Distinct urinary glycoprotein signatures in prostate cancer patients

dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorKAWAHARA, R.
dc.contributor.authorORTEGA, F.
dc.contributor.authorROSA-FERNANDES, L.
dc.contributor.authorGUIMARãES, V.
dc.contributor.authorQUINA, D.
dc.contributor.authorNAHAS, W.
dc.contributor.authorSCHWäMMLE, V.
dc.contributor.authorSROUGI, M.
dc.contributor.authorLEITE, K. R. M.
dc.contributor.authorTHAYSEN-ANDERSEN, M.
dc.contributor.authorLARSEN, M. R.
dc.contributor.authorPALMISANO, G.
dc.date.accessioned2019-03-13T17:07:02Z
dc.date.available2019-03-13T17:07:02Z
dc.date.issued2018
dc.description.abstractNovel biomarkers are needed to complement prostate specific antigen (PSA) in prostate cancer (PCa) diagnostic screening programs. Glycoproteins represent a hitherto largely untapped resource with a great potential as specific and sensitive tumor biomarkers due to their abundance in bodily fluids and their dynamic and cancer-associated glycosylation. However, quantitative glycoproteomics strategies to detect potential glycoprotein cancer markers from complex biospecimen are only just emerging. Here, we describe a glycoproteomics strategy for deep quantitative mapping of N- and O-glycoproteins in urine with a view to investigate the diagnostic value of the glycoproteome to discriminate PCa from benign prostatic hyperplasia (BPH), two conditions that remain difficult to clinically stratify. Total protein extracts were obtained, concentrated and digested from urine of six PCa patients (Gleason score 7) and six BPH patients. The resulting peptide mixtures were TMT-labeled and mixed prior to a multi-faceted sample processing including hydrophilic interaction liquid chromatography (HILIC) and titanium dioxide SPE based enrichment, endo-/exoglycosidase treatment and HILIC-HPLC pre-fractionation. The isolated N- and O-glycopeptides were detected and quantified using high resolution mass spectrometry. We accurately quantified 729 N-glycoproteins spanning 1,310 unique N-glycosylation sites and observed 954 and 965 unique intact N- and O-glycopeptides, respectively, across the two disease conditions. Importantly, a panel of 56 intact N-glycopeptides perfectly discriminated PCa and BPH (ROC: AUC = 1). This study has generated a panel of intact glycopeptides that has a potential for PCa detection. © Kawahara et al.eng
dc.description.indexPubMedeng
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo: 2015/02866-0
dc.description.sponsorshipGR11.172.1
dc.description.sponsorshipSyddansk Universitet, SDU
dc.identifier.citationONCOTARGET, v.9, n.69, p.33077-33097, 2018
dc.identifier.doi10.18632/oncotarget.26005
dc.identifier.issn1949-2553
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/31023
dc.language.isoeng
dc.publisherIMPACT JOURNALS LLCeng
dc.relation.ispartofOncotarget
dc.rightsrestrictedAccesseng
dc.rights.holderCopyright IMPACT JOURNALS LLCeng
dc.subjectGlycopeptideeng
dc.subjectGlycoproteomicseng
dc.subjectProstate cancereng
dc.subjectTMT-labelingeng
dc.subjectUrineeng
dc.subject.otherglycoproteineng
dc.subject.otherglycosidaseeng
dc.subject.othertumor markereng
dc.subject.otherarticleeng
dc.subject.otherdiagnostic valueeng
dc.subject.otherdifferential diagnosiseng
dc.subject.otherdisease markereng
dc.subject.othergleason scoreeng
dc.subject.otherglycoproteomicseng
dc.subject.otherhigh performance liquid chromatographyeng
dc.subject.otherhumaneng
dc.subject.otherhydrophilic interaction chromatographyeng
dc.subject.othermass spectrometryeng
dc.subject.otherprostate cancereng
dc.subject.otherprostate hypertrophyeng
dc.subject.otherproteomicseng
dc.subject.otherurineeng
