Evaluation of an Epigenetic Profile for the Detection of Bladder Cancer in Patients with Hematuria

详细信息    查看全文

• 作者：Kim E.M. van Kessel^a ; ^&lowast ; ; ^&dagger ; ; Leander Van Neste^b ; ^c ; ^&dagger ; ; ^&Dagger ; ; Irene Lurkin^a ; ^&lowast ; ; Ellen C. Zwarthoff^a ; ^&lowast ; ; Wim Van Criekinge^c ; ^d ; ^&lowast ; ; ^{wim.vancriekinge@mdxhealth.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：urinary bladder neoplasms ; hematuria ; epigenomics ; diagnosis ; risk
• 刊名：The Journal of Urology
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：195
• 期：3
• 页码：601-607
• 全文大小：494 K

文摘

Many patients enter the care cycle with gross or microscopic hematuria and undergo cystoscopy to rule out bladder cancer. Sensitivity of this invasive examination is limited, leaving many patients at risk for undetected cancer. To improve current clinical practice more sensitive and noninvasive screening methods should be applied.

Materials and Methods

A total of 154 urine samples were collected from patients with hematuria, including 80 without and 74 with bladder cancer. DNA from cells in the urine was epigenetically profiled using 2 independent assays. Methylation specific polymerase chain reaction was performed on TWIST1. SNaPshot™ methylation analysis was done for different loci of OTX1 and ONECUT2. Additionally all samples were analyzed for mutation status of TERT (telomerase reverse transcriptase), PIK3CA, FGFR3 (fibroblast growth factor receptor 3), HRAS, KRAS and NRAS.

Results

The combination of TWIST1, ONECUT2 (2 loci) and OTX1 resulted in the best overall performing panel. Logistic regression analysis on these methylation markers, mutation status of FGFR3, TERT and HRAS, and patient age resulted in an accurate model with 97% sensitivity, 83% specificity and an AUC of 0.93 (95% CI 0.88–0.98). Internal validation led to an optimism corrected AUC of 0.92. With an estimated bladder cancer prevalence of 5% to 10% in a hematuria cohort the assay resulted in a 99.6% to 99.9% negative predictive value.

Conclusions

Epigenetic profiling using TWIST1, ONECUT2 and OTX1 results in a high sensitivity and specificity. Accurate risk prediction might result in less extensive and invasive examination of patients at low risk, thereby reducing unnecessary patient burden and health care costs.