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Personalized screening for ovarian cancer using circulating miRNA risk profiles
In our original studies funded by Tina’s Wish, we demonstrated that measuring quantities of small genetic material in the blood called microRNA (miRNA) could separate women with ovarian cancer from healthy women or those with benign ovarian tumors. More recently, we used support from Tina’s Wish to define a unique miRNA signature in blood that can establish baseline ovarian cancer risk. This does so by identifying women with mutations in the genes BRCA 1 and BRCA 2 who are at the highest risk but are otherwise healthy. In this new proposal, we will extend these studies 1) to understand how miRNA profiles differ among high-risk and low-risk individuals with ovarian cancer and 2) to migrate these results to a clinical test for use in our prospective clinical trial. To accomplish this, we will use samples from the Centre hospitalier de l’Université de Montréal (CHUM) to explore whether plasma (blood) miRNAs that differ between BRCA1/2 mutation carriers with and without ovarian cancer are distinct from those plasma miRNAs that differ between non-mutation carriers with and without ovarian cancer. Second, we will validate these results using an independent set of samples from the Mass General Brigham Biobank. Finally, we will adapt the test to a smaller miRNA panel that will ultimately be used for the miRNA Detection Study (MiDe Study). This study is our nationwide trial describing the changes in miRNA profiles over long periods of time for women considered to be high-risk for ovarian cancer based on family or genetic history.
To learn more about Dr. Chowdhury’s and Dr. Elias’ work, click here. The MiDe Study (MicroRNA Detection Study) website is now live and enrolling participants at high-risk of ovarian cancer.
Dana-Farber Cancer Institute Winter 2019 Impact Newsletter: DR. DIPANJAN CHOWDHURY RECEIVES ADDITIONAL FUNDING FROM A GENEROUS DANA-FARBER DONOR
Dana-Farber Cancer Institute: NEW BLOOD TEST DEVELOPED TO DIAGNOSE OVARIAN CANCER
eLIFE, October 31, 2017 (FULL STUDY): Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer
December 7, 2023