Glioma is the most common and deadly disease affecting the CNS. Current projections suggest 22,000 new cases annually, of which 13,000 will be Glioblastoma Multiforme, which is universally fatal. Despite over 60 years of research, there have been no significant improvements to patient outcome. More recently, high throughput molecular sequencing technology has open the field of genomics and big data, in the hopes of providing novel insight to the disease and potential therapeutic inroads. However, these efforts have largely served to refine diagnosis rather than improve patient prognosis. In an effort to translate the wealth of patient genomics information beyond identifying novel informatics trends, our program seeks to biologically functionalize genomics information. More specifically, we have developed tools and approaches that overcome the pragmatic hurdles of traditional methods. We have taken our previously developed in utero electroporation- glioma model and added barcode targeting next generation sequencing, resulting in a fully in vivo, non-viral screening system to test at least 50 different genetic factors. In advancing forward, we seek to: 1) further pursue our previous findings to understand the molecular mechanisms driving the phenomenon we?ve observed, 2) advance and upgrade our methods to meet the needs of other systems, and 3) apply our approach to investigate glioma-associated epilepsy, an associated co-morbidity. Our larger initiative in functional genomics will: 1) provide new tools and methods for screening and testing genetic anomalies found in glioma, 2) provide molecular insight into the mechanism that differentially promote variant specific gliomagenesis within an allelic series, 3) begin to demonstrate the unique biology of familial glioma, and 4) further investigate the mechanisms underlying glioma driven hyperexcitably thereby addressing a much under investigated quality of life concern. Ultimately, our programs exists to gain greater insight into the molecular mechanisms that drive gliomagenesis and associated co-morbidities. This will provide understanding towards novel therapeutic vulnerabilities.
Glioblastoma Multiforme is the most common and deadliest cancer in the central nervous system. Our research seeks to take existing patient genomics information and translate that through biological modeling to understand the molecular mechanism of the disease and associated co-morbidities. Through our approach, we will identify patient specific pathways driving this disease, providing a much needed advance towards personalized medicine for this most deadly of diseases.
