Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States.
Department of Statistics, Purdue University, West Lafayette, Indiana 47907, United States.
J Proteome Res. 2020 Jun 5;19(6):2367-2378. doi: 10.1021/acs.jproteome.0c00038. Epub 2020 May 27.
Breast cancer (BC) is a heterogeneous malignancy that is responsible for a great portion of female cancer cases and cancer-related deaths in the United States. In comparison to other major BC subtypes, triple negative breast cancer (TNBC) presents with a relatively low survival rate and a high rate of metastasis. This has led to a strong, though largely unmet, need for more sensitive and specific methods of early-stage TNBC (ES-TNBC) detection to combat its high-grade pathology and relatively low survival rate. The current study employs a liquid chromatography-tandem mass spectrometry assay capable of targeted, highly specific, and sensitive detection of lipids to propose two diagnostic biomarker panels for TNBC/ES-TNBC. Using this approach, 110 lipids were reliably detected in 166 human plasma samples, 45 controls, and 121 BC (96 non-TNBC and 25 TNBC) subjects. Univariate and multivariate analyses allowed the construction and application of a 19-lipid biomarker panel capable of distinguishing TNBC (and ES-TNBC) from controls, as well as a 5-lipid biomarker panel capable of differentiating TNBC from non-TNBC and ES-TNBC from ES-non-TNBC. Receiver operating characteristic curves with notable classification performances were generated from the biomarker panels according to their orthogonal partial least-squares discrimination analysis models. TNBC was distinguished from controls with an area under the receiving operating characteristic curve (AUROC) = 0.93, sensitivity = 0.96, and specificity = 0.76 and ES-TNBC from controls with an AUROC = 0.96, sensitivity = 0.95, and specificity = 0.89. TNBC was differentiated from non-TNBC with an AUROC = 0.88, sensitivity = 0.88, and specificity = 0.79 and ES-TNBC from ES-non-TNBC with an AUROC = 0.95, sensitivity = 0.95, and specificity = 0.87. A pathway enrichment analysis between TNBC and controls also revealed significant disturbances in choline metabolism, sphingolipid signaling, and glycerophospholipid metabolism. To the best of our knowledge, this is the first study to propose a diagnostic lipid biomarker panel for TNBC detection. All raw mass spectrometry data have been deposited to MassIVE (dataset identifier MSV000085324).
乳腺癌（BC）是一种异质性恶性肿瘤，是导致美国女性癌症病例和癌症相关死亡的主要原因之一。与其他主要的 BC 亚型相比，三阴性乳腺癌（TNBC）的存活率相对较低，转移率较高。这导致了对更敏感和更特异的早期 TNBC（ES-TNBC）检测方法的强烈需求，但目前尚未得到满足，以应对其高分级病理学和相对较低的存活率。本研究采用液相色谱-串联质谱法（LC-MS/MS），能够靶向、高度特异性和敏感地检测脂质，提出了两种用于 TNBC/ES-TNBC 的诊断生物标志物组合。使用这种方法，在 166 个人血浆样本、45 个对照和 121 个 BC（96 个非 TNBC 和 25 个 TNBC）患者中可靠地检测到 110 种脂质。单变量和多变量分析允许构建和应用一个能够区分 TNBC（和 ES-TNBC）与对照的 19 种脂质生物标志物组合，以及一个能够区分 TNBC 与非 TNBC 和 ES-TNBC 与 ES-非 TNBC 的 5 种脂质生物标志物组合。根据正交偏最小二乘判别分析模型，从生物标志物组合中生成了具有显著分类性能的接收器工作特征曲线。TNBC 与对照的区分，曲线下面积（AUROC）为 0.93，灵敏度为 0.96，特异性为 0.76，ES-TNBC 与对照的区分，AUROC 为 0.96，灵敏度为 0.95，特异性为 0.89。TNBC 与非 TNBC 的区分，AUROC 为 0.88，灵敏度为 0.88，特异性为 0.79，ES-TNBC 与 ES-非 TNBC 的区分，AUROC 为 0.95，灵敏度为 0.95，特异性为 0.87。TNBC 与对照之间的通路富集分析也表明，胆碱代谢、鞘脂信号和甘油磷脂代谢存在显著紊乱。据我们所知，这是第一项提出用于 TNBC 检测的诊断脂质生物标志物组合的研究。所有原始质谱数据已存入 MassIVE（数据集标识符 MSV000085324）。
