Previous work has shown that cellular-level Optical Metabolic Imaging (OMI) of organoids derived from human breast cancer cell-line xenografts accurately and rapidly predicts in vivo response to therapy. To validate OMI as a predictive measure of treatment response in an immune-competent model, we used the polyomavirus middle-T (PyVmT) transgenic mouse breast cancer model. The PyVmT model includes intra-tumoral heterogeneity and a complex tumor microenvironment that can influence treatment responses. Three-dimensional organoids generated from primary PyVmT tumor tissue were treated with a chemotherapy (paclitaxel) and a PI3K inhibitor (XL147), each alone or in combination. Cellular subpopulations of response were measured using the OMI Index, a composite endpoint of metabolic response comprised of the optical redox ratio (ratio of the fluorescence intensities of metabolic co-enzymes NAD(P)H to FAD) as well as the fluorescence lifetimes of NAD(P)H and FAD. Combination treatment significantly decreased the OMI Index of PyVmT tumor organoids (p<0.0001) and in vivo tumors (p<0.0001) versus controls. Subpopulation analyses revealed a homogeneous response to combined therapy in both cultured organoids and in vivo tumors, while single agent treatment with XL147 alone or paclitaxel alone elicited heterogeneous responses in organoids. Tumor volume decreased with combination treatment through treatment day 30. These results indicate that OMI of organoids generated from PyVmT tumors can accurately reflect drug response in heterogeneous allografts with both innate and adaptive immunity. Thus, this method is promising for use in humans to predict long-term treatment responses accurately and rapidly, and could aid in clinical treatment planning.
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