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Autofluorescence flow sorting of breast cancer cell metabolism

机译:乳腺癌细胞新陈代谢的自体荧光流量分类

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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.
机译:临床癌症治疗旨在靶向肿瘤内的所有细胞群。 代谢辅因子NAD(P)H和FAD的自体荧光显微镜显示对抗癌治疗反应的敏感性。 或者,流式细胞术对于高通量分析和流量分选是吸引力的。 该研究在三种流式细胞术通道中测量细胞自发荧光,并施加细胞自荧光,将乳腺癌细胞的异质混合物分类成富含每种表型的群体。 将分选细胞生长在培养中,通过形态,自发荧光显微镜和受体表达验证分选。 最终,这种方法可以应用于改善药物开发和个性化治疗规划。

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