Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models

Autores
Hoare, Owen; Fraunhoffer Navarro, Nicolas Alejandro; Elkaoutari, Abdessamad; Gayet, Odile; Bigonnet, Martin; Roques, Julie; Nicolle, Rémy; McGuckin, Colin; Forraz, Nico; Sohier, Emilie; Tonon, Laurie; Wajda, Pauline; Boyault, Sandrine; Attignon, Valéry; Tabone, Luciana Belen; Barbier, Sandrine; Mignard, Caroline; Duchamp, Olivier; Iovanna, Juan; Dusetti, Nelson J.
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental De-sign: Three paired PDAC preclinical models—patient‐derived xenografts (PDX), xenograft‐derived pancreatic organoids (XDPO) and xenograft‐derived primary cell cultures (XDPCC)—were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal‐like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5‐fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity‐associated pathways and PDX and XDPCC for the chemoresistance‐associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal‐like/classical transcriptomic phenotype that strongly in-fluences their global chemosensitivity. Each preclinical model is imperfect but complementary, sug-gesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applica-bility to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.
Fil: Hoare, Owen. Centre National de la Recherche Scientifique; Francia
Fil: Fraunhoffer Navarro, Nicolas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; Argentina
Fil: Elkaoutari, Abdessamad. Centre National de la Recherche Scientifique; Francia
Fil: Gayet, Odile. Centre National de la Recherche Scientifique; Francia
Fil: Bigonnet, Martin. Centre National de la Recherche Scientifique; Francia
Fil: Roques, Julie. Centre National de la Recherche Scientifique; Francia
Fil: Nicolle, Rémy. No especifíca;
Fil: McGuckin, Colin. Cell Therapy Research Institute; Francia
Fil: Forraz, Nico. Cell Therapy Research Institute; Francia
Fil: Sohier, Emilie. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Tonon, Laurie. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Wajda, Pauline. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Boyault, Sandrine. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Attignon, Valéry. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Tabone, Luciana Belen. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Barbier, Sandrine. No especifíca;
Fil: Mignard, Caroline. No especifíca;
Fil: Duchamp, Olivier. No especifíca;
Fil: Iovanna, Juan. Centre National de la Recherche Scientifique; Francia
Fil: Dusetti, Nelson J.. Centre National de la Recherche Scientifique; Francia
Materia
CHEMOSENSITIVITY PREDICTION
IN VITRO MODELS
IN VIVO MODELS
PANCREATIC CANCER
PERSONALIZED MEDICINE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/182099

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oai_identifier_str oai:ri.conicet.gov.ar:11336/182099
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical modelsHoare, OwenFraunhoffer Navarro, Nicolas AlejandroElkaoutari, AbdessamadGayet, OdileBigonnet, MartinRoques, JulieNicolle, RémyMcGuckin, ColinForraz, NicoSohier, EmilieTonon, LaurieWajda, PaulineBoyault, SandrineAttignon, ValéryTabone, Luciana BelenBarbier, SandrineMignard, CarolineDuchamp, OlivierIovanna, JuanDusetti, Nelson J.CHEMOSENSITIVITY PREDICTIONIN VITRO MODELSIN VIVO MODELSPANCREATIC CANCERPERSONALIZED MEDICINEhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental De-sign: Three paired PDAC preclinical models—patient‐derived xenografts (PDX), xenograft‐derived pancreatic organoids (XDPO) and xenograft‐derived primary cell cultures (XDPCC)—were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal‐like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5‐fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity‐associated pathways and PDX and XDPCC for the chemoresistance‐associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal‐like/classical transcriptomic phenotype that strongly in-fluences their global chemosensitivity. Each preclinical model is imperfect but complementary, sug-gesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applica-bility to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.Fil: Hoare, Owen. Centre National de la Recherche Scientifique; FranciaFil: Fraunhoffer Navarro, Nicolas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; ArgentinaFil: Elkaoutari, Abdessamad. Centre National de la Recherche Scientifique; FranciaFil: Gayet, Odile. Centre National de la Recherche Scientifique; FranciaFil: Bigonnet, Martin. Centre National de la Recherche Scientifique; FranciaFil: Roques, Julie. Centre National de la Recherche Scientifique; FranciaFil: Nicolle, Rémy. No especifíca;Fil: McGuckin, Colin. Cell Therapy Research Institute; FranciaFil: Forraz, Nico. Cell Therapy Research Institute; FranciaFil: Sohier, Emilie. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; FranciaFil: Tonon, Laurie. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; FranciaFil: Wajda, Pauline. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; FranciaFil: Boyault, Sandrine. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; FranciaFil: Attignon, Valéry. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; FranciaFil: Tabone, Luciana Belen. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; FranciaFil: Barbier, Sandrine. No especifíca;Fil: Mignard, Caroline. No especifíca;Fil: Duchamp, Olivier. No especifíca;Fil: Iovanna, Juan. Centre National de la Recherche Scientifique; FranciaFil: Dusetti, Nelson J.. Centre National de la Recherche Scientifique; FranciaMDPI2021-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/182099Hoare, Owen; Fraunhoffer Navarro, Nicolas Alejandro; Elkaoutari, Abdessamad; Gayet, Odile; Bigonnet, Martin; et al.; Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models; MDPI; Cancers; 13; 10; 5-2021; 1-132072-6694CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3390/cancers13102473info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:43:05Zoai:ri.conicet.gov.ar:11336/182099instacron: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:34982025-09-29 09:43:05.655CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
title Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
spellingShingle Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
Hoare, Owen
CHEMOSENSITIVITY PREDICTION
IN VITRO MODELS
IN VIVO MODELS
PANCREATIC CANCER
PERSONALIZED MEDICINE
title_short Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
title_full Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
title_fullStr Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
title_full_unstemmed Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
title_sort Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models
dc.creator.none.fl_str_mv Hoare, Owen
Fraunhoffer Navarro, Nicolas Alejandro
Elkaoutari, Abdessamad
Gayet, Odile
Bigonnet, Martin
Roques, Julie
Nicolle, Rémy
McGuckin, Colin
Forraz, Nico
Sohier, Emilie
Tonon, Laurie
Wajda, Pauline
Boyault, Sandrine
Attignon, Valéry
Tabone, Luciana Belen
Barbier, Sandrine
Mignard, Caroline
Duchamp, Olivier
Iovanna, Juan
Dusetti, Nelson J.
