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 10(8)-10(9) 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. Evolutionary steering uses therapies to control tumour evolution by exploiting
trade-offs. Here, using a barcoding approach applied to large cell populations, the
authors explore evolutionary steering in lung cancer cells treated with EGFR inhibitors.
