Optimizing EGFR inhibitor-based therapies in glioblastoma
Principal Investigator: Jann Sarkaria, M.D.
Amplification of EGFR, with or without mutation, occurs in 40 percent of primary glioblastoma multiforme (GBM) tumors, and at least in this subset of tumors, elevated signaling from EGFR presumably plays a central role in the malignant character of these radiation resistant tumors. This relationship between EGFR amplification and malignant behavior has been well-documented, and, therefore, it is not surprising that several clinical trials are investigating the efficacy of EGFR inhibitors in GBM. However, it is not known whether the presence or absence of EGFR amplification is predictive of tumor sensitivity to EGFR-directed therapies.
At Mayo Clinic, 2 Phase II clinical trials are being run through the North Central Cancer Treatment Group (NCCTG) to evaluate the efficacy of small molecule EGFR kinase inhibitors in GBM. Tissue specimens from these trials, evaluating radiation combined with sequential (N0074) or concomitant (N0177) EGFR inhibitor therapy, will be available for correlative studies, as will an extensive GBM tissue archive from patients treated with radiation alone. In addition, we have established a panel of serially transplantable GBM xenografts that maintain the original EGFR amplification status and the histopathologic and invasive features of their derivative GBM tumors.
Using these resources, this project will identify molecular characteristics that predict for response to EGFR inhibitor therapy. We hypothesize that the anti-tumor effects of EGFR inhibitors result from suppression of a select subset of 1 or 2 essential pathways, and that resistance to EGFR inhibitor therapy results from compensatory signaling through these pathways caused by other GBM gene alterations (e.g. PTEN mutation). Thus, accurate prediction of sensitivity to EGFR inhibition may require information regarding the status of several molecular characteristics including EGFR amplification and mutation status. To succeed in identifying a predictive molecular fingerprint for sensitivity to EGFR inhibitor therapy in GBM, the following approach will be used:
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