author Hoare, Owen
author_facet Hoare, Owen
Fraunhoffer Navarro, Nicolas Alejandro
Elkaoutari, Abdessamad
Gayet, Odile
Bigonnet, Martin
Roques, Julie
Nicolle, Rémy
McGuckin, Colin
Forraz, Nico
Sohier, Emilie
Tonon, Laurie
Wajda, Pauline
Boyault, Sandrine
Attignon, Valéry
Tabone, Luciana Belen
Barbier, Sandrine
Mignard, Caroline
Duchamp, Olivier
Iovanna, Juan
Dusetti, Nelson J.
author_role author
author2 Fraunhoffer Navarro, Nicolas Alejandro
Elkaoutari, Abdessamad
Gayet, Odile
Bigonnet, Martin
Roques, Julie
Nicolle, Rémy
McGuckin, Colin
Forraz, Nico
Sohier, Emilie
Tonon, Laurie
Wajda, Pauline
Boyault, Sandrine
Attignon, Valéry
Tabone, Luciana Belen
Barbier, Sandrine
Mignard, Caroline
Duchamp, Olivier
Iovanna, Juan
Dusetti, Nelson J.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv CHEMOSENSITIVITY PREDICTION
IN VITRO MODELS
IN VIVO MODELS
PANCREATIC CANCER
PERSONALIZED MEDICINE
topic CHEMOSENSITIVITY PREDICTION
IN VITRO MODELS
IN VIVO MODELS
PANCREATIC CANCER
PERSONALIZED MEDICINE
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental De-sign: Three paired PDAC preclinical models—patient‐derived xenografts (PDX), xenograft‐derived pancreatic organoids (XDPO) and xenograft‐derived primary cell cultures (XDPCC)—were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal‐like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5‐fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity‐associated pathways and PDX and XDPCC for the chemoresistance‐associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal‐like/classical transcriptomic phenotype that strongly in-fluences their global chemosensitivity. Each preclinical model is imperfect but complementary, sug-gesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applica-bility to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.
Fil: Hoare, Owen. Centre National de la Recherche Scientifique; Francia
Fil: Fraunhoffer Navarro, Nicolas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Centro de Estudios Farmacológicos y Botánicos. Universidad de Buenos Aires. Facultad de Medicina. Centro de Estudios Farmacológicos y Botánicos; Argentina
Fil: Elkaoutari, Abdessamad. Centre National de la Recherche Scientifique; Francia
Fil: Gayet, Odile. Centre National de la Recherche Scientifique; Francia
Fil: Bigonnet, Martin. Centre National de la Recherche Scientifique; Francia
Fil: Roques, Julie. Centre National de la Recherche Scientifique; Francia
Fil: Nicolle, Rémy. No especifíca;
Fil: McGuckin, Colin. Cell Therapy Research Institute; Francia
Fil: Forraz, Nico. Cell Therapy Research Institute; Francia
Fil: Sohier, Emilie. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Tonon, Laurie. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Wajda, Pauline. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Boyault, Sandrine. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Attignon, Valéry. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Tabone, Luciana Belen. Le Centre Régional de Lutte Contre Le Cancer Léon Bérard; Francia
Fil: Barbier, Sandrine. No especifíca;
Fil: Mignard, Caroline. No especifíca;
Fil: Duchamp, Olivier. No especifíca;
Fil: Iovanna, Juan. Centre National de la Recherche Scientifique; Francia
Fil: Dusetti, Nelson J.. Centre National de la Recherche Scientifique; Francia
description Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental De-sign: Three paired PDAC preclinical models—patient‐derived xenografts (PDX), xenograft‐derived pancreatic organoids (XDPO) and xenograft‐derived primary cell cultures (XDPCC)—were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal‐like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5‐fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity‐associated pathways and PDX and XDPCC for the chemoresistance‐associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal‐like/classical transcriptomic phenotype that strongly in-fluences their global chemosensitivity. Each preclinical model is imperfect but complementary, sug-gesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applica-bility to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.
publishDate 2021
dc.date.none.fl_str_mv 2021-05
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/11336/182099
Hoare, Owen; Fraunhoffer Navarro, Nicolas Alejandro; Elkaoutari, Abdessamad; Gayet, Odile; Bigonnet, Martin; et al.; Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models; MDPI; Cancers; 13; 10; 5-2021; 1-13
2072-6694
CONICET Digital
CONICET
url http://hdl.handle.net/11336/182099
identifier_str_mv Hoare, Owen; Fraunhoffer Navarro, Nicolas Alejandro; Elkaoutari, Abdessamad; Gayet, Odile; Bigonnet, Martin; et al.; Exploring the complementarity of pancreatic ductal adenocarcinoma preclinical models; MDPI; Cancers; 13; 10; 5-2021; 1-13
2072-6694
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/cancers13102473
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
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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