Glioblastoma multiforme (GBM), the most common primary central nervous system neoplasm, is a complex, heterogeneous disease. The recent identification of stem cells in murine tumor xenografts that were capable of recapitulating the tumor phenotype adds a new dimension of complexity to the already challenging treatment of patients with GBMs. Although specific cellular and genetic changes are commonly associated with GBM, the mechanism by which those changes occur may have a significant impact on treatment outcome. Of the many bioinformatics techniques developed in recent years, gene expression profiling has become a commonly used research tool for investigating tumor characteristics, and the development of rationally targeted molecular therapies has also accelerated following the initial success of specifically designed inhibitors in the treatment of malignancies. Despite these advances in research techniques and targeted molecular therapies, however, limited clinical impact has been achieved in the treatment of infiltrative malignancies such as GBMs. Thus, further extension in survival of patients with GBMs may require use of multiple analyses of tumors to develop tailored therapies that reflect the inter- and intratumoral heterogeneity of this disease. In this review, the authors briefly consider the potential use of expression profiling combined with mutation analysis in the development of treatment modalities to address the heterogeneity of this complex tumor phenotype.