demonstrates fucosylated serum paraoxonase 1 alterations in small cell lung cancer. Mol Cell Proteomics. 2014;13:30–48.
pubmed: 24085812 doi: 10.1074/mcp.M113.028621
Mitchell A, Pickering C, Xu G, Rice R, Castellanos A, Bhadra R, et al. Glycoproteomics as a powerful liquid biopsy-based screening tool for non-small cell lung cancer. J Clin Oncol. 2022;40:e21148–e21148.
doi: 10.1200/JCO.2022.40.16_suppl.e21148
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global Cancer Statistics, 2012. CA Cancer J Clin. 2015;65:87–108.
pubmed: 25651787 doi: 10.3322/caac.21262
Lu KH. Screening for ovarian cancer in asymptomatic women. JAMA. 2018;319:557–8.
pubmed: 29450509 doi: 10.1001/jama.2017.21894
Charkhchi P, Cybulski C, Gronwald J, Wong FO, Narod SA, Akbari MR. CA125 and ovarian cancer: a comprehensive review. Cancers. 2020;12:3730.
pubmed: 33322519 pmcid: 7763876 doi: 10.3390/cancers12123730
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.
pubmed: 30917847 pmcid: 6436208 doi: 10.1186/s13048-019-0503-7
Ankenbauer KE, Rao TC, Mattheyses AL, Bellis SL. Sialylation of EGFR by ST6GAL1 induces receptor activation and modulates trafficking dynamics. J Biol Chem. 2023;299:105217.
pubmed: 37660914 pmcid: 10520885 doi: 10.1016/j.jbc.2023.105217
Dorsett KA, Jones RB, Ankenbauer KE, Hjelmeland AB, Bellis SL. Sox2 promotes expression of the ST6Gal-I glycosyltransferase in ovarian cancer cells. J Ovarian Res. 2019;12:93.
pubmed: 31610800 pmcid: 6792265 doi: 10.1186/s13048-019-0574-5
Schultz MJ, Holdbrooks AT, Chakraborty A, Grizzle WE, Landen CN, Buchsbaum DJ, et al. The tumor-associated glycosyltransferase ST6GaL-I regulates stem cell transcription factors and confers a cancer stem cell phenotype. Cancer Res. 2016;76:3978–88.
pubmed: 27216178 pmcid: 4930726 doi: 10.1158/0008-5472.CAN-15-2834
O’Flaherty R, Muniyappa M, Walsh I, Stöckmann H, Hilliard M, Hutson R, et al. A robust and versatile automated glycoanalytical technology for serum antibodies and acute phase proteins: ovarian cancer case study. Mol Cell Proteomics. 2019;18:2191–206.
pubmed: 31471495 pmcid: 6823853 doi: 10.1074/mcp.RA119.001531
Pan J, Hu Y, Sun S, Chen L, Schnaubelt M, Clark D, et al. Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer. Nat Commun. 2020;11:6139.
pubmed: 33262351 pmcid: 7708455 doi: 10.1038/s41467-020-19976-3
Hu Y, Pan J, Shah P, Ao M, Thomas SN, Liu Y, et al. Integrated proteomic and glycoproteomic characterization of human high-grade serous ovarian carcinoma. Cell Rep. 2020;33:108276.
pubmed: 33086064 pmcid: 7970828 doi: 10.1016/j.celrep.2020.108276
Serie D, Moser K, Pickering C, Aiyetan P, Xu G, Rice R, et al. Liquid-biopsy-derived glycoproteomic profiling as a novel means for noninvasive diagnosis of ovarian cancer. J Clin Oncol. 2022;40:e17604–e17604.
doi: 10.1200/JCO.2022.40.16_suppl.e17604
Lindpaintner K, Pickering C, Mitchell A, Xu G, Cong X, Serie D. Abstract 5314: A peripheral blood-based glycoproteomic predictor of checkpoint inhibitor treatment benefit in advanced non-small cell lung cancer. Cancer Res. 2023;83:5314–5314.
doi: 10.1158/1538-7445.AM2023-5314
Lindpaintner K, Srinivasan A, Mitchell A, Dixit A, Xu G, Cong X, et al. 158 A novel, highly accurate liquid biopsy-based glycoproteomic predictor of checkpoint inhibitor treatment benefit in advanced non-small cell lung cancer. Regular and Young Investigator Award Abstracts. BMJ Publishing Group Ltd; 2022. p. A171–A171.
Lindpaintner K, Cheng M, Prendergast J, Normington K, Wong M, Xu G, et al. 30 Blood-based glycoprotein signatures in advanced non-small-cell lung carcinoma (NSCLC) receiving first-line immune checkpoint blockade. J Immunother Cancer. 2021;9:A35–A35.
doi: 10.1136/jitc-2021-SITC2021.030
Wang Y-N, Lee H-H, Hsu JL, Yu D, Hung M-C. The impact of PD-L1 N-linked glycosylation on cancer therapy and clinical diagnosis. J Biomed Sci. 2020;27:77.
pubmed: 32620165 pmcid: 7333976 doi: 10.1186/s12929-020-00670-x
Lee H-H, Wang Y-N, Xia W, Chen C-H, Rau K-M, Ye L, et al. Removal of N-linked glycosylation enhances PD-L1 detection and predicts anti-PD-1/PD-L1 therapeutic efficacy. Cancer Cell. 2019;36:168–78.
pubmed: 31327656 pmcid: 6793936 doi: 10.1016/j.ccell.2019.06.008
Li C-W, Lim S-O, Xia W, Lee H-H, Chan L-C, Kuo C-W, et al. Glycosylation and stabilization of programmed death ligand-1 suppresses T-cell activity. Nat Commun. 2016;7:12632.
pubmed: 27572267 pmcid: 5013604 doi: 10.1038/ncomms12632
Li C-W, Lim S-O, Chung EM, Kim Y-S, Park AH, Yao J, et al. Eradication of triple-negative breast cancer cells by targeting glycosylated PD-L1. Cancer Cell. 2018;33:187–201.
pubmed: 29438695 pmcid: 5824730 doi: 10.1016/j.ccell.2018.01.009

Auteurs

Kai He (K)

James Comprehensive Cancer Center, The Ohio State University, Columbus, USA. kai.he@osumc.edu.

Maryam Baniasad (M)

InterVenn Biosciences, South San Francisco, USA.

Hyunwoo Kwon (H)

James Comprehensive Cancer Center, The Ohio State University, Columbus, USA.

Tomislav Caval (T)

InterVenn Biosciences, South San Francisco, USA.

Gege Xu (G)

InterVenn Biosciences, South San Francisco, USA.

Carlito Lebrilla (C)

Department of Biochemistry and Molecular Medicine, UC Davis Health, Sacramento, USA.

Daniel W Hommes (DW)

InterVenn Biosciences, South San Francisco, USA.

Carolyn Bertozzi (C)

Department of Chemistry, Stanford University, Stanford, USA.

Classifications MeSH