%0 Journal Article
%A Scheiner, Bernhard
%A Lombardi, Pasquale
%A D'Alessio, Antonio
%A Kim, Gwangil
%A Tafavvoghi, Masoud
%A Petrenko, Oleksandr
%A Goldin, Robert D
%A Fulgenzi, Claudia A M
%A Torkpour, Aria
%A Balcar, Lorenz
%A Mauri, Francesco A
%A Pomej, Katharina
%A Himmelsbach, Vera
%A Barsch, Maryam
%A Celsa, Ciro
%A Cabibbo, Giuseppe
%A Cheon, Jaekyung
%A Krall, Anja
%A Hucke, Florian
%A Di Tommaso, Luca
%A Bernasconi, Monica
%A Rimassa, Lorenza
%A Samson, Adel
%A Stefanini, Bernardo
%A Mozayani, Behrang
%A Trauner, Michael
%A Lackner, Carolin
%A Stauber, Rudolf
%A Vasuri, Francesco
%A Piscaglia, Fabio
%A Bengsch, Bertram
%A Finkelmeier, Fabian
%A Peck-Radosavljevic, Markus
%A Rasmussen Busund, Lill-Tove
%A Marafioti, Teresa
%A Rahbari, Mohammad
%A Heikenwalder, Mathias
%A Pinter, Matthias
%A Chon, Hong Jae
%A Rakaee, Mehrdad
%A Pinato, David J
%T Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab.
%J Journal for ImmunoTherapy of Cancer
%V 13
%N 10
%@ 2051-1426
%C London
%I BioMed Central
%M DKFZ-2025-02050
%P e010975
%D 2025
%X Spontaneously immunogenic hepatocellular carcinoma (HCC), identified by a dense immune cell infiltrate (ICI), responds better to immunotherapy, although no validated biomarker exists to identify these cases. We used machine learning (ML) to quantify ICI from standard H</td><td width="150">
%X E-stained tissue and evaluated its correlation with characteristics of the tumor microenvironment (TME) and clinical outcome from atezolizumab plus bevacizumab (A+B).We therefore employed a supervised ML algorithm on 102 pretreatment H</td><td width="150">
%X E slides collected from patients treated with A+B. We quantified tumor, stroma and immune cell counts/mm2 and dichotomized patients into ICI high and ICI low for clinicopathologic analysis. We correlated ICI signature with characteristics of the T-cell infiltrate (CD4+, FOXP3+, CD8+, PD1+) using multiplex immunohistochemistry in 62 resected specimens and evaluated gene expression profiles by bulk RNA sequencing in 44 samples.All patients treated with A+B were Child-Pugh A and received first-line A+B treatment for Barcelona Clinic Liver Cancer Stage C HCC (n=77, 75.5
%K Humans
%K Carcinoma, Hepatocellular: drug therapy
%K Carcinoma, Hepatocellular: immunology
%K Carcinoma, Hepatocellular: pathology
%K Carcinoma, Hepatocellular: mortality
%K Liver Neoplasms: drug therapy
%K Liver Neoplasms: immunology
%K Liver Neoplasms: pathology
%K Liver Neoplasms: mortality
%K Bevacizumab: therapeutic use
%K Bevacizumab: pharmacology
%K Male
%K Female
%K Antibodies, Monoclonal, Humanized: therapeutic use
%K Antibodies, Monoclonal, Humanized: pharmacology
%K Machine Learning
%K Middle Aged
%K Antineoplastic Combined Chemotherapy Protocols: therapeutic use
%K Antineoplastic Combined Chemotherapy Protocols: pharmacology
%K Aged
%K Tumor Microenvironment: immunology
%K Prognosis
%K Treatment Outcome
%K Biomarker (Other)
%K Hepatocellular Carcinoma (Other)
%K Immunotherapy (Other)
%K Tumor infiltrating lymphocyte - TIL (Other)
%K Bevacizumab (NLM Chemicals)
%K Antibodies, Monoclonal, Humanized (NLM Chemicals)
%K atezolizumab (NLM Chemicals)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:41052886
%R 10.1136/jitc-2024-010975
%U https://inrepo02.dkfz.de/record/305098