dc.titleDistinct urinary glycoprotein signatures in prostate cancer patientseng
dc.typearticleeng
dc.type.categoryoriginal articleeng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.affiliation.countryAustrália
hcfmusp.affiliation.countryDinamarca
hcfmusp.affiliation.countryisodk
hcfmusp.affiliation.countryisoau
hcfmusp.author.externalKAWAHARA, R.:Instituto de Ciências Biomédicas, Departamento de Parasitologia, Universidade de São Paulo, USP, São Paulo, Brazil
hcfmusp.author.externalROSA-FERNANDES, L.:Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
hcfmusp.author.externalQUINA, D.:Instituto de Ciências Biomédicas, Departamento de Parasitologia, Universidade de São Paulo, USP, São Paulo, Brazil
hcfmusp.author.externalSCHWäMMLE, V.:Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
hcfmusp.author.externalTHAYSEN-ANDERSEN, M.:Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
hcfmusp.author.externalLARSEN, M. R.:Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
hcfmusp.author.externalPALMISANO, G.:Instituto de Ciências Biomédicas, Departamento de Parasitologia, Universidade de São Paulo, USP, São Paulo, Brazil
hcfmusp.citation.scopus32
hcfmusp.contributor.author-fmusphcFABIO LEME ORTEGA
hcfmusp.contributor.author-fmusphcVANESSA RIBEIRO GUIMARAES SCHREITER
hcfmusp.contributor.author-fmusphcWILLIAM CARLOS NAHAS
hcfmusp.contributor.author-fmusphcMIGUEL SROUGI
hcfmusp.contributor.author-fmusphcKATIA RAMOS MOREIRA LEITE
hcfmusp.description.beginpage33077
hcfmusp.description.endpage33097
hcfmusp.description.issue69
hcfmusp.description.volume9
hcfmusp.origemSCOPUS
hcfmusp.origem.pubmed30237853
hcfmusp.origem.scopus2-s2.0-85052921731
hcfmusp.relation.referenceSiegel, R.L., Miller, K.D., Jemal, A., Cancer statistics, 2016 (2016) CA Cancer J Clin, 66, pp. 7-30. , https://doi.org/10.3322/caac.21332eng
hcfmusp.relation.referencePrensner, J.R., Rubin, M.A., Wei, J.T., Chinnaiyan, A.M., Beyond PSA: the next generation of prostate cancer biomarkers (2012) Sci Transl Med, 4, p. 127rv3. , https://doi.org/10.1126/scitranslmed.3003180eng
hcfmusp.relation.referenceAdhyam, M., Gupta, A.K., A Review on the Clinical Utility of PSA in Cancer Prostate (2012) Indian J Surg Oncol, 3, pp. 120-129. , https://doi.org/10.1007/s13193-012-0142-6eng
hcfmusp.relation.referenceDijkstra, S., Mulders, P.F., Schalken, J.A., Clinical use of novel urine and blood based prostate cancer biomarkers: a review (2014) Clin Biochem, 47, pp. 889-896. , https://doi.org/10.1016/j.clinbiochem.2013.10.023eng
hcfmusp.relation.referenceJamaspishvili, T., Kral, M., Khomeriki, I., Student, V., Kolar, Z., Bouchal, J., Urine markers in monitoring for prostate cancer (2010) Prostate Cancer Prostatic Dis, 13, pp. 12-19. , https://doi.org/10.1038/pcan.2009.31eng
hcfmusp.relation.referenceWood, S.L., Knowles, M.A., Thompson, D., Selby, P.J., Banks, R.E., Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers (2013) Nat Rev Urol, 10, pp. 206-218. , https://doi.org/10.1038/nrurol.2013.24eng
hcfmusp.relation.referenceHaj-Ahmad, T.A., Abdalla, M.A., Haj-Ahmad, Y., Potential Urinary Protein Biomarker Candidates for the Accurate Detection of Prostate Cancer among Benign Prostatic Hyperplasia Patients (2014) J Cancer, 5, pp. 103-114. , https://doi.org/10.7150/jca.6890eng
hcfmusp.relation.referenceJedinak, A., Curatolo, A., Zurakowski, D., Dillon, S., Bhasin, M.K., Libermann, T.A., Roy, R., Moses, M.A., Novel non-invasive biomarkers that distinguish between benign prostate hyperplasia and prostate cancer (2015) BMC Cancer, 15, p. 259. , https://doi.org/10.1186/s12885-015-1284-zeng
