Leibniz Institute of Photonics Technology, Albert Einstein str. 9, 07745 Jena, Germany.
Analyst. 2019 Oct 21;144(20):6098-6107. doi: 10.1039/c9an01176e. Epub 2019 Sep 18.
Raman spectroscopy can provide the biomolecular fingerprint of a cell in a label-free manner. Although a variety of clinical and biomedical applications have been demonstrated, the method remains largely a niche technology. The two main problems are the complexity of data acquisition and the complexity of data analysis. Generally, Raman measurements are performed manually and require a substantial amount of time. This, on the other hand, frequently results in a low number of samples and hence with questionable statistical evaluation. Here, we propose an automated high content screening Raman spectroscopy (HCS-RS) platform, which can perform a series of experiments without human interaction, significantly increasing the number of measured samples and making the measurement more reliable. The automated image processing of bright field images in combination with automatic spectral acquisition of the molecular fingerprint of cells exposed to different physiological conditions enables label-free high content screening applications. The performance of the developed HCS-RS platform is demonstrated by investigating the effect of panitumumab on SW48 and SW480 colorectal cancer cells with wild-type and mutated K-RAS, respectively, in a series of concentrations. Our result indicates that the increased content of panitumumab prohibits the activation of the MAP kinase of the colorectal cancer cells with wild-type K-RAS strongly, whereas there is no significant effect on the K-RAS mutated cells. Moreover, the relative amount of the panitumumab content present in the cells is determined from the Raman spectral information, which could be beneficial for personalized patient treatment.
拉曼光谱可以提供无标记的细胞生物分子指纹。尽管已经证明了该方法在各种临床和生物医学应用中具有重要作用,但它仍然主要是一种利基技术。两个主要问题是数据采集的复杂性和数据分析的复杂性。通常,拉曼测量是手动进行的,需要大量时间。这在另一方面,通常会导致样本数量较少,因此统计评估存在疑问。在这里,我们提出了一种自动化高内涵筛选拉曼光谱(HCS-RS)平台,该平台可以在无人干预的情况下进行一系列实验,显著增加测量样本的数量,并使测量更可靠。与自动采集暴露于不同生理条件下的细胞的分子指纹的自动光谱采集相结合的明场图像的自动图像处理,可以实现无标记的高内涵筛选应用。通过在一系列浓度下研究panitumumab 对野生型和突变型 K-RAS 的 SW48 和 SW480 结直肠癌细胞的影响,证明了所开发的 HCS-RS 平台的性能。我们的结果表明,panitumumab 含量的增加强烈抑制了野生型 K-RAS 的结直肠癌细胞中 MAP 激酶的激活,而对突变型 K-RAS 细胞则没有明显影响。此外,从拉曼光谱信息中可以确定细胞中存在的 panitumumab 含量的相对量,这可能有助于患者的个性化治疗。