Toward more accurate preclinical glioblastoma modeling: Reverse translation of clinical standard of care in a glioblastoma mouse model.

CT-2A Combination therapies Glioblastoma HGG Mouse model Preclinical Radiotherapy Surgery Temozolomide

Journal

Methods in cell biology
ISSN: 0091-679X
Titre abrégé: Methods Cell Biol
Pays: United States
ID NLM: 0373334

Informations de publication

Date de publication:
2024
Historique:
medline: 29 3 2024
pubmed: 29 3 2024
entrez: 28 3 2024
Statut: ppublish

Résumé

Glioblastoma (GBM) is the deadliest of all brain cancers. GBM patients receive an intensive treatment schedule consisting of surgery, radiotherapy and chemotherapy, which only modestly extends patient survival. Therefore, preclinical studies are testing novel experimental treatments. In such preclinical studies, these treatments are administered as monotherapy in the majority of cases; conversely, in patients the new treatments are always combined with the standard of care. Most likely, this difference contributes to the failure of clinical trials despite the successes of the preclinical studies. In this methodological study, we show in detail how to implement the full clinical standard of care in preclinical GBM research. Systematically testing new treatments, including cellular immunotherapies, in combination with the clinical standard of care can result in a better translation of preclinical results to the clinic and ultimately increase patient survival.

Identifiants

pubmed: 38548420
pii: S0091-679X(23)00132-2
doi: 10.1016/bs.mcb.2023.07.003
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

381-397

Informations de copyright

Copyright © 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Déclaration de conflit d'intérêts

Conflicts of interest The authors declare no conflict of interest.

Auteurs

Aaron Ziani-Zeryouh (A)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Roxanne Wouters (R)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium; Oncoinvent, A.S., Oslo, Norway.

Gitte Thirion (G)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Katja Vandenbrande (K)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Ann Vankerckhoven (A)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Yani Berckmans (Y)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Sien Bevers (S)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Jelle Verbeeck (J)

Laboratory for Disease Mechanisms in Cancer, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

Kim De Keersmaecker (K)

Laboratory for Disease Mechanisms in Cancer, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium.

An Coosemans (A)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium. Electronic address: an.coosemans@kuleuven.be.

Matteo Riva (M)

Laboratory of Tumor Immunology and Immunotherapy, Department of Oncology, Leuven Cancer Institute, KU Leuven, Leuven, Belgium; Department of Neurosurgery, Mont-Godinne Hospital, UCL Namur, Yvoir, Belgium.

Classifications MeSH