Abstract
Meningiomas are common intracranial tumors that can be cured by surgical resection in most cases. However, the most disconcerting is high-grade meningiomas, which frequently recur despite initial successful treatment, eventually conferring poor prognosis. Therefore, the early diagnosis and classification of meningioma is necessary for the subsequent intervention and an improved prognosis. A growing body of evidence demonstrates the potential of multi-omics study (including genomics, transcriptomics, epigenomics, proteomics) for meningioma diagnosis and mechanistic links to potential pathological mechanism. This thesis addresses a neglected aspect of recent advances in the field of meningiomas at multiple omics levels, highlighting that the integration of multi-omics can reveal the mechanism of meningiomas, which provides a timely and necessary scientific basis for the treatment of meningiomas.
Highlights
Meningiomas account for 13–36.6% of the primary malignant tumors of the central nervous system [1]
Methylation of TIMP3, CDKN2, and other genes that can regulate the progression of meningiomas have been identified by genome-wide methylation DNA analysis [37]; further work reveals the connection between the H3K27me3 signal and hypermethylated phenotype in meningiomas, integrating with microarray analysis of the transcriptional network controlled by E2F2 and FOXM1
This study identified the 15 proteins that were significantly related to atypical meningioma, and nine proteins can be used to discriminate atypical from anaplastic meningiomas [57]
Summary
Meningiomas account for 13–36.6% of the primary malignant tumors of the central nervous system [1]. Integration of multi-omics with clinical data represents an accurate and promising methodology to provide very accurate prediction models for meningioma progression (Figure 1), suggesting the potential of early and accurate diagnosis, effective therapeutic strategies, and favorable prognosis of meningioma [9, 10].
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