The identification of biomarkers that enable the early detection and prognosis of disease, or that facilitate measurement of the efficacy of response to a specific therapeutic intervention, holds great promise in advancing the capabilities of individualized medicine. Recent technological advances, particularly in the development and application of sensitive and robust mass spectrometry approaches, have enabled large scale biomarker discovery efforts to be initiated, including within the emerging field of lipidomics. Lipids are a diverse group of compounds, including fatty acyls, sterols, glycerolipids, glycerophospholipids and sphingolipids that play key biological roles as the main structural component of cell membranes, in energy storage and metabolism, and in cell signaling. A large number of studies have demonstrated that the disruption of lipid metabolism or signaling pathways can play a key role in the onset and progression of human disease. Thus, a comprehensive comparative analysis of changes in lipid profiles that occur between normal and diseased cells, tissues or organs, may enable the identification and characterization of specific lipids that can serve as effective biomarker signatures of disease. Here, we propose to (i) critically evaluate and optimize extraction and sample handling procedures associated with the isolation of lipids from specific tissue types and (ii) develop a comprehensive strategy, based on the use of electrospray ionization and complementary tandem mass spectrometry approaches, coupled with automated data analysis and principle component analysis methods for lipid identification and quantification. Then, we will apply this lipid biomarker identification approach to examining changes in lipid profiles that are observed between normal tissue and the end organs of two common human disease models in which lipids play a major role, namely diabetes (retina) and hepatocellular carcinoma (liver), and to correlate these changes with those occurring in the blood fractions (plasma, erythrocytes and leukocytes) of these subjects for use as potential clinically relevant biomarkers for early disease diagnosis.
The successful completion of these studies will lead to the development of robust and sensitive bioanalytical mass spectrometry methods for comprehensive lipid analysis, and for the identification of biomarkers of diabetes and diabetic complications, and hepatocellular carcinoma. The results from this work will therefore provide information leading to the development of effective clinical methods for the early detection and monitoring of these diseases.
