Cancer as a moving target: understanding the composition and rebound growth kinetics of recurrent tumors

摘要: We introduce a stochastic branching process model of diversity in recurrent tumors whose growth is driven by drug resistance. Here, an initially declining population can escape certain extinction via the production mutants fitness drawn at random from mutational landscape. Using combination analytical and computational techniques, we study rebound kinetics composition relapsed tumor. find that strongly affected shape distribution. Interestingly, exhibits qualitative shift behavior depending on balance between mutation rate initial size. In high settings, recurrence timing strong predictor tumor, whereas low regime, good tumor aggressiveness. Analysis reveals stochasticity survival small resistant populations rather than variability resistance sensitive population, opposite true setting. These conclusions contribute to evolutionary understanding suitability size time as prognostic predictive factors cancer.