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Review
. 2024 Nov 4;26(11):1964-1980.
doi: 10.1093/neuonc/noae131.

In vivo mouse models for adult brain tumors: Exploring tumorigenesis and advancing immunotherapy development

John Figg  1 , Dongjiang Chen  2 , Laura Falceto Font  1 , Catherine Flores  1 , Dan Jin  1
Affiliations
Review

In vivo mouse models for adult brain tumors: Exploring tumorigenesis and advancing immunotherapy development

John Figg et al. Neuro Oncol. .

Abstract

Brain tumors, particularly glioblastoma (GBM), are devastating and challenging to treat, with a low 5-year survival rate of only 6.6%. Mouse models are established to understand tumorigenesis and develop new therapeutic strategies. Large-scale genomic studies have facilitated the identification of genetic alterations driving human brain tumor development and progression. Genetically engineered mouse models (GEMMs) with clinically relevant genetic alterations are widely used to investigate tumor origin. Additionally, syngeneic implantation models, utilizing cell lines derived from GEMMs or other sources, are popular for their consistent and relatively short latency period, addressing various brain cancer research questions. In recent years, the success of immunotherapy in specific cancer types has led to a surge in cancer immunology-related research which specifically necessitates the utilization of immunocompetent mouse models. In this review, we provide a comprehensive summary of GEMMs and syngeneic mouse models for adult brain tumors, emphasizing key features such as model origin, genetic alteration background, oncogenic mechanisms, and immune-related characteristics. Our review serves as a valuable resource for the brain tumor research community, aiding in the selection of appropriate models to study cancer immunology.

Keywords: adult brain tumor; genetically engineered mouse models; immunotherapy response; syngeneic implantation model.

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Conflict of interest statement

C.F. is a founder of iOncologi. Other authors declare no conflicts of interest.

Figures

Figure 1.
Figure 1.
Factors that determine the rigor of a brain tumor model. Balancing technical and fiscal considerations, models ideally reflect the pathological features observed in patients such as the tumor microenvironment milieu, intratumoral heterogeneity, and the mutational landscape, in addition to being highly reproducible across research studies. Figure is generated by biorender.
Figure 2.
Figure 2.
Normal cells can transform into cancer cells through spontaneous carcinogenesis or exposure to carcinogenic chemicals and other agents. GEMMs can be created by introducing genetic material into normal cells using methods such as transposon-based systems, viral vectors, or electroporation. The temporal and spatial control of these genetic modifications allows for more accurate modeling of tumorigenesis
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