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Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials
Currently, drug development efforts and clinical trials to test them are often prioritized by targeting genes with high frequencies of somatic variants among tumors. However, differences in oncogenic mutation rate—not necessarily the effect the variant has on tumor growth—contribute enormously to so...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5976461/ https://www.ncbi.nlm.nih.gov/pubmed/29854275 http://dx.doi.org/10.18632/oncotarget.25155 |
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author | Wilkins, Jon F. Cannataro, Vincent L. Shuch, Brian Townsend, Jeffrey P. |
author_facet | Wilkins, Jon F. Cannataro, Vincent L. Shuch, Brian Townsend, Jeffrey P. |
author_sort | Wilkins, Jon F. |
collection | PubMed |
description | Currently, drug development efforts and clinical trials to test them are often prioritized by targeting genes with high frequencies of somatic variants among tumors. However, differences in oncogenic mutation rate—not necessarily the effect the variant has on tumor growth—contribute enormously to somatic variant frequency. We argue that decoupling the contributions of mutation and cancer lineage selection to the frequency of somatic variants among tumors is critical to understanding—and predicting—the therapeutic potential of different interventions. To provide an indicator of that strength of selection and therapeutic potential, the frequency at which we observe a given variant across patients must be modulated by our expectation given the mutation rate and target size to provide an indicator of that strength of selection and therapeutic potential. Additionally, antagonistic and synergistic epistasis among mutations also impacts the potential therapeutic benefit of targeted drug development. Quantitative approaches should be fostered that use the known genetic architectures of cancer types, decouple mutation rate, and provide rigorous guidance regarding investment in targeted drug development. By integrating evolutionary principles and detailed mechanistic knowledge into those approaches, we can maximize our ability to identify those targeted therapies most likely to yield substantial clinical benefit. |
format | Online Article Text |
id | pubmed-5976461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-59764612018-05-31 Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials Wilkins, Jon F. Cannataro, Vincent L. Shuch, Brian Townsend, Jeffrey P. Oncotarget Research Perspective Currently, drug development efforts and clinical trials to test them are often prioritized by targeting genes with high frequencies of somatic variants among tumors. However, differences in oncogenic mutation rate—not necessarily the effect the variant has on tumor growth—contribute enormously to somatic variant frequency. We argue that decoupling the contributions of mutation and cancer lineage selection to the frequency of somatic variants among tumors is critical to understanding—and predicting—the therapeutic potential of different interventions. To provide an indicator of that strength of selection and therapeutic potential, the frequency at which we observe a given variant across patients must be modulated by our expectation given the mutation rate and target size to provide an indicator of that strength of selection and therapeutic potential. Additionally, antagonistic and synergistic epistasis among mutations also impacts the potential therapeutic benefit of targeted drug development. Quantitative approaches should be fostered that use the known genetic architectures of cancer types, decouple mutation rate, and provide rigorous guidance regarding investment in targeted drug development. By integrating evolutionary principles and detailed mechanistic knowledge into those approaches, we can maximize our ability to identify those targeted therapies most likely to yield substantial clinical benefit. Impact Journals LLC 2018-04-27 /pmc/articles/PMC5976461/ /pubmed/29854275 http://dx.doi.org/10.18632/oncotarget.25155 Text en Copyright: © 2018 Wilkins et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Perspective Wilkins, Jon F. Cannataro, Vincent L. Shuch, Brian Townsend, Jeffrey P. Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
title | Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
title_full | Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
title_fullStr | Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
title_full_unstemmed | Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
title_short | Analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
title_sort | analysis of mutation, selection, and epistasis: an informed approach to cancer clinical trials |
topic | Research Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5976461/ https://www.ncbi.nlm.nih.gov/pubmed/29854275 http://dx.doi.org/10.18632/oncotarget.25155 |
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