Network-informed discovery of multidrug combinations for ER alpha+/HER2-/PI3K alpha-mutant breast cancer

Breast cancer is a persistent threat to women worldwide. A large proportion of breast cancers are dependent on the estrogen receptor alpha (ER alpha) for tumor progression. Therefore, targeting ER alpha with antagonists, such as tamoxifen, or estrogen deprivation by aromatase inhibitors remain standard therapies for ER alpha + breast cancer. The clinical benefits of monotherapy are often counterbalanced by off-target toxicity and development of resistance. Combinations of more than two drugs might be of great therapeutic value to prevent resistance, and to reduce doses, and hence, decrease toxicity. We mined data from the literature and public repositories to construct a network of potential drug targets for synergistic multidrug combinations. With 9 drugs, we performed a phenotypic combinatorial screen with ER alpha + breast cancer cell lines. We identified two optimized low-dose combinations of 3 and 4 drugs of high therapeutic relevance to the frequent ER alpha + /HER2-/PI3K alpha-mutant subtype of breast cancer. The 3-drug combination targets ER alpha in combination with PI3K alpha and cyclin-dependent kinase inhibitor 1 (p21). In addition, the 4-drug combination contains an inhibitor for poly (ADP-ribose) polymerase 1 (PARP1), which showed benefits in long-term treatments. Moreover, we validated the efficacy of the combinations in tamoxifen-resistant cell lines, patient-derived organoids, and xenograft experiments. Thus, we propose multidrug combinations that have the potential to overcome the standard issues of current monotherapies.

Automated summary

Breast cancer is a persistent threat to women worldwide, and current monotherapies often face issues of drug resistance and toxicity. By mining data and constructing a network, we identified two multidrug combinations with high therapeutic relevance for ER alpha positive/HER2-/PI3K alpha mutant subtype of breast cancer.