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自体荧光成像可在单细胞水平上识别肿瘤细胞周期状态。

Autofluorescence imaging identifies tumor cell-cycle status on a single-cell level.

作者信息

Heaster Tiffany M, Walsh Alex J, Zhao Yue, Hiebert Scott W, Skala Melissa C

机构信息

Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, 53715, USA.

National Research Council, JBSA Fort Sam Houston, Texas, 78234, USA.

出版信息

J Biophotonics. 2018 Jan;11(1). doi: 10.1002/jbio.201600276. Epub 2017 May 9.

Abstract

The goal of this study is to validate fluorescence intensity and lifetime imaging of metabolic co-enzymes NAD(P)H and FAD (optical metabolic imaging, or OMI) as a method to quantify cell-cycle status of tumor cells. Heterogeneity in tumor cell-cycle status (e. g. proliferation, quiescence, apoptosis) increases drug resistance and tumor recurrence. Cell-cycle status is closely linked to cellular metabolism. Thus, this study applies cell-level metabolic imaging to distinguish proliferating, quiescent, and apoptotic populations. Two-photon microscopy and time-correlated single photon counting are used to measure optical redox ratio (NAD(P)H fluorescence intensity divided by FAD intensity), NAD(P)H and FAD fluorescence lifetime parameters. Redox ratio, NAD(P)H and FAD lifetime parameters alone exhibit significant differences (p<0.05) between population means. To improve separation between populations, linear combination models derived from partial least squares - discriminant analysis (PLS-DA) are used to exploit all measurements together. Leave-one-out cross validation of the model yielded high classification accuracies (92.4 and 90.1 % for two and three populations, respectively). OMI and PLS-DA also identifies each sub-population within heterogeneous samples. These results establish single-cell analysis with OMI and PLS-DA as a label-free method to distinguish cell-cycle status within intact samples. This approach could be used to incorporate cell-level tumor heterogeneity in cancer drug development.

摘要

本研究的目标是验证代谢辅酶NAD(P)H和FAD的荧光强度及寿命成像(光学代谢成像,即OMI)作为一种量化肿瘤细胞细胞周期状态的方法。肿瘤细胞周期状态的异质性(例如增殖、静止、凋亡)会增加耐药性和肿瘤复发。细胞周期状态与细胞代谢密切相关。因此,本研究应用细胞水平的代谢成像来区分增殖、静止和凋亡细胞群体。使用双光子显微镜和时间相关单光子计数来测量光学氧化还原比(NAD(P)H荧光强度除以FAD强度)、NAD(P)H和FAD荧光寿命参数。单独的氧化还原比、NAD(P)H和FAD寿命参数在群体均值之间显示出显著差异(p<0.05)。为了提高群体之间的区分度,使用源自偏最小二乘判别分析(PLS-DA)的线性组合模型来综合利用所有测量值。该模型的留一法交叉验证产生了较高的分类准确率(两个群体分别为92.4%和90.1%,三个群体分别为92.4%和90.1%)。OMI和PLS-DA还能识别异质样本中的每个亚群体。这些结果确立了使用OMI和PLS-DA进行单细胞分析作为一种无标记方法来区分完整样本中的细胞周期状态。这种方法可用于在癌症药物开发中纳入细胞水平的肿瘤异质性。

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