In the last decade, cancer genomics studies have led to the remarkable revelation that cancer is a much broader and complex disease then initially thought. In parallel, dramatic advances in our ability to design drugs against cancer have created an extensive toolbox of therapeutics. The use of these “targeted” drugs in clinics has met with remarkable successes, but also disappointing failures. Since not all patient tumours are identical, some patients may respond to specific drugs, while others may not. The key, therefore, to enhancing efficacy of anti-cancer drugs is personalized medicine, matching the right patient to the right therapy or again, to pick the right tool to treat each individual patient’s disease. This project proposes to develop qTAP, a transformative diagnostic platform that will provide a global view of an individual patient’s tumour with the goal of identifying the types of drugs which might be most effective at treating their cancer. In addition, and as importantly, this project aims at developing novel classes of drugs that target understudied cancer-causing genes. By using qTAP, Wrana’s team wishes to enable clinicians to design customised treatments involving optimal drug combinations that will provide patients with a more effective cancer therapy to prevent relapse commonly observed in clinics. |
Jeff Wrana Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital Co-Investigators Anne-Claude Gingras Andrei Yudin Alexandre Zlotta Andrew Roughton Azar Azad |