Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures

Autores
Chanez, Brice; Delaye, Matthieu; Fraunhoffer Navarro, Nicolas Alejandro; Iovanna, Juan; Neuzillet, Cindy; Dusetti, Nelson Javier
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, with chemotherapy as the mainstay but highly variable efficacy and toxicity. Current regimens, such as FOLFIRINOX and gemcitabine‐based combinations, are selected empirically without validated biomarkers to guide choice. Several strategies have been explored to personalize therapy. Patientderived organoids and molecular classifiers such as PurIST have improved biological understanding but have limited clinical applicability. More recently, predictive transcriptomic signatures have emerged as practical tools. GemPred identifies patients likely to benefit from adjuvant gemcitabine; GemCore, validated in both resected and metastatic tumors, is compatible with small biopsies; and Pancreas‐View integrates multiple drug‐specific predictors, including for all FOLFIRINOX components and gemcitabine, enhanced by AI. These approaches, retrospectively validated in large cohorts and clinical trials, consistently link predicted sensitivity with improved survival. Beyond regimen selection, signatures enable treatment de‐escalation, optimizefirst‐line choices, and identify multidrug‐resistant tumors. Ongoing prospective trials will establish their feasibility, supporting transcriptomic profiling as a step toward precision chemotherapy in PDAC.
Fil: Chanez, Brice. Inserm; Francia
Fil: Delaye, Matthieu. Versailles‐Saint Quentin University; 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: Iovanna, Juan. Inserm; Francia
Fil: Neuzillet, Cindy. Versailles‐Saint Quentin University; Francia
Fil: Dusetti, Nelson Javier. Inserm; Francia
Materia
PANCREATIC CANCER
PRECISION ONCOLOGY
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/291022
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic SignaturesChanez, BriceDelaye, MatthieuFraunhoffer Navarro, Nicolas AlejandroIovanna, JuanNeuzillet, CindyDusetti, Nelson JavierPANCREATIC CANCERPRECISION ONCOLOGYhttps://purl.org/becyt/ford/3.2https://purl.org/becyt/ford/3Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, with chemotherapy as the mainstay but highly variable efficacy and toxicity. Current regimens, such as FOLFIRINOX and gemcitabine‐based combinations, are selected empirically without validated biomarkers to guide choice. Several strategies have been explored to personalize therapy. Patientderived organoids and molecular classifiers such as PurIST have improved biological understanding but have limited clinical applicability. More recently, predictive transcriptomic signatures have emerged as practical tools. GemPred identifies patients likely to benefit from adjuvant gemcitabine; GemCore, validated in both resected and metastatic tumors, is compatible with small biopsies; and Pancreas‐View integrates multiple drug‐specific predictors, including for all FOLFIRINOX components and gemcitabine, enhanced by AI. These approaches, retrospectively validated in large cohorts and clinical trials, consistently link predicted sensitivity with improved survival. Beyond regimen selection, signatures enable treatment de‐escalation, optimizefirst‐line choices, and identify multidrug‐resistant tumors. Ongoing prospective trials will establish their feasibility, supporting transcriptomic profiling as a step toward precision chemotherapy in PDAC.Fil: Chanez, Brice. Inserm; FranciaFil: Delaye, Matthieu. Versailles‐Saint Quentin University; 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: Iovanna, Juan. Inserm; FranciaFil: Neuzillet, Cindy. Versailles‐Saint Quentin University; FranciaFil: Dusetti, Nelson Javier. Inserm; FranciaWiley2025-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/291022Chanez, Brice; Delaye, Matthieu; Fraunhoffer Navarro, Nicolas Alejandro; Iovanna, Juan; Neuzillet, Cindy; et al.; Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures; Wiley; United European Gastroenterology Journal; 13; 10; 12-2025; 1905-19122050-6414CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/full/10.1002/ueg2.70124info:eu-repo/semantics/altIdentifier/doi/10.1002/ueg2.70124info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T15:30:41Zoai:ri.conicet.gov.ar:11336/291022instacron: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:34982026-08-25 15:30:41.615CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
title Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
spellingShingle Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
Chanez, Brice
PANCREATIC CANCER
PRECISION ONCOLOGY
title_short Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
title_full Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
