Next-generation sequencing analysis and algorithms for PDX and CDX models

Autores
Khandelwal, Garima; Girotti, Maria Romina; Smowton, Christopher; Taylor, Sam; Wirth, Christopher; Dynowski, Marek; Frese, Kristopher K.; Brady, Ged; Dive, Caroline; Marais, Richard; Miller, Crispin
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Patient-derived xenograft (PDX) and CTC-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these methods have been applied to multiple questions including the study of metastatic progression, genetic evolution and therapeutic drug responses. Since PDX and CDX models can recapitulate the highly heterogeneous characteristics of a patient tumor, as well as their response to chemotherapy, there is considerable interest in combining them with next-generation sequencing (NGS) in order to monitor the genomic, transcriptional, and epigenetic changes that accompany oncogenesis. When used for this purpose, their reliability is highly dependent on being able to accurately distinguish between sequencing reads that originate from the host, and those that arise from the xenograft itself. Here we demonstrate that failure to correctly identify contaminating host reads, when analyzing DNA- and RNA-sequencing (DNA-Seq and RNA-Seq) data from PDX and CDX models is a major confounding factor that can lead to incorrect mutation calls and a failure to identify canonical mutation signatures associated with tumorigenicity. In addition, a highly sensitive algorithm and open source software tool for identifying and removing contaminating host sequences is described. Importantly, when applied to PDX and CDX models of melanoma, these data demonstrate its utility as a sensitive and selective tool for the correction of PDX- and CDX-derived whole exome and RNA-Seq data.
Fil: Khandelwal, Garima. University of Manchester; Reino Unido
Fil: Girotti, Maria Romina. University of Manchester; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Smowton, Christopher. University of Manchester; Reino Unido
Fil: Taylor, Sam. University of Manchester; Reino Unido
Fil: Wirth, Christopher. University of Manchester; Reino Unido
Fil: Dynowski, Marek. University of Manchester; Reino Unido
Fil: Frese, Kristopher K.. University of Manchester; Reino Unido
Fil: Brady, Ged. University of Manchester; Reino Unido
Fil: Dive, Caroline. University of Manchester; Reino Unido
Fil: Marais, Richard. University of Manchester; Reino Unido
Fil: Miller, Crispin. University of Manchester; Reino Unido
Materia
CDXs
PDXs
SEQUENCING
MELANOMA
Nivel de accesibilidad
acceso embargado
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/24586
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/24586
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Next-generation sequencing analysis and algorithms for PDX and CDX modelsKhandelwal, GarimaGirotti, Maria RominaSmowton, ChristopherTaylor, SamWirth, ChristopherDynowski, MarekFrese, Kristopher K.Brady, GedDive, CarolineMarais, RichardMiller, CrispinCDXsPDXsSEQUENCINGMELANOMAhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1https://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Patient-derived xenograft (PDX) and CTC-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these methods have been applied to multiple questions including the study of metastatic progression, genetic evolution and therapeutic drug responses. Since PDX and CDX models can recapitulate the highly heterogeneous characteristics of a patient tumor, as well as their response to chemotherapy, there is considerable interest in combining them with next-generation sequencing (NGS) in order to monitor the genomic, transcriptional, and epigenetic changes that accompany oncogenesis. When used for this purpose, their reliability is highly dependent on being able to accurately distinguish between sequencing reads that originate from the host, and those that arise from the xenograft itself. Here we demonstrate that failure to correctly identify contaminating host reads, when analyzing DNA- and RNA-sequencing (DNA-Seq and RNA-Seq) data from PDX and CDX models is a major confounding factor that can lead to incorrect mutation calls and a failure to identify canonical mutation signatures associated with tumorigenicity. In addition, a highly sensitive algorithm and open source software tool for identifying and removing contaminating host sequences is described. Importantly, when applied to PDX and CDX models of melanoma, these data demonstrate its utility as a sensitive and selective tool for the correction of PDX- and CDX-derived whole exome and RNA-Seq