The past two decades of cancer research have given rise to a number of therapies and diagnostic tools tailored for more personalized treatments. These clinical tools have helped to slow disease progression in some cancers and have helped clinicians predict who has a higher likelihood of responding to a given therapy, thus paving the way to the era of personalized medicine. However, clinicians still face a group of cancer patients who either do not respond well to any existing therapies, or sooner or later experience reappearance of tumors that have become resistant to therapies to which they previously responded. These are the cases that account for the actual cancer related mortality rate that has not substantially improved within the past decades. Using breast cancer as an example, we hypothesize that there exist yet to be identified cellular mechanisms that define patient poor prognosis. To test our hypothesis, we first apply computational approaches to publicly available clinical databases to identify things that may make the tumors more aggressive, more likely to spread, and/or more resistant to existing therapies. Then, we vigorously study these cancer causing factors in mice. Thus, the proposed research is aimed at both discovering novel targets against aggressive subtypes of breast cancer that are currently lethal, and at identifying and validating potentially effective treatment strategies against these tumors. Mouse cancer models are the most advanced laboratory animal models available to test novel therapeutic concepts, and thus the successful execution of the proposed research has the potential for contributing to significantly lowering the breast cancer mortality rate.
|Effective start/end date||9/1/17 → 8/31/18|
- Northwestern Memorial Hospital (NMH 11 Exhibit B.10 Signed 10/04/17)