Highly-accurate metabolomic detection of early-stage ovarian cancer
Scientific Reports2015Vol. 5(1), pp. 16351–16351
Citations Over TimeTop 10% of 2015 papers
David A. Gaul, Roman Mezencev, Long Tran Quoc, Christina M. Jones, Benedict B. Benigno, Alexander Gray, Facundo M. Fernández, John F. McDonald
Abstract
High performance mass spectrometry was employed to interrogate the serum metabolome of early-stage ovarian cancer (OC) patients and age-matched control women. The resulting spectral features were used to establish a linear support vector machine (SVM) model of sixteen diagnostic metabolites that are able to identify early-stage OC with 100% accuracy in our patient cohort. The results provide evidence for the importance of lipid and fatty acid metabolism in OC and serve as the foundation of a clinically significant diagnostic test.
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