External Replication of Urinary Bladder Cancer Prognostic Polymorphisms in the UK Biobank

• Main Authors: Nadezda Lipunova, Anke Wesselius, Kar K. Cheng, Frederik J. van Schooten, Jean-Baptiste Cazier, Richard T. Bryan, Maurice P. Zeegers
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2019-10-01
• Series: Frontiers in Oncology
• Subjects: bladder cancer; SNP; replication; UK Biobank; prognosis
• Online Access: https://www.frontiersin.org/article/10.3389/fonc.2019.01082/full

Introduction: Multiple studies have reported genetic associations with prognostic outcomes of urinary bladder cancer. However, the lack of replication of these associations prohibits establishing further evidence-based research directions. Moreover, there is a lack of independent bladder cancer patient samples that contain prognostic measures, making genetic replication analyses even more challenging.Materials and Methods: We have identified 1,534 eligible patients and used data on Hospital Episode Statistics in the UK Biobank to model variables of otherwise non-collected events on bladder cancer recurrence and progression. Data on survival was extracted from the Death Registry. We have used SNPTEST software to replicate previously reported genetic associations with bladder cancer recurrence (N = 69), progression (N = 23), survival (N = 53), and age at the time of diagnosis (N = 20).Results: Using our algorithm, we have identified 618 recurrence and 58 UBC progression events. In total, there were 209 deaths (106 UBC-specific). In replication analyses, eight SNPs have reached nominal statistical significance (p < 0.05). Rs2042329 (CWC27) for UBC recurrence; rs804256, rs4639, and rs804276 (in/close to NEIL2) for NMIBC recurrence; rs2293347 (EGFR) for UBC OS; rs3756712 (PDCD6) for NMIBC OS; rs2344673 (RGS5) for MIBC OS, and rs2297518 (NOS2) for UBC progression. However, none have remained significant after adjustments for multiple comparisons.Discussion: External replication in genetic epidemiology is an essential step to identify credible findings. In our study, we identify potential genetic targets of higher interest for UBC prognosis. In addition, we propose an algorithm for identifying UBC recurrence and progression using routinely-collected data on patient interventions.