Dataset Information

M⁶A Regulator Expression Segregates Meningiomas Into Biologically Distinct Subtypes.

ABSTRACT:

Background

Meningiomas are the most common primary intracranial tumors in adults. According to the 2021 World Health Organization (WHO) classification of central nervous system tumors, approximately 80% of meningiomas are WHO grade 1, that is, histopathologically benign, whereas about 20% are WHO grade 2 or grade 3, showing signs of atypia or malignancy. The dysregulation of N6-methylation (m⁶A) regulators is associated with disorders of diverse critical biological processes in human cancer. This study aimed to explore whether m⁶A regulator expression was associated with meningioma molecular subtypes and immune infiltration.

Methods

We evaluated the m⁶A modification patterns of 160 meningioma samples based on 19 m⁶A regulators and correlated them with immune infiltration characteristics. Novel molecular subtypes were defined based on prognostic hub gene expression.

Results

Two meningioma clusters were identified based on the expression of 19 m⁶A regulators. In cluster 1, 607 differentially expressed genes (DEGs) were upregulated and 519 were downregulated. A total of 1,126 DEGs comprised three gene expression modules characterized by turquoise, blue, and gray. Functional annotation suggested that the turquoise module was involved in Wnt-related and other important cancer-related pathways. We identified 32 hub genes in this module by constructing a protein-protein interaction network. The meningioma samples were divided into two molecular subtypes. EPN1, EXOSC4, H2AX, and MZT2B not only showed significant differences between meningioma molecular subtypes but also had the potential to be the marker genes of specific meningioma subtypes.

Conclusion

m⁶A regulator gene expression may be a novel prognostic marker in meningioma.

SUBMITTER: Chen J

PROVIDER: S-EPMC8727752 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe growth factor receptor network (GFRN) plays a significant role in driving key oncogenic processes. However, assessment of global GFRN activity is challenging due to complex crosstalk among GFRN components, or pathways, and the inability to study complex signaling networks in patient tumors. Here, pathway-specific genomic signatures were used to interrogate GFRN activity in breast tumors and the consequent phenotypic impact of GRFN activity patterns.MethodsNovel pathway signatures were generated in human primary mammary epithelial cells by overexpressing key genes from GFRN pathways (HER2, IGF1R, AKT1, EGFR, KRAS (G12V), RAF1, BAD). The pathway analysis toolkit Adaptive Signature Selection and InteGratioN (ASSIGN) was used to estimate pathway activity for GFRN components in 1119 breast tumors from The Cancer Genome Atlas (TCGA) and across 55 breast cancer cell lines from the Integrative Cancer Biology Program (ICBP43). These signatures were investigated for their relationship to pro- and anti-apoptotic protein expression and drug response in breast cancer cell lines.ResultsApplication of these signatures to breast tumor gene expression data identified two novel discrete phenotypes characterized by concordant, aberrant activation of either the HER2, IGF1R, and AKT pathways ("the survival phenotype") or the EGFR, KRAS (G12V), RAF1, and BAD pathways ("the growth phenotype"). These phenotypes described a significant amount of the variability in the total expression data across breast cancer tumors and characterized distinctive patterns in apoptosis evasion and drug response. The growth phenotype expressed lower levels of BIM and higher levels of MCL-1 proteins. Further, the growth phenotype was more sensitive to common chemotherapies and targeted therapies directed at EGFR and MEK. Alternatively, the survival phenotype was more sensitive to drugs inhibiting HER2, PI3K, AKT, and mTOR, but more resistant to chemotherapies.ConclusionsGene expression profiling revealed a bifurcation pattern in GFRN activity represented by two discrete phenotypes. These phenotypes correlate to unique mechanisms of apoptosis and drug response and have the potential of pinpointing targetable aberration(s) for more effective breast cancer treatments.

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M⁶A Regulator Expression Segregates Meningiomas Into Biologically Distinct Subtypes.

Background

Methods

Results

Conclusion

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Methods

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M⁶A Regulator Expression Segregates Meningiomas Into Biologically Distinct Subtypes.