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Poster #71 - Ijeoma Meremikwu

  • vitod24
  • Oct 20
  • 2 min read

Spatial Profiling of the Tumor Immune Microenvironment in Higher-Grade Meningioma


Ijeoma C. Meremikwu, Mingshuang Wang, Emily Ling-Lin Pai, Amy E. Baxter, Christina Jackson, Derek A. Oldridge


Meningiomas are the most common central nervous system tumors, with higher-grade meningiomas (HGM) being more aggressive and faster growing than lower grades. Additionally, HGMs can invade brain tissue, which poses greater challenges for treatment. The gold standard of treatment is a combination of surgery and radiation, while there are no effective systemic therapies. Thus, there is a need to understand molecular and cellular mechanisms associated with meningioma grade progression in HGM. Compared to lower grades, HGMs are enriched with a higher proportion of immunosuppressive cells, including myeloid-derived suppressor cells, but their role in disease progression is poorly understood. We performed spatial transcriptomics (Visium HD) to study meningioma progression using patient-matched, longitudinally paired HGM samples. We then employed single-cell segmentation to identify cells and used single-cell analysis techniques to identify cell populations in our meningioma samples with spatial resolution. We have made efforts to characterize immune subsets, including their overall cellular proportions and spatial interactions, across grades II and III HGM. We have identified hypoxia as an important aspect of tumor architecture. Additionally, we found across HGM, there are tight island-like formations enriched with interferon-stimulated gene expression. Finally, grade III HGM lacks these hypoxia-related layered islands, which are still seen in grade II HGM. We hypothesize that there are differential neoplastic-immune cellular interactions between grade II and III HGM that promote signaling programs important for tumor cell proliferation and invasion. Understanding the role of immunologic signaling in malignant meningioma will provide insight into new therapeutic targets that can inform the development of more effective treatment strategies.

 
 
 

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