Capillary electrochromatography (CEC) is a major capillary electrophoresis (CE) mode that have been interfaced to mass spectrometry (MS) for sensitive and selective analysis of chiral compounds. This research expands CEC applications in cancer biomarker and chiral CE analysis. Chapter 1 is a review of liquid chromatography-mass spectrometry (LC/MS), gas chromatography-mass spectrometry (GC/MS), and capillary electrophoresis mass spectrometry (CE/MS) for analysis of metabolites in prostate cancer diagnostics and therapies. In this chapter, a literature survey was performed within the databases PubMed, 4 Caplus/Webline and Web of Sciences. A total 17 studies reporting on various analytical platforms for metabolite identification in prostate cancer research, which often include case-control comparison were identified and reviewed. Chapter 2 described the analysis of metabolite biomarkers in prostate cancer tissues by capillary electrochromatography mass spectrometry. In this chapter, a capillary CEC–MS/MS method was developed for the simultaneous determination and separation of eight proofs of concept (POC) metabolites (betaine, malate, proline, N-acetyl aspartate, N-acetylglucosamine, uracil, xanthine, and alanine) as potential prostate cancer diagnostic markers. A polymeric monolith column with a hydrophilic crosslinker and strong anion-exchange mixed-mode has been fabricated by an in situ copolymerization of vinyl benzyl trimethylammonium chloride, and bisphenol A glycerolate dimethacrylate (BisGMA) in the presence of methanol and dodecyl alcohol as porogens and AIBN as initiator. After CEC separation, samples were analyzed by a triple–quadrupole mass spectrometer operated in positive ion mode. After optimization, the data showed that the CEC-MS/MS method using monolithic column achieved a much better chromatographic selectivity compared to coated columns and increased sensitivity than bare fused silica column The effect of mobile phase pH, ACN percentage and additive were studies. Under the optimum mobile phase conditions, this method was carried out to separate and detect eight metabolites in the biopsy sample. The LOD for the metabolites is between 50nM-100nM. This method has successfully used to examine patients’ prostate cancer with an accuracy of 95%. Chapter 3 demonstrates Insights into Chiral Recognition Mechanisms in CEC using linear salvation energy relationship. By varying the linker (amide and carbamate), head group (alanine, leucine, and valine) and chain length (C8, C10 and C12) of the amino acid bound surfactants; monolithic column was made to ultimately understand the factors governing chiral stationary solid phase. Through the comparison of system parameters, we can see that surfactant head group, linker and chain length affect the separation of achiral and chiral compounds. Also, with the same type surfactant, data was presented to show how the trend of LSER parameters and how it affects separation between in CEC. This study showed the predictive capability of LSER to understand the aforementioned intermolecular processes controlling retention and by doing so, be able to quantitatively predict the experimental conditions to achieve an acceptable chiral separation.
| Identifer | oai:union.ndltd.org:GEORGIA/oai:scholarworks.gsu.edu:chemistry_diss-1131 |
| Date | 06 January 2017 |
| Creators | Lu, Yang |
| Publisher | ScholarWorks @ Georgia State University |
| Source Sets | Georgia State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Chemistry Dissertations |
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