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Identifying Potential Serum Biomarkers of Breast Cancer Through Targeted Free Fatty Acid Profiles Screening Based on GC-MS Platform

Binbin Tan, Ying Zhang, Tiantian Zhang, Jinsong He, Xueying Luo, Xiqing Bian, Jianlin Wu, Chang Zou, Yangzhi Wang, Li Fu

Biomed Chromatogr. 2020 Jun 14;e4922.

PMID: 32537761

Abstract:

Recent advances suggest that abnormal fatty acid metabolism highly correlates with breast cancer (BC), which provide clues to discover potential biomarkers of BC. This study aims to identify serum free fatty acid (FFA) metabolic profiles and screen potential biomarkers for BC diagnosis. Gas chromatography-mass spectrometry (GC-MS) and our in-house fatty acid methyl ester standard substances library were combined to accurately identify FFA profiles in serum samples of BC patients and breast adenosis patients (as controls). Potential biomarkers were screened by applying statistical analysis. A total of eighteen free fatty acids were accurately identified in serum sample. Two groups of patients were correctly discriminated by the orthogonal partial least squares-discriminant analysis (OPLS-DA) model based on FFA profiles. Seven FFA levels were significantly higher in serum from BC patients than that in controls, and exhibited positive correlation with malignant degrees of disease. Furthermore, five candidates (palmitic acid, oleic acid, cis-8,11,14-eicosatrienoic acid, docosanoic acid, and the ratio of oleic acid to stearic acid) were selected as potential serum biomarkers for differential diagnosis of BC. Our study would help to reveal the metabolic signature of FFA in BC patients, and provided valuable information for facilitating clinical non-invasive diagnosis.

Chemicals Related in the Paper:

Catalog Number Product Name Structure CAS Number Price
AP21061109 cis-8,11,14-Eicosatrienoic acid methyl ester cis-8,11,14-Eicosatrienoic acid methyl ester 21061-10-9 Price
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