Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation

Abstract Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover...

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Autores principales:	Lőrinc Pongor, Hajnalka Harami-Papp, Előd Méhes, András Czirók, Balázs Győrffy
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8fe08173e9b344939e6095849762a2a4
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spelling	oai:doaj.org-article:8fe08173e9b344939e6095849762a2a42021-12-02T15:05:40ZCell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation10.1038/s41598-017-07487-z2045-2322https://doaj.org/article/8fe08173e9b344939e6095849762a2a42017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-07487-zhttps://doaj.org/toc/2045-2322Abstract Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover will account for mutational proportions. We show that cancer cells can penetrate neighboring and distinct areas in a matter of days. In next generation sequencing runs, higher proportions of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. When multiple cell lines were co-cultured, cellular movement altered observed mutation frequency by up to 18.5%. We propose that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. In brief, cell movement will lead to a significant technical (sampling) bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses.Lőrinc PongorHajnalka Harami-PappElőd MéhesAndrás CzirókBalázs GyőrffyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lőrinc Pongor Hajnalka Harami-Papp Előd Méhes András Czirók Balázs Győrffy Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation
description	Abstract Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover will account for mutational proportions. We show that cancer cells can penetrate neighboring and distinct areas in a matter of days. In next generation sequencing runs, higher proportions of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. When multiple cell lines were co-cultured, cellular movement altered observed mutation frequency by up to 18.5%. We propose that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. In brief, cell movement will lead to a significant technical (sampling) bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses.
format	article
author	Lőrinc Pongor Hajnalka Harami-Papp Előd Méhes András Czirók Balázs Győrffy
author_facet	Lőrinc Pongor Hajnalka Harami-Papp Előd Méhes András Czirók Balázs Győrffy
author_sort	Lőrinc Pongor
title	Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation
title_short	Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation
title_full	Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation
title_fullStr	Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation
title_full_unstemmed	Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation
title_sort	cell dispersal influences tumor heterogeneity and introduces a bias in ngs data interpretation
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/8fe08173e9b344939e6095849762a2a4
work_keys_str_mv	AT lorincpongor celldispersalinfluencestumorheterogeneityandintroducesabiasinngsdatainterpretation AT hajnalkaharamipapp celldispersalinfluencestumorheterogeneityandintroducesabiasinngsdatainterpretation AT elodmehes celldispersalinfluencestumorheterogeneityandintroducesabiasinngsdatainterpretation AT andrasczirok celldispersalinfluencestumorheterogeneityandintroducesabiasinngsdatainterpretation AT balazsgyorffy celldispersalinfluencestumorheterogeneityandintroducesabiasinngsdatainterpretation
_version_	1718388780086329344

Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation

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