Nel Ivonne, Morawetz Erik W, Tschodu Dimitrij, Käs Josef A, Aktas Bahriye
Department of Gynecology, Medical Center, University of Leipzig, 04103 Leipzig, Germany.
Soft Matter Physics Division, Peter-Debye-Institute Leipzig, University of Leipzig, 04103 Leipzig, Germany.
Cancers (Basel). 2021 Mar 5;13(5):1119. doi: 10.3390/cancers13051119.
Circulating tumor cells (CTCs) are a potential predictive surrogate marker for disease monitoring. Due to the sparse knowledge about their phenotype and its changes during cancer progression and treatment response, CTC isolation remains challenging. Here we focused on the mechanical characterization of circulating non-hematopoietic cells from breast cancer patients to evaluate its utility for CTC detection. For proof of premise, we used healthy peripheral blood mononuclear cells (PBMCs), human MDA-MB 231 breast cancer cells and human HL-60 leukemia cells to create a CTC model system. For translational experiments CD45 negative cells-possible CTCs-were isolated from blood samples of patients with mamma carcinoma. Cells were mechanically characterized in the optical stretcher (OS). Active and passive cell mechanical data were related with physiological descriptors by a random forest (RF) classifier to identify cell type specific properties. Cancer cells were well distinguishable from PBMC in cell line tests. Analysis of clinical samples revealed that in PBMC the elliptic deformation was significantly increased compared to non-hematopoietic cells. Interestingly, non-hematopoietic cells showed significantly higher shape restoration. Based on Kelvin-Voigt modeling, the RF algorithm revealed that elliptic deformation and shape restoration were crucial parameters and that the OS discriminated non-hematopoietic cells from PBMC with an accuracy of 0.69, a sensitivity of 0.74, and specificity of 0.63. The CD45 negative cell population in the blood of breast cancer patients is mechanically distinguishable from healthy PBMC. Together with cell morphology, the mechanical fingerprint might be an appropriate tool for marker-free CTC detection.
循环肿瘤细胞（CTC）是疾病监测中一种潜在的预测替代标志物。由于对其表型以及在癌症进展和治疗反应过程中的变化了解甚少，CTC分离仍然具有挑战性。在此，我们聚焦于乳腺癌患者循环非造血细胞的力学特性，以评估其在CTC检测中的效用。为了验证前提，我们使用健康外周血单个核细胞（PBMC）、人MDA-MB 231乳腺癌细胞和人HL-60白血病细胞构建了一个CTC模型系统。对于转化实验，从乳腺癌患者的血样中分离出CD45阴性细胞（可能是CTC）。在光镊（OS）中对细胞进行力学特性分析。通过随机森林（RF）分类器将主动和被动细胞力学数据与生理描述符相关联，以识别细胞类型特异性特性。在细胞系测试中，癌细胞与PBMC能够很好地区分。临床样本分析显示，与非造血细胞相比，PBMC中的椭圆变形显著增加。有趣的是，非造血细胞显示出显著更高的形状恢复能力。基于开尔文-沃伊特模型，RF算法表明椭圆变形和形状恢复是关键参数，并且OS区分非造血细胞与PBMC的准确率为0.69，灵敏度为0.74，特异性为0.63。乳腺癌患者血液中的CD45阴性细胞群体在力学上可与健康PBMC区分开来。连同细胞形态一起，力学指纹可能是一种用于无标记CTC检测的合适工具。
