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Optimal control to reach eco-evolutionary stability in metastatic castrate-resistant prostate cancer.

Authors :
Jessica Cunningham
Frank Thuijsman
Ralf Peeters
Yannick Viossat
Joel Brown
Robert Gatenby
Kateřina Staňková
Source :
PLoS ONE, Vol 15, Iss 12, p e0243386 (2020)
Publication Year :
2020
Publisher :
Public Library of Science (PLoS), 2020.

Abstract

In the absence of curative therapies, treatment of metastatic castrate-resistant prostate cancer (mCRPC) using currently available drugs can be improved by integrating evolutionary principles that govern proliferation of resistant subpopulations into current treatment protocols. Here we develop what is coined as an 'evolutionary stable therapy', within the context of the mathematical model that has been used to inform the first adaptive therapy clinical trial of mCRPC. The objective of this therapy is to maintain a stable polymorphic tumor heterogeneity of sensitive and resistant cells to therapy in order to prolong treatment efficacy and progression free survival. Optimal control analysis shows that an increasing dose titration protocol, a very common clinical dosing process, can achieve tumor stabilization for a wide range of potential initial tumor compositions and volumes. Furthermore, larger tumor volumes may counter intuitively be more likely to be stabilized if sensitive cells dominate the tumor composition at time of initial treatment, suggesting a delay of initial treatment could prove beneficial. While it remains uncertain if metastatic disease in humans has the properties that allow it to be truly stabilized, the benefits of a dose titration protocol warrant additional pre-clinical and clinical investigations.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
15
Issue :
12
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.9a498e2f3f9646fc8c36bc3b3e54ebf0
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0243386