Development and implementation analytical methods for integrated omics analyses to be used to identify phenotypes of glioblastoma multiforme, meningioma (primary) and metastasis (secondary) brain tumors

A thorough examination of intermediate molecular levels such as protein, metabolite, and lipid is required to establish direct causal and functional links between genotype and phenotype. Comprehensive metabolomics and lipidomics analysis require the optimization of analysis conditions, as well as the use of multiple analytical techniques. In the thesis, metabolomics analyses were performed with GC-MS and LC-qTOF-MS, and lipidomic analyses were carried out with LC-qTOF-MS. The analytical techniques utilized were optimized with several experimental designs. The optimum solvent combinations for the extraction of metabolites, lipids, and even proteins were determined to be methanol:water:chloroform (3:1:3, v/v/v) for plasma samples and methanol:water:dichloromethane (2:1:3, v/v/v) for tissue samples. For GC-MS based metabolomics analyses performed with tissue samples; incubation time and temperature of silylation reagent, methoxyamine concentration-methanol volume interaction, and for plasma samples; methoxyamine concentration, incubation time of silylation reagent and methanol-methoxyamine volume interaction, were found to be important parameters affecting the analysis results. The mobile phase composition used as reconstitution solution for LC-qTOF-MS based metabolomics analyses was determined to have a significant effect on the analysis results. The Box-Behnken design was used to optimize the parameters affecting the chromatographic conditions of LC-qTOF-MS based metabolomics and lipidomics analyses. The developed analytical methods were applied to tissue and plasma samples of patients and control groups. The phenotypes of the tumors were illuminated by comparing them to the control group, and the results were evaluated in a holistic manner from a clinical point of view.