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Approaches to experimental modeling of neuroinflammation in neurodegenerative diseases: part 3 — cell lines

https://doi.org/10.37489/2587-7836-2026-3-22-34

EDN: JJCIRW

Abstract

Background. Neuroinflammation is a key pathogenic mechanism in a wide range of central nervous system disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and ischemic stroke. To study the molecular mechanisms of neuroinflammation and screen potential drug candidates, researchers have access to a wide arsenal of in vitro models. Immortalized cell lines remain an indispensable tool at the early stages of pharmacological research; however, their selection requires a critical evaluation of the advantages and limitations of each model.
Objective. To conduct a critical analysis of the main immortalized cell lines of microglia, astrocytes, and neurons used for modeling neuroinflammation, and based on this analysis, to formulate recommendations for their selection depending on experimental objectives.
Methods. A narrative literature review was performed, summarizing data on the origin, phenotypic characteristics, functional activity, and applications of cell lines. A comparative analysis was conducted for microglial lines (BV-2, N9, N13, EOC, HAPI, HMC3, HMO6), astrocytic lines (U-87, U-251, U-373, A-172, T98G), and neuronal lines (SH-SY5Y, PC-12), with emphasis on their response to inflammatory stimuli, mediator production, and preservation of specific markers.
Results. The BV-2 line retains 90 % of genes induced in primary microglia and is considered the "gold standard" for primary screening of anti-inflammatory compounds; however, it exhibits an elevated basal activation level. Spontaneously immortalized lines EOC and HAPI/SIM-A9 are phenotypically closer to primary cells and retain functional phagocytosis. Among human lines, HMO6 demonstrates TREM2-dependent phagocytosis of β-amyloid and the ability for M1/M2 polarization, whereas HMC3 does not express key microglial markers (P2RY12, TREM2) and expresses pericyte markers, which significantly limits its value. Astrocytic lines differ in their sensitivity to IL-1β: U-251 and U-373 show a pronounced response, whereas T98G is resistant. Neuronal lines SH-SY5Y and PC-12 retain sensitivity to neurotoxic stimuli; however, their application depends on the specific pathology (Alzheimer's disease vs. Parkinson's disease).
Conclusion. An optimal strategy for experimental modeling of neuroinflammation involves a multi-level approach: primary screening on standardized cell lines followed by validation on primary cultures, co-culture systems, and iPSC-derived cells. The presented critical analysis allows researchers to reasonably select the most appropriate cell model for specific tasks, taking into account its advantages and limitations, as well as the boundaries for translating the results to in vivo systems.

About the Authors

Yu. Yu. Firstova
Federal research center for innovator and emerging biomedical and pharmaceutical technologies
Russian Federation

Yulia Yu. Firstova — PhD, Cand. Sci. (Biol.), Senior Researcher, Laboratory of Molecular Pharmacology

Moscow 



S. A. Simukhina
Federal research center for innovator and emerging biomedical and pharmaceutical technologies
Russian Federation

Svetlana A. Simukhina — Research Assistant, Molecular Pharmacology Laboratory

Moscow 



E. V. Vasileva
Federal research center for innovator and emerging biomedical and pharmaceutical technologies
Russian Federation

Ekaterina V. Vasileva — PhD, Cand. Sci. (Biol.), Senior Researcher, Laboratory of Molecular Pharmacology

Moscow 



L. F. Zainullina
Federal research center for innovator and emerging biomedical and pharmaceutical technologies
Russian Federation

Liana F. Zainullina — PhD, Cand. Sci. (Biol.), Head of the Molecular Pharmacology Laboratory, Leading Researcher

Moscow 



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Firstova Yu.Yu., Simukhina S.A., Vasileva E.V., Zainullina L.F. Approaches to experimental modeling of neuroinflammation in neurodegenerative diseases: part 3 — cell lines. Pharmacokinetics and Pharmacodynamics. 2026;(3):22-34. (In Russ.) https://doi.org/10.37489/2587-7836-2026-3-22-34. EDN: JJCIRW

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