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RISING STAR GRANT
A MURINE MODEL FOR EARLY OVARIAN CANCER DETECTION USING CIRCULATING MICRORNA
In preliminary work, we have shown we can detect a type of genetic information known as microRNA in blood samples and that the microRNA profile of women with ovarian cancer is different from women without ovarian cancer. Our model can identify women with ovarian cancer even at Stage I disease, when the chance of cure is greater than 90%. This award will fund our next step in translating our research into an early diagnostic test for ovarian cancer by examining early changes in microRNAs during cancer initiation using a mouse model, where the timing of ovarian cancer development can be precisely controlled. We can then correlate the early microRNA changes in the mouse ovary with changes int he blood microRNAs. These studies will provide the data we need to validate the model using blood samples from women with a high genetic risk of developing ovarian cancer, some of whom unexpectedly had very early stage ovarian cancers at the time of prophylactic surgery to remove their ovaries. Together, these data would provide the scientific basis to proceed with a prospective clinical trial of a microRNA-based test to screen for ovarian cancer.
CLICK HERE to view our Facebook Live featuring Dr. Elias to learn more about his research.
Brigham and Women’s Hospital Press Release, October 31, 2017: 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