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.

中文翻译：

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通过基于GC-MS平台的靶向游离脂肪酸谱筛选，鉴定乳腺癌的潜在血清生物标志物。

最新进展表明，异常的脂肪酸代谢与乳腺癌高度相关，这为发现潜在的乳腺癌生物标志物提供了线索。这项研究旨在确定血清游离脂肪酸（FFA）代谢谱并筛选潜在的生物标志物，以进行乳腺癌诊断。气相色谱-质谱联用和我们内部的脂肪酸甲酯标准物质库结合在一起，可以准确地识别乳腺癌患者和乳腺腺病患者（作为对照）的血清样品中的FFA谱。通过应用统计分析筛选潜在的生物标志物。在血清样品中总共准确鉴定出18种FFA。通过基于FFA轮廓的正交偏最小二乘判别分析模型正确区分了两组患者。乳腺癌患者血清中的七个FFA水平显着高于对照组，并且与疾病的恶性程度呈正相关。此外，还有五种候选物（棕榈酸，油酸，选择顺式‐8,11,14-二十碳三烯酸，二十二碳酸和油酸与硬脂酸的比例）作为潜在的血清生物标志物，可用于乳腺癌的鉴别诊断。我们的研究将有助于揭示乳腺癌患者中FFA的代谢特征，并为促进临床无创诊断提供有价值的信息。