hcfmusp.relation.referenceDurand, G., Seta, N., Protein glycosylation and diseases: blood and urinary oligosaccharides as markers for diagnosis and therapeutic monitoring (2000) Clin Chem, 46, pp. 795-805eng
hcfmusp.relation.referenceDrake, P.M., Cho, W., Li, B., Prakobphol, A., Johansen, E., Anderson, N.L., Regnier, F.E., Fisher, S.J., Sweetening the pot: adding glycosylation to the biomarker discovery equation (2010) Clin Chem, 56, pp. 223-236. , https://doi.org/10.1373/clinchem.2009.136333eng
hcfmusp.relation.referenceChen, K., Gentry-Maharaj, A., Burnell, M., Steentoft, C., Marcos-Silva, L., Mandel, U., Jacobs, I., Blixt, O., Microarray Glycoprofiling of CA125 improves differential diagnosis of ovarian cancer (2013) J Proteome Res, 12, pp. 1408-1418. , https://doi.org/10.1021/pr3010474eng
hcfmusp.relation.referenceZhang, D., Chen, B., Wang, Y., Xia, P., He, C., Liu, Y., Zhang, R., Li, Z., Disease-specific IgG Fc N-glycosylation as personalized biomarkers to differentiate gastric cancer from benign gastric diseases (2016) Sci Rep, 6, p. 25957. , https://doi.org/10.1038/srep25957eng
hcfmusp.relation.referenceKirwan, A., Utratna, M., O'Dwyer, M.E., Joshi, L., Kilcoyne, M., Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics (2015) Biomed Res Int, 2015. , https://doi.org/10.1155/2015/490531eng
hcfmusp.relation.referenceBelický, Š., Tkac, J., Can glycoprofiling be helpful in detecting prostate cancer? (2015) Chem Zvesti, 69, pp. 90-111. , https://doi.org/10.1515/chempap-2015-0052eng
hcfmusp.relation.referenceVermassen, T., Van Praet, C., Poelaert, F., Lumen, N., Decaestecker, K., Hoebeke, P., Van Belle, S., Delanghe, J., Diagnostic accuracy of urinary prostate protein glycosylation profiling in prostatitis diagnosis (2015) Biochem Med (Zagreb), 25, pp. 439-449. , https://doi.org/10.11613/BM.2015.045eng
hcfmusp.relation.referencePinho, S.S., Reis, C.A., Glycosylation in cancer: mechanisms and clinical implications (2015) Nat Rev Cancer, 15, pp. 540-555. , https://doi.org/10.1038/nrc3982eng
hcfmusp.relation.referenceMunkley, J., Elliott, D.J., Hallmarks of glycosylation in cancer (2016) Oncotarget, 7, pp. 35478-35489. , https://doi.org/10.18632/oncotarget.8155eng
hcfmusp.relation.referenceMunkley, J., Mills, I.G., Elliott, D.J., The role of glycans in the development and progression of prostate cancer (2016) Nat Rev Urol, 13, pp. 324-333. , https://doi.org/10.1038/nrurol.2016.65eng
hcfmusp.relation.referenceVermassen, T., Van Praet, C., Lumen, N., Decaestecker, K., Vanderschaeghe, D., Callewaert, N., Villeirs, G., Delanghe, J., Urinary prostate protein glycosylation profiling as a diagnostic biomarker for prostate cancer (2015) Prostate, 75, pp. 314-322. , https://doi.org/10.1002/pros.22918eng
hcfmusp.relation.referenceShah, P., Wang, X., Yang, W., Toghi Eshghi, S., Sun, S., Hoti, N., Chen, L., Zhang, H., Integrated Proteomic and Glycoproteomic Analyses of Prostate Cancer Cells Reveal Glycoprotein Alteration in Protein Abundance and Glycosylation (2015) Mol Cell Proteomics, 14, pp. 2753-2763. , https://doi.org/10.1074/mcp.M115.047928eng
hcfmusp.relation.referenceLiu, Y., Chen, J., Sethi, A., Li, Q.K., Chen, L., Collins, B., Gillet, L.C., Aebersold, R., Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness (2014) Mol Cell Proteomics, 13, pp. 1753-1768. , https://doi.org/10.1074/mcp.M114.038273eng
hcfmusp.relation.referenceCima, I., Schiess, R., Wild, P., Kaelin, M., Schüffler, P., Lange, V., Picotti, P., Wyler, S., Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer (2011) Proc Natl Acad Sci U S A, 108, pp. 3342-3347. , https://doi.org/10.1073/pnas.1013699108eng
