Toward Understanding Ovarian Tumor Metabolism Using NMR-Based Metabonomics Data
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Metabonomics can be considered as an advanced methodology to proficiently obtain information from experimental profiles acquired for biofluids. Metabonomics studies use statistical analysis to diagnose diseases, monitor the progression of the diseases and gain insights on the changes of metabolic phenotypes. This thesis covers different points with the aim of understanding the metabolism of ovarian tumors using data obtained from NMR-based metabonomics. Chapter 1 covers the definition `of metabonomics and the analytical techniques employed for prognosis of cancer. Chapter 2 presents an overview of different metabolic pathways that are affected by the onset of cancer. Chapter 3 focuses on the p-values threshold, assumption of normality, Bonferroni correction used in statistical analyses in different cancer studies. Chapter 4 encloses two different sections: (i) summary and critiques of the review article "metabolic signature of cancer unveiled by NMR spectroscopy of human biofluids". (ii) Followed by the metabolism section, which covers the hypotheses associated with the metabolite, lipid and macromolecular component concentration changes detected by NMR-based metabonomics. These concentration changes observed in ovarian tumors are also compared to other concentration changes reported in different studies. The chapter 5 gives an insight into the future of metabonomics studies.