Identifying potential serum biomarkers of breast cancer through targeted free fatty acid profiles screening based on a GC–MS platform |
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| Authors: | Binbin Tan Ying Zhang Tiantian Zhang Jinsong He Xueying Luo Xiqing Bian Jianlin Wu Chang Zou Yangzhi Wang Li Fu |
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| Institution: | 1. Guangdong Key Laboratory for Genome Stability & Disease Prevention, Department of Pharmacology and Shenzhen University International Cancer Center, Shenzhen University School of Medicine, Shenzhen, China;2. Department of Breast Surgery, Peking University Shenzhen Hospital, Shenzhen, China;3. State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macao, China;4. Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University, Shenzhen People's Hospital, Shenzhen, China;5. Department of Chemistry, University of California, Berkeley, CA, USA |
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| Abstract: | Recent advances suggest that abnormal fatty acid metabolism highly correlates with breast cancer, which provide clues to discover potential biomarkers of breast cancer. This study aims to identify serum free fatty acid (FFA) metabolic profiles and screen potential biomarkers for breast cancer diagnosis. Gas chromatography–mass spectrometry and our in-house fatty acid methyl ester standard substances library were combined to accurately identify FFA profiles in serum samples of breast cancer patients and breast adenosis patients (as controls). Potential biomarkers were screened by applying statistical analysis. A total of 18 FFAs were accurately identified in serum sample. Two groups of patients were correctly discriminated by the orthogonal partial least squares–discriminant analysis model based on FFA profiles. Seven FFA levels were significantly higher in serum from breast cancer 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 breast cancer. Our study will help to reveal the metabolic signature of FFAs in breast cancer patients, and provides valuable information for facilitating clinical noninvasive diagnosis. |
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| Keywords: | breast cancer free fatty acid biomarker GC–MS |
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