data.Fil: Khandelwal, Garima. University of Manchester; Reino UnidoFil: Girotti, Maria Romina. University of Manchester; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Smowton, Christopher. University of Manchester; Reino UnidoFil: Taylor, Sam. University of Manchester; Reino UnidoFil: Wirth, Christopher. University of Manchester; Reino UnidoFil: Dynowski, Marek. University of Manchester; Reino UnidoFil: Frese, Kristopher K.. University of Manchester; Reino UnidoFil: Brady, Ged. University of Manchester; Reino UnidoFil: Dive, Caroline. University of Manchester; Reino UnidoFil: Marais, Richard. University of Manchester; Reino UnidoFil: Miller, Crispin. University of Manchester; Reino UnidoAmerican Association for Cancer Research2017-04-25info:eu-repo/date/embargoEnd/2018-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/24586Khandelwal, Garima; Girotti, Maria Romina; Smowton, Christopher; Taylor, Sam; Wirth, Christopher; et al.; Next-generation sequencing analysis and algorithms for PDX and CDX models; American Association for Cancer Research; Molecular Cancer Research; 15; 8; 25-4-2017; 1012-10161541-77861557-3125CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://mcr.aacrjournals.org/content/15/8/1012.longinfo:eu-repo/semantics/altIdentifier/doi/10.1158/1541-7786.MCR-16-0431info:eu-repo/semantics/altIdentifier/pmid/28442585info:eu-repo/semantics/embargoedAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:37:29Zoai:ri.conicet.gov.ar:11336/24586instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:37:29.707CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Next-generation sequencing analysis and algorithms for PDX and CDX models
title Next-generation sequencing analysis and algorithms for PDX and CDX models
spellingShingle Next-generation sequencing analysis and algorithms for PDX and CDX models
Khandelwal, Garima
CDXs
PDXs
SEQUENCING
MELANOMA
title_short Next-generation sequencing analysis and algorithms for PDX and CDX models
title_full Next-generation sequencing analysis and algorithms for PDX and CDX models
title_fullStr Next-generation sequencing analysis and algorithms for PDX and CDX models
title_full_unstemmed Next-generation sequencing analysis and algorithms for PDX and CDX models
title_sort Next-generation sequencing analysis and algorithms for PDX and CDX models
dc.creator.none.fl_str_mv Khandelwal, Garima
Girotti, Maria Romina
Smowton, Christopher
Taylor, Sam
Wirth, Christopher
Dynowski, Marek
Frese, Kristopher K.
Brady, Ged
Dive, Caroline
Marais, Richard
Miller, Crispin
author Khandelwal, Garima
author_facet Khandelwal, Garima
Girotti, Maria Romina
Smowton, Christopher
Taylor, Sam
Wirth, Christopher
Dynowski, Marek
Frese, Kristopher K.
Brady, Ged
Dive, Caroline
Marais, Richard
Miller, Crispin
author_role author
author2 Girotti, Maria Romina
Smowton, Christopher
Taylor, Sam
Wirth, Christopher
Dynowski, Marek
Frese, Kristopher K.
Brady, Ged
Dive, Caroline
Marais, Richard
Miller, Crispin
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv CDXs
PDXs
SEQUENCING
MELANOMA
topic CDXs
PDXs
SEQUENCING
MELANOMA
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Patient-derived xenograft (PDX) and CTC-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these methods have been applied to multiple questions including the study of metastatic progression, genetic evolution and therapeutic drug responses. Since PDX and CDX models can recapitulate the highly heterogeneous characteristics of a patient tumor, as well as their response to chemotherapy, there is considerable interest in combining them with next-generation sequencing (NGS) in order to monitor the genomic, transcriptional, and epigenetic changes that accompany oncogenesis. When used for this purpose, their reliability is highly dependent on being able to accurately distinguish between sequencing reads that originate from the host, and those that arise from the xenograft itself. Here we demonstrate that failure to correctly identify contaminating host reads, when analyzing DNA- and RNA-sequencing (DNA-Seq and RNA-Seq) data from PDX and CDX models is a major confounding factor that can lead to incorrect mutation calls and a failure to identify canonical mutation signatures associated with tumorigenicity. In addition, a highly sensitive algorithm and open source software tool for identifying and removing contaminating host sequences is described. Importantly, when applied to PDX and CDX models of melanoma, these data demonstrate its utility as a sensitive and selective tool for the correction of PDX- and CDX-derived whole exome and RNA-Seq data.
