乳腺癌细胞代谢的自发荧光流式分选
Autofluorescence flow sorting of breast cancer cell metabolism.
作者信息
Shah Amy T, Cannon Taylor M, Higginbotham James N, Coffey Robert J, Skala Melissa C
机构信息
Department of Biomedical Engineering, Vanderbilt University, Station B, Box 1631, Nashville, TN, 37235, USA.
Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
出版信息
J Biophotonics. 2017 Aug;10(8):1026-1033. doi: 10.1002/jbio.201600128. Epub 2016 Oct 12.
Abstract
Clinical cancer treatment aims to target all cell subpopulations within a tumor. Autofluorescence microscopy of the metabolic cofactors NAD(P)H and FAD has shown sensitivity to anti-cancer treatment response. Alternatively, flow cytometry is attractive for high throughput analysis and flow sorting. This study measures cellular autofluorescence in three flow cytometry channels and applies cellular autofluorescence to sort a heterogeneous mixture of breast cancer cells into subpopulations enriched for each phenotype. Sorted cells were grown in culture and sorting was validated by morphology, autofluorescence microscopy, and receptor expression. Ultimately, this method could be applied to improve drug development and personalized treatment planning.
摘要
临床癌症治疗旨在针对肿瘤内的所有细胞亚群。代谢辅助因子NAD(P)H和FAD的自发荧光显微镜检查已显示出对抗癌治疗反应的敏感性。另外，流式细胞术对于高通量分析和流式分选很有吸引力。本研究在三个流式细胞术通道中测量细胞自发荧光，并应用细胞自发荧光将乳腺癌细胞的异质混合物分选成富含每种表型的亚群。分选后的细胞在培养中生长，并通过形态学、自发荧光显微镜检查和受体表达验证分选结果。最终，该方法可用于改进药物开发和个性化治疗方案。
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