Exploiting evolutionary steering to induce collateral drug sensitivity in cancer

Ahmet Acar, Daniel Nichol, Javier Fernandez-Mateos, George D. Cresswell, Iros Barozzi, Sung Pil Hong, Nicholas Trahearn, Inmaculada Spiteri, Mark Stubbs, Rosemary Burke, Adam Stewart, Giulio Caravagna, Benjamin Werner, Georgios Vlachogiannis, Carlo C. Maley, Luca Magnani, Nicola Valeri, Udai Banerji () and Andrea Sottoriva ()
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Ahmet Acar: The Institute of Cancer Research
Daniel Nichol: The Institute of Cancer Research
Javier Fernandez-Mateos: The Institute of Cancer Research
George D. Cresswell: The Institute of Cancer Research
Iros Barozzi: Imperial College London
Sung Pil Hong: Imperial College London
Nicholas Trahearn: The Institute of Cancer Research
Inmaculada Spiteri: The Institute of Cancer Research
Mark Stubbs: The Institute of Cancer Research
Rosemary Burke: The Institute of Cancer Research
Adam Stewart: The Institute of Cancer Research
Giulio Caravagna: The Institute of Cancer Research
Benjamin Werner: The Institute of Cancer Research
Georgios Vlachogiannis: The Institute of Cancer Research
Carlo C. Maley: Arizona State University
Luca Magnani: Imperial College London
Nicola Valeri: The Institute of Cancer Research
Udai Banerji: The Institute of Cancer Research
Andrea Sottoriva: The Institute of Cancer Research

Nature Communications, 2020, vol. 11, issue 1, 1-14

Abstract: 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 fecundity or increased sensitivity to another drug. These evolutionary trade-offs can be exploited using ‘evolutionary steering’ to control the tumour population and delay resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here, we present an approach for evolutionary steering based on a combination of single-cell barcoding, 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 steering in a lung cancer model, showing that it shifts the clonal composition of the tumour in our favour, leading to collateral sensitivity and proliferative costs. Genomic profiling revealed some of the mechanisms that drive evolved sensitivity. This approach allows modelling evolutionary steering strategies that can potentially control treatment resistance.

Date: 2020
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DOI: 10.1038/s41467-020-15596-z

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