While substantial progress has been made in understanding different cancers (how they evolve, how they signal) and while new treatments continue to come into the marketplace, we continue to learn that there is great heterogeneity in most tumors and that the heterogeneity may increase as patients undergo treatment and the tumor figures out ways (evolves) to get around treatments.Analyzing genomic data is one way we can uncover what is happening specifically in a patient's tumor, what key driver genes are mutated, what signaling pathways are altered, and then whether we can better match a more appropriate treatment to a given patient's condition.
Our Personalized Cancer Therapy program explores the use of genomic data in cancer patients and sophisticated predictive models of a given type of cancer to inform on treatments that may be very specific to the exact type of cancer a given patient has.
In this program we are sequencing the tumor DNA of patients, their "normal" DNA (as passed on by their mothers and fathers), and RNA in the tumor. This tells us what changes in the patient's tumor are specific to the tumor and so candidates for causing the progression of the cancer or resistance to drugs. These data are then interpreted in the context of all the available data for the given type of cancer to then inform on the possible treatment paths for the given patient. This is a precision medicine approach to cancer.
In summary, our approach is:
- Collecting data
- Building a network model
- Making clinical predictions on potential therapeutic options
- Delivering that information to the clinician/physician to inform treatment
New York Genome Center: Mount Sinai Cancer Tumor Study Seeks to Nail Moving Targets (3/13/13)