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
- type diabetes
- breast cancer risk
- healthcare
- high throughput
- small molecule
- oxidative stress
- adverse drug
- emergency department
- pregnant women
- dna damage
- poor prognosis
- risk assessment
- high dose
- randomized controlled trial
- cell death
- open label
- insulin resistance
- cell cycle
- adipose tissue
- big data
- cell proliferation
- metabolic syndrome
- skeletal muscle
- childhood cancer
- artificial intelligence
- cell cycle arrest
- network analysis
- pregnancy outcomes