| Objectives To screen and identify the differential proteins in urine of low-grade bladder urothelial carcinoma(LBUC)by using a joint strategy of isobaric tags for relative and absolute quantitation(i TRAQ),bioinformatics analysis and multiple reaction monitoring(MRM)to establish a urine differential protein database which also included BUC urine proteins identified by other research groups obtained by Meta analysis,and to comfirm the diagnostic value of single candidate differential protein as a urine biaomarker which will be included in the BUC diagnostic model.Methods Urine samples from healthy donors and patiens diagnosed with LBUC were collected and mixed in proportion to obtain two control groups(N1,N2)and two LBUC groups(L1,L2).i TRAQ-based quantitative proteomic analysis was performed to detect the differential proteins.The proteins which is significantly asociated with the tumorigenesis and development of bladder cancer were selected based on Gene Ontology(GO)and protein pathway analysis and further verified by MRM approach using 10 urine samples(L = 5 cases and N = 5 cases).Urine differential proteins of BUC,identified by other research groups were obtained by Meta analysis,were combined with the ones verified by our group in this research to establish a urine differential protein database.Interaction network analysis of all proteins in the database was performed online by using STRING database(https://string-db.org/).Single candidate differential protein apolipoprotein E(APOE)was selected and its concentration in urine samples(L=48 cases and N = 36 cases)was tested by enzyme-linked immuno sorbent assay(ELISA).The Optimal Operating Point(OOP)of APOE for LBUC diagnosis was determined by using the Receiver Operating Characteristic(ROC)curve.Clinical value and discriminatory power were evaluated.Results1 A total of 1842 proteins were identified by i TRAQ.Compared with control group,145 proteins including 41 up-regulated proteins and 104 down-regulated proteins were shown differential expression in the LBUC group with a fold change greater than 1.2.Bioinformatics analysis showed those differentially expressed urine proteins were mainly related with cell proliferation,signal transduction pathway,and other functions.2 16 proteins were selected from 67 candidate differentially expressed proteins with a fold change greater than 1.5 to perform MEM analysis,and finally 11 proteins were successfully verified.alpha-1-antitrypsin(A1AT),apolipoprotein E(APOE),alpha-2-macroglobulin(A2MG)and apolipoprotein A-IV(APOA4)were up-regulated while phospholipase D3(PLD3),mannose associated serine protease 2(MASP2),cell-surface antigen heavy chain(4F2),fibulin 2(FBLN2),stromal cell-derived factor 1(SDF1),melanoma inhibitory activity member 3(MIA3)and phosphohistidine phosphatase 14 k Da(PHP14)were down-regulated.3 3 urine differential proteins of BUC including alpha-1-antitrypsin(A1AT),angiogenin(ANG)and apolipoprotein A-I(APOA1)identified by other research groups were obtained by Meta analysis and combined with the 11 proteins verified in this research to establish a urine differential protein database in which 13 urine differential proteins were included.4 The concentration of differential protein APOE in urine samples was tested by ELISA.ROC curve indicated LBUC patients will be well discriminated from the controls by using 0.45 pg/ml as an OOP,with a sensitivity as 81.25% and a specificity as 88.9%.Conclusions1 11 urine differential proteins of LBUC were screened and identified by using a joint strategy of i TRAQ,bioinformatics analysis and MRM.2 By using Meta analysis,3 urine proteins were identified for BUC diagnosis.A urine differential protein database of BUC were established including A1 AT,APOE,A2 MG,APOA4,ANG,APOA1,PLD3,MASP2,4F2,FBLN2,SDF1,MIA3 and PHP14,3 Urine differential protein APOE as a biomarker has potential clinical significance for LBUC diagnosis.Figure 14;Table17;Reference 123... |
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