Fig. 2: HT-DBP predicts in vivo response in breast cancer models.

(A) Change in tumor volume relative to the start of treatment over time for select drug treatment in MMTV-PyMT tumors. Data are mean ± SEM of at least 7 mice per group. (B) Fold change in tumor volume at day 14 relative to the start of treatment for MMTV-PyMT tumors. Each dot represents a single mouse; data are mean ± SEM of at least 7 mice per group. Dasatinib (10 mg/kg, i.p), 17-DMAG (10 mg/kg, i.p), AZD2014 (15 mg/kg, p.o), lapatinib (50 mg/kg, p.o), or sunitinib (50 mg/kg, p.o) were dosed daily 5 days a week for 2 weeks. Navitoclax (100mg/kg, p.o) was dosed daily for 2 weeks. (C) Correlation between dynamic BH3 profiling, and MMTV-PyMT tumor response in vivo. (R² = 0.83; p = 0.004; Pearson). Delta priming data (horizontal) are mean ± SD of n=3 independent experiments at 1 μM of drug. Tumor volume data (vertical) are mean ± SEM from 7–15 mice per group. (D) HT-DBP of select drug combinations in the DF-BM355 breast cancer PDX model. Each point represents an independent experiment. Lines represent mean of N = 2 experiments. (E) Correlation between dynamic BH3 profiling, and median survival of DF-BM355 mice treated with compounds. N = 5–9 mice per group. (R² = 0.82, p=0.005; Pearson).