Dynamics and implications of models for intermittent androgen suppression therapy

Tin Phan, Changhan He, Alejandro Martinez, Yang Kuang

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

In this paper, we formulate a three cell population model of intermittent androgen suppression therapy for cancer patients to study the treatment resistance development. We compare it with other models that have different underlying cell population structure using patient prostate specific antigen (PSA) and androgen data sets. Our results show that in the absence of extensive data, a two cell population structure performs slightly better in replicating and forecasting the dynamics observed in clinical PSA data. We also observe that at least one absorbing state should be present in the cell population structure of a plausible model for it to produce treatment resistance under continuous hormonal therapy. This suggests that the heterogeneity of prostate cancer cell population can be represented by two types of cells differentiated by their level of dependence on androgen, where the two types are linked via an irreversible transformation.

Original languageEnglish (US)
Pages (from-to)187-204
Number of pages18
JournalMathematical Biosciences and Engineering
Volume16
Issue number1
DOIs
StatePublished - Jan 1 2019

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Keywords

  • cell quota model
  • data fitting
  • hormonal therapy
  • population structure
  • predict treatment outcome
  • prostate cancer modeling

ASJC Scopus subject areas

  • Modeling and Simulation
  • Agricultural and Biological Sciences(all)
  • Computational Mathematics
  • Applied Mathematics

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