Meningioma Cell Models for Research

Meningiomas are the most common primary intracranial tumors, accounting for approximately 37-40% of all primary brain tumors in the United States, with an incidence of about 8-10 per 100,000 person-years (CBTRUS, 2023). The World Health Organization (WHO) classifies meningiomas into three grades: Grade I (benign, ~80%), Grade II (atypical, ~15-20%), and Grade III (malignant/anaplastic, ~1-3%). The 5-year survival rates are high for Grade I (over 90%), but drop to 78% for Grade II and 55% for Grade III (NCI SEER data). Risk factors include ionizing radiation exposure, neurofibromatosis type 2 (NF2) syndrome, and female sex (hormonal influences). Despite surgical resection being the primary treatment, recurrence rates remain high, especially for Grade II and III tumors, necessitating the development of targeted therapies and reliable preclinical models.

Meningiomas are ideal for mechanistic studies due to their well-defined genetic landscape, including recurrent mutations in NF2, AKT1, TRAF7, SMO, and PIK3CA. The availability of large genomic datasets (TCGA, COSMIC) and public repositories (GEO) allows for robust data mining. Open questions include the role of tumor microenvironment, hormonal signaling, and the transition from benign to malignant phenotypes. Gene-edited cell models enable functional validation of these mutations and the study of resistance mechanisms, making them essential for drug discovery and personalized medicine approaches.

Meningioma pathogenesis involves several key pathways:

• • NF2/Merlin pathway: Loss of NF2 (encoding Merlin) leads to dysregulation of the Hippo signaling pathway, resulting in increased cell proliferation and survival.
• • PI3K/AKT/mTOR pathway: Activating mutations (e.g., AKT1 E17K) promote cell growth and survival.
• • Hedgehog signaling: Mutations in SMO (e.g., L412F) lead to constitutive activation of the pathway, driving tumorigenesis.
• • TRAF7 pathway: Mutations in TRAF7, a ubiquitin ligase, affect NF-kB signaling and apoptosis regulation.

These pathways are interconnected, and their dysregulation contributes to the heterogeneity of meningiomas.

Data from TCGA and COSMIC databases.

Key signaling networks deregulated in meningioma include:

• • Hippo/YAP pathway: Loss of NF2 leads to YAP/TAZ nuclear translocation, promoting cell proliferation and invasion.
• • PI3K/AKT/mTOR pathway: Mutations in AKT1 and PIK3CA activate this pathway, leading to increased cell survival and metabolism.
• • Hedgehog pathway: SMO mutations cause uncontrolled activation of GLI transcription factors.
• • NF-kB pathway: TRAF7 mutations alter NF-kB signaling, affecting inflammation and apoptosis.

These networks are potential therapeutic targets, and gene-edited cell models can be used to dissect their roles.

Organoid models derived from patient tumors preserve the 3D architecture and tumor microenvironment, providing a more physiologically relevant platform for drug testing. However, they are more complex to maintain and less amenable to high-throughput screening compared to 2D cell lines.

Animal models for meningioma include:

• • Patient-derived xenografts (PDX): Implantation of patient tumor tissue into immunodeficient mice, preserving tumor heterogeneity.
• • Genetically engineered mouse models (GEMM): Conditional knockout of Nf2 in arachnoidal cells leads to meningioma formation.
• • Orthotopic models: Injection of meningioma cells into the subdural space of mice to mimic intracranial growth.

These models are valuable for studying tumor progression and testing therapeutics, but they are time-consuming and costly.

CRISPR-based gene editing enables the creation of isogenic cell lines with specific mutations, such as NF2 knockout, AKT1 E17K knock-in, or SMO L412F knock-in. These models allow researchers to study the functional consequences of individual mutations in a controlled genetic background. Commercially available, sequence-verified gene-edited cell lines (e.g., from commercial sources) accelerate research by providing validated tools. For example, an NF2 knockout in a benign meningioma cell line can be used to study the transition to malignancy. These models are essential for drug screening and target validation.

Gene-edited cells are used to validate the role of specific genes in meningioma biology. For instance, knocking out NF2 in a normal arachnoidal cell line can recapitulate tumorigenic features, confirming its tumor suppressor function. Similarly, introducing AKT1 E17K into a benign cell line can enhance proliferation and survival, demonstrating its oncogenic role. These models enable high-throughput screens to identify genetic modifiers and synthetic lethal interactions.

Isogenic cell line pairs (e.g., NF2 wild-type vs. knockout) are used to screen for compounds that selectively kill mutant cells. This approach identifies drugs with a therapeutic window. Additionally, gene-edited models can be used to study resistance mechanisms by exposing cells to increasing concentrations of a drug and selecting for resistant clones. For example, AKT1 E17K knock-in cells can be used to test AKT inhibitors and identify resistance mutations.

CRISPR screens using gene-edited meningioma cells can identify genes whose loss sensitizes cells to specific treatments, revealing potential biomarkers. For example, a synthetic lethality screen in NF2-deficient cells may identify genes that are essential for survival only in the mutant context, serving as novel therapeutic targets. These findings can be translated into clinical biomarkers for patient stratification.