hcfmusp.relation.referenceThaysen-Andersen, M., Packer, N.H., Advances in LC-MS/ MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N-and O-glycoproteome (2014) Biochim Biophys Acta, 1844, pp. 1437-1452. , https://doi.org/10.1016/j.bbapap.2014.05.002eng
hcfmusp.relation.referenceThaysen-Andersen, M., Packer, N.H., Schulz, B.L., Maturing Glycoproteomics Technologies Provide Unique Structural Insights into the N-glycoproteome and Its Regulation in Health and Disease (2016) Mol Cell Proteomics, 15, pp. 1773-1790. , https://doi.org/10.1074/mcp.O115.057638eng
hcfmusp.relation.referenceCao, L., Qu, Y., Zhang, Z., Wang, Z., Prytkova, I., Wu, S., Intact glycopeptide characterization using mass spectrometry (2016) Expert Rev Proteomics, 13, pp. 513-522. , https://doi.org/10.1586/14789450.2016.1172965eng
hcfmusp.relation.referenceTsai, P.L., Chen, S.F., A Brief Review of Bioinformatics Tools for Glycosylation Analysis by Mass Spectrometry (2017) Mass Spectrom (Tokyo), 6, p. S0064. , https://doi.org/10.5702/massspectrometry.S0064eng
hcfmusp.relation.referenceKawahara, R., Saad, J., Angeli, C.B., Palmisano, G., Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides (2016) Glycoconj J, 33, pp. 937-951. , https://doi.org/10.1007/s10719-016-9677-zeng
hcfmusp.relation.referenceLarsen, M.R., Jensen, S.S., Jakobsen, L.A., Heegaard, N.H., Exploring the sialiome using titanium dioxide chromatography and mass spectrometry (2007) Mol Cell Proteomics, 6, pp. 1778-1787. , https://doi.org/10.1074/mcp.M700086-MCP200eng
hcfmusp.relation.referencePalmisano, G., Lendal, S.E., Engholm-Keller, K., Leth-Larsen, R., Parker, B.L., Larsen, M.R., Selective enrichment of sialic acid-containing glycopeptides using titanium dioxide chromatography with analysis by HILIC and mass spectrometry (2010) Nat Protoc, 5, pp. 1974-1982. , https://doi.org/10.1038/nprot.2010.167eng
hcfmusp.relation.referenceMysling, S., Palmisano, G., Højrup, P., Thaysen-Andersen, M., Utilizing ion-pairing hydrophilic interaction chromatography solid phase extraction for efficient glycopeptide enrichment in glycoproteomics (2010) Anal Chem, 82, pp. 5598-5609. , https://doi.org/10.1021/ac100530weng
hcfmusp.relation.referenceThaysen-Andersen, M., Mysling, S., Højrup, P., Site-specific glycoprofiling of N-linked glycopeptides using MALDITOF MS: strong correlation between signal strength and glycoform quantities (2009) Anal Chem, 81, pp. 3933-3943. , https://doi.org/10.1021/ac900231weng
hcfmusp.relation.referenceBern, M.W., Kil, Y.J., Two-dimensional target decoy strategy for shotgun proteomics (2011) J Proteome Res, 10, pp. 5296-5301. , https://doi.org/10.1021/pr200780jeng
hcfmusp.relation.referencePalmisano, G., Parker, B.L., Engholm-Keller, K., Lendal, S.E., Kulej, K., Schulz, M., Schwämmle, V., Larsen, M.R., A novel method for the simultaneous enrichment, identification, and quantification of phosphopeptides and sialylated glycopeptides applied to a temporal profile of mouse brain development (2012) Mol Cell Proteomics, 11, pp. 1191-1202. , https://doi.org/10.1074/mcp.M112.017509eng
hcfmusp.relation.referenceHouel, S., Hilliard, M., Yu, Y.Q., McLoughlin, N., Martin, S.M., Rudd, P.M., Williams, J.P., Chen, W., N-and O-glycosylation analysis of etanercept using liquid chromatography and quadrupole time-of-flight mass spectrometry equipped with electron-transfer dissociation functionality (2014) Anal Chem, 86, pp. 576-584. , https://doi.org/10.1021/ac402726heng
hcfmusp.relation.referenceMaupin, K.A., Liden, D., Haab, B.B., The fine specificity of mannose-binding and galactose-binding lectins revealed using outlier motif analysis of glycan array data (2012) Glycobiology, 22, pp. 160-169. , https://doi.org/10.1093/glycob/cwr128eng
