This goal of this application is to support a Mentored Quantitative Research Career Development Award (K25) for the applicant, Jared Weis, Ph.D., in the field of cancer biology, modeling, and imaging. A career development plan has been developed that includes immersive advanced didactic coursework and laboratory training that is essential to build Dr. Weis's knowledge and skill in cancer biology, both basic science and translational. This career development plan will also build upon the essential skills required of an independent investigator: grant writing, mentoring, scientific review, and research ethics. During the training, Dr. Weis will acquire expertise in cancer cellular/molecular biology and translational research techniques. Combined with the applicant's previous formal training in biomedical engineering, including computational modeling and imaging sciences, this career development award will ensure transition into independent investigator status researching multi-scale cancer mechanobiology with a particular emphasis in mathematical oncology/computational modeling. A multidisciplinary committee of exceptional investigators in fields of breast cancer biology, mathematical modeling, biostatistics, cancer mechanobiology, and imaging science has been formed and will guide Dr. Weis's career development in cancer research. The proposed career development plan will provide protected time to gain valuable cancer biology research knowledge and experience and enable Dr. Weis to make important impacts in oncology early in his career as an independent investigator. In this application, the proposed work represents an innovative and highly significant approach that seeks to investigate the development and validation of a cohesive multi-scale biomechanical mathematical modeling approach to link the cellular level mechanobiology interactions between cancer cells and extracellular matrix that direct cancer cell proliferation, motility, and aggressiveness, with clinically relevant non-invasive imaging data. The approach utilizes innovative image-based methods for measuring mechanical stiffness combined with mathematical models of tumor cell growth and response to treatment.
The specific aims reflect a comprehensive study that seeks to validate modeling approaches and quantitatively characterize the association between mechanics and cancer, integrating information derived from multiple length scales, from the cellular level to the macroscopic level and includes: in vitr cell culture studies (Aim 1), in vitro bioreactor studies (Aim 2), and in vivo pre-clinical cancer models (Aim 3). If successful, the methods described in this proposal will provide a sound biomechanical mathematical modeling framework that is initialized and constrained by clinically relevant non-invasive imaging (elastography and diffusion-weighted MRI) that parameterizes key cellular level information influenced by mechanical signaling. The parameterization is then utilized for efforts directed at predictive modeling of tumor growth and response to therapy, sensitive to tumor mechanics-induced aggressiveness.
Mechanical signaling is strongly implicated in contributing to tumor progression and therapeutic resistance. This application investigates the use of image-based mathematical models to quantify and characterize the association between mechanics and cancer at multiple length scales, spanning from cellular to tissue scale. The overall goal of this application is to develop biomechanical mathematical models that guide the use of clinically relevant non-invasive imaging data to identify cellular level mechanobiology properties of cancer and predict responsiveness to therapy.
