TY  - JOUR
AU  - Scheiner, Bernhard
AU  - Lombardi, Pasquale
AU  - D'Alessio, Antonio
AU  - Kim, Gwangil
AU  - Tafavvoghi, Masoud
AU  - Petrenko, Oleksandr
AU  - Goldin, Robert D
AU  - Fulgenzi, Claudia A M
AU  - Torkpour, Aria
AU  - Balcar, Lorenz
AU  - Mauri, Francesco A
AU  - Pomej, Katharina
AU  - Himmelsbach, Vera
AU  - Barsch, Maryam
AU  - Celsa, Ciro
AU  - Cabibbo, Giuseppe
AU  - Cheon, Jaekyung
AU  - Krall, Anja
AU  - Hucke, Florian
AU  - Di Tommaso, Luca
AU  - Bernasconi, Monica
AU  - Rimassa, Lorenza
AU  - Samson, Adel
AU  - Stefanini, Bernardo
AU  - Mozayani, Behrang
AU  - Trauner, Michael
AU  - Lackner, Carolin
AU  - Stauber, Rudolf
AU  - Vasuri, Francesco
AU  - Piscaglia, Fabio
AU  - Bengsch, Bertram
AU  - Finkelmeier, Fabian
AU  - Peck-Radosavljevic, Markus
AU  - Rasmussen Busund, Lill-Tove
AU  - Marafioti, Teresa
AU  - Rahbari, Mohammad
AU  - Heikenwalder, Mathias
AU  - Pinter, Matthias
AU  - Chon, Hong Jae
AU  - Rakaee, Mehrdad
AU  - Pinato, David J
TI  - 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.
JO  - Journal for ImmunoTherapy of Cancer
VL  - 13
IS  - 10
SN  - 2051-1426
CY  - London
PB  - BioMed Central
M1  - DKFZ-2025-02050
SP  - e010975
PY  - 2025
AB  - 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">
AB  - 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">
AB  - 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
KW  - Humans
KW  - Carcinoma, Hepatocellular: drug therapy
KW  - Carcinoma, Hepatocellular: immunology
KW  - Carcinoma, Hepatocellular: pathology
KW  - Carcinoma, Hepatocellular: mortality
KW  - Liver Neoplasms: drug therapy
KW  - Liver Neoplasms: immunology
KW  - Liver Neoplasms: pathology
KW  - Liver Neoplasms: mortality
KW  - Bevacizumab: therapeutic use
KW  - Bevacizumab: pharmacology
KW  - Male
KW  - Female
KW  - Antibodies, Monoclonal, Humanized: therapeutic use
KW  - Antibodies, Monoclonal, Humanized: pharmacology
KW  - Machine Learning
KW  - Middle Aged
KW  - Antineoplastic Combined Chemotherapy Protocols: therapeutic use
KW  - Antineoplastic Combined Chemotherapy Protocols: pharmacology
KW  - Aged
KW  - Tumor Microenvironment: immunology
KW  - Prognosis
KW  - Treatment Outcome
KW  - Biomarker (Other)
KW  - Hepatocellular Carcinoma (Other)
KW  - Immunotherapy (Other)
KW  - Tumor infiltrating lymphocyte - TIL (Other)
KW  - Bevacizumab (NLM Chemicals)
KW  - Antibodies, Monoclonal, Humanized (NLM Chemicals)
KW  - atezolizumab (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:41052886
DO  - DOI:10.1136/jitc-2024-010975
UR  - https://inrepo02.dkfz.de/record/305098
ER  -