Network-informed discovery of multidrug combinations for ERα+/HER2-/PI3Kα-mutant breast cancer.
Dina HanyMarloes ZoetemelkKaushik BhattacharyaPatrycja Nowak-SliwinskaDidier PicardPublished in: Cellular and molecular life sciences : CMLS (2023)
Breast cancer is a persistent threat to women worldwide. A large proportion of breast cancers are dependent on the estrogen receptor α (ERα) for tumor progression. Therefore, targeting ERα with antagonists, such as tamoxifen, or estrogen deprivation by aromatase inhibitors remain standard therapies for ERα + 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 ERα + breast cancer cell lines. We identified two optimized low-dose combinations of 3 and 4 drugs of high therapeutic relevance to the frequent ERα + /HER2-/PI3Kα-mutant subtype of breast cancer. The 3-drug combination targets ERα in combination with PI3Kα 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.
Keyphrases
- estrogen receptor
- breast cancer cells
- low dose
- endoplasmic reticulum
- systematic review
- dna damage
- healthcare
- high throughput
- type diabetes
- mental health
- oxidative stress
- machine learning
- drug induced
- cancer therapy
- adverse drug
- insulin resistance
- drug delivery
- human health
- young adults
- climate change
- metabolic syndrome
- cell death
- multidrug resistant
- big data
- skeletal muscle
- open label
- wild type
- single cell
- long non coding rna