ISSN: 1837-9664Journal of Cancer
Global reach, higher impact
J Cancer 2016; 7(10):1265-1272. doi:10.7150/jca.15074 This issue Cite
Research Paper
Use of Plasma Metabolomics to Identify Diagnostic Biomarkers for Early Stage Epithelial Ovarian Cancer
1. National Center for Endemic Disease Control, Harbin Medical University, Harbin, China;
2. Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China;
3. Department of Gynecology Oncology, The Third Affiliated Hospital of Harbin Medical University, Harbin, China;
4. Department of Biostatistics, School of Public Health and Community Medicine, University of Washington, Seattle, USA.
Abstract
The early detection of ovarian carcinoma is difficult due to the absence of recognizable physical symptoms and a lack of sensitive screening methods. The currently available biomarkers (such as CA125 and HE4) are insufficiently reliable to distinguish early stage (I/II) epithelial ovarian cancer (EOC) patients from normal individuals because they possess a relatively poor sensitivity and specificity. To evaluate the application of metabolomics to biomarker discovery in the early stages of epithelial ovarian cancer (EOC), plasma samples from 21 early stage EOC patients and 31 healthy controls were analyzed with ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-Tof/MS) in conjunction with multivariate statistical analysis. Eighteen metabolites, including lysophospholipids, 2-piperidone and MG (18:2), were found to be disturbed in early stage EOC with satisfactory diagnostic accuracy (AUC=0.920). These biomarkers were specifically validated in the EOC nude mouse model, and five of the biomarkers (lysophospholipids, adrenoyl ethanolamide et al.) were highly suspected of being associated with EOC because they were differentially expressed with the same tendency in the EOC nude mice versus normal controls. In conclusion, the selected metabolic biomarkers have considerable utility and significant potential for diagnosing early ovarian cancer and investigating its underlying mechanisms.
Keywords: metabolomics, epithelial ovarian cancer, biomarkers, plasma, diagnosis.
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