| Abstract |
Glioblastoma Multiforme is a type of aggressive, malignant brain tumor with a poor prognosis, despise efforts in novel treatments. In this project, I investigated the role of the MGMT gene on patients’ health. I hypothesised that MGMT methylation, alongside key correlating factors, positively affect the prognosis of Glioblastoma patients.
To evaluate my initial hypothesis, I analysed data from the open access Ivy Glioblastoma Atlas Project database, from which I used RNA sequencing data to find the effect of methylation on factors such as survival days and age which influence a patient’s health. I then created an algorithm to find correlating factors to predicting MGMT methylation, which I also trained to be able to diagnose methylation status in unseen data based on other factors such as age, other genetic factors and KPS, with adequate accuracy.
From my analysis, I concluded that my results supported my initial hypothesis, and also identified novel factors correlating to MGMT methylation, most notably multifocality and molecular subtype. These findings highlight the potential of MGMT as a prognostic factor, biomarker, and a factor to base personalised and more effective therapies on. Moreover, factors identified to correlate with methylation may be valuable prognostic factors, and help to understand the underlying molecular mechanisms of Glioblastoma.
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