Chen Jun, Yongqiang Wang, Lu Fang, Abai Xu, Chong Li, Chuanxia Zhang, Youcheng Lin, Dan An, Xin Chen, Chunxiao Liu, Pei Dong, Yu Fu, Huiling Jiang, Fangjian Zhou, Zhiming Cai, Duo Zhang, Yong Hou, Song Wu, Yuan Yu, Wei Lu, Mingwei Chen, Qiaoling Li, Meng Zhang, Guosheng Yang, and Rui Ye
// Yongqiang Wang 1, 2, * , Yuan Yu 3, * , Rui Ye 3, * , Duo Zhang 3, * , Qiaoling Li 3 , Dan An 3 , Lu Fang 4 , Youcheng Lin 5 , Yong Hou 3 , Abai Xu 5 , Yu Fu 6 , Wei Lu 4 , Xin Chen 1 , Mingwei Chen 4 , Meng Zhang 4 , Huiling Jiang 7 , Chuanxia Zhang 8 , Pei Dong 1 , Chong Li 9 , Jun Chen 10 , Guosheng Yang 6 , Chunxiao Liu 5 , Zhiming Cai 11 , Fangjian Zhou 1 , Song Wu 2, 11 1 Department of Urology, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Guangzhou, 510060, China 2 The Affiliated Luohu Hospital of Shenzhen University, Shenzhen Luohu Hospital Group, Shenzhen 518000, China 3 BGI-Shenzhen, Shenzhen 518083, China 4 Anhui Medical University, Hefei 230032, China 5 Department of Urology, Zhujiang Hospital of Southern Medical University, Guangzhou 510280, China 6 The Second People’s Hospital of Guangdong Province, Guangzhou 510310, China 7 The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China 8 Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China 9 CAS Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 10 The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510630, China 11 Department of Urological Surgery, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen 518000, China * These authors contributed equally to this work Correspondence to: Song Wu, e-mail: doctor_wusong@126.com Fangjian Zhou, e-mail: zhoufj@sysucc.org.cn Keywords: bladder cancer, epigenetics, methylation, biomarkers, qMSP Received: May 07, 2015 Accepted: November 20, 2015 Published: December 19, 2015 ABSTRACT To develop a routine and effectual procedure of detecting bladder cancer (BlCa), an optimized combination of epigenetic biomarkers that work synergistically with high sensitivity and specificity is necessary. In this study, methylation levels of seven biomarkers ( EOMES , GDF15 , NID2 , PCDH17 , POU4F2 , TCF21 , and ZNF154 ) in 148 individuals—which including 58 urothelial cell carcinoma (UCC) patients, 20 infected urinary calculi (IUC) patients, 20 kidney cancer (KC) patients,20 prostate cancer (PC) patients, and 30 healthy volunteers (HV)—were quantified by qMSP using the urine sediment DNA. Receiver operating characteristic (ROC) curves were generated for each biomarker. The combining predictors of possible combinations were calculated through logistic regression model. Subsequently, ROC curves of the three best performing combinations were constructed. Then, we validated the three best performing combinations and POU4F2 in another 72 UCC, 21 IUC, 26 KC and 22 PC, and 23 HV urine samples. The combination of POU4F2/PCDH17 has yielded the highest sensitivity and specificity of 90.00% and 93.96% in all the 312 individuals, showing the capability of detecting BlCa effectively among pathologically varied sample groups.