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Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab-bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective study.

par Zeng, Qinghe;Klein, Christophe;Caruso, Stefano;Maille, Pascale;Allende, Daniela S;Mínguez, Beatriz;Iavarone, Massimo;Ningarhari, Massih;Casadei-Gardini, Andrea;Pedica, Federica;Rimini, Margherita;Perbellini, Riccardo;Boulagnon-Rombi, Camille;Heurgué, Alexandra;Maggioni, Marco;Trepo, Eric ;Vij, Mukul;Baulande, Sylvain;Legoix, Patricia;Lameiras, Sonia;HCC-AI study group, Léa;Bruges, Viviane;Gnemmi, Jean Charles;Nault, Claudia;Campani, Hyungjin;Rhee, Young Nyun;Park, Mercedes;Iñarrairaegui, Guillermo;Garcia-Porrero, Josepmaria;Argemi, Bruno;Sangro, Antonio;D'Alessio, Bernhard;Scheiner, David James;Pinato, Matthias;Pinter, Valérie;Paradis, Aurélie;Beaufrère, Simon;Peter, Lorenza;Rimassa, Luca;Di Tommaso, Arndt;Vogel, Sophie;Michalak, Jérôme;Boursier, Nicolas;Loménie, Marianne;Ziol, Julien;Calderaro,
Référence Lancet oncology, 24, 12, page (1411-1422)
Publication Publié, 2023-12-01

Article révisé par les pairs

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Résumé :

Clinical benefits of atezolizumab plus bevacizumab (atezolizumab-bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and the development of biomarkers is needed to improve therapeutic strategies. The atezolizumab-bevacizumab response signature (ABRS), assessed by molecular biology profiling techniques, has been shown to be associated with progression-free survival after treatment initiation. The primary objective of our study was to develop an artificial intelligence (AI) model able to estimate ABRS expression directly from histological slides, and to evaluate if model predictions were associated with progression-free survival.