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

Area of Science:

• Biomedical Optics
• Cancer Research
• Cell Biology

Background:

• Tumor cell-cycle heterogeneity drives drug resistance and recurrence.
• Cell-cycle status is intrinsically linked to cellular metabolism.
• Accurate quantification of cell-cycle populations is crucial for effective cancer therapy.

Purpose of the Study:

• To validate optical metabolic imaging (OMI) as a method for quantifying tumor cell-cycle status.
• To assess the utility of NAD(P)H and FAD fluorescence imaging for distinguishing cell populations.
• To develop a label-free approach for analyzing cell-level tumor heterogeneity.

Main Methods:

• Utilized two-photon microscopy and time-correlated single photon counting.
• Measured optical redox ratio (NAD(P)H/FAD intensity) and fluorescence lifetime parameters.
• Applied partial least squares-discriminant analysis (PLS-DA) for multi-parameter analysis.

Main Results:

• Individual OMI parameters (redox ratio, lifetimes) showed significant differences between cell populations (p<0.05).
• PLS-DA models integrating all OMI measurements achieved high classification accuracies (92.4% for two, 90.1% for three populations).
• OMI and PLS-DA successfully identified distinct subpopulations within heterogeneous samples.

Conclusions:

• Single-cell analysis using OMI and PLS-DA is a validated, label-free method to distinguish cell-cycle status.
• This approach enables the characterization of cell-level tumor heterogeneity in intact samples.
• This technique holds potential for improving cancer drug development by incorporating cellular heterogeneity.