TY - JOUR
T1 - Autofluorescence imaging identifies tumor cell-cycle status on a single-cell level
AU - Heaster, Tiffany M.
AU - Walsh, Alex J.
AU - Zhao, Yue
AU - Hiebert, Scott W.
AU - Skala, Melissa C.
N1 - Funding Information:
Acknowledgements We would like to acknowledge the funding sources, including grants for the National Institutes of Health (R01 CA185747, R01 CA142888), the National Science Foundation (CBET-1554027), Stand Up To Cancer (Innovative Research Grant), and National Science Foundation Graduate Research Fellowship (DGE-0909667). Furthermore, we acknowledge Dr. Jonathan Irish, Kirsten Diggens, Deon Doxie, and Nalin Leelatin for their guidance in designing flow cytometry experiments. Flow cytometry experiments were performed in the VUMC Flow Cytometry Shared Resource. The VUMC Flow Cytometry Shared Resource is supported by the Vanderbilt Ingram Cancer Center (P30 CA68485) and the Vanderbilt Digestive Disease Research Center (DK058404).
Funding Information:
We would like to acknowledge the funding sources, including grants for the National Institutes of Health (R01 CA185747, R01 CA142888), the National Science Foundation (CBET-1554027), Stand Up To Cancer (Innovative Research Grant), and National Science Foundation Graduate Research Fellowship (DGE-0909667). Furthermore, we acknowledge Dr. Jonathan Irish, Kirsten Diggens, Deon Doxie, and Nalin Leelatin for their guidance in designing flow cytometry experiments. Flow cytometry experiments were performed in the VUMC Flow Cytometry Shared Resource. The VUMC Flow Cytometry Shared Resource is supported by the Vanderbilt Ingram Cancer Center (P30 CA68485) and the Vanderbilt Digestive Disease Research Center (DK058404).
Publisher Copyright:
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/1
Y1 - 2018/1
N2 - 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. (Figure presented.).
AB - 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. (Figure presented.).
KW - Quiescence
KW - cell-cycle status
KW - fluorescence lifetime
KW - metabolic imaging
KW - single-cell analysis
KW - tumor dormancy
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U2 - 10.1002/jbio.201600276
DO - 10.1002/jbio.201600276
M3 - Article
C2 - 28485124
AN - SCOPUS:85019080899
VL - 11
JO - Journal of Biophotonics
JF - Journal of Biophotonics
SN - 1864-063X
IS - 1
M1 - e201600276
ER -