title_fullStr Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
title_full_unstemmed Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
title_sort Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures
dc.creator.none.fl_str_mv Chanez, Brice
Delaye, Matthieu
Fraunhoffer Navarro, Nicolas Alejandro
Iovanna, Juan
Neuzillet, Cindy
Dusetti, Nelson Javier
author Chanez, Brice
author_facet Chanez, Brice
Delaye, Matthieu
Fraunhoffer Navarro, Nicolas Alejandro
Iovanna, Juan
Neuzillet, Cindy
Dusetti, Nelson Javier
author_role author
author2 Delaye, Matthieu
Fraunhoffer Navarro, Nicolas Alejandro
Iovanna, Juan
Neuzillet, Cindy
Dusetti, Nelson Javier
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv PANCREATIC CANCER
PRECISION ONCOLOGY
topic PANCREATIC CANCER
PRECISION ONCOLOGY
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.2
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, with chemotherapy as the mainstay but highly variable efficacy and toxicity. Current regimens, such as FOLFIRINOX and gemcitabine‐based combinations, are selected empirically without validated biomarkers to guide choice. Several strategies have been explored to personalize therapy. Patientderived organoids and molecular classifiers such as PurIST have improved biological understanding but have limited clinical applicability. More recently, predictive transcriptomic signatures have emerged as practical tools. GemPred identifies patients likely to benefit from adjuvant gemcitabine; GemCore, validated in both resected and metastatic tumors, is compatible with small biopsies; and Pancreas‐View integrates multiple drug‐specific predictors, including for all FOLFIRINOX components and gemcitabine, enhanced by AI. These approaches, retrospectively validated in large cohorts and clinical trials, consistently link predicted sensitivity with improved survival. Beyond regimen selection, signatures enable treatment de‐escalation, optimizefirst‐line choices, and identify multidrug‐resistant tumors. Ongoing prospective trials will establish their feasibility, supporting transcriptomic profiling as a step toward precision chemotherapy in PDAC.
Fil: Chanez, Brice. Inserm; Francia
Fil: Delaye, Matthieu. Versailles‐Saint Quentin University; 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: Iovanna, Juan. Inserm; Francia
Fil: Neuzillet, Cindy. Versailles‐Saint Quentin University; Francia
Fil: Dusetti, Nelson Javier. Inserm; Francia
description Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, with chemotherapy as the mainstay but highly variable efficacy and toxicity. Current regimens, such as FOLFIRINOX and gemcitabine‐based combinations, are selected empirically without validated biomarkers to guide choice. Several strategies have been explored to personalize therapy. Patientderived organoids and molecular classifiers such as PurIST have improved biological understanding but have limited clinical applicability. More recently, predictive transcriptomic signatures have emerged as practical tools. GemPred identifies patients likely to benefit from adjuvant gemcitabine; GemCore, validated in both resected and metastatic tumors, is compatible with small biopsies; and Pancreas‐View integrates multiple drug‐specific predictors, including for all FOLFIRINOX components and gemcitabine, enhanced by AI. These approaches, retrospectively validated in large cohorts and clinical trials, consistently link predicted sensitivity with improved survival. Beyond regimen selection, signatures enable treatment de‐escalation, optimizefirst‐line choices, and identify multidrug‐resistant tumors. Ongoing prospective trials will establish their feasibility, supporting transcriptomic profiling as a step toward precision chemotherapy in PDAC.
publishDate 2025
dc.date.none.fl_str_mv 2025-12
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/11336/291022
Chanez, Brice; Delaye, Matthieu; Fraunhoffer Navarro, Nicolas Alejandro; Iovanna, Juan; Neuzillet, Cindy; et al.; Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures; Wiley; United European Gastroenterology Journal; 13; 10; 12-2025; 1905-1912
2050-6414
CONICET Digital
CONICET
url http://hdl.handle.net/11336/291022
identifier_str_mv Chanez, Brice; Delaye, Matthieu; Fraunhoffer Navarro, Nicolas Alejandro; Iovanna, Juan; Neuzillet, Cindy; et al.; Toward Precision Chemotherapy for Pancreatic Cancer Guided by Transcriptomic Signatures; Wiley; United European Gastroenterology Journal; 13; 10; 12-2025; 1905-1912
2050-6414
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/full/10.1002/ueg2.70124
info:eu-repo/semantics/altIdentifier/doi/10.1002/ueg2.70124
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
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 13.24418

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