Somatic alterations in brain tumors

Brain Tumors: Development, Drug Resistance, and Sensitization - An Epigenetic Approach

In this article, we describe contrasting developmental aspects of paediatric and adult brain tumours. We hypothesize that the formation of cancer progenitor cells, for both paediatric and adult, could be due to epigenetic events. However, the progression of adult brain tumours selectively involves more mutations compared to paediatric tumours. We further discuss epigenetic switches, comprising both histone modifications and DNA methylation, and how they can differentially regulate transcription and expression of oncogenes and tumour suppressor genes. Next, we summarize the currently available therapies for both types of brain tumours, explaining the merits and failures leading to drug resistance. We analyse different mechanisms of drug resistance and the role of epigenetics in this process. We then provide a rationale for combination therapy, which includes epigenetic drugs. In the end, we postulate a concept which describes how a combination therapy could be initiated. The timing, doses, and order of individual drug regimens will depend on the individual case. This type of combination therapy will be part of a personalized medicine which will differ from patient to patient.

Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations

Large-scale sequencing of cancer genomes has uncovered thousands of DNA alterations, but the functional relevance of the majority of these mutations to tumorigenesis is unknown. We have developed a computational method, called Cancer-specific High-throughput Annotation of Somatic Mutations (CHASM), to identify and prioritize those missense mutations most likely to generate functional changes that enhance tumor cell proliferation. The method has high sensitivity and specificity when discriminating between known driver missense mutations and randomly generated missense mutations (area under receiver operating characteristic curve, >0.91; area under Precision-Recall curve, >0.79). CHASM substantially outperformed previously described missense mutation function prediction methods at discriminating known oncogenic mutations in P53 and the tyrosine kinase epidermal growth factor receptor. We applied the method to 607 missense mutations found in a recent glioblastoma multiforme sequencing study. Based on a model that assumed the glioblastoma multiforme mutations are a mixture of drivers and passengers, we estimate that 8% of these mutations are drivers, causally contributing to tumorigenesis.