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Description
Ovarian cancer (OC) is the second most common form of gynecologic cancer and is the most fatal among all forms of gynecologic malignancies. Despite the pivotal role of metabolic processes in the molecular pathogenesis of OC, robust metabolic markers to

Ovarian cancer (OC) is the second most common form of gynecologic cancer and is the most fatal among all forms of gynecologic malignancies. Despite the pivotal role of metabolic processes in the molecular pathogenesis of OC, robust metabolic markers to enable effective screening, rapid diagnosis, accurate surveillance, and therapeutic monitoring of OC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolic profiling approach for the identification of metabolite biomarker candidates that could enable expedited, highly sensitive and specific OC detection. Using this targeted approach, 90 plasma metabolites from many metabolic pathways of potential biological significance were reliably detected and monitored in 218 plasma samples taken from three groups of subjects (78 OC patients, 50 benign samples, and 90 healthy controls). Univariate significance testing and receiver operating characteristic (ROC) analysis revealed 7 metabolites with high predictive accuracy [area under curve (AUC) > 0.90] for distinguishing healthy controls from OC patients. The results of our multivariate model development informed the construction of a 5-metabolite panel of potential plasma biomarkers for enhanced discrimination of OC samples from benign specimens, exhibiting roughly 75% predictive accuracy using a 50% random-split training set. ROC analysis that was generated based on a logistic regression classifier showed enhanced classification performance relative to individual metabolites, with more than 75% accuracy using a testing data set for external validation. Pathway analysis revealed significant disturbances in glycine, serine, and threonine metabolism; glyoxylate and dioxylate metabolism; the pentose phosphate pathway; and histidine metabolism. The results expand basic knowledge of the metabolome related to OC pathogenesis relative to healthy controls and benign samples, revealing potential pathways or markers that can be targeted therapeutically. This study also provides a promising basis for the development of larger multi-site projects to validate our findings across population groups and further advance the development of improved clinical care for OC patients.


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Details

Title
  • Ovarian Cancer Detection Using Targeted Plasma Metabolic Profiling
Contributors
Date Created
2020-05
Resource Type
  • Text
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