Metabolomics

A growing research avenue in my group is related to the use of systems-level metabolomic measurements in biofluids to diagnose disease. Although metabolite levels in biofluids such as urine have been used since the Middle Ages for diagnostic purposes, our approach is based on the combined use of metabolite panels and multivariate scoring functions to provide a more personalized view of the health status of a given subject. The decision to go into this line of research stems from our interest in both bioanalytical chemistry and multivariate/multiway analysis [1-3], which have also shaped a new graduate-level class recently designed (CHEM 6271). Our early work which we started in 2007 dealt with the detection of early stage ovarian cancer by means of LC-MS metabolomics combined with support vector machine (SVM) analysis [4]. We carried out this work as part of an interdisciplinary team of researchers from the Integrated Cancer Research Center at GT (ICRC, http://www.icrc.gatech.edu/). Follow up work improved on the detection scheme by replacing LC-MS with DART-MS, helping improve reproducibility and enabling a larger number of replicates [5, 6]. Serum metabolic profiles of 44 women diagnosed with serous papillary ovarian cancer (3 stage I/II, 41 stage II/IV) and 50 healthy women or women with benign conditions (e.g., serous, simple, or follicular cysts) were obtained with DART MS. Application of SVM classification to these profiles demonstrated an unprecedented 99% to 100% accuracy (100% sensitivity and 100% specificity) [7]. Following this work, we partnered with the Matzuk Lab at Baylor College of Medicine to investigate if similar metabolic changes were observed in the first successful mouse model of high-grade serous carcinoma (HGSC), the most common and deadliest type of ovarian cancer.

We also continue to apply our growing metabolomics expertise to projects that involve a wide range of metabolomic questions such as the investigation of metabolome changes observed in ill whale sharks kept in captivity [8], the study of the allelopathic effects of red tide algae on plankton, IMS-MS investigation of metabolome changes associated with cystic fibrosis-related diabetes, and prostate cancer progression.
 
 
(1)       F. Blasco-Gomez, M. J. Medina-Hernandez, S. Sagrado-Vives, F. M. Fernandez; "Simultaneous spectrophotometric determination of calcium and magnesium in mineral waters by means of multivariate partial least-squares regression". Analyst 122, 639-643 (1997).
(2)       M. Azubel, F. M. Fernandez, M. B. Tudino, O. E. Troccoli; "Novel application and comparison of multivariate calibration for the simultaneous determination of cu, zn and mn at trace levels using flow injection diode array spectrophotometry". Anal. Chim. Acta 398, 93-102 (1999).
(3)       F. M. Fernandez, M. B. Tudino, O. E. Troccoli; "Multicomponent kinetic determination of cu, zn, co, ni and fe at trace levels by first and second order multivariate calibration". Anal. Chim. Acta 433, 119-133 (2001).
(4)       W. Guan, M. S. Zhou, C. Y. Hampton, B. B. Benigno, D. Walker, A. Gray, J. F. McDonald, F. M. Fernandez; "Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines". BMC Bioinformatics 10, 259-273 (2009).doi: 10.1186/1471-2105-10-259
(5)       M. Zhou, W. Guan, L. D. Walker, R. Mezencev, B. B. Benigno, A. Gray, F. M. Fernandez, J. F. McDonald; "Rapid mass spectrometric metabolic profiling of blood sera detects ovarian cancer with high accuracy". Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 19, 2262-2271 (2010).doi: 10.1158/1055-9965.EPI-10-0126
(6)       M. Zhou, J. F. McDonald, F. M. Fernandez; "Optimization of a direct analysis in real time/time-of-flight mass spectrometry method for rapid serum metabolomic fingerprinting". J. Am. Soc. Mass Spectrom. 21, 68-75 (2010).doi: 10.1016/j.jasms.2009.09.004
(7)       M. S. Zhou, W. Guan, L. D. Walker, R. Mezencev, B. B. Benigno, A. Gray, F. M. Fernandez, J. F. McDonald; "Rapid mass spectrometric metabolic profiling of blood sera detects ovarian cancer with high accuracy". Cancer Epidemiol Biomark Prev 19, 2262-2271 (2010).doi: 10.1158/1055-9965.Epi-10-0126
(8)       A. D. Dove, J. Leisen, M. Zhou, J. J. Byrne, K. Lim-Hing, H. D. Webb, L. Gelbaum, M. R. Viant, J. Kubanek, F. M. Fernandez; "Biomarkers of whale shark health: A metabolomic approach". PLoS One 7, e49379 (2012).doi: 10.1371/journal.pone.0049379