Purpose: Gliomas, a genetically heterogeneous group of primary central nervous system tumors, continue to pose a significant clinical challenge. Discovery of chromosomal rearrangements involving kinase genes has enabled precision therapy, and improved outcomes in several malignancies.
Experimental Design: Positing that similar benefit could be accomplished for patients with brain cancer, we evaluated The Cancer Genome Atlas (TCGA) glioblastoma dataset.
Background: Emerging immunotherapeutic strategies for the treatment of glioblastoma (GBM) such as dendritic cell (DC) vaccines, heat shock proteins, peptide vaccines, and adoptive T-cell therapeutics, to name a few, have transitioned from the bench to clinical trials. With upcoming strategies and developing therapeutics, it is challenging to critically evaluate the practical, clinical potential of individual approaches and to advise patients on the most promising clinical trials.
Methods: The authors propose a system to prioritize such therapies in an organized and data-driven fashion.