Clinical Research Papers:
Development and prospective multicenter evaluation of the long noncoding RNA MALAT-1 as a diagnostic urinary biomarker for prostate cancer
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Fubo Wang1,*, Shancheng Ren1,*, Rui Chen1,*, Ji Lu1, Xiaolei Shi1, Yasheng Zhu1, Wei Zhang1, Taile Jing1, Chao Zhang1, Jian Shen1,2, Chuanliang Xu1, Huiqing Wang1, Haifeng Wang1, Yang Wang3, Bin Liu1, Yaoming Li1, Ziyu Fang1, Fei Guo1, Meng Qiao1, Chengyao Wu1, Qiang Wei4, Danfeng Xu5, Dan Shen1, Xin Lu1, Xu Gao1, Jianguo Hou1 and Yinghao Sun1
1 Department of Urology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China
2 Department of Urology, Changshu NO. 2 People’s Hospital, Changshu, Jiangsu Province, China
3 Department of Pathology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China
4 Department of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
5 Department of Urology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China
* These authors contributed equally to this work
Yinghao Sun, email:
Keywords: prostate cancer, urine, biomarker, prostate biopsy, PSA, MALAT-1
Received: August 24, 2014 Accepted: November 04, 2014 Published: November 04, 2014
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.
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