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Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling

Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle‐level understanding is a clinically important issue. To achieve this goal, an interdisc...

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Detalles Bibliográficos
Autores principales: Niida, Atsushi, Nagayama, Satoshi, Miyano, Satoru, Mimori, Koshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891172/
https://www.ncbi.nlm.nih.gov/pubmed/29352488
http://dx.doi.org/10.1111/cas.13510
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author Niida, Atsushi
Nagayama, Satoshi
Miyano, Satoru
Mimori, Koshi
author_facet Niida, Atsushi
Nagayama, Satoshi
Miyano, Satoru
Mimori, Koshi
author_sort Niida, Atsushi
collection PubMed
description Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle‐level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting.
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spelling pubmed-58911722018-04-13 Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling Niida, Atsushi Nagayama, Satoshi Miyano, Satoru Mimori, Koshi Cancer Sci Review Articles Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle‐level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting. John Wiley and Sons Inc. 2018-02-28 2018-04 /pmc/articles/PMC5891172/ /pubmed/29352488 http://dx.doi.org/10.1111/cas.13510 Text en © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Review Articles
Niida, Atsushi
Nagayama, Satoshi
Miyano, Satoru
Mimori, Koshi
Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
title Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
title_full Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
title_fullStr Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
title_full_unstemmed Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
title_short Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
title_sort understanding intratumor heterogeneity by combining genome analysis and mathematical modeling
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891172/
https://www.ncbi.nlm.nih.gov/pubmed/29352488
http://dx.doi.org/10.1111/cas.13510
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