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Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center by Francoise Galateau Salle; Nolwenn Le Stang; Franck Tirode; Pierre Courtiol; Andrew G. Nicholson; Ming-Sound Tsao; Henry D. Tazelaar; Andrew Churg; Sanja Dacic; Victor Roggli; Daniel Pissaloux; Charles Maussion; Matahi Moarii; Mary Beth Beasley; Hugues Begueret; David B. Chapel; Marie Christine Copin; Allen R. Gibbs; Sonja Klebe; Sylvie Lantuejoul; Kazuki Nabeshima; Jean-Michel Vignaud; Richard Attanoos; Luka Brcic; Frederique Capron; Lucian R. Chirieac; Francesca Damiola; Ruth Sequeiros; Aurélie Cazes; Diane Damotte; Armelle Foulet; Sophie Giusiano-Courcambeck; Kenzo Hiroshima; Veronique Hofman; Aliya N. Husain; Keith Kerr; Alberto Marchevsky; Severine Paindavoine; Jean Michel Picquenot; Isabelle Rouquette; Christine Sagan; Jennifer Sauter; Francoise Thivolet; Marie Brevet; Philippe Rouvier; William D. Travis; Gaetane Planchard; Birgit Weynand; Thomas Clozel; Gilles Wainrib; Lynnette Fernandez-Cuesta; Jean-Claude Pairon; Valerie Rusch; Nicolas Girard is a Medicine article available to read on EtoBox.

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## Introduction: Histologic subtypes of malignant pleural mesothelioma are a major prognostic indicator and decision denominator for all therapeutic strategies. in an ambiguous case, a rare transitional mesothelioma (tm) pattern may be diagnosed by pathologists either as epithelioid mesothelioma (em), biphasic mesothelioma (bm), or sarcomatoid mesothelioma (sm). this study aimed to better characterize the tm subtype from a histological, immunohistochemical, and molecular standpoint. deep learning of pathologic slides was applied to this cohort. ## Methods: A random selection of 49 representative digitalized sections from surgical biopsies of tm was reviewed by 16 panelists. we evaluated bap1 expression and cdkn2a (p16) homozygous deletion. we conducted a comprehensive, integrated, transcriptomic analysis. an unsupervised deep learning algorithm was trained to classify tumors. ## Results: The 16 panelists recorded 784 diagnoses on the 49 cases. even though a kappa value of 0.42 is moderate, the presence of a tm component was diagnosed in 51%. in 49% of the histological evaluation, the reviewers classified the lesion as em in 53%, sm in 33%, or bm in 14%. median survival was 6.7 mont

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Author

Francoise Galateau Salle; Nolwenn Le Stang; Franck Tirode; Pierre Courtiol; Andrew G. Nicholson; Ming-Sound Tsao; Henry D. Tazelaar; Andrew Churg; Sanja Dacic; Victor Roggli; Daniel Pissaloux; Charles Maussion; Matahi Moarii; Mary Beth Beasley; Hugues Begueret; David B. Chapel; Marie Christine Copin; Allen R. Gibbs; Sonja Klebe; Sylvie Lantuejoul; Kazuki Nabeshima; Jean-Michel Vignaud; Richard Attanoos; Luka Brcic; Frederique Capron; Lucian R. Chirieac; Francesca Damiola; Ruth Sequeiros; Aurélie Cazes; Diane Damotte; Armelle Foulet; Sophie Giusiano-Courcambeck; Kenzo Hiroshima; Veronique Hofman; Aliya N. Husain; Keith Kerr; Alberto Marchevsky; Severine Paindavoine; Jean Michel Picquenot; Isabelle Rouquette; Christine Sagan; Jennifer Sauter; Francoise Thivolet; Marie Brevet; Philippe Rouvier; William D. Travis; Gaetane Planchard; Birgit Weynand; Thomas Clozel; Gilles Wainrib; Lynnette Fernandez-Cuesta; Jean-Claude Pairon; Valerie Rusch; Nicolas Girard

Publisher

Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 1556-1380)

Published

2020

Language

EN

Field

Medicine (Health Sciences)