Identification and validation of AIB1 and EIF5A2 for noninvasive detection of bladder cancer in urine samples
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Bang-Fen Zhou1,2,*, Jin-Huan Wei3,*, Zhen-Hua Chen3,*, Pei Dong4, Ying-Rong Lai5, Yong Fang1, Hui-Ming Jiang1,6, Jun Lu1, Fang-Jian Zhou4, Dan Xie1, Jun-Hang Luo3, Wei Chen3
1Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
2Department of Urology, Hainan Provincal Nongken General Hospital, Haikou, Hainan, China
3Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
4Department of Urology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
5Department of Pathology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
6Department of Urology, Meizhou People’s Hospital, Guangdong, China
*These authors have contributed equally to this work
Dan Xie, email: email@example.com
Jun-Hang Luo, email: firstname.lastname@example.org
Wei Chen, email: email@example.com
Keywords: bladder cancer, AIB1, EIF5A2, diagnostic model, urine biomarkers
Received: October 23, 2015 Accepted: March 28, 2016 Published: May 17, 2016
We previously demonstrated that amplified in breast cancer 1 (AIB1) and eukaryotic initiation factor 2 (EIF5A2) overexpression was an independent predictor of poor clinical outcomes for patients with bladder cancer (BCa). In this study, we evaluated the usefulness of AIB1 and EIF5A2 alone and in combination with nuclear matrix protein 22 (NMP22) as noninvasive diagnostic tests for BCa. Using urine samples from 135 patients (training set, controls [n = 50] and BCa [n = 85]), we detected the AIB1, EIF5A2, and NMP22 concentrations using enzyme-linked immunosorbent assay. We applied multivariate logistic regression analysis to build a model based on the three biomarkers for BCa diagnosis. The diagnostic accuracy of the three biomarkers and the model were assessed and compared by the area under the curve (AUC) of the receiver operating characteristic. We validated the diagnostic accuracy of these biomarkers and the model in an independent validation cohort of 210 patients. In the training set, urinary concentrations of AIB1, EIF5A2, and NMP22 were significantly elevated in BCa. The AUCs of AIB1, EIF5A2, NMP22, and the model were 0.846, 0.761, 0.794, and 0.919, respectively. The model had the highest diagnostic accuracy when compared with AIB1, EIF5A2, or NMP22 (p < 0.05 for all). The model had 92% sensitivity and 92% specificity. We obtained similar results in the independent validation cohort. AIB1 and EIF5A2 show promise for the noninvasive detection of BCa. The model based on AIB1, EIF5A2, and NMP22 outperformed each of the three individual biomarkers for detecting BCa.
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