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In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment
Angiogenesis is a crucial step in tumour progression, as this process allows tumours to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenesis remains a viable strategy for cancer therapy. However, anti-angiogenic therapy has not proved to be...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127173/ https://www.ncbi.nlm.nih.gov/pubmed/30135261 http://dx.doi.org/10.1098/rsif.2018.0243 |
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author | Wu, Qianhui Arnheim, Alyssa D. Finley, Stacey D. |
author_facet | Wu, Qianhui Arnheim, Alyssa D. Finley, Stacey D. |
author_sort | Wu, Qianhui |
collection | PubMed |
description | Angiogenesis is a crucial step in tumour progression, as this process allows tumours to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenesis remains a viable strategy for cancer therapy. However, anti-angiogenic therapy has not proved to be effective in reducing tumour growth across a wide range of tumours, and no reliable predictive biomarkers have been found to determine the efficacy of anti-angiogenic treatment. Using our previously established computational model of tumour-bearing mice, we sought to determine whether tumour growth kinetic parameters could be used to predict the outcome of anti-angiogenic treatment. A model trained with datasets from six in vivo mice studies was used to generate a randomized in silico tumour-bearing mouse population. We analysed tumour growth in untreated mice (control) and mice treated with an anti-angiogenic agent and determined the Kaplan–Meier survival estimates based on simulated tumour volume data. We found that the ratio between two kinetic parameters, k(0) and k(1), which characterize the tumour's exponential and linear growth rates, as well as k(1) alone, can be used as prognostic biomarkers of the population survival outcome. Our work demonstrates a robust, quantitative approach for identifying tumour growth kinetic parameters as prognostic biomarkers and serves as a template that can be used to identify other biomarkers for anti-angiogenic treatment. |
format | Online Article Text |
id | pubmed-6127173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-61271732018-09-07 In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment Wu, Qianhui Arnheim, Alyssa D. Finley, Stacey D. J R Soc Interface Life Sciences–Engineering interface Angiogenesis is a crucial step in tumour progression, as this process allows tumours to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenesis remains a viable strategy for cancer therapy. However, anti-angiogenic therapy has not proved to be effective in reducing tumour growth across a wide range of tumours, and no reliable predictive biomarkers have been found to determine the efficacy of anti-angiogenic treatment. Using our previously established computational model of tumour-bearing mice, we sought to determine whether tumour growth kinetic parameters could be used to predict the outcome of anti-angiogenic treatment. A model trained with datasets from six in vivo mice studies was used to generate a randomized in silico tumour-bearing mouse population. We analysed tumour growth in untreated mice (control) and mice treated with an anti-angiogenic agent and determined the Kaplan–Meier survival estimates based on simulated tumour volume data. We found that the ratio between two kinetic parameters, k(0) and k(1), which characterize the tumour's exponential and linear growth rates, as well as k(1) alone, can be used as prognostic biomarkers of the population survival outcome. Our work demonstrates a robust, quantitative approach for identifying tumour growth kinetic parameters as prognostic biomarkers and serves as a template that can be used to identify other biomarkers for anti-angiogenic treatment. The Royal Society 2018-08 2018-08-22 /pmc/articles/PMC6127173/ /pubmed/30135261 http://dx.doi.org/10.1098/rsif.2018.0243 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Life Sciences–Engineering interface Wu, Qianhui Arnheim, Alyssa D. Finley, Stacey D. In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
title | In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
title_full | In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
title_fullStr | In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
title_full_unstemmed | In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
title_short | In silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
title_sort | in silico mouse study identifies tumour growth kinetics as biomarkers for the outcome of anti-angiogenic treatment |
topic | Life Sciences–Engineering interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127173/ https://www.ncbi.nlm.nih.gov/pubmed/30135261 http://dx.doi.org/10.1098/rsif.2018.0243 |
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