{"id":62626,"date":"2022-08-10T15:33:13","date_gmt":"2022-08-10T13:33:13","guid":{"rendered":"https:\/\/cri1149.fr\/?post_type=publications&p=62626"},"modified":"2025-09-11T16:47:59","modified_gmt":"2025-09-11T14:47:59","slug":"pacpaint-a-deep-learning-approach-to-identify-molecular-subtypes-of-pancreatic-adenocarcinoma-on-histology-slides","status":"publish","type":"publication","link":"https:\/\/cri1149.fr\/en\/publication\/pacpaint-a-deep-learning-approach-to-identify-molecular-subtypes-of-pancreatic-adenocarcinoma-on-histology-slides\/","title":{"rendered":"PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides"},"content":{"rendered":"","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false},"category_publication":[],"class_list":["post-62626","publication","type-publication","status-publish","hentry"],"acf":{"numero_de_publication":"BioRXiv","date_de_publication":"20220105","numero_doi":"","equipe":[237],"auteurs-liste":[{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]C. Saillard[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]F. Delecourt[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]B. Schmauch[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]O. Moindrot[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]M. Svrcek[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]A. Bardier-Dupas[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]J-F. Emile[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]M. Ayadi[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]V. Rebours[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]L. de Mestier[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]P. Hammel[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]C. Neuzillet[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]J-B. Bachet[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]J. Iovanna[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]N. Dusetti[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]Y. Blum[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]M. Richard[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]Y. Kermezli[:]"},{"texte_libre":false,"auteur-lien":13135,"auteur-text":""},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]M. Zaslavskiy[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]P. Courtiol[:]"},{"texte_libre":true,"auteur-lien":null,"auteur-text":"[:fr]A. Kamoun[:]"},{"texte_libre":false,"auteur-lien":47152,"auteur-text":""},{"texte_libre":false,"auteur-lien":13055,"auteur-text":""}],"auteurs-manuel":"","liens_externes":null,"liens":[{"lien":"https:\/\/www.biorxiv.org\/content\/10.1101\/2022.01.04.474951v1"}],"paragraphe":"[:fr]

Abstract<\/h2>\r\n

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 \u201cpure\u201d 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.<\/p>[:]","paragraphe_en":"[:fr]

Abstract<\/h2>\r\n

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 \u201cpure\u201d 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.<\/p>[:]","documents":null},"yoast_head":"\nPACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides - CRI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/cri1149.fr\/publication\/pacpaint-a-deep-learning-approach-to-identify-molecular-subtypes-of-pancreatic-adenocarcinoma-on-histology-slides\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides - CRI\" \/>\n<meta property=\"og:url\" content=\"https:\/\/cri1149.fr\/publication\/pacpaint-a-deep-learning-approach-to-identify-molecular-subtypes-of-pancreatic-adenocarcinoma-on-histology-slides\/\" \/>\n<meta property=\"og:site_name\" content=\"CRI\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/CRI-Centre-de-recherche-sur-linflammation-100116118884153\" \/>\n<meta property=\"article:modified_time\" content=\"2025-09-11T14:47:59+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/cri1149.fr\\\/publication\\\/pacpaint-a-deep-learning-approach-to-identify-molecular-subtypes-of-pancreatic-adenocarcinoma-on-histology-slides\\\/\",\"url\":\"https:\\\/\\\/cri1149.fr\\\/publication\\\/pacpaint-a-deep-learning-approach-to-identify-molecular-subtypes-of-pancreatic-adenocarcinoma-on-histology-slides\\\/\",\"name\":\"PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides - 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