Molecular analysis of glioblastoma: pathway profiling and its implications for patient therapy

Abstract

Technological advances in the ability to analyze patterns of gene expression and signal transduction pathway activation are improving our understanding of cancer. Previously unrecognized molecular subsets and pathway profiles that convey predictive and prognostic information about individual cancer patients are being identified. Patients with glioblastoma, the most common malignant primary brain tumor of adults, stand to benefit considerably from these advances. Recent data suggest that morphologically indistinguishable glioblastomas have distinct classes of causal oncogene activation, and that these subclasses may be targetable by oncogene/signaling pathway specific therapies. Oncogene/signaling pathway inhibitors show great promise for the treatment of patients with some types of cancer, but their clinical application for glioblastoma has been severely limited by an inability to determine which inhibitor is most likely to benefit a specific patient. Identifying biologically relevant molecular subsets of glioblastoma and detecting pathway profiles that can be used to guide patient therapy are likely to result in significant improvement in the survival of glioblastoma patients.