Dynamics and implications of models for intermittent androgen suppression therapy

Tin Phan; Changhan He; Alejandro Martinez; Yang Kuang; Tin Phan; Changhan He; Alejandro Martinez; Yang Kuang

doi:10.3934/mbe.2019010

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 1: 187-204. doi: 10.3934/mbe.2019010

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Dynamics and implications of models for intermittent androgen suppression therapy

1.
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, USA
2.
Department of Physics,Department of Physics, Tempe, AZ 85287, USA

Received: 11 October 2018 Accepted: 12 October 2018 Published: 11 December 2018

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.
- prostate cancer modeling,
- data fitting,
- hormonal therapy,
- population structure,
- predict treatment outcome,
- cell quota model
Citation: Tin Phan, Changhan He, Alejandro Martinez, Yang Kuang. Dynamics and implications of models for intermittent androgen suppression therapy[J]. Mathematical Biosciences and Engineering, 2019, 16(1): 187-204. doi: 10.3934/mbe.2019010

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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.

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