Using Exome Sequencing to Improve Prediction of FOLFIRINOX First Efficacy for Pancreatic Adenocarcinoma.

FOLFIRINOX exome sequencing PDAC prognostic biomarkers

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
13 Apr 2021
Historique:
received: 18 02 2021
revised: 01 04 2021
accepted: 08 04 2021
entrez: 30 4 2021
pubmed: 1 5 2021
medline: 1 5 2021
Statut: epublish

Résumé

The first line treatment of advanced pancreatic ductal adenocarcinoma cancer (PDAC) comprises a FOLFIRINOX regimen for most patients with good performance status. However, no biomarker to predict efficacy is currently available. We investigated whether exome sequencing could be used to predict progression-free and overall survival in patients undergoing FOLFIRINOX for PDAC. In this single-center observational study, we included 78 patients with advanced PDAC who underwent somatic and germline exome analyses during first line therapy with FOLFIRINOX or gemcitabine. Exome-derived variables associated with outcome were then used in Cox regression models to generate a composite biomarker. Performance status, tumor stage, liver metastasis, and lung metastasis were retained to generate a prognostic clinical score associated with overall and progression-free survival. Clonality, ploidy, and copy number variant (CNV) signatures 1 and 5, as well as gene variants in the calcium, non-homologous end-joining (NHEJ), and spliceosome pathways, were retained to generate a genomic prognostic score. The addition of genomic score improved the prediction of prognosis compared to the clinical score alone. This study underlines that structural and pathway genomic features could be used to predict FOLFIRINOX survival in patients with advanced PDAC.

Identifiants

pubmed: 33924443
pii: cancers13081851
doi: 10.3390/cancers13081851
pmc: PMC8070262
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Julie Lecuelle (J)

Platform of Transfer in Biological Oncology, Georges François Leclerc Cancer Center-Unicancer, 1 rue du Professeur Marion, 21000 Dijon, France.
UMR INSERM 1231, 7 Boulevard Jeanne d'Arc, 21000 Dijon, France.

Anne Aarnink (A)

Department of Medical Oncology, Georges François Leclerc Cancer Center-Unicancer, 1 rue du Professeur Marion, 21000 Dijon, France.

Zoé Tharin (Z)

Department of Medical Oncology, Georges François Leclerc Cancer Center-Unicancer, 1 rue du Professeur Marion, 21000 Dijon, France.

Caroline Truntzer (C)

Platform of Transfer in Biological Oncology, Georges François Leclerc Cancer Center-Unicancer, 1 rue du Professeur Marion, 21000 Dijon, France.
UMR INSERM 1231, 7 Boulevard Jeanne d'Arc, 21000 Dijon, France.
Genomic and Immunotherapy Medical Institute, Dijon University Hospital, 14 rue Paul Gaffarel, 21000 Dijon, France.

François Ghiringhelli (F)

Platform of Transfer in Biological Oncology, Georges François Leclerc Cancer Center-Unicancer, 1 rue du Professeur Marion, 21000 Dijon, France.
UMR INSERM 1231, 7 Boulevard Jeanne d'Arc, 21000 Dijon, France.
Department of Medical Oncology, Georges François Leclerc Cancer Center-Unicancer, 1 rue du Professeur Marion, 21000 Dijon, France.
Genomic and Immunotherapy Medical Institute, Dijon University Hospital, 14 rue Paul Gaffarel, 21000 Dijon, France.
University of Burgundy-Franche Comté, Maison de l'université Esplanade Erasme, 21000 Dijon, France.

Classifications MeSH