Model-guided discovery of MTOR-oriented synergistic drug combinations in colorectal cancer

Abstract Colorectal cancer (CRC) exhibits high genetic heterogeneity and frequent resistance to single-agent therapies, highlighting the need for rationally designed drug combinations. We apply a mechanistic modelling framework to prioritise synergistic combinations in 16 CRC cell lines. Simulations of 210 double perturbations among 21 targeted inhibitors guided the selection of 17 combinations for experimental validation. Of 704 tested conditions, 68% showed synergy, most involving PI3K/AKT/MTOR-related inhibitors. We report six novel compound combinations that inhibit CRC cell-line growth by targeting MTOR and ERK, or MTOR and BCL2. In silico analysis indicates that feedback suppression via S6K–FOXO3 mediates the MTORi–ERKi synergy, whereas apoptotic reinforcement explains the MTORi–BCL2i effect. These results demonstrate that model-guided prioritisation enables the efficient discovery of synergistic drug pairs, mechanistic insight into their action, and a scalable route to rational combination-therapy design in CRC.

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Publication Details

Journal
npj Systems Biology and Applications
Published
2026-07-23
DOI
https://doi.org/10.1038/s41540-026-00783-3
Primary Topic
FOXO transcription factor regulation
Type
article
Field-Weighted Citation Impact
0.00

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article

Model-guided discovery of MTOR-oriented synergistic drug combinations in colorectal cancer

Åsmund Flobak, Torkild Visnes, Vu To Nakstad, Laurence Calzone et al.
npj Systems Biology and Applications
FOXO transcription factor regulation
article

Model-guided discovery of MTOR-oriented synergistic drug combinations in colorectal cancer

Åsmund Flobak, Torkild Visnes, Vu To Nakstad, Laurence Calzone, Saran Pankaew, Eirini Tsirvouli, Henri Colyn Bwanika, Tonje H. Haukaas, Margrét S. Sigfúsdóttir, Viviam Solangeli Bermúdez Paiva, Christine Sers, Kristine Sletta
article en

Abstract

Abstract Colorectal cancer (CRC) exhibits high genetic heterogeneity and frequent resistance to single-agent therapies, highlighting the need for rationally designed drug combinations. We apply a mechanistic modelling framework to prioritise synergistic combinations in 16 CRC cell lines. Simulations of 210 double perturbations among 21 targeted inhibitors guided the selection of 17 combinations for experimental validation. Of 704 tested conditions, 68% showed synergy, most involving PI3K/AKT/MTOR-related inhibitors. We report six novel compound combinations that inhibit CRC cell-line growth by targeting MTOR and ERK, or MTOR and BCL2. In silico analysis indicates that feedback suppression via S6K–FOXO3 mediates the MTORi–ERKi synergy, whereas apoptotic reinforcement explains the MTORi–BCL2i effect. These results demonstrate that model-guided prioritisation enables the efficient discovery of synergistic drug pairs, mechanistic insight into their action, and a scalable route to rational combination-therapy design in CRC.

npj Systems Biology and Applications
Inserm (FR), SINTEF (NO), Norwegian University of Science and Technology (NO), Université Paris Sciences et Lettres (FR), Humboldt-Universität zu Berlin (DE), Freie Universität Berlin (DE), Charité - Universitätsmedizin Berlin (DE)
Norges Teknisk-Naturvitenskapelige Universitet, Helse Midt-Norge, Norges Forskningsråd
Good health and well-being
Openalex Percentile: Top 15%
FOXO transcription factor regulation
DOIOpen Access PDFOpenAlex
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