Fil: Khandelwal, Garima. University of Manchester; Reino Unido
Fil: Girotti, Maria Romina. University of Manchester; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina
Fil: Smowton, Christopher. University of Manchester; Reino Unido
Fil: Taylor, Sam. University of Manchester; Reino Unido
Fil: Wirth, Christopher. University of Manchester; Reino Unido
Fil: Dynowski, Marek. University of Manchester; Reino Unido
Fil: Frese, Kristopher K.. University of Manchester; Reino Unido
Fil: Brady, Ged. University of Manchester; Reino Unido
Fil: Dive, Caroline. University of Manchester; Reino Unido
Fil: Marais, Richard. University of Manchester; Reino Unido
Fil: Miller, Crispin. University of Manchester; Reino Unido
description Patient-derived xenograft (PDX) and CTC-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these methods have been applied to multiple questions including the study of metastatic progression, genetic evolution and therapeutic drug responses. Since PDX and CDX models can recapitulate the highly heterogeneous characteristics of a patient tumor, as well as their response to chemotherapy, there is considerable interest in combining them with next-generation sequencing (NGS) in order to monitor the genomic, transcriptional, and epigenetic changes that accompany oncogenesis. When used for this purpose, their reliability is highly dependent on being able to accurately distinguish between sequencing reads that originate from the host, and those that arise from the xenograft itself. Here we demonstrate that failure to correctly identify contaminating host reads, when analyzing DNA- and RNA-sequencing (DNA-Seq and RNA-Seq) data from PDX and CDX models is a major confounding factor that can lead to incorrect mutation calls and a failure to identify canonical mutation signatures associated with tumorigenicity. In addition, a highly sensitive algorithm and open source software tool for identifying and removing contaminating host sequences is described. Importantly, when applied to PDX and CDX models of melanoma, these data demonstrate its utility as a sensitive and selective tool for the correction of PDX- and CDX-derived whole exome and RNA-Seq data.
publishDate 2017
dc.date.none.fl_str_mv 2017-04-25
info:eu-repo/date/embargoEnd/2018-09-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/24586
Khandelwal, Garima; Girotti, Maria Romina; Smowton, Christopher; Taylor, Sam; Wirth, Christopher; et al.; Next-generation sequencing analysis and algorithms for PDX and CDX models; American Association for Cancer Research; Molecular Cancer Research; 15; 8; 25-4-2017; 1012-1016
1541-7786
1557-3125
CONICET Digital
CONICET
url http://hdl.handle.net/11336/24586
identifier_str_mv Khandelwal, Garima; Girotti, Maria Romina; Smowton, Christopher; Taylor, Sam; Wirth, Christopher; et al.; Next-generation sequencing analysis and algorithms for PDX and CDX models; American Association for Cancer Research; Molecular Cancer Research; 15; 8; 25-4-2017; 1012-1016
1541-7786
1557-3125
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://mcr.aacrjournals.org/content/15/8/1012.long
info:eu-repo/semantics/altIdentifier/doi/10.1158/1541-7786.MCR-16-0431
info:eu-repo/semantics/altIdentifier/pmid/28442585
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv embargoedAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Association for Cancer Research
publisher.none.fl_str_mv American Association for Cancer Research
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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