Title |
MicroRNA-410-5p as a potential serum biomarker for the diagnosis of prostate cancer
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Published in |
Cancer Cell International, February 2016
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DOI | 10.1186/s12935-016-0285-6 |
Pubmed ID | |
Authors |
Jiaqi Wang, Huamao Ye, Dandan Zhang, Yijun Hu, Xiya Yu, Long Wang, Changjing Zuo, Yongwei Yu, Guixia Xu, Shanrong Liu |
Abstract |
Prostate cancer (PCa) remains to be a diagnostic challenge due to its variable presentation and the lack of reliable diagnosis tool. MicroRNAs (miRNAs) regulate gene in extensive range of pathophysiologic processes. Plasma miRNAs are ideal biomarkers in heart failure, diabetes and other disease. However, using circulating miRNAs as biomarkers for the diagnosis of PCa is still unknown. 149 PCa patients, 57 healthy controls, and 121 non-cancer patients (benign prostatic hyperplasia and other urinary diseases) were enrolled in this study. The reverse transcription of miRNA and SYBR-Green-based double standards curve miRNA quantitative polymerase chain reactions (qPCR) were used to evaluate the dysregulated miR-410-5p. Receiver operator characteristic (ROC) curve analysis was used to evaluate the diagnostic accuracy of miR-410-5p identified as the alternative biomarker. Circulating miRNA-410-5p (miR-410-5p) level was significantly higher in the PCa patients than in healthy controls or non-cancer patients. ROC curve analysis showed that plasma miR-410-5p was a specific diagnostic biomarker of PCa with an area under curve(AUC) of 0.8097 (95 % confidence interval, 0.7371-0.8823; P < 0.001). The serum miR-410-5p level is a potential biomarker for the diagnosis of PCa. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Canada | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 39 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 10 | 26% |
Student > Ph. D. Student | 7 | 18% |
Student > Bachelor | 4 | 10% |
Researcher | 2 | 5% |
Lecturer | 2 | 5% |
Other | 3 | 8% |
Unknown | 11 | 28% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 12 | 31% |
Medicine and Dentistry | 8 | 21% |
Agricultural and Biological Sciences | 4 | 10% |
Chemistry | 2 | 5% |
Immunology and Microbiology | 1 | 3% |
Other | 2 | 5% |
Unknown | 10 | 26% |