Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.

Cancer develops through a multistep process in which normal cells progress to malignant tumors via the evolution of their genomes as a result of the acquisition of mutations in cancer driver genes. The number, identity and mode of action of cancer driver genes, and how they contribute to tumor evolu...

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Main Authors: Christiaan Klijn, Marco J Koudijs, Jaap Kool, Jelle ten Hoeve, Mandy Boer, Joost de Moes, Waseem Akhtar, Martine van Miltenburg, Annabel Vendel-Zwaagstra, Marcel J T Reinders, David J Adams, Maarten van Lohuizen, John Hilkens, Lodewyk F A Wessels, Jos Jonkers
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3653918?pdf=render
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spelling doaj-235dc4eda4554bda99cc85df5fced7112020-11-24T20:50:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0185e6211310.1371/journal.pone.0062113Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.Christiaan KlijnMarco J KoudijsJaap KoolJelle ten HoeveMandy BoerJoost de MoesWaseem AkhtarMartine van MiltenburgAnnabel Vendel-ZwaagstraMarcel J T ReindersDavid J AdamsMaarten van LohuizenJohn HilkensLodewyk F A WesselsJos JonkersCancer develops through a multistep process in which normal cells progress to malignant tumors via the evolution of their genomes as a result of the acquisition of mutations in cancer driver genes. The number, identity and mode of action of cancer driver genes, and how they contribute to tumor evolution is largely unknown. This study deployed the Mouse Mammary Tumor Virus (MMTV) as an insertional mutagen to find both the driver genes and the networks in which they function. Using deep insertion site sequencing we identified around 31000 retroviral integration sites in 604 MMTV-induced mammary tumors from mice with mammary gland-specific deletion of Trp53, Pten heterozygous knockout mice, or wildtype strains. We identified 18 known common integration sites (CISs) and 12 previously unknown CISs marking new candidate cancer genes. Members of the Wnt, Fgf, Fgfr, Rspo and Pdgfr gene families were commonly mutated in a mutually exclusive fashion. The sequence data we generated yielded also information on the clonality of insertions in individual tumors, allowing us to develop a data-driven model of MMTV-induced tumor development. Insertional mutations near Wnt and Fgf genes mark the earliest "initiating" events in MMTV induced tumorigenesis, whereas Fgfr genes are targeted later during tumor progression. Our data shows that insertional mutagenesis can be used to discover the mutational networks, the timing of mutations, and the genes that initiate and drive tumor evolution.http://europepmc.org/articles/PMC3653918?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Christiaan Klijn
Marco J Koudijs
Jaap Kool
Jelle ten Hoeve
Mandy Boer
Joost de Moes
Waseem Akhtar
Martine van Miltenburg
Annabel Vendel-Zwaagstra
Marcel J T Reinders
David J Adams
Maarten van Lohuizen
John Hilkens
Lodewyk F A Wessels
Jos Jonkers
spellingShingle Christiaan Klijn
Marco J Koudijs
Jaap Kool
Jelle ten Hoeve
Mandy Boer
Joost de Moes
Waseem Akhtar
Martine van Miltenburg
Annabel Vendel-Zwaagstra
Marcel J T Reinders
David J Adams
Maarten van Lohuizen
John Hilkens
Lodewyk F A Wessels
Jos Jonkers
Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.
PLoS ONE
author_facet Christiaan Klijn
Marco J Koudijs
Jaap Kool
Jelle ten Hoeve
Mandy Boer
Joost de Moes
Waseem Akhtar
Martine van Miltenburg
Annabel Vendel-Zwaagstra
Marcel J T Reinders
David J Adams
Maarten van Lohuizen
John Hilkens
Lodewyk F A Wessels
Jos Jonkers
author_sort Christiaan Klijn
title Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.
title_short Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.
title_full Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.
title_fullStr Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.
title_full_unstemmed Analysis of tumor heterogeneity and cancer gene networks using deep sequencing of MMTV-induced mouse mammary tumors.
title_sort analysis of tumor heterogeneity and cancer gene networks using deep sequencing of mmtv-induced mouse mammary tumors.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description Cancer develops through a multistep process in which normal cells progress to malignant tumors via the evolution of their genomes as a result of the acquisition of mutations in cancer driver genes. The number, identity and mode of action of cancer driver genes, and how they contribute to tumor evolution is largely unknown. This study deployed the Mouse Mammary Tumor Virus (MMTV) as an insertional mutagen to find both the driver genes and the networks in which they function. Using deep insertion site sequencing we identified around 31000 retroviral integration sites in 604 MMTV-induced mammary tumors from mice with mammary gland-specific deletion of Trp53, Pten heterozygous knockout mice, or wildtype strains. We identified 18 known common integration sites (CISs) and 12 previously unknown CISs marking new candidate cancer genes. Members of the Wnt, Fgf, Fgfr, Rspo and Pdgfr gene families were commonly mutated in a mutually exclusive fashion. The sequence data we generated yielded also information on the clonality of insertions in individual tumors, allowing us to develop a data-driven model of MMTV-induced tumor development. Insertional mutations near Wnt and Fgf genes mark the earliest "initiating" events in MMTV induced tumorigenesis, whereas Fgfr genes are targeted later during tumor progression. Our data shows that insertional mutagenesis can be used to discover the mutational networks, the timing of mutations, and the genes that initiate and drive tumor evolution.
url http://europepmc.org/articles/PMC3653918?pdf=render
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