Glioblastoma Multiforme: análise de dados ômicos para a caracterização do processo tumoral

Abstract

Glioblastoma multiforme is a cancer of the central nervous system that affects astrocytes. Despite its low incidence in the world population (297,000 cases in 2018), it is difficult to treat due to its high degree of staging (grade IV). In addition, like all cancers, the causes of the manifestation are diverse and have a non-linear relationship. To this end, this study set out to investigate the risk factors and the various molecular mechanisms that contribute to its genesis and maintenance. This task was carried out using bioinformatics tools and had as its data source the cohort of 600 patients from the TCGA (The Cancer Genome Atlas) project. The analysis was based on survival curves, risk ratios, genomic analysis, methylation, differential gene expression and functional enrichment of pathways, using R language and R Studio development environment. Were identified race and sex as significant risk factors; methylation as main genomic factor for pathology development; IDH gene as a biomarker of favorable prognosis; 359 days as cohort‘s average survival time; the frequently altered genes, such as PTEN, TP53 and EGFR; the expression level of differentially expressed genes (EPYC, SFRP5, C6ORF15 and SLC25A15P2); the most affected metabolic pathways such as TP53, TGF-Beta, RTK-RAS. To sum up, the precise understanding of the molecular mechanisms of glioma can help to develop treatments based on precision medicine to offer an alternative to traditional methods, which are still very debilitating for organism.