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Lung Cancer - BioRxiv

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Last Updated: 15 May 2022

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Measuring competitive exclusion in non-small cell lung cancer

Therapeutic approaches for tumor prevention have traditionally believed that tumor volume reduction can be correlated with clinical success. The evolutionary game assay reveals how we experimentally determine the frequency-dependent interactions between a gefitinib-resistant non-small cell lung cancer population and its more asymptomatic ancestor. We find that the cost of resistance is insufficient to accurately predict competitive exclusion, and that frequency-dependent growth rate measurements are required. We then show that gefitinib therapy results in competitive exclusion of the ancestor's labour, with an apparent but not guaranteed exclusion of the resistant strain. Lastly, we show that including ecological growth factors can dramatically reduce the predicted time to catastrophic strain extinction by using our empirically derived growth rates to constrain simulations. In addition, we discovered that elevated drug levels may not result in the most effective reduction of tumor burdens.

Source link: https://doi.org/10.1101/2020.09.18.303966


Measuring competitive exclusion in non-small cell lung cancer

Therapeutic approaches for tumor prevention have traditionally assumed that tumor volume reduction correlates with clinical success. Evolutionary-based treatment approaches seek to combat resistance by selecting judicious therapies that maintain a significant treatable subpopulation. This study was conducted in an experimental fashion assay by a genetic game assay, a gefitinib resistant non-small cell lung cancer population and its disease-sensitive ancestor. Using frequency-dependent growth rate data, we now demonstrate that gefitinib treatment results in competitive exclusion of the ancestor, while absence of treatment results showed a possible but not guaranteed exclusion of the resistant strain. Lastly, we show that including ecological growth factors can dramatically reduce the predicted time to catastrophic strain extinction by using our empirically derived growth rates to constrain simulations. In addition, we also found that elevated drug concentrations may not lead to the most effective reduction in tumor burden.

Source link: https://doi.org/10.1101/2020.09.18.303966

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions