Microfluidic cell sorting by stiffness to examine heterogenic responses of cancer cells to chemotherapy.
Microfluidic cell sorting by stiffness to examine heterogenic responses of cancer cells to chemotherapy.
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DOI：
10.1038/s41419-018-0266-x
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发表时间：
2018-02-14
影响因子：
9
通讯作者：
Sulchek T
中科院分区：
文献类型：
--
作者：
Islam M;Mezencev R;McFarland B;Brink H;Campbell B;Tasadduq B;Waller EK;Lam W;Alexeev A;Sulchek T
癌症由异质细胞群组成，这些细胞群可能通过耐药亚群对治疗产生不同的反应。这些耐药亚群的稀缺性使得了解如何对抗其耐药性具有挑战性。我们报告了一种无标记的微流体方法，根据细胞硬度的差异将化疗治疗的癌细胞分离成富含化学抗性和化学敏感细胞的亚群。分选方法使得能够分析抗性细胞和敏感细胞之间的分子差异。因此，确定了多种耐药机制的作用，包括对细胞凋亡的敏感性降低，代谢增强和药物的挤出，并且首次确定了雌激素受体在白血病细胞耐药中的作用。为了验证这些发现，用化疗测试了几种用于鉴定的耐药途径的抑制剂，以使细胞毒性增加七倍。因此，微流体分选可以鉴定耐药性的分子机制，以检查癌症对治疗的异质性反应。
Cancers consist of a heterogeneous populations of cells that may respond differently to treatment through drug-resistant sub-populations. The scarcity of these resistant sub-populations makes it challenging to understand how to counter their resistance. We report a label-free microfluidic approach to separate cancer cells treated with chemotherapy into sub-populations enriched in chemoresistant and chemosensitive cells based on the differences in cellular stiffness. The sorting approach enabled analysis of the molecular distinctions between resistant and sensitive cells. Consequently, the role of multiple mechanisms of drug resistance was identified, including decreased sensitivity to apoptosis, enhanced metabolism, and extrusion of drugs, and, for the first time, the role of estrogen receptor in drug resistance of leukemia cells. To validate these findings, several inhibitors for the identified resistance pathways were tested with chemotherapy to increase cytotoxicity sevenfold. Thus, microfluidic sorting can identify molecular mechanisms of drug resistance to examine heterogeneous responses of cancers to therapies.
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惯性微流体电池担架（IMC）：完全自动化，高通量和接近实时的细胞机械分型。
DOI：
10.1002/smll.201700705
发表时间：
2017-07
期刊：
Small (Weinheim an der Bergstrasse, Germany)
影响因子：
--
作者：
Deng Y;Davis SP;Yang F;Paulsen KS;Kumar M;Sinnott DeVaux R;Wang X;Conklin DS;Oberai A;Herschkowitz JI;Chung AJ
通讯作者：
Chung AJ
影响因子：
4.6
作者：
Dhar M;Pao E;Renier C;Go DE;Che J;Montoya R;Conrad R;Matsumoto M;Heirich K;Triboulet M;Rao J;Jeffrey SS;Garon EB;Goldman J;Rao NP;Kulkarni R;Sollier-Christen E;Di Carlo D
通讯作者：
Di Carlo D
影响因子：
3.4
作者：
Bongiorno, Tom;Chojnowski, Jena L.;Sulchek, Todd
通讯作者：
Sulchek, Todd
影响因子：
3.9
作者：
Hessler, JA;Budor, A;Baker, J
通讯作者：
Baker, J
影响因子：
9.7
作者：
Ferrandiz, Nuria;Caraballo, Juan M.;Leon, Javier
通讯作者：
Leon, Javier