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

// Fubo Wang 1,* , Shancheng Ren 1,* , Rui Chen 1,* , Ji Lu 1 , Xiaolei Shi 1 , Yasheng Zhu 1 , Wei Zhang 1 , Taile Jing 1 , Chao Zhang 1 , Jian Shen 1,2 , Chuanliang Xu 1 , Huiqing Wang 1 , Haifeng Wang 1 , Yang Wang 3 , Bin Liu 1 , Yaoming Li 1 , Ziyu Fang 1 , Fei Guo 1 , Meng Qiao 1 , Chengyao Wu 1 , Qiang Wei 4 , Danfeng Xu 5 , Dan Shen 1 , Xin Lu 1 , Xu Gao 1 , Jianguo Hou 1 and Yinghao Sun 1 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 Correspondence: 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 Abstract 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.