The program will build on established and new collaborations, including ongoing activities in computational modeling of biological systems in cooperating MIT departments, and will represent a closely integrated collaborative effort between cancer biologists (cell and molecular biologists and geneticists) and computationally sophisticated modelers to analyze the properties and behavior of cancer cells in vitro and in intact animals and to generate refinable and portable computational models of cancer progression. The program will focus on the use of murine models of cancer progression to generate genome-scale data sets on the genes and proteins associated with the various steps in cancer progression. These data sets will be analyzed for reproducible patterns. Filtered data from the in vivo models, as well as from cell culture models derived from them, will be used as substrates for generation of computational models for cellular programs contributing to individual aspects of cancer progression. These will include both cell-intrinsic programs as well as programs responding to inputs to the cancer cells from their surroundings. Areas of initial concentration for modeling will include: cellular responses to growth factors, cell-matrix adhesion and DNA damage as well as cell polarization and migration. An important component of the program will be testing of the computational models by perturbation of the in vivo and cellular model systems by RNA interference and, where appropriate, genetic engineering of the mice harboring the cancer models. This testing will lead to validation and refinement of the computational models. This cycle of data generation and analysis, computational modeling and validation/refinement will be repeated to develop increasingly robust and rich models of cancer cells functioning in their environment. Training and education of interdisciplinary scientists conversant with the different approaches and their effective integration will be an integral part of the program and will include the development of new courses and educational activities to complement those already in place at MIT.
Showing the most recent 10 out of 222 publications
