Scientific article
OA Policy
English

Network-informed discovery of multidrug combinations for ERα+/HER2-/PI3Kα-mutant breast cancer

Published inCellular and molecular life sciences, vol. 80, no. 3, 80
Publication date2023-03-03
First online date2023-03-03
Abstract

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.

Keywords
  • Estrogen receptor
  • PARP
  • Synthetic lethality
  • Tamoxifen resistance
  • p21 Waf1/Cip1
Citation (ISO format)
HANY, Dina et al. Network-informed discovery of multidrug combinations for ERα+/HER2-/PI3Kα-mutant breast cancer. In: Cellular and molecular life sciences, 2023, vol. 80, n° 3, p. 80. doi: 10.1007/s00018-023-04730-x
Main files (1)
Article (Published version)
Identifiers
Additional URL for this publicationhttps://link.springer.com/10.1007/s00018-023-04730-x
Journal ISSN1420-682X
125views
343downloads

Technical informations

Creation04/03/2023 17:29:00
First validation04/03/2023 17:29:00
Update26/09/2023 11:39:02
Status update26/09/2023 11:39:02
Last indexation01/11/2024 04:32:21
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack