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 reports 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.
Germline prognostic markers and gene-environment interaction with smoking for urinary bladder cancer
It has been argued improvements in clinical management of urinary bladder cancer would provide most benefit to both patients and health systems. However, the inclusion of genetic information for disease prognostication has been challenging due to inconsistent findings and overall complexity of genetic variation and observed phenotypes. We aim to further explore the issue by investigating whether there are mutations associated with certain tumour and patient characteristics at the time of diagnosis (that can directly affect prognosis) or cancer recurrence itself. As it has been observed germline variation may have a different effect for smokers and non-smokers, we also aim to investigate whether there is evidence for gene-environment interaction with smoking for baseline characteristics of urinary bladder cancer and/or disease recurrence.
The project is set to last for until September 2019 and will provide evidence that may be further used to calibrate existing urinary bladder cancer management approaches.
|Lead investigator:||Nadezda Lipunova|
|Lead institution:||University of Birmingham|