A Combined Mass Spectrometry and Nuclear Magnetic Resonance Metabolomics Approach to Detect Breast Cancer Recurrence

Wed 3:30 PM - Track 2: Discovery Metabolomics

Daniel Raftery Purdue University

Daniel Raftery, Purdue University Vincent Asiago, Purdue University Leiddy Alvarado, Purdue University Lingyan Liu, Purdue University Murthy Shanaiah, Matrix-Bio, Inc.

The need for improved diagnostics in oncology is driving efforts to develop and employ advanced methods for molecular based medicine. For example, the detection of recurrent breast cancer is limited by poorly performing CA markers that are both insensitive and late markers. A better approach, we believe, is the use of metabolite markers that provide better diagnostic performance and earlier detection, which should result in improved therapy outcomes. Metabolite profiling provides an instantaneous snap shot of the biological status in health and disease. As a result, global metabolite profiling has gained prominence in the research laboratory as a means to identify promising biomarkers of a number of important disease states, among its numerous applications. We are pursuing a novel approach in metabolite profiling to discover and validate metabolic markers of breast cancer recurrence. The use of mass spectrometry in clinical analyses has grown considerably because of its ability to deliver highly sensitive and specific molecular analyses and because of the need for additional molecular information that can be used to make better clinical decisions. However, the ability of MS in the area of global metabolite profiling is still somewhat limited by issues related to reproducibility, sensitivity to sample preparation and the challenge of turning data into useful information. We have found that the combination of MS and NMR improves metabolite profiling results significantly. The combination of NMR and MS improves our ability to classify cohorts and to identify additional potential biomarkers using metabolic network approaches. Mapping the observed changes on to the metabolic pathways provides insight regarding the complex and correlated network of metabolic perturbations that occur in disease. The application of this combined approach has revealed a set of biomarkers that are very sensitive and specific for detecting the recurrence of early and late stage breast cancer. The derived metabolite profile is twice as sensitive as the current CA 15-3 assay, and detects recurrence 10 months earlier, providing a new window for second line therapies. Performance of the metabolite biomarker profile in several hundred patient samples, as well as the future outlook of the approach described above will be discussed.

Email: raftery@purdue.edu

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