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Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)

In this study, we investigated the impact of initial tumor volume, rate of tumor growth, cohort size, study duration, and data analysis method on chemotherapy treatment response classifications in patient-derived xenografts (PDXs). The analyses were conducted on cisplatin treatment response data for...

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Autores principales: Malcolm, Joan E., Stearns, Timothy M., Airhart, Susan D., Graber, Joel H., Bult, Carol J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441558/
https://www.ncbi.nlm.nih.gov/pubmed/30944774
http://dx.doi.org/10.7717/peerj.6586
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author Malcolm, Joan E.
Stearns, Timothy M.
Airhart, Susan D.
Graber, Joel H.
Bult, Carol J.
author_facet Malcolm, Joan E.
Stearns, Timothy M.
Airhart, Susan D.
Graber, Joel H.
Bult, Carol J.
author_sort Malcolm, Joan E.
collection PubMed
description In this study, we investigated the impact of initial tumor volume, rate of tumor growth, cohort size, study duration, and data analysis method on chemotherapy treatment response classifications in patient-derived xenografts (PDXs). The analyses were conducted on cisplatin treatment response data for 70 PDX models representing ten cancer types with up to 28-day study duration and cohort sizes of 3–10 tumor-bearing mice. The results demonstrated that a 21-day dosing study using a cohort size of eight was necessary to reliably detect responsive models (i.e., tumor volume ratio of treated animals to control between 0.1 and 0.42)—independent of analysis method. A cohort of three tumor-bearing animals led to a reliable classification of models that were both highly responsive and highly nonresponsive to cisplatin (i.e., tumor volume ratio of treated animals to control animals less than 0.10). In our set of PDXs, we found that tumor growth rate in the control group impacted treatment response classification more than initial tumor volume. We repeated the study design factors using docetaxel treated PDXs with consistent results. Our results highlight the importance of defining endpoints for PDX dosing studies when deciding the size of cohorts to use in dosing studies and illustrate that response classifications for a study do not differ significantly across the commonly used analysis methods that are based on tumor volume changes in treatment versus control groups.
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spelling pubmed-64415582019-04-03 Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX) Malcolm, Joan E. Stearns, Timothy M. Airhart, Susan D. Graber, Joel H. Bult, Carol J. PeerJ Bioengineering In this study, we investigated the impact of initial tumor volume, rate of tumor growth, cohort size, study duration, and data analysis method on chemotherapy treatment response classifications in patient-derived xenografts (PDXs). The analyses were conducted on cisplatin treatment response data for 70 PDX models representing ten cancer types with up to 28-day study duration and cohort sizes of 3–10 tumor-bearing mice. The results demonstrated that a 21-day dosing study using a cohort size of eight was necessary to reliably detect responsive models (i.e., tumor volume ratio of treated animals to control between 0.1 and 0.42)—independent of analysis method. A cohort of three tumor-bearing animals led to a reliable classification of models that were both highly responsive and highly nonresponsive to cisplatin (i.e., tumor volume ratio of treated animals to control animals less than 0.10). In our set of PDXs, we found that tumor growth rate in the control group impacted treatment response classification more than initial tumor volume. We repeated the study design factors using docetaxel treated PDXs with consistent results. Our results highlight the importance of defining endpoints for PDX dosing studies when deciding the size of cohorts to use in dosing studies and illustrate that response classifications for a study do not differ significantly across the commonly used analysis methods that are based on tumor volume changes in treatment versus control groups. PeerJ Inc. 2019-03-28 /pmc/articles/PMC6441558/ /pubmed/30944774 http://dx.doi.org/10.7717/peerj.6586 Text en ©2019 Malcolm et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioengineering
Malcolm, Joan E.
Stearns, Timothy M.
Airhart, Susan D.
Graber, Joel H.
Bult, Carol J.
Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)
title Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)
title_full Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)
title_fullStr Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)
title_full_unstemmed Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)
title_short Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)
title_sort factors that influence response classifications in chemotherapy treated patient-derived xenografts (pdx)
topic Bioengineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441558/
https://www.ncbi.nlm.nih.gov/pubmed/30944774
http://dx.doi.org/10.7717/peerj.6586
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