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Differential plasma lipids profiling and lipid signatures as biomarkers in the early diagnosis of ovarian carcinoma using UPLC-MS

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Abstract

Biological requirements for tumor cell proliferation include the sustained increase of structural, energetic, signal transduction and biosynthetic precursors. Because lipids participate in the self-assembly of phospholipids to form biological membranes, they play important roles in membrane construction, energy storage, and cell signaling. We hypothesized that the differences in lipids between malignant ovarian carcinomas, benign ovarian tumors and normal controls could be reflected in the bio-fluids. A total of 215 pre-operative plasma samples were collected from 139 epithelial ovarian cancer (EOC), 38 benign ovarian tumor (BOT) and 38 uterine fibroid (UF) patients; these samples were then characterized by lipid profiling using ultra performance liquid chromatography/electrospray ionization mass spectrometry (UPLC–MS). The lipid profiles of the EOC and control samples (BOT/UF) as well as the different stages and histological subtypes of EOC were compared. Differentially expressed lipids were categorized as glycerophospholipids, sphingolipids and glyceroglycolipids and were found to be linked with three pathways. Almost all glycerophospholipids were down-regulated, especially phosphatidylcholine and phosphoethanolamine plasmalogens, whereas sphingolipids were up-regulated in the EOC patients compared to the controls. Lipids associated with pathological stage and histological subtype were also identified. We further identified five diagnostic lipids that were complementary to CA125. The predictive accuracy of five diagnostic lipids together with CA125 was higher than that of CA125 alone when distinguishing EOC and BOT/UF. In the future, the differential lipids identified may provide biologists with additional information regarding lipid metabolism and guide clinicians in making individualized therapeutic decisions if these results are confirmed in a larger study.

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Acknowlegments

This work has received financial support from the National Natural Science Foundation of China (81473072), National Natural Science Foundation of Heilonglong Jiang Province (QC2015098) and Wu LianDe Youth Innovation Fund (WLD-QN1105).

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Correspondence to Ge Lou or Kang Li.

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No potential conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Yan Hou and Junnan Li have contributed equally to this work.

Kang Li is the first corresponding author and Ge Lou is the second corresponding author.

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Hou, Y., Li, J., Xie, H. et al. Differential plasma lipids profiling and lipid signatures as biomarkers in the early diagnosis of ovarian carcinoma using UPLC-MS. Metabolomics 12, 18 (2016). https://doi.org/10.1007/s11306-015-0891-7

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  • DOI: https://doi.org/10.1007/s11306-015-0891-7

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