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Exploiting evolutionary herding to control drug resistance in cancer

Ahmet Acar, Daniel Nichol, Javier Fernandez-Mateos, George D. Cresswell, Iros Barozzi, Sung Pil Hong, Inmaculada Spiteri, Mark Stubbs, Rosemary Burke, Adam Stewart, Georgios Vlachogiannis, Carlo C. Maley, View ORCID ProfileLuca Magnani, Nicola Valeri, Udai Banerji, View ORCID ProfileAndrea Sottoriva
doi: https://doi.org/10.1101/566950
Ahmet Acar
1Evolutionary Genomics & Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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Daniel Nichol
1Evolutionary Genomics & Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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Javier Fernandez-Mateos
1Evolutionary Genomics & Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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George D. Cresswell
1Evolutionary Genomics & Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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Iros Barozzi
2Imperial College London, London, UK
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Sung Pil Hong
2Imperial College London, London, UK
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Inmaculada Spiteri
1Evolutionary Genomics & Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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Mark Stubbs
3CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK
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Rosemary Burke
3CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK
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Adam Stewart
4Clinical Pharmacology - Adaptive Therapy Group, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, UK
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Georgios Vlachogiannis
5Gastrointestinal Cancer Biology and Genomics, Centre for Molecular Pathology, The Institute of Cancer Research, London, UK
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Carlo C. Maley
6Biodesign Institute, Arizona State University, Tempe, USA
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Luca Magnani
2Imperial College London, London, UK
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  • ORCID record for Luca Magnani
Nicola Valeri
5Gastrointestinal Cancer Biology and Genomics, Centre for Molecular Pathology, The Institute of Cancer Research, London, UK
7Department of Medicine, The Royal Marsden NHS Trust, London, UK
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Udai Banerji
4Clinical Pharmacology - Adaptive Therapy Group, Division of Cancer Therapeutics and Clinical Studies, The Institute of Cancer Research, London, UK
5Gastrointestinal Cancer Biology and Genomics, Centre for Molecular Pathology, The Institute of Cancer Research, London, UK
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  • For correspondence: udai.banerji@icr.ac.uk andrea.sottoriva@icr.ac.uk
Andrea Sottoriva
1Evolutionary Genomics & Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
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  • ORCID record for Andrea Sottoriva
  • For correspondence: udai.banerji@icr.ac.uk andrea.sottoriva@icr.ac.uk
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Abstract

Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased growth rate or increased sensitivity to another drug due to evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here we present a novel approach for evolutionary herding based on a combination of single-cell barcoding, very large populations of 108–109 cells grown without re-plating, longitudinal non-destructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary herding in non-small cell lung cancer, showing that herding allows shifting the clonal composition of a tumour in our favour, leading to collateral drug sensitivity and proliferative fitness costs. Through genomic analysis and single-cell sequencing, we were also able to determine the mechanisms that drive such evolved sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can potentially be translated into the clinic to control treatment resistance.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted March 04, 2019.
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Exploiting evolutionary herding to control drug resistance in cancer
Ahmet Acar, Daniel Nichol, Javier Fernandez-Mateos, George D. Cresswell, Iros Barozzi, Sung Pil Hong, Inmaculada Spiteri, Mark Stubbs, Rosemary Burke, Adam Stewart, Georgios Vlachogiannis, Carlo C. Maley, Luca Magnani, Nicola Valeri, Udai Banerji, Andrea Sottoriva
bioRxiv 566950; doi: https://doi.org/10.1101/566950
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Exploiting evolutionary herding to control drug resistance in cancer
Ahmet Acar, Daniel Nichol, Javier Fernandez-Mateos, George D. Cresswell, Iros Barozzi, Sung Pil Hong, Inmaculada Spiteri, Mark Stubbs, Rosemary Burke, Adam Stewart, Georgios Vlachogiannis, Carlo C. Maley, Luca Magnani, Nicola Valeri, Udai Banerji, Andrea Sottoriva
bioRxiv 566950; doi: https://doi.org/10.1101/566950

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