hcfmusp.relation.referenceRitchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., Smyth, G.K., limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) Nucleic Acids Res, 43. , https://doi.org/10.1093/nar/gkv007eng
hcfmusp.relation.referencePeterson, A.C., Russell, J.D., Bailey, D.J., Westphall, M.S., Coon, J.J., Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics (2012) Mol Cell Proteomics, 11, pp. 1475-1488. , https://doi.org/10.1074/mcp.O112.020131eng
hcfmusp.relation.referenceCampbell, M.P., Peterson, R., Mariethoz, J., Gasteiger, E., Akune, Y., Aoki-Kinoshita, K.F., Lisacek, F., Packer, N.H., UniCarbKB: building a knowledge platform for glycoproteomics (2014) Nucleic Acids Res, 42. , https://doi.org/10.1093/nar/gkt1128eng
hcfmusp.relation.referenceSamraj, A.N., Läubli, H., Varki, N., Varki, A., Involvement of a non-human sialic Acid in human cancer (2014) Front Oncol, 4, p. 33eng
hcfmusp.relation.referenceDavalieva, K., Kiprijanovska, S., Komina, S., Petrusevska, G., Zografska, N.C., Polenakovic, M., Proteomics analysis of urine reveals acute phase response proteins as candidate diagnostic biomarkers for prostate cancer (2015) Proteome Sci, 13, p. 2. , https://doi.org/10.1186/s12953-014-0059-9eng
hcfmusp.relation.referenceXu, C., Jung, M., Burkhardt, M., Stephan, C., Schnorr, D., Loening, S., Jung, K., Kristiansen, G., Increased CD59 protein expression predicts a PSA relapse in patients after radical prostatectomy (2005) Prostate, 62, pp. 224-232. , https://doi.org/10.1002/pros.20134eng
hcfmusp.relation.referenceJarvis, G.A., Li, J., Hakulinen, J., Brady, K.A., Nordling, S., Dahiya, R., Meri, S., Expression and function of the complement membrane attack complex inhibitor protectin (CD59) in human prostate cancer (1997) Int J Cancer, 71, pp. 1049-1055. , https://doi.org/10.1002/(SICI)1097-0215(19970611)71:6<1049::AID-IJC22>3.0.CO;2-7eng
hcfmusp.relation.referenceSaraon, P., Musrap, N., Cretu, D., Karagiannis, G.S., Batruch, I., Smith, C., Drabovich, A.P., Diamandis, E.P., Proteomic profiling of androgen-independent prostate cancer cell lines reveals a role for protein S during the development of high grade and castration-resistant prostate cancer (2012) J Biol Chem, 287, pp. 34019-34031. , https://doi.org/10.1074/jbc.M112.384438eng
hcfmusp.relation.referenceRizzi, F., Bettuzzi, S., Targeting Clusterin in prostate cancer (2008) J Physiol Pharmacol, 59, pp. 265-274eng
hcfmusp.relation.referencePins, M.R., Fiadjoe, J.E., Korley, F., Wong, M., Rademaker, A.W., Jovanovic, B., Yoo, T.K., Lee, C., Clusterin as a possible predictor for biochemical recurrence of prostate cancer following radical prostatectomy with intermediate Gleason scores: a preliminary report (2004) Prostate Cancer Prostatic Dis, 7, pp. 243-248. , https://doi.org/10.1038/sj.pcan.4500722eng
hcfmusp.relation.referenceHalim, A., Nilsson, J., Rüetschi, U., Hesse, C., Larson, G., Human urinary glycoproteomicseng
hcfmusp.relation.referenceattachment site specific analysis of N-and O-linked glycosylations by CID and ECD (2012) Mol Cell Proteomics, 11. , https://doi.org/10.1074/mcp.M111.013649eng
hcfmusp.relation.referenceSaraswat, M., Joenväära, S., Musante, L., Peltoniemi, H., Holthofer, H., Renkonen, R., N-linked (N-) glycoproteomics of urinary exosomes [Corrected] (2015) Mol Cell Proteomics, 14, pp. 263-276. , https://doi.org/10.1074/mcp.M114.040345.Erratumin:N-linked(N-)GlycoproteomicsofUrinaryExosomes.[MolCellProteomics.2015]eng
hcfmusp.relation.referenceNagaraj, N., Mann, M., Quantitative analysis of the intra-and inter-individual variability of the normal urinary proteome (2011) J Proteome Res, 10, pp. 637-645. , https://doi.org/10.1021/pr100835seng
