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Development and prospective multicenter evaluation of the long noncoding RNA MALAT-1 as a diagnostic urinary biomarker for prostate cancer

The current strategy for diagnosing prostate cancer (PCa) is mainly based on the serum prostate-specific antigen (PSA) test. However, PSA has low specificity and has led to numerous unnecessary biopsies. We evaluated the effectiveness of urinary metastasis-associated lung adenocarcinoma transcript 1...

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Detalles Bibliográficos
Autores principales: Wang, Fubo, Ren, Shancheng, Chen, Rui, Lu, Ji, Shi, Xiaolei, Zhu, Yasheng, Zhang, Wei, Jing, Taile, Zhang, Chao, Shen, Jian, Xu, Chuanliang, Wang, Huiqing, Wang, Haifeng, Wang, Yang, Liu, Bin, Li, Yaoming, Fang, Ziyu, Guo, Fei, Qiao, Meng, Wu, Chengyao, Wei, Qiang, Xu, Danfeng, Shen, Dan, Lu, Xin, Gao, Xu, Hou, Jianguo, Sun, Yinghao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4294360/
https://www.ncbi.nlm.nih.gov/pubmed/25526029
Descripción
Sumario:The current strategy for diagnosing prostate cancer (PCa) is mainly based on the serum prostate-specific antigen (PSA) test. However, PSA has low specificity and has led to numerous unnecessary biopsies. We evaluated the effectiveness of urinary metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1), a long noncoding RNA, for predicting the risk of PCa before biopsy. The MALAT-1 score was tested in a discovery phase and a multi-center validation phase. The predictive power of the MALAT-1 score was evaluated by the area under receiver operating characteristic (ROC) curve (AUC) and by decision curve analysis. As an independent predictor of PCa, the MALAT-1 score was significantly higher in men with a positive biopsy than in those with a negative biopsy. The ROC analysis showed a higher AUC for the MALAT-1 score (0.670 and 0.742) vs. the total PSA (0.545 and 0.601) and percent free PSA (0.622 and 0.627) in patients with PSA values of 4.0-10 ng/ml. According to the decision curve analysis, using a probability threshold of 25%, the MALAT-1 model would prevent 30.2%-46.5% of unnecessary biopsies in PSA 4–10 ng/ml cohorts, without missing any high-grade cancers. Our results demonstrate that urine MALAT-1 is a promising biomarker for predicting prostate cancer risk.