Contrasting the impact of cytotoxic and cytostatic drug therapies on tumour progression Journal Article
| Authors: | Anttila, J. V.; Shubin, M.; Cairns, J.; Borse, F.; Guo, Q.; Mononen, T.; Vázquez-García, I.; Pulkkinen, O.; Mustonen, V. |
| Article Title: | Contrasting the impact of cytotoxic and cytostatic drug therapies on tumour progression |
| Abstract: | A tumour grows when the total division (birth) rate of its cells exceeds their total mortality (death) rate. The capability for uncontrolled growth within the host tissue is acquired via the accumulation of driver mutations which enable the tumour to progress through various hallmarks of cancer. We present a mathematical model of the penultimate stage in such a progression. We assume the tumour has reached the limit of its present growth potential due to cell competition that either results in total birth rate reduction or death rate increase. The tumour can then progress to the final stage by either seeding a metastasis or acquiring a driver mutation. We influence the ensuing evolutionary dynamics by cytotoxic (increasing death rate) or cytostatic (decreasing birth rate) therapy while keeping the effect of the therapy on net growth reduction constant. Comparing the treatments head to head we derive conditions for choosing optimal therapy. We quantify how the choice and the related gain of optimal therapy depends on driver mutation, metastasis, intrinsic cell birth and death rates, and the details of cell competition. We show that detailed understanding of the cell population dynamics could be exploited in choosing the right mode of treatment with substantial therapy gains. © 2019 Anttila et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Keywords: | controlled study; cytotoxic agent; phenotype; cell population; mutational analysis; mathematical model; metastasis potential; tumor growth; tumor seeding; growth rate; cytostatic agent; mortality rate; birth rate; limit of quantitation; human; article; driver mutation; net growth reduction constant |
| Journal Title: | PLoS Computational Biology |
| Volume: | 15 |
| Issue: | 11 |
| ISSN: | 1553-7358 |
| Publisher: | Public Library of Science |
| Date Published: | 2019-11-01 |
| Start Page: | e1007493 |
| Language: | English |
| DOI: | 10.1371/journal.pcbi.1007493 |
| PUBMED: | 31738747 |
| PROVIDER: | scopus |
| PMCID: | PMC6886869 |
| DOI/URL: | |
| Notes: | Article -- Source: Scopus |
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