hcfmusp.relation.referenceMaes, E., Valkenborg, D., Baggerman, G., Willems, H., Landuyt, B., Schoofs, L., Mertens, I., Determination of variation parameters as a crucial step in designing TMT-based clinical proteomics experiments (2015) PLoS One, 10. , https://doi.org/10.1371/journal.pone.0120115eng
hcfmusp.relation.referenceAhrné, E., Glatter, T., Viganò, C., Schubert, C., Nigg, E.A., Schmidt, A., Evaluation and Improvement of Quantification Accuracy in Isobaric Mass Tag-Based Protein Quantification Experiments (2016) J Proteome Res, 15, pp. 2537-2547. , https://doi.org/10.1021/acs.jproteome.6b00066eng
hcfmusp.relation.referenceKarp, N.A., Huber, W., Sadowski, P.G., Charles, P.D., Hester, S.V., Lilley, K.S., Addressing accuracy and precision issues in iTRAQ quantitation (2010) Mol Cell Proteomics, 9, pp. 1885-1897. , https://doi.org/10.1074/mcp.M900628-MCP200eng
hcfmusp.relation.referenceChristoforou, A.L., Lilley, K.S., Isobaric tagging approaches in quantitative proteomics: the ups and downs (2012) Anal Bioanal Chem, 404, pp. 1029-1037. , https://doi.org/10.1007/s00216-012-6012-9eng
hcfmusp.relation.referenceCox, J., Mann, M., MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification (2008) Nat Biotechnol, 26, pp. 1367-1372. , https://doi.org/10.1038/nbt.1511eng
hcfmusp.relation.referenceFuster, M.M., Esko, J.D., The sweet and sour of cancer: glycans as novel therapeutic targets (2005) Nat Rev Cancer, 5, pp. 526-542. , https://doi.org/10.1038/nrc1649eng
hcfmusp.relation.referencePadler-Karavani, V., Aiming at the sweet side of cancer: aberrant glycosylation as possible target for personalizedmedicine (2014) Cancer Lett, 352, pp. 102-112. , https://doi.org/10.1016/j.canlet.2013.10.005eng
hcfmusp.relation.referenceMeany, D.L., Chan, D.W., Aberrant glycosylation associated with enzymes as cancer biomarkers (2011) Clin Proteomics, 8, p. 7. , https://doi.org/10.1186/1559-0275-8-7eng
hcfmusp.relation.referenceWang, X., Chen, J., Li, Q.K., Peskoe, S.B., Zhang, B., Choi, C., Platz, E.A., Zhang, H., Overexpression of a (1,6) fucosyltransferase associated with aggressive prostate cancer (2014) Glycobiology, 24, pp. 935-944. , https://doi.org/10.1093/glycob/cwu051eng
hcfmusp.relation.referenceVermassen, T., Van Praet, C., Vanderschaeghe, D., Maenhout, T., Lumen, N., Callewaert, N., Hoebeke, P., Delanghe, J., Capillary electrophoresis of urinary prostate glycoproteins assists in the diagnosis of prostate cancer (2014) Electrophoresis, 35, pp. 1017-1024. , https://doi.org/10.1002/elps.201300332eng
hcfmusp.relation.referenceMeany, D.L., Zhang, Z., Sokoll, L.J., Zhang, H., Chan, D.W., Glycoproteomics for prostate cancer detection: changes in serum PSA glycosylation patterns (2009) J Proteome Res, 8, pp. 613-619. , https://doi.org/10.1021/pr8007539eng
hcfmusp.relation.referenceBarfeld, S.J., East, P., Zuber, V., Mills, I.G., Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes (2014) BMC Med Genomics, 7, p. 513. , https://doi.org/10.1186/s12920-014-0074-9eng
hcfmusp.relation.referenceTabarés, G., Radcliffe, C.M., Barrabés, S., Ramírez, M., Aleixandre, R.N., Hoesel, W., Dwek, R.A., de Llorens, R., Different glycan structures in prostatespecific antigen from prostate cancer sera in relation to seminal plasma PSA (2006) Glycobiology, 16, pp. 132-145. , https://doi.org/10.1093/glycob/cwj042eng
hcfmusp.relation.referenceLlop, E., Ferrer-Batallé, M., Barrabés, S., Guerrero, P.E., Ramírez, M., Saldova, R., Rudd, P.M., Peracaula, R., Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes (2016) Theranostics, 6, pp. 1190-1204. , https://doi.org/10.7150/thno.15226eng
