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Ovarian cancer continues to be the most lethal of the gynaecologic malignancies. Every year in Canada alone, about 2300 women will be diagnosed with ovarian cancer.
Because of a lack of reliable early detection methods and poor therapeutic management of recurrent disease, about 1700 of these women will die (2007 Canadian Cancer Statistics . The statistics have not improved in more than a decade.
Our group’s work is based on the concept the translational application of fundamental, well supported ovarian cancer research has the potential to vastly improve the clinical outcome of patients with ovarian cancer.
The idea for establishing the Translational Ovarian Cancer Research Program came from the vision of scientists and clinicians at both the London Regional Cancer Program and The University of Western Ontario.
Over the last several years, partial funding for the program has been generated through London’s Run for Ovarian Cancer. Additional fundraising efforts, spearheaded by the same group, have garnered generous donations to the London Health Sciences Foundation as well.
The Translational Ovarian Cancer Research Program was officially initiated in January 2007 with the recruitment of Dr. Trevor Shepherd as a Translational Oncology Scientist to organize the research efforts of the group.
The Translational Ovarian Cancer Research Group consists of both basic scientists of the Cancer Research Laboratory Program Dr. Trevor Shepherd, Dr. Gabriel DiMattia, and Dr. Jim Koropatnick and clinicians of the Division of Gynaecologic Oncology in the Department of Obstetrics & Gynaecology Dr. Monique Bertrand, Dr.Akira Sugimoto and Dr. Michel Préfontaine at the University of Western Ontario.
Our research efforts will continue to broaden as the group expands to include other research scientists and clinicians.
The Translational Ovarian Cancer Research Program presently includes two major research streams:
The Translational Ovarian Cancer Research Group is focused on gaining a better understanding of ovarian cancer pathogenesis. By simultaneously integrating patient sample analyses and the rapid development of accurate disease models we hope to more quickly impact results at the clinical level.