Jens Meiler is co-founder of Vanderbilt University’s Program in Personalized Structural Biology / Precision Medicine ( https://my.vanderbilt.edu/psbp/ ). This trans-institutional initiative applies computational techniques in structural biology to answer mechanistic questions directly impacting the care of individual patients.

Tumor cells carry a unique set of mutations in its genome that alter normal cell functions. For example, some mutations may accelerate cell growth, while others may prevent cells from dying when the cease to function properly. The challenge is that these mutations are “personal” to the tumor and patient; i.e., not all types of breast cancer carry the same set of mutations, and as a result, different patients have a different, personal set of mutations. For some cancer causing mutations effective treatment strategies have been established and are routinely applied. However, all too often tumors harbor novel mutations - so called “Variants of Unknown Significance” - for which the most effective strategy is unknown. In this scenario, doctors must make difficult choices, and in many cases, they are forced to try multiple treatments after common strategies fail. This process can be time-consuming, wearing, and demoralizing for the patient. This is an area of unmet need where cancer investigators and providers require guidance as to the implications of those variants for cancer care.

The goal of our research is to provide doctors with key, additional information to choose best treatment strategies for breast cancers with novel mutations of unknown significance. Specifically, we construct a three-dimensional, structural model of the cancer mutation in the computer, study the mutation’s consequences on cell function, and computationally evaluate possible treatments. This information will enable physicians to develop evidence-based personalized treatment strategies.