Autofluorescence imaging captures heterogeneous drug response differences between 2D and 3D breast cancer cultures.

Two-photon microscopy of cellular autofluorescence intensity and lifetime (optical metabolic imaging, or OMI) is a promising tool for preclinical drug development. OMI, which exploits the endogenous fluorescence from the metabolic coenzymes NAD(P)H and FAD, is sensitive to changes in cell metabolism produced by drug treatment. Previous studies have shown that drug response, genetic expression, cell-cell communication, and cell signaling in 3D culture match those of the original in vivo tumor, but not those of 2D culture. The goal of this study is to use OMI to quantify dynamic cell-level metabolic differences in drug response in 2D cell lines vs. 3D organoids generated from xenograft tumors of the same cell origin. BT474 cells and Herceptin-resistant BT474 (HR6) cells were tested. Cells were treated with vehicle control, Herceptin, XL147 (PI3K inhibitor), and the combination. The OMI index was used to quantify response, and is a linear combination of the redox ratio (intensity of NAD(P)H divided by FAD), mean NADH lifetime, and mean FAD lifetime. The results confirm that the OMI index resolves significant differences (p<0.05) in drug response for 2D vs. 3D cultures, specifically for BT474 cells 24 hours after Herceptin treatment, for HR6 cells 24 and 72 hours after combination treatment, and for HR6 cells 72 hours after XL147 treatment. Cell-level analysis of the OMI index also reveals differences in the number of cell sub-populations in 2D vs. 3D culture at 24, 48, and 72 hours post-treatment in control and treated groups. Finally, significant increases (p<0.05) in the mean lifetime of NADH and FAD were measured in 2D vs. 3D for both cell lines at 72 hours post-treatment in control and all treatment groups. These whole-population differences in the mean NADH and FAD lifetimes are supported by differences in the number of cell sub-populations in 2D vs. 3D. Overall, these studies confirm that OMI is sensitive to differences in drug response in 2D vs. 3D, and provides further information on dynamic changes in the relative abundance of metabolic cell sub-populations that contribute to this difference.