The genomic landscapes of many common human cancers have been deciphered and many of the driver gene mutations that are responsible for cancer initiation and progression have been identified. An important question to address now is when do these driver mutations occur during the evolution of cancers and does the order in which they appear matters? Although the identity of the driver mutations and their role in various cancers including primary malignant brain cancer is not debated, the order in which they occur and the consequences of any given order on tumor physiology are much less studied. Studies on the temporal occurrence of driver gene mutations have been a critical barrier to our understanding of molecular mechanisms of therapeutic resistance and sensitivity. This project proposes to directly study the consequences of sequential driver gene mutations on therapeutic treatment sensitivity using glioblastoma multiforme (GBM) as a cancer model. In this application, we will use genetically engineered mouse models of GBM that we developed based on the most common groups of driver gene mutations;overexpression/activation of EGFR together with loss of the Cdkn2a tumor suppressor gene with and without loss of PTEN and overexpression/activation of PDGFR-? together with loss of p53 with and without loss of PTEN. Preliminary studies using our EGFR;Cdkn2a-/- mice indicate that the timing of PTEN loss plays a significant role in the molecular wiring of the tumors and their responses to EGFR inhibition. We propose to reveal how the timing of PTEN loss influences the utilization of downstream pathways within the EGFR and PDGFR-? signaling networks and dictate the molecular wiring of the resulting tumor cells (Aim 1). The goal of these studies is to reveal previously unexplored molecular vulnerabilities for therapeutic strategies. We also propose to study how the temporal loss of PTEN affects mechanisms of molecular re-wiring during therapeutic intervention (Aim 2). The research presented here is very important because GBM with seemingly identical genotypes (e.g. mutant for PTEN) may intrinsically behave differently when exposed to therapeutics due to the order with which driver gene mutations arose. A molecular understanding of this process will directly lead to better stratification of patients and choice of suitable treatments.
Cancers evolve through the accumulation of driver gene mutations over time. In this application, we will study the temporal effects of driver gene mutations occurrence on the global wiring of tumor cells and their responses to therapeutic intervention. We will use clinically accurate genetically engineered mouse models of glioblastoma multiforme in which we can induce in a temporal fashion the loss of a key tumor suppressor gene and study the consequences of this loss on therapeutic treatments.