Authors
[:en]Yuna Blum[:],
[:en]Pauline Duconseil[:],
[:en]Charles Vanbrugghe[:],
[:en]Nicolas Brandone[:],
[:en]Flora Poizat[:],
[:en]Julie Roques[:],
[:en]Martin Bigonnet[:],
[:en]Odile Gayet[:],
[:en]Marion Rubis[:],
[:en]Nabila Elarouci[:],
[:en]Lucile Armenoult[:],
[:en]Mira Ayadi[:],
[:en]Aurélien de Reyniès[:],
[:en]Marc Giovannini[:],
[:en]Philippe Grandval[:],
[:en]Stephane Garcia[:],
[:en]Cindy Canivet[:],
[:en]Barbara Bournet[:],
[:en]Louis Buscail[:],
[:en]BACAP Consortium[:],
[:en]Vincent Moutardier[:],
[:en]Marine Gilabert[:],
[:en]Juan Iovanna[:],
[:en]Nelson Dusetti[:],
[:en]
Abstract
Background
A significant gap in pancreatic ductal adenocarcinoma (PDAC) patient’s care is the lack of molecular parameters characterizing tumours and allowing a personalized treatment.
Methods
Patient-derived xenografts (PDX) were obtained from 76 consecutive PDAC and classified according to their histology into five groups. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n = 598) of resected tumours; ii/ 60 advanced tumours obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumours.
Findings
A unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumours (e.g. 308 consecutive resected PDAC, uHR=0.321 95% CI [0.207–0.5] and 60 locally-advanced or metastatic PDAC, uHR=0.308 95% CI [0.113–0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumour response: -0.67, p-value < 0.001).
Interpretation
PAMG unify all PDAC pre-existing classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient.
Funding
Project funding was provided by INCa (Grants number 2018–078 and 2018–079, BACAP BCB INCa_6294), Canceropole PACA, DGOS (labellisation SIRIC), Amidex Foundation, Fondation de France, INSERM and Ligue Contre le Cancer.
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Other publications
04 Jan 2022
Authors :
[:fr]C. Saillard[:],
[:fr]F. Delecourt[:],
[:fr]B. Schmauch[:],
[:fr]O. Moindrot[:],
[:fr]M. Svrcek[:],
[:fr]A. Bardier-Dupas[:],
[:fr]J-F. Emile[:],
[:fr]M. Ayadi[:],
[:fr]V. Rebours[:],
[:fr]L. de Mestier[:],
[:fr]P. Hammel[:],
[:fr]C. Neuzillet[:],
[:fr]J-B. Bachet[:],
[:fr]J. Iovanna[:],
[:fr]N. Dusetti[:],
[:fr]Y. Blum[:],
[:fr]M. Richard[:],
[:fr]Y. Kermezli[:],
Paradis Valérie,
[:fr]M. Zaslavskiy[:],
[:fr]P. Courtiol[:],
[:fr]A. Kamoun[:],
Nicolle Rémy,
Cros Jérome,
17 Mar 2021
Authors :
Hilmi Marc,
Cros Jérome,
[:fr]Francesco Puleo[:],
[:fr]Jeremy Augustin[:],
[:fr]Jean-Francois Emile[:],
[:fr]Magali Svrcek[:],
Hammel Pascal,
[:fr]Tatjana Arsenijevic[:],
[:fr]Jean-Luc Van Laethem[:],
[:fr]Jean-Baptiste Bachet[:],
Nicolle Rémy,
A transcriptomic signature to predict adjuvant gemcitabine sensitivity in pancreatic adenocarcinoma
[:fr]Annals of Oncology.[:]
10 Nov 2020
Authors :
Nicolle Rémy,
[:fr]O. Gayet[:],
[:fr]P. Duconseil[:],
[:fr]C. Vanbrugghe[:],
[:fr]J. Roques[:],
[:fr]M. Bigonnet[:],
[:fr]Y. Blum[:],
[:fr]N. Elarouci[:],
[:fr]L. Armenoult[:],
[:fr]M. Ayadi[:],
[:fr]A. de Reyniès[:],
[:fr]F. Puleo[:],
[:fr]J. Augustin[:],
[:fr]J.F. Emile[:],
[:fr]M. Svrcek[:],
[:fr]T. Arsenijevic[:],
[:fr]P. Hammel[:],
[:fr]M. Giovannini[:],
[:fr]P. Grandval[:],
[:fr]L. Dahan[:],
[:fr]V. Moutardier[:],
[:fr]M. Gilabert[:],
[:fr]J.L. Van Laethem[:],
[:fr]J.B. Bachet[:],
Cros Jérome,
[:fr]J. Iovanna[:],
[:fr]N.J. Dusetti[:],