Mpth-37. Computational Modeling Approach in Deriving a Mesenchymal Transition Landscape in Low Grade and High Grade Gliomas
Year: 2016
Type: conference-abstract
Abstract: One of the important question in glioma therapy is that the biological modeling of gliomas in vitro is inadequate due to the heterogeneous and aggressive nature of this disease. The existing experimental techniques are insufficient to study the molecular diversity and processes like epithelial to mesenchymal transition (MT) which are known to be responsible for resistance to various therapeutic agents in many cancers including glioblastomas. In the current study, we address this issue by integrating publically available database, computational modeling, pathway enrichment network analysis and data validation tools to come up with a prognostic index gene signature for glioblastomas. By analyzing 275 glioma samples consisting of low grade gliomas (grade II) and high grade glioblastoma (grade IV) from The Cancer Genome Atlas database, we report specific differences between the two, including molecular markers associated with increased survival, and potential therapeutic targets. We stratified our cohort based on a recently proposed 64-gene MT signature as high MT (overexpressing this signature) and low MT (with relatively low expression of the signature). Transcription factor and enrichment analysis of these cohorts identified 5 major pathways and 118 transcription factors regulating these cohorts. Using a penalized regression method, LASSO, we explored the Extracellular matrix organization, the most significant pathway, for prognostic relevance and prioritized a 20-gene signature including 5 transcription factors associated with survival outcome. The signature genes showed a prognostic index hazard ratio (HR = 3.2. 95% CI = 1.53-8.33) in glioblastomas. Validation in an independent data confirmed the results. We also found that the signature is strongly correlated with the putative stem cell marker CD44. Our results suggest that transition of low grade gliomas to glioblastoma is associated with a shift in the expression of the signature genes, raising the possibility of inhibiting this transition might prolong the survival in glioma patients.
Source: Neuro-Oncology
Institutions: National Institutes of Health, National Cancer Institute
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2587968945