Kim E M van Kessel1, Leander Van Neste2, Irene Lurkin1, Ellen C Zwarthoff1, Wim Van Criekinge3. 1. Department of Pathology, Erasmus Medical Center, Rotterdam, The Netherlands. 2. Department of Pathology, GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands; MDxHealth, Inc., Irvine, California. 3. MDxHealth, Inc., Irvine, California; Laboratory of Bioinformatics and Computational Genomics, Ghent University, Ghent, Belgium. Electronic address: wim.vancriekinge@mdxhealth.com.
Abstract
PURPOSE: 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.
PURPOSE: 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.
Authors: Andrew Feber; Pawan Dhami; Liqin Dong; Patricia de Winter; Wei Shen Tan; Mónica Martínez-Fernández; Dirk S Paul; Antony Hynes-Allen; Sheida Rezaee; Pratik Gurung; Simon Rodney; Ahmed Mehmood; Felipe Villacampa; Federico de la Rosa; Charles Jameson; Kar Keung Cheng; Maurice P Zeegers; Richard T Bryan; Nicholas D James; Jesus M Paramio; Alex Freeman; Stephan Beck; John D Kelly Journal: Clin Epigenetics Date: 2017-01-31 Impact factor: 6.551
Authors: Mohamad M Kronfol; Mikhail G Dozmorov; Rong Huang; Patricia W Slattum; Joseph L McClay Journal: Expert Rev Precis Med Drug Dev Date: 2017-01-31
Authors: Douglas G Ward; Laura Baxter; Naheema S Gordon; Sascha Ott; Richard S Savage; Andrew D Beggs; Jonathan D James; Jennifer Lickiss; Shaun Green; Yvonne Wallis; Wenbin Wei; Nicholas D James; Maurice P Zeegers; K K Cheng; Glenn M Mathews; Prashant Patel; Michael Griffiths; Richard T Bryan Journal: PLoS One Date: 2016-02-22 Impact factor: 3.240