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Approved research

Evaluating Biomarkers in Predicting Ovarian Cancer Risk

Principal Investigator: Dr Shelley Tworoger
Approved Research ID: 26189
Approval date: June 18th 2019

Lay summary

Our research aims to evaluate various biomarkers and their roles of predicting ovarian cancer risk. Ovarian cancer has the highest mortality rate among gynecological cancers with approximately 50% patients dying within five-year of diagnosis. Therefore, identifying factors associated with ovarian cancer development, including novel biomarkers, can identify new prevention target. Previous studies suggested critical biomarkers, including CRP and sex hormones, are associated with ovarian risk. Therefore, it is meaningful to use U.K. Biobank to confirm these biomarkers and more importantly, to identify new biomarkers, which can be used to evaluate risk of ovarian cancer in the general population. Currently, early detection for ovarian cancer screening is not recommended at population level, as current screening tools (transvaginal ultrasound and CA-125 blood test) have limitations. Thus, prevention becomes critical. Identifying new biomarkers that predict ovarian cancer risk may help identify women at high risk of ovarian cancer who could benefit from targeted prevention as well as open up new opportunities for chemo-prevention, which ultimately could be implemented in future health settings. U.K. Biobank provides a unique opportunity on a large scale with large study populations. Our research will benefit the public by improving women's health. We will investigate association between biomarkers assessed in U.K. Biobank full cohort and risk of ovarian cancer, just using this dataset. Further, our group is leading the Ovarian Cancer Cohort Consortium (OC3), a collaboration of 27 cohorts with more than 8000 ovarian cancer cases, nearly 2000 of which have pre-diagnosis blood samples. Our long-term goal would be to include U.K. Biobank as a cohort in OC3, which is crucial to evaluate biomarkers and other risk factors by tumor subtypes. For example, we are currently doing a pooled analysis of CRP across studies with previously measured letters. We further aim to use the genomic data from U.K. Biobank to examine the association between biomarker levels, risk factors in conjunction with individual genomic profile by conducting Mendelian randomization and mediation analysis to further enrich our understanding about relevant biomarkers in relation to ovarian cancer.