Modeling the Subclonal Evolution of Cancer Cell Populations

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Abstract
Increasing evidence shows that tumor clonal architectures are often the consequence of a complex branching process, yet little is known about the expected dynamics and extent to which these divergent subclonal expansions occur. Here, we develop and implement more than 88,000 instances of a stochastic evolutionary model simulating genetic drift and neoplastic progression. Under different combinations of population genetic parameter values, including those estimated for colorectal cancer and glioblastoma multiforme, the distribution of sizes of subclones carrying driver mutations had a heavy right tail at the time of tumor detection, with only 1 to 4 dominant clones present at ≥10% frequency. In contrast, the vast majority of subclones were present at Significance: The model presented in this paper addresses tumor heterogeneity by framing expectations for the number of resistant subclones in a tumor, with implications for future studies of the evolution of therapeutic resistance. Cancer Res; 78(3); 830–9. ©2017 AACR.
Funding Information
  • School of Life Sciences, Arizona State University (ASU School of Life Sciences) (Startup)
  • NIH (R01 CA140657)
  • CDMRP Breast Cancer Research Program Award (BC132057)
  • NIH (5R21CA196460)
  • Biodesign Institute, Arizona State University (Startup)
  • Flinn Foundation (Pilot Funds)
  • Breast Cancer Research Foundation (BCRF) (Award)
  • NIH (R21 CA196460)
  • NIH (P01 CA91955)
  • NIH (R01 CA149566)
  • NIH (R01 CA170595)
  • NIH (R01 CA185138)

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