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Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures

Human cancers accumulate various mutations during development and consist of highly heterogeneous cell populations. This phenomenon is called intratumor heterogeneity (ITH). ITH is known to be involved in tumor growth, progression, invasion, and metastasis, presenting obstacles to accurate diagnoses...

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Autores principales: Kikutake, Chie, Yoshihara, Minako, Sato, Tetsuya, Saito, Daisuke, Suyama, Mikita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6340877/
https://www.ncbi.nlm.nih.gov/pubmed/30701024
http://dx.doi.org/10.18632/oncotarget.26485
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author Kikutake, Chie
Yoshihara, Minako
Sato, Tetsuya
Saito, Daisuke
Suyama, Mikita
author_facet Kikutake, Chie
Yoshihara, Minako
Sato, Tetsuya
Saito, Daisuke
Suyama, Mikita
author_sort Kikutake, Chie
collection PubMed
description Human cancers accumulate various mutations during development and consist of highly heterogeneous cell populations. This phenomenon is called intratumor heterogeneity (ITH). ITH is known to be involved in tumor growth, progression, invasion, and metastasis, presenting obstacles to accurate diagnoses and effective treatments. Numerous studies have explored the dynamics of ITH, including constructions of phylogenetic trees in cancer samples using multiregional ultradeep sequencing and simulations of evolution using statistical models. Although ITH is associated with prognosis, it is still challenging to use the characteristics of ITH as prognostic factors because of difficulties in quantifying ITH precisely. In this study, we analyzed the relationship between patient prognosis and the distribution of variant allele frequencies (VAFs) in cancer samples (n = 6,064) across 16 cancer types registered in The Cancer Genome Atlas. To measure VAF distributions multidimensionally, we adopted parameters that define the shape of VAF distributions and evaluated the relationships between these parameters and prognosis. In seven cancer types, we found significant relationships between prognosis and VAF distributions. Moreover, we observed that samples with a larger amount of mutations were not necessarily linked to worse prognosis. By evaluating the ITH from multidimensional viewpoints, it will be possible to provide a more accurate prediction of cancer prognosis.
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spelling pubmed-63408772019-01-30 Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures Kikutake, Chie Yoshihara, Minako Sato, Tetsuya Saito, Daisuke Suyama, Mikita Oncotarget Research Paper Human cancers accumulate various mutations during development and consist of highly heterogeneous cell populations. This phenomenon is called intratumor heterogeneity (ITH). ITH is known to be involved in tumor growth, progression, invasion, and metastasis, presenting obstacles to accurate diagnoses and effective treatments. Numerous studies have explored the dynamics of ITH, including constructions of phylogenetic trees in cancer samples using multiregional ultradeep sequencing and simulations of evolution using statistical models. Although ITH is associated with prognosis, it is still challenging to use the characteristics of ITH as prognostic factors because of difficulties in quantifying ITH precisely. In this study, we analyzed the relationship between patient prognosis and the distribution of variant allele frequencies (VAFs) in cancer samples (n = 6,064) across 16 cancer types registered in The Cancer Genome Atlas. To measure VAF distributions multidimensionally, we adopted parameters that define the shape of VAF distributions and evaluated the relationships between these parameters and prognosis. In seven cancer types, we found significant relationships between prognosis and VAF distributions. Moreover, we observed that samples with a larger amount of mutations were not necessarily linked to worse prognosis. By evaluating the ITH from multidimensional viewpoints, it will be possible to provide a more accurate prediction of cancer prognosis. Impact Journals LLC 2018-12-28 /pmc/articles/PMC6340877/ /pubmed/30701024 http://dx.doi.org/10.18632/oncotarget.26485 Text en Copyright: © 2018 Kikutake 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 Paper
Kikutake, Chie
Yoshihara, Minako
Sato, Tetsuya
Saito, Daisuke
Suyama, Mikita
Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
title Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
title_full Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
title_fullStr Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
title_full_unstemmed Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
title_short Pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
title_sort pan-cancer analysis of intratumor heterogeneity associated with patient prognosis using multidimensional measures
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6340877/
https://www.ncbi.nlm.nih.gov/pubmed/30701024
http://dx.doi.org/10.18632/oncotarget.26485
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