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Autofluorescence flow sorting of breast cancer cell metabolism
Author(s) -
Shah Amy T.,
Can Taylor M.,
Higginbotham James N.,
Coffey Robert J.,
Skala Melissa C.
Publication year - 2017
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201600128
Subject(s) - autofluorescence , flow cytometry , cancer cell , breast cancer , cell sorting , sorting , biology , cancer , chemistry , cancer research , microbiology and biotechnology , pathology , medicine , fluorescence , computer science , genetics , physics , quantum mechanics , programming language
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.