We present a hybrid cellular-tumor level model of brain tumor progression. The model describes tumor progression as the collective outcome of individual tumor cells, the behavior of which is governed by the interplay of intracellular signaling pathways (i.e., MAPK pathway) and the spatial-temporal distribution of key biochemical cues (e.g., oxygen, growth factors). The model is deployed to simulate the effect of different schedule-dose combinations of a chemotherapeutic agent (i.e., temozolomide) on tumor growth in murine orthotopic models of glioma. Simulation results are in good quantitative agreement with experimental measurements. In addition, the model is used to predict the outcome of alternative treatment strategies. Model simulations can be helpful for designing more efficient treatment strategies.