From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response

by Jill A. Gallaher, Susan C. Massey, Andrea Hawkins-Daarud, Sonal S. Noticewala, Russell C. Rockne, Sandra K. Johnston, Luis Gonzalez-Cuyar, Joseph Juliano, Orlando Gil, Kristin R. Swanson, Peter Canoll, Alexander R. A. Anderson Glioblastomas are aggressive primary brain tumors known for their inter- and intratumor heterogeneity. This disease is uniformly fatal, with intratumor heterogeneity the major reason for treatment failure and recurrence. Just like the nature vs nurture debate, heterogeneity can arise from intrinsi c or environmental influences. Whilst it is impossible to clinically separate observed behavior of cells from their environmental context, using a mathematical framework combined with multiscale data gives us insight into the relative roles of variation from different sources. To better understand t he implications of intratumor heterogeneity on therapeutic outcomes, we created a hybrid agent-based mathematical model that captures both the overall tumor kinetics and the individual cellular behavior. We track single cells as agents, cell density on a coarser scale, and growth factor diffusion an d dynamics on a finer scale over time and space. Our model parameters were fit utilizing serial MRI imaging and cell tracking data from ex vivo tissue slices acquired from a growth-factor driven glioblastoma murine model. When fitting our model to serial imaging only, there was a spectrum of equally -good parameter fits corresponding to a wide range of phenotypic be...
Source: PLoS Computational Biology - Category: Biology Authors: Source Type: research