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
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The immunological landscape in pancreatic ductal adenocarcinoma and overcoming resistance to immunotherapy
Lancet Gastroenterol Hepatol.
Publication date :
30 Nov 2023Authors :
Hilmi Marc,
Matthieu Delaye,
Milena Muzzolini,
Nicolle Rémy,
Cros Jérome,
Hammel Pascal,
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Publication date :
13 Nov 2023Authors :
Nicolle Rémy,
Jean-Baptiste Bachet,
Alexandre Harlé,
Juan Iovanna,
Hammel Pascal,
Rebours Vinciane,
Anthony Turpin,
Meher Ben Abdelghani,
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Eric François,
Pascal Artru,
Aurélien Lambert,
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Laure Monard,
Marjorie Mauduit,
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