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  • Author or Editor: Shuhan He x
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Shuhan He, Martin H. Pham, Matthew Pease, Gabriel Zada, Steven L. Giannotta, Kai Wang and William J. Mack

Object

A more comprehensive understanding of the epigenetic abnormalities associated with meningioma tumorigenesis, growth, and invasion may provide useful targets for molecular classification and development of targeted therapies for meningiomas.

Methods

The authors performed a review of the current literature to identify the epigenetic modifications associated with the formation and/or progression of meningiomas.

Results

Several epigenomic alterations, mainly pertaining to DNA methylation, have been associated with meningiomas. Hypermethylation of TIMP3 inactivates its tumor suppression activity while CDKN2 (p14[ARF]) and TP73 gene hypermethylation and HIST1H1c upregulation interact with the p53 regulation of cell cycle control. Other factors such as HOX, IGF, WNK2, and TGF-β epigenetic modifications allow either upregulation or downregulation of critical pathways for meningioma development, progression, and recurrence.

Conclusions

Genome-wide methylation profiling demonstrated that global hypomethylation correlates with tumor grades and severity. Identification of additional epigenetic changes, such as histone modification and higher-order chromosomal structure, may allow for a more thorough understanding of tumorigenesis and enable future individualized treatment strategies for meningiomas.

Free access

Xiao Chang, Lingling Shi, Fan Gao, Jonathan Russin, Liyun Zeng, Shuhan He, Thomas C. Chen, Steven L. Giannotta, Daniel J. Weisenberger, Gabriel Zada, Kai Wang and William J. Mack

Object

Meningiomas are among the most common primary adult brain tumors. Although typically benign, roughly 2%–5% display malignant pathological features. The key molecular pathways involved in malignant transformation remain to be determined.

Methods

Illumina expression microarrays were used to assess gene expression levels, and Illumina single-nucleotide polymorphism arrays were used to identify copy number variants in benign, atypical, and malignant meningiomas (19 tumors, including 4 malignant ones). The authors also reanalyzed 2 expression data sets generated on Affymetrix microarrays (n = 68, including 6 malignant ones; n = 56, including 3 malignant ones). A weighted gene coexpression network approach was used to identify coexpression modules associated with malignancy.

Results

At the genomic level, malignant meningiomas had more chromosomal losses than atypical and benign meningiomas, with average length of 528, 203, and 34 megabases, respectively. Monosomic loss of chromosome 22 was confirmed to be one of the primary chromosomal level abnormalities in all subtypes of meningiomas. At the transcriptome level, the authors identified 23 coexpression modules from the weighted gene coexpression network. Gene functional enrichment analysis highlighted a module with 356 genes that was highly related to tumorigenesis. Four intramodular hubs within the module (GAB2, KLF2, ID1, and CTF1) were oncogenic in other cancers such as leukemia. A putative meningioma tumor suppressor MN1 was also identified in this module with differential expression between malignant and benign meningiomas.

Conclusions

The authors' genomic and transcriptome analysis of meningiomas provides novel insights into the molecular pathways involved in malignant transformation of meningiomas, with implications for molecular heterogeneity of the disease.