Detection of Volatile Organic Compounds (VOCs) in Urine via Gas Chromatography-Mass Spectrometry QTOF to Differentiate Between Localized and Metastatic Models of Breast Cancer
Detection of Volatile Organic Compounds (VOCs) in Urine via Gas Chromatography-Mass Spectrometry QTOF to Differentiate Between Localized and Metastatic Models of Breast Cancer
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DOI：
10.1038/s41598-019-38920-0
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发表时间：
2019-02-21
影响因子：
4.6
通讯作者：
Agarwal, Mangilal
中科院分区：
文献类型：
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作者：
Woollam, Mark;Teli, Meghana;Agarwal, Mangilal
乳腺癌是女性中最常见的癌症，目前对该疾病的筛查方法并不敏感。挥发性有机化合物 (VOC) 包括内源性代谢物，可提供有关健康和疾病的信息，这可能有助于开发更好的乳腺癌筛查方法。本研究的目的是对有肿瘤和无肿瘤的小鼠进行分类，并通过尿液中挥发性有机化合物的差异来比较位于乳垫的肿瘤和注射到髂动脉的肿瘤细胞。将4T1.2肿瘤细胞注射到BALB/c小鼠的乳垫或髂动脉中后，收集尿液，通过固相微萃取浓缩尿液顶部空间的VOC，并通过气相色谱-质谱四极杆飞行时间分析结果。采用多变量和单变量统计分析在小鼠模型中寻找乳腺癌和转移性乳腺癌的潜在生物标志物。通过五倍交叉验证，一组六种 VOC 对有和没有肿瘤的小鼠进行分类，其接受者操作特征 (ROC AUC) 下的面积为 0.98（95% 置信区间 [0.85, 1.00]）。使用一组不同的六种 VOC 对乳垫和髂动脉患有肿瘤的小鼠进行分类，ROC AUC 为 0.96（95% 置信区间 [0.75, 1.00]）。
Breast cancer is the most common cancer detected in women and current screening methods for the disease are not sensitive. Volatile organic compounds (VOCs) include endogenous metabolites that provide information about health and disease which might be useful to develop a better screening method for breast cancer. The goal of this study was to classify mice with and without tumors and compare tumors localized to the mammary pad and tumor cells injected into the iliac artery by differences in VOCs in urine. After 4T1.2 tumor cells were injected into BALB/c mice either in the mammary pad or into the iliac artery, urine was collected, VOCs from urine headspace were concentrated by solid phase microextraction and results were analyzed by gas chromatography-mass spectrometry quadrupole time-of-flight. Multivariate and univariate statistical analyses were employed to find potential biomarkers for breast cancer and metastatic breast cancer in mice models. A set of six VOCs classified mice with and without tumors with an area under the receiver operator characteristic (ROC AUC) of 0.98 (95% confidence interval [0.85, 1.00]) via five-fold cross validation. Classification of mice with tumors in the mammary pad and iliac artery was executed utilizing a different set of six VOCs, with a ROC AUC of 0.96 (95% confidence interval [0.75, 1.00]).