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MPscore: A Novel Predictive and Prognostic Scoring for Progressive Meningioma
Feili Liu1,2,3,4, Jin Qian5, Chenkai Ma6
1Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China.
Abstract:
Meningioma is the most common tumor in central nervous system (CNS). Although most cases of meningioma are benign (WHO grade I) and curable by surgical resection, a few tumors remain diagnostically and therapeutically challenging due to the frequent recurrence and progression. The heterogeneity of meningioma revealed by DNA methylation profiling suggests the demand of subtyping for meningioma. Therefore, we performed a clustering analyses to characterize the progressive features of meningioma and constructed a meningioma progression score to predict the risk of the recurrence. A total of 179 meningioma transcriptome from RNA sequencing was included for progression subtype clustering. Four biologically distinct subtypes (subtype 1, subtype 2, subtype 3 and subtype 4) were identified. Copy number alternation and genomewide DNA methylation of each subtype was also characterized. Immune cell infiltration was examined by the microenvironment cell populations counter. All anaplastic meningiomas (7/7) and most atypical meningiomas (24/32) are enriched in subtype 3 while no WHO II or III meningioma presents in subtype 1, suggesting subtype 3 meningioma is a progressive subtype. Stemness index and immune response are also heterogeneous across four subtypes. Monocytic lineage is the most immune cell type in all meningiomas, except for subtype 1. CD8 positive T cells are predominantly observed in subtype 3. To extend the clinical utility of progressive meningioma subtyping, we constructed the meningioma progression score (MPscore) by the signature genes in subtype 3. The predictive accuracy and prognostic capacity of MPscore has also been validated in three independent cohort. Our study uncovers four biologically distinct subtypes in meningioma and the MPscore is potentially helpful in the recurrence risk prediction and response to treatments stratification in meningioma.
Insights
Researchers identified four distinct meningioma subtypes and developed a meningioma progression score (MPscore) to predict recurrence risk. This score aids in stratifying patients for treatment and predicting outcomes for this common central nervous system tumor.
Area of Science:
- Neuro-oncology
- Genomics
- Cancer Biology
Background:
- Meningioma is the most common central nervous system (CNS) tumor, with most cases being benign but some posing therapeutic challenges due to recurrence.
- Tumor heterogeneity necessitates subtyping for better diagnosis and treatment strategies.
- DNA methylation profiling indicates significant molecular diversity within meningiomas.
Purpose of the Study:
- To characterize progressive features of meningioma through clustering analyses.
- To identify distinct meningioma subtypes based on transcriptomic data.
- To develop and validate a meningioma progression score (MPscore) for predicting recurrence risk.
Main Methods:
- Transcriptome sequencing data from 179 meningioma samples were analyzed using clustering.
- Copy number alterations, DNA methylation, and immune cell infiltration were characterized for each subtype.
- A meningioma progression score (MPscore) was constructed using signature genes from the progressive subtype and validated in independent cohorts.
Main Results:
- Four biologically distinct meningioma subtypes were identified, with subtype 3 enriched in aggressive tumors (anaplastic and atypical meningiomas).
- Subtype 3 showed higher infiltration of CD8-positive T cells, indicating a distinct immune microenvironment.
- The validated MPscore demonstrated predictive accuracy and prognostic capacity for meningioma recurrence.
Conclusions:
- The study uncovers four distinct molecular subtypes of meningioma, offering new insights into tumor biology.
- The MPscore is a promising tool for predicting meningioma recurrence risk and guiding treatment stratification.
- Further research into these subtypes could lead to more targeted and effective therapeutic strategies for challenging meningioma cases.

