Study On The Diagnosis Method Of Common Gynecological Tumors Based On The Proteoglycan Profiles

Protein glycosylation is ubiquitous in eukaryotic cell. The glycan structure changesof proteins in human cells surface and body fluids are associated with the developmentand progression of diseases. Currently, carcinoembryonic antigen, cancer antigen125and cancer antigen15-3are the biomarkers often used for the diagnostic of commongynecological tumors (breast cancer, cervical cancer, ovarian cancer), they areglycosylated proteins. The detection method used frequently in clinical diagnosis wasbased on the core protein levels of tumor biomarkers, there is little for the detection ofprotein glycan patterns. In fact, the diagnostic value based on the protein markerprofiles was limited. Thus, the detection and analysis of protein glycosylation patterns isimportant to the clinical diagnosis of tumor disease.In this study, we develop a method of antibody-lectin sandwich microarray to allowthe efficient study of glycan patterns of protein biomarkers from serum samples. Firstly,we used the antibody microarray targeted for three protein biomarkers (CEA, CA125,CA15-3) to capture these proteins from the serum samples. Then,15kinds of labeledlectins (AAL, LCA, MALⅡ,SNA, ConA, WGA, DBA, SBA, PNA, VVL, DSL, SJA,UEAⅠ, GSLⅡ, LEL) targeting different glycan structural motifs (fucose, sialic acid,mannose, N-acetylglucosamine, N-acetylgalactosamine) were used to detect theglycosylation patterns on the captured proteins. After the optimization research ofexperimental conditions, an effective and feasible method for the analysis of glycanpatterns of specific proteins was developed, which was used for the detection of glycanpatterns on the three protein biomarkers in123clinical serum samples (31breast cancer,24cervical cancer,19ovarian cancer and49healthy individuals). After the comparative analysis of glycan levels on specific protein biomarker in different sample groups, boththe fucose level on CA153and the N-acetylgalactosamine level on CEA in breast cancerserum samples showed significantly elevations, the sialic acid level on CEA showedsignificantly elevations in both breast cancer and cervical cancer serum samples, thesialic acid level on CA153showed significantly elevations in ovarian cancer serumsamples.To probing the clinical values of the human serum glycoprotein profiles for thediagnosis of common gynecological tumors. A lectin microarray consisting of15lectinswith different glycan binding specificities was used to determine the glycancharacteristic of glycoprotein in123serum samples. Stepwise discrimination analysismethod was adopted to establish function model of clinical serum samples classificationwith SPSS15.0software. As a result, two grades of diagnostic discrimination functionmodels were established. The first grade discrimination function could differentiategynecological tumor from healthy individuals, the total diagnostic accuracy rate ofretrospective inspection was84.6%. The second grade discrimination function wereused to differentiate breast tumor, cervical tumor and ovarian tumor, the total diagnosticaccuracy rate of retrospective inspection was85.1%.The results show that the glycan alterations whether on specific protein biomarkersor in serum sample were related with gynecological tumor, and has an helpful referencevalue for the clinical diagnosis of gynecological tumor.