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Fingerprinting Breast Cancer vs. Normal Mammary Cells by Mass Spectrometric Analysis of Volatiles

机译:挥发性成分的质谱分析指纹图谱对乳腺癌与正常乳腺细胞的关系

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摘要

There is increasing interest in the development of noninvasive diagnostic methods for early cancer detection, to improve the survival rate and quality of life of cancer patients. Identification of volatile metabolic compounds may provide an approach for noninvasive early diagnosis of malignant diseases. Here we analyzed the volatile metabolic signature of human breast cancer cell lines versus normal human mammary cells. Volatile compounds in the headspace of conditioned culture medium were directly fingerprinted by secondary electrospray ionization-mass spectrometry. The mass spectra were subsequently treated statistically to identify discriminating features between normal vs. cancerous cell types. We were able to classify different samples by using feature selection followed by principal component analysis (PCA). Additionally, high-resolution mass spectrometry allowed us to propose their chemical structures for some of the most discriminating molecules. We conclude that cancerous cells can release a characteristic odor whose constituents may be used as disease markers.
机译:人们对开发用于早期癌症检测的非侵入性诊断方法以提高癌症患者的生存率和生活质量的兴趣日益浓厚。挥发性代谢化合物的鉴定可为恶性疾病的非侵入性早期诊断提供一种方法。在这里,我们分析了人乳腺癌细胞系与正常人乳腺细胞的挥发性代谢特征。通过二次电喷雾电离质谱直接鉴定条件培养基顶部空间中的挥发性化合物。随后对质谱进行统计学处理,以识别正常与癌细胞类型之间的区别特征。我们能够通过使用特征选择然后进行主成分分析(PCA)对不同的样本进行分类。此外,高分辨率质谱法使我们能够为某些最具区分性的分子提出其化学结构。我们得出结论,癌细胞可以释放特征性气味,其成分可用作疾病标志物。

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