hcfmusp.relation.referenceOhyama, C., Hosono, M., Nitta, K., Oh-eda, M., Yoshikawa, K., Habuchi, T., Arai, Y., Fukuda, M., Carbohydrate structure and differential binding of prostate specific antigen to Maackia amurensis lectin between prostate cancer and benign prostate hypertrophy (2004) Glycobiology, 14, pp. 671-679. , https://doi.org/10.1093/glycob/cwh071eng
hcfmusp.relation.referenceBabiker, A.A., Nilsson, B., Ronquist, G., Carlsson, L., Ekdahl, K.N., Transfer of functional prostasomal CD59 of metastatic prostatic cancer cell origin protects cells against complement attack (2005) Prostate, 62, pp. 105-114. , https://doi.org/10.1002/pros.20102eng
hcfmusp.relation.referenceRudd, P.M., Morgan, B.P., Wormald, M.R., Harvey, D.J., van den Berg, C.W., Davis, S.J., Ferguson, M.A., Dwek, R.A., The glycosylation of the complement regulatory protein, human erythrocyte CD59 (1997) J Biol Chem, 272, pp. 7229-7244. , https://doi.org/10.1074/jbc.272.11.7229eng
hcfmusp.relation.referenceTokugawa, Y., Kunishige, I., Kubota, Y., Shimoya, K., Nobunaga, T., Kimura, T., Saji, F., Hayaishi, O., Lipocalin-type prostaglandin D synthase in human male reproductive organs and seminal plasma (1998) Biol Reprod, 58, pp. 600-607. , https://doi.org/10.1095/biolreprod58.2.600eng
hcfmusp.relation.referenceJørgensen, A., Nielsen, J.E., Nielsen, B.F., Morthorst, J.E., Bjerregaard, P., Leffers, H., Expression of prostaglandin synthases (pgds and pges) during zebrafish gonadal differentiation (2010) Comp Biochem Physiol A Mol Integr Physiol, 157, pp. 102-108. , https://doi.org/10.1016/j.cbpa.2010.03.014eng
hcfmusp.relation.referenceMoniot, B., Farhat, A., Aritake, K., Declosmenil, F., Nef, S., Eguchi, N., Urade, Y., Boizet-Bonhoure, B., Hematopoietic prostaglandin D synthase (H-Pgds) is expressed in the early embryonic gonad and participates to the initial nuclear translocation of the SOX9 protein (2011) Dev Dyn, 240, pp. 2335-2343. , https://doi.org/10.1002/dvdy.22726eng
hcfmusp.relation.referenceBadawi, A.F., The role of prostaglandin synthesis in prostate cancer (2000) BJU Int, 85, pp. 451-462. , https://doi.org/10.1046/j.1464-410x.2000.00507.xeng
hcfmusp.relation.referenceRagolia, L., Hall, C.E., Palaia, T., Post-translational modification regulates prostaglandin D2 synthase apoptotic activity: characterization by site-directed mutagenesis (2007) Prostaglandins Other Lipid Mediat, 83, pp. 25-32. , https://doi.org/10.1016/j.prostaglandins.2006.09.006eng
hcfmusp.relation.referenceKim, Y., Jeon, J., Mejia, S., Yao, C.Q., Ignatchenko, V., Nyalwidhe, J.O., Gramolini, A.O., Kislinger, T., Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer (2016) Nat Commun, 7, p. 11906. , https://doi.org/10.1038/ncomms11906eng
hcfmusp.relation.referenceSong, E., Pyreddy, S., Mechref, Y., Quantification of glycopeptides by multiple reaction monitoring liquid chromatography/tandem mass spectrometry (2012) Rapid Commun Mass Spectrom, 26, pp. 1941-1954. , https://doi.org/10.1002/rcm.6290eng
hcfmusp.relation.referencede la Fouchardière, C., Flechon, A., Droz, J.P., Coagulopathy in prostate cancer (2003) Neth J Med, 61, pp. 347-354eng
hcfmusp.relation.referenceNavarro, M., Ruiz, I., Martín, G., Cruz, J.J., Patient with disseminated intravascular coagulation as the first manifestation of adenocarcinoma of the prostate Risks of prostatic biopsy (2006) Prostate Cancer Prostatic Dis, 9, pp. 190-191. , https://doi.org/10.1038/sj.pcan.4500854eng
hcfmusp.relation.referenceAdamson, A.S., Francis, J.L., Witherow, R.O., Snell, M.E., Coagulopathy in the prostate cancer patient: prevalence and clinical relevance (1993) Ann R Coll Surg Engl, 75, pp. 100-104eng
