The article discusses the timing and heterogeneity of mutations that lead to drug resistance in metastatic cancers. It uses mathematical modeling to describe the spectrum of resistance mutations in metastatic lesions and compares predictions with clinical data. The study finds that most detectable lesions harbor multiple resistant subclones and provides insights for designing treatment strategies to control resistance.
documents/EFTA01201684.pdf
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