Models including plasma levels of sphingomyelins and phosphatidylcholines as diagnostic and prognostic biomarkers of endometrial cancer.
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Abstract | :
In endometrial cancer, biomarkers for preoperative identification of patients with low risk for disease progression would enable stratification according to the extent of surgery needed, and would avoid the complications that can be associated with radical surgery. A panel of proteins, amino acids, enzymes, and miRNA has been investigated as potential biomarkers for endometrial cancer. At the time of the manuscript submission targeted metabolomics/lipidomics approaches have not been applied to biomarker research in endometrial cancer. Using electrospray ionization-tandem mass spectrometry we quantified 163 metabolites in 126 plasma samples (61 patients with endometrial cancer, 65 control patients). Three single phosphatidylcholines were identified with significantly decreased levels in patients with endometrial cancer. A diagnostic model was defined as the ratio between acylcarnitine C16 and phosphatidylcholine PCae C40:1, the ratio between proline and tyrosine, and the ratio between the two phosphatidylcholines PCaa C42:0 and PCae C44:5; which provided sensitivity of 85.25%, specificity of 69.23%, and AUC of 0.837. Addition of smoking status further improved the constructed diagnostic model (AUC = 0.855). The presence of the major prognostic factors of deep myometrial invasion and lymphovascular invasion were also associated with altered metabolite concentrations. A prognostic model for deep myometrial invasion included the ratio between two hydroxysphingomyelins SMOH C14:1 and SMOH C24:1, and the ratio between two phosphatidylcholines PCaa C40:2 and PCaa C42:6, which provided sensitivity of 81.25%, specificity of 86.36%, and AUC of 0.857. The model for lymphovascular invasion included the ratio between two phosphatidylcholines PCaa C34:4 and PCae C38:3, and the ratio between acylcarnitine C16:2 and phosphatidylcholine PCaa C38:1, which provided sensitivity of 88.89%, specificity of 84.31%, and AUC of 0.935. |
Year of Publication | :
2018
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Journal | :
The Journal of steroid biochemistry and molecular biology
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Date Published | :
2018
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ISSN Number | :
0960-0760
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URL | :
http://linkinghub.elsevier.com/retrieve/pii/S0960-0760(18)30022-0
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DOI | :
10.1016/j.jsbmb.2018.01.012
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Short Title | :
J Steroid Biochem Mol Biol
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