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Diagnostics of tumor cells by combination of Raman spectroscopy and microfluidics

机译:拉曼光谱和微流控技术相结合的肿瘤细胞诊断

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Circulating epithelial tumor cells are of increasing importance for tumor diagnosis and therapy monitoring of cancer patients. The definite identification of the rare tumor cells within numerous blood cells is challenging. Therefore, within the research initiative "Jenaer Zell-Identifizierungs-Gruppe" (JenZIG) we develop new methods for cell identification, micromanipulation and sorting based on spectroscopic methods and microfluidic systems. In this contribution we show, that classification models based on Raman spectroscopic analysis allow a precise discrimination of tumor cells from non-tumor cells with high prediction accuracies, up to more than 99% for dried cells. That holds true for unknown cell mixtures (tumor cells and leukocytes/erythrocytes) under dried conditions as well as in solution using the Raman laser as an optical tweezers to keep the cells in focus. We extended our studies by using a capillary system consisting of a quartz capillary, fiber optics and an adjustable fitting to trap cells. This system allows a prediction accuracy of 92.2% on the single cell level, and is a prerequisite for the development of a cell sorting and identification device based on a microfluidic chip. Initial experiments show that tumor cell lines can be differentiated from healthy leukocyte cells with an accuracy of more than 98%.
机译:循环上皮肿瘤细胞对于癌症患者的肿瘤诊断和治疗监测越来越重要。对众多血细胞中稀有肿瘤细胞的确切鉴定具有挑战性。因此,在“ Jenaer Zell-Identifizierungs-Gruppe”研究计划(JenZIG)中,我们开发了基于光谱方法和微流体系统的细胞鉴定,微处理和分选的新方法。在这一贡献中,我们表明,基于拉曼光谱分析的分类模型可以准确区分肿瘤细胞与具有高预测准确性的非肿瘤细胞,对于干细胞,高达99%以上。对于干燥条件下的未知细胞混合物(肿瘤细胞和白细胞/红细胞),以及在使用拉曼激光作为光学镊子的溶液中保持细胞集中的情况下,都是如此。我们通过使用毛细管系统扩展了我们的研究,该系统包括石英毛细管,光纤和可调节的装置以捕获细胞。该系统在单个细胞水平上的预测准确度达到92.2%,是开发基于微流控芯片的细胞分选和识别设备的前提。最初的实验表明,可以将肿瘤细胞系与健康白细胞区别开来,其准确度超过98%。

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