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Spatial genomic, biochemical, and cellular mechanisms drive meningioma heterogeneity and evolution
Calixto-Hope Lucas1, Kanish Mirchia2, Kyounghee Seo2
1Johns Hopkins University.
Abstract:
Intratumor heterogeneity underlies cancer evolution and treatment resistance1-5, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all current medical therapies6,7. High-grade meningiomas cause significant neurological morbidity and mortality and are distinguished from low-grade meningiomas by increased intratumor heterogeneity arising from clonal evolution and divergence8. Here we integrate spatial transcriptomic and spatial protein profiling approaches across high-grade meningiomas to identify genomic, biochemical, and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal, and spatial evolution of cancer. We show divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current clinical classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of sub-clonal copy number variants underlies treatment resistance. Multiplexed sequential immunofluorescence (seqIF) and spatial deconvolution of meningioma single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling, and increased cell proliferation drive meningioma recurrence. To translate these findings to clinical practice, we use epigenetic editing and lineage tracing approaches in meningioma organoid models to identify new molecular therapy combinations that target intratumor heterogeneity and block tumor growth. Our results establish a foundation for personalized medical therapy to treat patients with high-grade meningiomas and provide a framework for understanding therapeutic vulnerabilities driving intratumor heterogeneity and tumor evolution.
Insights
Intratumor heterogeneity in high-grade meningiomas drives cancer evolution and treatment resistance. New therapies targeting this heterogeneity are identified using spatial profiling and organoid models for personalized treatment.
Area of Science:
- Oncology and Cancer Biology
- Genomics and Proteomics
- Neuroscience
Background:
- Intratumor heterogeneity is a key driver of cancer evolution and treatment resistance, particularly in high-grade meningiomas, the most common primary brain tumors.
- Current therapies are ineffective against high-grade meningiomas, which exhibit significant intratumor heterogeneity due to clonal evolution.
Approach:
- Integrated spatial transcriptomic and protein profiling of high-grade meningiomas to identify mechanisms of intratumor heterogeneity.
- Analyzed matched primary and recurrent meningiomas, alongside single-cell RNA sequencing data, using multiplexed sequential immunofluorescence (seqIF) and spatial deconvolution.
- Utilized epigenetic editing and lineage tracing in meningioma organoid models to discover novel therapeutic strategies.
Key Points:
- Divergent gene and protein expression programs distinguish high-grade meningiomas beyond current classifications.
- Spatial expansion of sub-clonal copy number variants contributes to treatment resistance in recurrent tumors.
- Decreased immune infiltration, reduced MAPK signaling, increased PI3K-AKT signaling, and elevated cell proliferation characterize recurrent meningiomas.
Conclusions:
- Identified molecular, temporal, and spatial mechanisms linking intratumor heterogeneity to meningioma evolution and treatment resistance.
- Discovered novel molecular therapy combinations targeting intratumor heterogeneity to inhibit tumor growth in preclinical models.
- Established a foundation for personalized therapies for high-grade meningioma patients by understanding therapeutic vulnerabilities.
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