Cell migration sculpts evolutionary dynamics favouring therapy resistance in lung cancer

Authors list

Ajay Bhargava Xiao Fu Sasha Bailey Yutaka Naito Hamid Mohammadi Rob Hynds Steven Hooper Dhruva Biswas Alix Le Marois Sunil Kumar Yuriy Alexandrov Paul M French James McGinty Paul Bates Charles Swanton Erik Sahai

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Abstract

The evolution of cancer undermines the long-term efficacy of therapy. In this study, we combine experimental, computational, and clinical data analysis to investigate factors influencing the competition of subclones in lung cancer. Lineage tracing reveals unexpected variation in the long-term fate of neutral subclones, with subclones arising near the edge of tumours being favoured. Low levels of cell migration and cell mixing lead to high cell densities in the interior of the tumour that suppress proliferation. Using agent-based modelling and in silico analysis we inferred the extent of cell mixing in human tumours from the TRACERx lung cancer study. This reveals correlations between Epithelial to Mesenchymal Transition (EMT), stromal fibroblasts and levels of cell mixing. Experimental analysis confirms that both TGFβ-driven EMT and stromal fibroblasts reduce the variability in subclone fate and promote subclone mixing. Moreover, mixing favours clonal sweeps by subclones resistant to therapy-induced cell killing. Together, these analyses demonstrate that EMT and stromal fibroblasts sculpt tumour evolution by promoting cell mixing and thereby favour the rapid dominance of therapy resistant subclones.