⚠️ This content is not available in English.

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,

[:fr]

Abstract

Pancreatic ductal adenocarcinoma (PAC) is a highly heterogeneous and plastic tumor with different transcriptomic molecular subtypes that hold great prognostic and theranostic values. We developed PACpAInt, a multistep approach using deep learning models to determine tumor cell type and their molecular phenotype on routine histological preparation at a resolution enabling to decipher complete intratumor heterogeneity on a massive scale never achieved before. PACpAInt effectively identified molecular subtypes at the slide level in three validation cohorts and had an independent prognostic value. It identified an interslide heterogeneity within a case in 39% of tumors that impacted survival. Diving at the cell level, PACpAInt identified “pure” classical and basal-like main subtypes as well as an intermediary phenotype and hybrid tumors that co-carried both classical and basal-like phenotypes. These novel artificial intelligence-based subtypes, together with the proportion of basal-like cells within a tumor had a strong prognostic impact.

[:]

Other publications

Tumour and stroma RNA signatures predict more accurately distant recurrence than clinicopathological factors in resected pancreatic adenocarcinoma

Eur J Cancer .
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,
Find out more

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[:],
Find out more

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer

EBioMedicine.
02 Jul 2020
Authors :
Nicolle Rémy,
[: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[:],
Cros Jérome,
[:en]Barbara Bournet[:],
[:en]Louis Buscail[:],
[:en]BACAP Consortium[:],
[:en]Vincent Moutardier[:],
[:en]Marine Gilabert[:],
[:en]Juan Iovanna[:],
[:en]Nelson Dusetti[:],
Find out more