Glioblastoma multiforme (GBM) is among the most aggressive and challenging human cancers, accounting for 50-60% of primary brain tumors in adults (Mohin, 2006) and associated with a median survival of 10-12 months after diagnosis (Alford, 1991). Aside from its high resistance to conventional cancer treatments such as radiotherapy (Kleinsmith, 2006) and vulnerable region of genesis, the invasiveness of GBM tumor cells is primarily what has rendered it a very deadly disorder and why even seemingly complete surgical resection of the tumor fails uniformly. In vivo experimental results have verified this characteristic, as glioma cells have been identified throughout the central nervous system within 7 days of tumor xenograft implantation in a rat brain (Silbergeld, 1997).
The current presentation will focus on our efforts to capture these effects more effectively in a relevant mathematical description and implement current treatment methods. Specifically, a hybrid discrite/continuous model of a glioblastoma multiforme (GBM) tumor that was developed in (Vital-Lopez, 2010) was modified to include haptotactic migration strategies and radiotherapeutic treatment methods. Haptotactic migration strategies in the model showed little improvement in overall tumor growth and this component likely will involve further modification with the parameters describing the dynamics of the coupled effects of extracellular matrix degradation and repair. Radiotherapy methods were analyzed against typical fractionation schemes with and without quiescent cell killing assumed and the model was tested against fractionation schemes in vivo as well. Assumption of quiescent cell killing provided the greatest fidelity with other models, but neither method accurately depicted the relative effect of high-dose fractionation schemes against other schemes of equal cumulative dosage. Lastly, analysis of the model against combination therapies in vivo confirmed a synergistic effect with concomitant temozolomide and radiotherapy and provides a template for future work investigating specific synergism parameters.
Alford, E. C., et al. (1991). The Pathology of the Aging Human Nervous System. Philadelphia: Lea and Febiger
Kleinsmith, L. J., et al. (2006). Principles of Cancer Biology. San Francisco: Pearson Education.
Mohin, G., et al. (2006). Glioblastoma Multiforme: advances in postsurgical management. Community Oncology , 3, 678-684.
Silbergeld, D., et al. (1997). Isolation and characterization of human malignant glioma cells from histologically normal brain. Journal of Neurosurgery , 86, 525-531.
Vital-Lopez, F., et al. (2010). Modeling the effect of chemotaxis on glioblastoma tumor progression. American Institute of Chemical Engineers Journal , 57, 778-792.