Characterizing inhibited tumor growth in stem-cell-driven non-spatial cancers

Ignacio A Rodriguez-Brenes1, Dominik Wodarz1, Natalia L Komarova1

  • 1Department of Mathematics, University of California, Irvine, CA 92651, USA; Department of Ecology and Evolution, University of California, Irvine, CA 92651, USA.

Mathematical Biosciences
|September 8, 2015
PubMed

Insights

Cancer growth can be slow and sub-exponential when feedback inhibition on stem cell self-renewal is lost. This study models this inhibited growth, revealing power-law dynamics for stem and differentiated cells, with implications for slow-progressing cancers.

Area of Science:

  • Oncology
  • Mathematical Biology
  • Cell Biology

Background:

  • Homeostasis in healthy tissues relies on regulated stem cell division and self-renewal via negative feedback.
  • Cancer involves escaping these regulatory mechanisms, leading to abnormal growth.
  • Previous work identified 'inhibited growth' in non-solid tumors with partial loss of feedback control.

Purpose of the Study:

  • To mathematically model and characterize the cell dynamics of inhibited cancer growth.
  • To analyze the impact of feedback inhibition strength on tumor progression using Hill equations.
  • To understand the implications for slow-progressing cancers like Chronic Myeloid Leukemia (CML).

Main Methods:

  • Modeling feedback inhibition of stem cell self-renewal and division using Hill equations.
  • Deriving asymptotic approximations for stem and differentiated cell population growth rates.
  • Analyzing the mathematical relationship between growth rates and the Hill coefficient (k).

Main Results:

  • Stem cells exhibit power-law growth: t^(1/k+1).
  • Differentiated cells exhibit power-law growth: t^(1/k).
  • The fraction of undifferentiated cells increases as the tumor mass grows.

Conclusions:

  • The strength of the inhibitory signal (k) dictates the specific power-law dynamics of inhibited cancer growth.
  • Undifferentiated cells increasingly dominate the tumor population over time.
  • These findings offer insights into the progression of slow-growing cancers and potential therapeutic strategies.