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

作者：Heaster Tiffany M; Walsh Alex J; Zhao Yue; Hiebert Scott W; Skala Melissa C^*

来源：Journal of Biophotonics, 2018, 11(1): UNSP e201600276.

DOI：10.1002/jbio.201600276

• Quiescence
• tumor dormancy
• fluorescence lifetime
• metabolic imaging
• cell-cycle status
• single-cell analysis

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 PLSDA 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.
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• 出版日期2018-1