Glioblastoma is unfortunately both the most common and the most malignant form of brain cancer comprising approximately 50% of all brain tumors. Treatment for glioblastoma is multimodal in nature, consisting of surgical resection of the main tumor mass followed by concomitant chemo- and radio- therapy. Glioblastoma is a highly infiltrative tumor with cancer cells invading far into healthy adjacent tissue highlighting the nee for efficient chemotherapy to target these diffusive cells. Despite aggressive treatment, resistance and recurrence are hallmarks of the disease, underscoring the need to identify mechanisms by which glioblastoma cells acquire resistance to therapy. Frontline chemotherapy for glioblastoma consists of temozolomide, a DNA mono-alkylating agent. On average, TMZ extends survival by only one to two months, with recurrent glioblastoma showing a strong resistance to the alkylating agent. The p53 transcription factor is commonly described as the guardian of the genome due to its vast anti-tumorigenic activities. Although mutated in 35% of glioblastoma tumors its role as a prognostic indicator in the disease is not well defined. Recently, it has been suggested that p53 activity may protect glioblastoma cells from DNA damaging agents including temozolomide and may contribute to chemoresistance in p53 proficient tumors. However, as resistance to temozolomide also occurs in p53 deficient tumors, we hypothesize that the genomic and cellular signaling network alterations leading to temozolomide resistance are very different in p53 proficient and p53 deficient cells. In this study I will examine the response of glioblastoma cells to temozolomide in p53 proficient and p53 deficient contexts. Using computational modeling, cellular signaling network measurements, including quantitative immunoblotting and transcriptional profiling, will be compared to proliferation, cell cycle, senescence and cell death measurements to identify correlations between pathways responsive to damage and the phenotypic response of cells to temozolomide treatment. Furthermore, these techniques will be applied to temozolomide resistant cell lines produced from p53 proficient and p53 deficient glioblastoma cells to investigate how the signaling network changes as a result of acquired chemoresistance. Finally, perturbations at the molecular level of pathways predicted from our model to lead to sensitivity or resistance to temozolomide will identify targets most likely to alter therapeutic outcome.
Glioblastoma is unfortunately both the most common and most malignant form of brain cancer, which, despite aggressive treatment, displays a strong radio- and chemo-resistant phenotype. This proposal focuses on identifying mechanisms of cellular response and resistance to temozolomide, the frontline chemotherapeutic used in glioblastoma treatment, in the context of p53 proficient and p53 deficient glioblastoma cells. Using computational, systems biology and molecular biology approaches we aim to identify novel combinatorial therapies to potentiate temozolomide toxicity as well as ways to target resistant disease.