Abstract
Targeted inhibition of aberrant signaling is an important treatment strategy in cancer, but responses are often short-lived. Multi-drug combinations have the potential to mitigate this, but to avoid toxicity such combinations must be selective and given at low dosages. Here, we present a pipeline to identify promising multi-drug combinations. We perturbed an isogenic PI3K mutant and wild-type cell line pair with a limited set of drugs and recorded their signaling state and cell viability. We then reconstructed their signaling networks and mapped the signaling response to changes in cell viability. The resulting models, which allowed us to predict the effect of unseen combinations, indicated that no combination selectively reduces the viability of the PI3K mutant cells. However, we were able to validate 25 of the 30 combinations that we predicted to be anti-selective. Our pipeline enables efficient prioritization of multi-drug combinations from the enormous search space of possible combinations.
Original language | English |
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Article number | 104760 |
Pages (from-to) | 1-18 |
Number of pages | 18 |
Journal | iScience |
Volume | 25 |
Issue number | 8 |
Early online date | 15 Jul 2022 |
DOIs | |
Publication status | Published - 19 Aug 2022 |
Bibliographical note
Funding Information:This work was supported by funding from the Oncode Institute and the Gravity Program CGC .nl, funded by The Netherlands Organisation for Scientific Research (NWO) and the German Ministry of Education and Research ( BMBF ), project ZiSSTrans ( 02NUK047E ). L.F.A.W. received project funding from Genmab BV and BMS .
Publisher Copyright:
© 2022 The Authors
Keywords
- Bioinformatics
- In silico biology
- Pharmacoinformatics
- Systems biology