首页> 外文期刊>Journal of proteome research >Untargeted Mass Spectrometry-Based Metabolomic Profiling of Pleural Effusions: Fatty Acids as Novel Cancer Biomarkers for Malignant Pleural Effusions
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Untargeted Mass Spectrometry-Based Metabolomic Profiling of Pleural Effusions: Fatty Acids as Novel Cancer Biomarkers for Malignant Pleural Effusions

机译:基于非靶向质谱的胸腔积液代谢组学分析:脂肪酸作为恶性胸腔积液的新型癌症生物标志物。

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Untargeted mass spectrometry-based metabolomic profiling is a powerful analytical method used for broad-spectrum identification and quantification of metabolites in biofluids in human health and disease states. In this study, we exploit metabolomic profiling for cancer biomarker discovery for diagnosis of malignant pleural effusions. We envisage the result will be clinically useful since currently there are no cancer biomarkers that are accurate enough for the diagnosis of malignant pleural effusions. Metabolomes of 32 malignant pleural effusions from lung cancer patients and 18 benign effusions from patients with pulmonary tuberculosis were analyzed using reversed-phase liquid chromatography tandem mass spectrometry (LC-MS/MS) using AB SCIEX TripleTOF 5600. MS spectra were analyzed using XCMS, PeakView, and LipidView. Metabolome-Wide Association Study (MWAS) was performed by Receiver Operating Characteristic Curve Explorer and Tester (ROCCET). Insignificant markers were filtered out using a metabolome-wide significance level (MWSL) with p-value < 2 × 10~(-5) for t test. Only compounds in Human Metabolome Database (HMDB) will be used as cancer biomarkers. ROCCET analysis of ESI positive and negative MS spectra revealed free fatty acid (FFA) 18:1 (oleic acid) had the largest area-under-ROC of 0.96 (95% CI = 0.87-1.00) in malignant pleural effusions. Using a ratio of FFA 18:1-to-ceramide (d18:1/16:0), the area-under-ROC was further increased to 0.99 (95% CI = 0.91-1.00) with sensitivity 93.8% and specificity 100.0%. Using untargeted metabolomic profiling, the diagnostic cancer biomarker with the largest area-under-ROC can be determined objectively. This lipogenic phenotype could be explained by overexpression of fatty acid synthase (FASN) in cancer cells. The diagnostic performance of FFA 18:1-to-ceramide (d18:1/16:0) ratio supports its use for diagnosis of malignant pleural effusions.
机译:基于非靶向质谱的代谢组学谱分析是一种功能强大的分析方法,可用于广谱鉴定和量化人体健康和疾病状态下生物流体中的代谢物。在这项研究中,我们利用代谢组学谱分析发现癌症生物标志物,以诊断恶性胸腔积液。我们认为该结果在临床上将是有用的,因为目前还没有足够准确的癌症生物标志物可用于诊断恶性胸腔积液。使用AB SCIEX TripleTOF 5600反相液相色谱串联质谱(LC-MS / MS)分析了肺癌患者32例恶性胸腔积液和18例肺结核患者良性积液的代谢组。 PeakView和LipidView。代谢组全关联研究(MWAS)由受试者工作特征曲线浏览器和测试仪(ROCCET)进行。使用p值<2×10〜(-5)的代谢组范围内的显着性水平(MWSL)滤除微不足道的标志物,以进行t检验。人类代谢组数据库(HMDB)中的仅化合物将用作癌症生物标志物。对ESI阳性和阴性MS光谱的ROCCET分析显示,在恶性胸腔积液中,游离脂肪酸(FFA)18:1(油酸)的ROC下面积最大,为0.96(95%CI = 0.87-1.00)。使用FFA 18:1-神经酰胺的比例(d18:1/16:0),ROC下面积进一步增加到0.99(95%CI = 0.91-1.00),灵敏度为93.8%,特异性为100.0% 。使用非靶向代谢组学分析,可以客观地确定ROC下面积最大的诊断性癌症生物标志物。这种脂肪生成的表型可以用癌细胞中脂肪酸合酶(FASN)的过表达来解释。 FFA 18:1-神经酰胺(d18:1/16:0)比率的诊断性能支持其用于恶性胸腔积液的诊断。

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