Methodology for NMR-based metabonomics and application for detection of early stage epithelial ovarian cancer

NMR-based metabonomics can be viewed as an approach to efficiently extract information from a large number of NMR spectra for biofluids using statistical analysis to diagnose diseases and to gain insights on the changes of metabolic phenotype. This thesis focuses on methodology for NMR-based metabonomics along with its application for detection of early stage epithelial ovarian cancer (EOC). Chapter 1 aims to provide a brief introduction on metabonomics and prepares the reader for what to expect in the succeeding chapters. The description and implementation of NMR experiments for metabonomics are discussed in Chapter 2. Standard operating procedures (SOPs), which are crucial for unbiased metabolic profiling, make up Chapter 3. These SOPs build a high-throughput (HTP) platform for NMR-based metabonomics studies, which was primarily used for metabonomics studies of serum to diagnose early stage EOC, but it can also be adapted readily for other body fluids and can be used to investigate other diseases. In Chapter 4, the utility of 1H NMR-based metabonomics of serum using a microflow NMR probe to develop a predictive model to diagnose EOC at an early stage is discussed. The impact of (i) increased spectrometer sensitivity when using a cryogenic probe and (ii) profiling with several different types of NMR experiments on the accuracy of predictive models for EOC is subsequently covered in Chapter 4. The perturbation of metabolism associated with the onset of early stage EOC and benign tumorigenesis, which are captured as changes in serum metabolite concentration profiles, are interpreted in Chapter 5. These interpretations could provide insights about EOC tumorigenesis and possibly tumor metabolism in general.