COMPREHENSIVE LIPID PROFILING OF GLIOMA AND BRAIN AROUND TUMOR HETEROGENEITY BY MRM-MS FOR THERAPEUTIC TARGET IDENTIFICATION

Abstract

Glioma is the most common and deadliest form of brain cancer. The highly aggressive nature of this disease drives progression toward malignancy and patient overall survival average between 12-15 months. Standard treatment protocol has minimally changed over the last decade, consisting of resection surgery, radiation, and TMZ-based chemotherapy. Sadly, this approach has had limited success in bettering patient outcomes, predominantly due to ineffective treatments currently available. Therefore, there is a critical need to identify novel therapeutic targets to improve on current treatments that will increase patient overall survival. Recent studies have shown lipids maintain distinct expression in glioma compared brain, due to metabolic reprogramming, and support tumor growth, progression, and drug resistance. This dissertation utilized multiple reaction monitoring-mass spectrometry to define lipid profiles in glioma and brain around tumor, using three screening methods (M1, M2, and PC) to investigate differences: 1) by glioma grade, 2) by BAT grade, and 3) between glioma and BAT, to elucidate lipids critical to glioma progression that can serve as therapeutic targets. In each study, an integrated workflow combining histological analysis, laser capture microdissection, and MRM-MS characterized lipids expressed specifically in both glioma and BAT tissue. MRM is a fast, sensitive approach capable of profiling lipids in small sample volumes and evaluated lipid alterations across glioma grades I-IV. With each increase in glioma grade, the disease becomes more aggressive and untreatable, potentially attributed to lipid composition changes. This study identified significant differences in lipid profiles between low- and high-grade glioma. Phosphatidylcholine (PC) and sphingomyelin (SM) lipids were differentially expressed as glioma undergoes malignant transition. Distinctions in PC and SM saturation and chain length relative abundance were shown to be grade specific. Lastly, individual PC and SM were observed to possess strong discriminating power in ROC curve analysis to distinguish between low- and high-grade glioma. Results suggested lipid composition changes as glioma progresses. BAT profiling by MRM indicated highly distinct lipid composition between BAT exposed to different glioma grades. Low-grade BAT expressed greater relative abundances of carnitines, TAG, and high unsaturated PC compared to high-grade. Conversely, high-grade BAT maintained significantly higher low unsaturated PC vs low-grade. A significant transition from high unsaturated PC to low unsaturated PC average sum relative abundance was observed in low- and high-grade respectively. ROC analysis also determined strong discriminating power of PC and SM to differentiate between low- and high-grade BAT. This study indicated major PC and SM expression changes in BAT proximal to different grades of glioma. In the final study, MRM profiling determined glioma and BAT maintain largely similar lipid compositions based on applied MRM-MS methods. Multivariate analysis demonstrated proximal localization of clusters between groups, indicating comparable lipid profiles. Cluster analysis visualized slight distinction in expression of low unsaturated and high unsaturated PC in BAT and glioma respectively. Five PC and SM lipids were significantly different between glioma and BAT however, similarity in overall profiles reduced their discriminating power in ROC analysis. The results of this study indicate BAT molecular changes predate morphological changes, suggesting potential influence of glioma on its surrounding tissue. Taken together, the applied integrative workflow is a powerful tool to comprehensively profile distinct lipids in glioma and brain around tumor at small sample volumes. Overall, results indicate PC and SM lipid expression are significantly at different stages of progression in glioma and BAT tissue. Studies in Chapters 3-5 will highlight the importance of defining lipid profiles in glioma and the surrounding brain to identify novel therapeutic lipid targets that both specifically target glioma, but also improve overall patient survival.