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无标记微流控技术从腹水中富集癌细胞与非癌细胞。

Label-free microfluidic enrichment of cancer cells from non-cancer cells in ascites.

机构信息

The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

Department of Mechanical Engineering, Indian Institute of Technology Patna, Bihar, 801103, India.

出版信息

Sci Rep. 2021 Sep 9;11(1):18032. doi: 10.1038/s41598-021-96862-y.

Abstract

The isolation of a patient's metastatic cancer cells is the first, enabling step toward treatment of that patient using modern personalized medicine techniques. Whereas traditional standard-of-care approaches select treatments for cancer patients based on the histological classification of cancerous tissue at the time of diagnosis, personalized medicine techniques leverage molecular and functional analysis of a patient's own cancer cells to select treatments with the highest likelihood of being effective. Unfortunately, the pure populations of cancer cells required for these analyses can be difficult to acquire, given that metastatic cancer cells typically reside in fluid containing many different cell populations. Detection and analyses of cancer cells therefore require separation from these contaminating cells. Conventional cell sorting approaches such as Fluorescence Activated Cell Sorting or Magnetic Activated Cell Sorting rely on the presence of distinct surface markers on cells of interest which may not be known nor exist for cancer applications. In this work, we present a microfluidic platform capable of label-free enrichment of tumor cells from the ascites fluid of ovarian cancer patients. This approach sorts cells based on differences in biomechanical properties, and therefore does not require any labeling or other pre-sort interference with the cells. The method is also useful in the cases when specific surface markers do not exist for cells of interest. In model ovarian cancer cell lines, the method was used to separate invasive subtypes from less invasive subtypes with an enrichment of ~ sixfold. In ascites specimens from ovarian cancer patients, we found the enrichment protocol resulted in an improved purity of P53 mutant cells indicative of the presence of ovarian cancer cells. We believe that this technology could enable the application of personalized medicine based on analysis of liquid biopsy patient specimens, such as ascites from ovarian cancer patients, for quick evaluation of metastatic disease progression and determination of patient-specific treatment.

摘要

分离患者的转移性癌细胞是迈向使用现代个性化医疗技术治疗该患者的第一步。传统的标准治疗方法根据诊断时癌组织的组织学分类为癌症患者选择治疗方法,而个性化医疗技术则利用患者自身癌细胞的分子和功能分析来选择最有可能有效的治疗方法。不幸的是,由于转移性癌细胞通常存在于含有许多不同细胞群体的液体中,因此这些分析所需的癌细胞纯培养物很难获得。因此,需要从这些污染细胞中分离出癌细胞。传统的细胞分选方法,如荧光激活细胞分选或磁性激活细胞分选,依赖于感兴趣的细胞上存在独特的表面标记,而这些标记可能未知或不存在于癌症应用中。在这项工作中,我们提出了一种微流控平台,能够从卵巢癌患者的腹水液中无标记地富集肿瘤细胞。这种方法基于细胞生物力学特性的差异对细胞进行分选,因此不需要对细胞进行任何标记或其他预分选干扰。当感兴趣的细胞不存在特定的表面标记时,该方法也很有用。在卵巢癌细胞系模型中,该方法用于分离侵袭性亚型和侵袭性较弱的亚型,富集倍数约为六倍。在卵巢癌患者的腹水标本中,我们发现富集方案导致 P53 突变细胞的纯度提高,表明存在卵巢癌细胞。我们相信,这项技术可以使基于液体活检患者标本(如卵巢癌患者的腹水)的个性化医疗应用成为可能,用于快速评估转移性疾病进展并确定患者特异性治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5c9/8429413/9f0303c9e999/41598_2021_96862_Fig1_HTML.jpg

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