hcfmusp.relation.referenceDuran, I., Tannock, I.F., Disseminated intravascular coagulation as the presenting sign of metastatic prostate cancer (2006) J Gen Intern Med, 21, pp. C6-C8. , https://doi.org/10.1111/j.1525-1497.2006.00506.xeng
hcfmusp.relation.referenceOng, S.Y., Taverna, J., Jokerst, C., Enzler, T., Hammode, E., Rogowitz, E., Green, M.R., Babiker, H.M., Prostate Cancer-Associated Disseminated Intravascular Coagulation with Excessive Fibrinolysis Treated with Degarelix (2015) Case Rep Oncol Med, 2015. , https://doi.org/10.1155/2015/212543eng
hcfmusp.relation.referencePio, R., Corrales, L., Lambris, J.D., The role of complement in tumor growth (2014) Adv Exp Med Biol, 772, pp. 229-262. , https://doi.org/10.1007/978-1-4614-5915-6_11eng
hcfmusp.relation.referencePio, R., Ajona, D., Lambris, J.D., Complement inhibition in cancer therapy (2013) Semin Immunol, 25, pp. 54-64. , https://doi.org/10.1016/j.smim.2013.04.001eng
hcfmusp.relation.referenceKawahara, R., Meirelles, G.V., Heberle, H., Domingues, R.R., Granato, D.C., Yokoo, S., Canevarolo, R.R., Barbuto, J.A., Integrative analysis to select cancer candidate biomarkers to targeted validation (2015) Oncotarget, 6, pp. 43635-43652. , https://doi.org/10.18632/oncotarget.6018eng
hcfmusp.relation.referenceManning, M.L., Williams, S.A., Jelinek, C.A., Kostova, M.B., Denmeade, S.R., Proteolysis of complement factors iC3b and C5 by the serine protease prostate-specific antigen in prostatic fluid and seminal plasma (2013) J Immunol, 190, pp. 2567-2574. , https://doi.org/10.4049/jimmunol.1200856eng
hcfmusp.relation.referenceHuang, H., Haar Petersen, M., Ibañez-Vea, M., Lassen, P.S., Larsen, M.R., Palmisano, G., Simultaneous Enrichment of Cysteine-containing Peptides and Phosphopeptides Using a Cysteine-specific Phosphonate Adaptable Tag (CysPAT) in Combination with titanium dioxide (TiO2) Chromatography (2016) Mol Cell Proteomics, 15, pp. 3282-3296. , https://doi.org/10.1074/mcp.M115.054551eng
hcfmusp.relation.referenceBern, M., Kil, Y.J., Becker, C., Byonic: advanced peptide and protein identification software (2012) Curr Protoc Bioinformatics, , https://doi.org/10.1002/0471250953.bi1320s40, Chapter 13 Unit13.20eng
hcfmusp.relation.referenceBern, M., Cai, Y., Goldberg, D., Lookup peaks: a hybrid of de novo sequencing and database search for protein identification by tandem mass spectrometry (2007) Anal Chem, 79, pp. 1393-1400. , https://doi.org/10.1021/ac0617013eng
hcfmusp.relation.referenceLee, L.Y., Moh, E.S., Parker, B.L., Bern, M., Packer, N.H., Thaysen-Andersen, M., Toward Automated N-Glycopeptide Identification in Glycoproteomics (2016) J Proteome Res, 15, pp. 3904-3915. , https://doi.org/10.1021/acs.jproteome.6b00438eng
hcfmusp.relation.referenceCox, J., Neuhauser, N., Michalski, A., Scheltema, R.A., Olsen, J.V., Mann, M., Andromeda: a peptide search engine integrated into the MaxQuant environment (2011) J Proteome Res, 10, pp. 1794-1805. , https://doi.org/10.1021/pr101065jeng
hcfmusp.relation.referenceSchwämmle, V., León, I.R., Jensen, O.N., Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates (2013) J Proteome Res, 12, pp. 3874-3883. , https://doi.org/10.1021/pr400045ueng
hcfmusp.relation.referenceXia, J., Sinelnikov, I.V., Han, B., Wishart, D.S., MetaboAnalyst 3.0-making metabolomics more meaningful (2015) Nucleic Acids Res, 43, pp. W251-W257. , https://doi.org/10.1093/nar/gkv380eng
hcfmusp.relation.referenceShannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Ideker, T., Cytoscape: a software environment for integrated models of biomolecular interaction networks (2003) Genome Res, 13, pp. 2498-2504. , https://doi.org/10.1101/gr.1239303eng
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