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Comparative Characterization of High-grade Glioma Models in Rats: Importance for Neurobiology

Submitted:

02 December 2025

Posted:

03 December 2025

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Abstract
The high attrition rates in glioblastoma (GB) therapeutic development stem largely from preclinical models that fail to adequately recapitulate the dynamic tumor-host ecosystem. Unlike previous reviews that characterize glioma cell lines in isolation, this article integrates tumor biology with the distinct neuro-immune-endocrine landscapes of major laboratory rat strains. We critically evaluate standard rat malignant glioma cell lines (C6, F98, RG2, 9L) alongside transplantable tissue models (GB 101.8, GB 15/47), which offer enhanced translational relevance, demonstrating that the predictive value of any model is contingent upon the specific "glioma model and host strain" pairing and the individual physiological characteristics of the host. We provide evidence that strain-specific hypothalamic-pituitary-adrenal (HPA) axis reactivity (e.g., hyper-reactive Fischer 344 versus normo-reactive Wistar) acts as a decisive, yet often overlooked, modulator of the tumor microenvironment and therapeutic response. The review delineates the utility and limitations of these models, specifically addressing the MHC incompatibilities of the widely used C6 model in immunotherapy research, while contrasting it with the immune-evasive phenotypes of RG2 and the GB 101.8 tissue model. Furthermore, we highlight the superiority of tissue transplants in preserving cellular polyclonality and diffuse infiltration patterns compared to the circumscribed growth often observed in cell line-derived tumors. Consequently, we propose a strategic selection paradigm wherein immunogenic models serve as bioindicators of host immunocompetence, while invasive, non-immunogenic systems (F98, RG2, GB 101.8) are utilized to investigate therapeutic resistance and systemic host-tumor interactions.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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