Metabolomics based methods for biomarkers discovery: Application to breast cancer

Vincent M Asiago, Purdue University

Abstract

Metabolomics and the closely related fields of metabonomics and metabolite profiling, involve the quantitative detection of multiple small molecules in the biological system as a results of pathophysiological stimuli. Metabolite profiling utilizes high-resolution analytical methods such as nuclear magnetic resonance (NMR) spectroscopy and mass spectroscopy (MS) for the quantitative analysis of hundreds of small molecules (less than ~ 1000 Da) present in biological samples. Owing to the complexity of the metabolic profile, multivariate statistical methods are extensively used for data analysis. The high sensitivity of metabolite profiles to even subtle stimuli can provide the means to detect the early onset of various biological perturbations in real time. Metabolite profiling has applications in a growing number of areas, including early disease diagnosis, investigation of metabolic pathways, pharmaceutical development, toxicology and nutritional studies. Moreover, the ability to link the metabolome, which constitutes the downstream products of cellular functions, to genotype and phenotype can provide a better understanding of complex biological states that promises routes to new therapy development. This thesis describes primarily the work on the development of novel methods to identify biomarkers using NMR and MS-based metabolomics for early diagnosis and prognosis of breast cancer. The first part describes a methodology developed to try to minimize the effect of pH and ionic strength on the chemical shift of common urine metabolites in metabolomics analysis. The second part of this thesis describes the development and validation of potential biomarkers for early detection of breast cancer using serum samples from multiple sites. We compared the metabolite profiles of female subjects from four different locations and at three different age groups. Finally the last part describes the development of a monitoring test for recurrent breast cancer. This test is capable of detecting breast cancer relapse 13 months before it occurs, opening a window of opportunity for patients and oncologist to improve treatment.

Degree

Ph.D.

Advisors

Rafftery, Purdue University.

Subject Area

Biochemistry

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