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A multiplex model of combining gene-based, protein-based, and metabolite-based with positive and negative markers in urine for the early diagnosis of prostate cancer.
MedLine Citation:
PMID:  20957673     Owner:  NLM     Status:  In-Data-Review    
BACKGROUND: Multiplex urine-based assay emerged outperforms single biomarker (e.g., prostate-specific antigen, PSA) for predicting prostate cancer (CaP), whereas its combined mode has to be fully optimized. Our aim is to determine whether a strategy of combining gene-based, protein-based, metabolite-based with positive, negative makers in urine could optimize a multiplex model for detecting CaP.
METHODS: Using quantitative PCR, Western blot, and liquid chromatography-mass spectrometry, expression patterns of PCA3, TMPRSS2: ERG, Annexin A3, Sarcosine, and urine PSA were evaluated in urine samples from 86 untreated patients with CaP and 45 patients with no evidence of malignancy. Multivariate logistic regression analysis was used to generate a final model and receiver-operating characteristic (ROC) analysis and special bootstrap software to assess diagnostic performance of tested variables.
RESULTS: The expression patterns of PCA3, TMPRSS2: ERG, Annexin A3, Sarcosine, and a panel including these biomarkers were significant predictors of CaP both in patients with PSA 4-10 ng/ml and in all patients (all P < 0.05). Employing ROC analysis, the area under the curves of the panel in these both cohorts were 0.840 and 0.856, respectively, which outperform that of any single biomarker (PCA3: 0.733 and 0.739; TMPRSS2: ERG: 0.720 and 0.732; Annexin A3: 0.716 and 0.728; Sarcosine: 0.659 and 0.665, respectively).
CONCLUSIONS: Compared with single biomarker, the multiplex model including PCA3, TMPRSS2: ERG, Annexin A3 and Sarcosine adds even more to the diagnostic performance for predicting CaP. Further validation experiments and optimization for the strategy of constructing this model are warranted. Prostate 71:700-710, 2011. © 2010 Wiley-Liss, Inc.
Da-Long Cao; Ding-Wei Ye; Hai-Liang Zhang; Yao Zhu; Yi-Xuan Wang; Xu-Dong Yao
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Publication Detail:
Type:  Journal Article     Date:  2010-10-18
Journal Detail:
Title:  The Prostate     Volume:  71     ISSN:  1097-0045     ISO Abbreviation:  Prostate     Publication Date:  2011 May 
Date Detail:
Created Date:  2011-10-03     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8101368     Medline TA:  Prostate     Country:  United States    
Other Details:
Languages:  eng     Pagination:  700-10     Citation Subset:  IM    
Copyright Information:
Copyright © 2010 Wiley-Liss, Inc.
Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
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