Mouse models of diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL) is a genetically highly heterogeneous disease. Yet, to date, the vast majority of patients receive standardized frontline chemo-immune-therapy consisting of an anthracycline backbone. Using these regimens, approximately 65% of patients can be cured, whereas the...

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Published inFrontiers in immunology Vol. 14; p. 1313371
Main Authors Tabatabai, Areya, Arora, Aastha, Höfmann, Svenja, Jauch, Maximilian, von Tresckow, Bastian, Hansen, Julia, Flümann, Ruth, Jachimowicz, Ron D, Klein, Sebastian, Reinhardt, Hans Christian, Knittel, Gero
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 06.12.2023
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Summary:Diffuse large B cell lymphoma (DLBCL) is a genetically highly heterogeneous disease. Yet, to date, the vast majority of patients receive standardized frontline chemo-immune-therapy consisting of an anthracycline backbone. Using these regimens, approximately 65% of patients can be cured, whereas the remaining 35% of patients will face relapsed or refractory disease, which, even in the era of CAR-T cells, is difficult to treat. To systematically tackle this high medical need, it is important to design, generate and deploy suitable model systems that capture disease biology, heterogeneity and drug response. Recently published, large comprehensive genomic characterization studies, which defined molecular sub-groups of DLBCL, provide an ideal framework for the generation of autochthonous mouse models, as well as an ideal benchmark for cell line-derived or patient-derived mouse models of DLBCL. Here we discuss the current state of the art in the field of mouse modelling of human DLBCL, with a particular focus on disease biology and genetically defined molecular vulnerabilities, as well as potential targeting strategies.
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These authors have contributed equally to this work
Edited by: Juan M. Zapata, Consejo Superior de Investigaciones Científicas (CSIC), Spain
Reviewed by: Anthony Uren, University of Plymouth, United Kingdom; Katia Basso, Columbia University, United States
ISSN:1664-3224
1664-3224
DOI:10.3389/fimmu.2023.1313371