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Interpreting whole genome and exome sequencing data of individual gastric cancer samples

BACKGROUND: Gastric cancer is the fourth most common cancer and the second leading cause of cancer death worldwide. In order to understand the genetic background, we sequenced the whole exome and the whole genome of one microsatellite stable as well as one microsatellite unstable tumor and the match...

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Autores principales: Esser, Daniela, Holze, Niklas, Haag, Jochen, Schreiber, Stefan, Krüger, Sandra, Warneke, Viktoria, Rosenstiel, Philip, Röcken, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501078/
https://www.ncbi.nlm.nih.gov/pubmed/28683819
http://dx.doi.org/10.1186/s12864-017-3895-z
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author Esser, Daniela
Holze, Niklas
Haag, Jochen
Schreiber, Stefan
Krüger, Sandra
Warneke, Viktoria
Rosenstiel, Philip
Röcken, Christoph
author_facet Esser, Daniela
Holze, Niklas
Haag, Jochen
Schreiber, Stefan
Krüger, Sandra
Warneke, Viktoria
Rosenstiel, Philip
Röcken, Christoph
author_sort Esser, Daniela
collection PubMed
description BACKGROUND: Gastric cancer is the fourth most common cancer and the second leading cause of cancer death worldwide. In order to understand the genetic background, we sequenced the whole exome and the whole genome of one microsatellite stable as well as one microsatellite unstable tumor and the matched healthy tissue on two different NGS platforms. We here aimed to provide a comparative approach for individual clinical tumor sequencing and annotation using different sequencing technologies and mutation calling algorithms. RESULTS: We applied a population-based whole genome resource as a novel pathway-based filter for interpretation of genomic alterations from single nucleotide variations (SNV), indels, and large structural variations. In addition to a comparison with tumor genome database resources and a filtering approach using data from the 1000 Genomes Project, we performed pyrosequencing analysis and immunohistochemistry in a large cohort of 428 independent gastric cancer cases. CONCLUSION: We here provide an example comparing the usefulness and potential pitfalls of different technologies for a clinical interpretation of genomic sequence data of individual gastric cancer samples. Using different filtering approaches, we identified a multitude of novel potentially damaging mutations and could show a validated association between a mutation in GNAS and gastric cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3895-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-55010782017-07-10 Interpreting whole genome and exome sequencing data of individual gastric cancer samples Esser, Daniela Holze, Niklas Haag, Jochen Schreiber, Stefan Krüger, Sandra Warneke, Viktoria Rosenstiel, Philip Röcken, Christoph BMC Genomics Research Article BACKGROUND: Gastric cancer is the fourth most common cancer and the second leading cause of cancer death worldwide. In order to understand the genetic background, we sequenced the whole exome and the whole genome of one microsatellite stable as well as one microsatellite unstable tumor and the matched healthy tissue on two different NGS platforms. We here aimed to provide a comparative approach for individual clinical tumor sequencing and annotation using different sequencing technologies and mutation calling algorithms. RESULTS: We applied a population-based whole genome resource as a novel pathway-based filter for interpretation of genomic alterations from single nucleotide variations (SNV), indels, and large structural variations. In addition to a comparison with tumor genome database resources and a filtering approach using data from the 1000 Genomes Project, we performed pyrosequencing analysis and immunohistochemistry in a large cohort of 428 independent gastric cancer cases. CONCLUSION: We here provide an example comparing the usefulness and potential pitfalls of different technologies for a clinical interpretation of genomic sequence data of individual gastric cancer samples. Using different filtering approaches, we identified a multitude of novel potentially damaging mutations and could show a validated association between a mutation in GNAS and gastric cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3895-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-07-06 /pmc/articles/PMC5501078/ /pubmed/28683819 http://dx.doi.org/10.1186/s12864-017-3895-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Esser, Daniela
Holze, Niklas
Haag, Jochen
Schreiber, Stefan
Krüger, Sandra
Warneke, Viktoria
Rosenstiel, Philip
Röcken, Christoph
Interpreting whole genome and exome sequencing data of individual gastric cancer samples
title Interpreting whole genome and exome sequencing data of individual gastric cancer samples
title_full Interpreting whole genome and exome sequencing data of individual gastric cancer samples
title_fullStr Interpreting whole genome and exome sequencing data of individual gastric cancer samples
title_full_unstemmed Interpreting whole genome and exome sequencing data of individual gastric cancer samples
title_short Interpreting whole genome and exome sequencing data of individual gastric cancer samples
title_sort interpreting whole genome and exome sequencing data of individual gastric cancer samples
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501078/
https://www.ncbi.nlm.nih.gov/pubmed/28683819
http://dx.doi.org/10.1186/s12864-017-3895-z
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