Dataset Information

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome

ABSTRACT: Meningiomas are the most common primary intracranial tumors in humans. While most of these tumors are benign, some are malignant, rapidly recur after multimodal treatment with surgery and radiotherapy, and can ultimately be fatal. The current WHO grade system does not always identify high risk meningiomas, therefore better characterizations of the biology of aggressive tumors are needed. In order to address these challenges, we combined 13 bulk RNA-Seq datasets, corrected for batch effects, and applied Uniform Manifold Approximation and Projection (UMAP) to create a reference landscape of ~1300 meningioma tumors. Our analyses revealed multiple distinct meningioma subtypes with specific biological signatures. Clinical metadata, mutations, copy number alterations, and gene-fusion data effectively correlated with regions of the UMAP. Notably, regional distribution of time to recurrence identified major clusters as well as intra-cluster differences of meningiomas with varying patient outcomes. The most aggressive subtype, characterized by an enrichment of higher WHO grades, frequent tumor recurrences, and shorter time to recurrence, exhibited elevated proliferation rates and RNA expression resembling muscle development. To facilitate clinical applications, we developed a cross-validated nearest-neighbors-based algorithm that accurately maps new patients onto this UMAP landscape. Our study highlights the utility of transcriptomic analysis in discerning meningioma heterogeneity as well as successful combination of multiple datasets from various sources. We provide a valuable tool for understanding the disease, predicting tumor biology and patient prognosis. This resource is accessible via the open source, interactive online tool Oncoscape, where the scientific community can explore the landscape and mine clinical and genomic metadata.

ORGANISM(S): Homo sapiens

PROVIDER: GSE252291 | GEO | 2024/04/26

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Purpose: In this study, we try to investigate the possible signaling pathways involved in the tumorigenesis of fibroblastic and anaplastic meningiomas. We also attempt to investigate EGFL6 gene expression in brain arachnoidal tissues and various tumors and to measure EGFL6 levels in serum samples from healthy people and patients with various tumors by using ELISA. Experimental Design: Differential gene expression profiles between meningiomas and brain arachnoidal tissues were established by using Affymetrix GeneChip Human U133 Plus 2.0 Array. KEGG pathway analysis was performed to identify potential gene pathways that may be involved in the pathogenesis of meningiomas. Quantitative real-time PCR (qRT-PCR) was performed to validate the differentially expressed genes in the KEGG pathways. EGFL6 mRNA levels were also determined in brain arachnoidal tissues, meningiomas, and other tumors by qRT-PCR. EGFL6 levels were measured in serum samples from healthy people and patients with various tumors by using ELISA. Results: Fibroblastic meningioma exhibited upregulated PI3K/Akt and TGFÎ² signaling pathways, and accelerated G1/S progression cell cycle. KEGG analysis also demonstrated that focal adhesion and ECM-receptor interaction pathways were activated in anaplastic meningioma. Benign meningiomas had significantly higher levels of EGFL6 mRNA than brain arachnoidal tissues and atypical and anaplastic meningiomas (P<0.001). EGFL6 gene was also highly expressed in ovarian cancer, but expressed lowly in all other investigated tumors. EGFL6 was hardly detectable in serum samples of healthy people. The mean serum EGFL6 concentration was 675, 118, and 126 pg/ml in patients with benign, atypical, and anaplastic meningiomas respectively. Patients with ovarian cancers also had high serum EGFL6 levels (mean concentration: 617 pg/ml). Patients with all other investigated tumors, however, had low levels of serum EGFL6 with mean concentration less than 240 pg/ml. Conclusion: We proposed that deregulation of cell cycle and PI3K/Akt pathways might play important roles in the tumorigenesis of fibroblastic meningioma. It was also suggested that the activated integrin-mediated signaling pathways were involved in the pathogenesis of anaplastic meningioma. We presented evidence that EGFL6 might serve as a novel serum biomarker for benign meningioma and ovarian cancer. It was also suggested that EGFL6 could help discriminate benignancy or malignancy of meningiomas before surgery or at early time points. Differential gene expression profiles between meningiomas and brain arachnoidal tissues were established by using Affymetrix GeneChip Human U133 Plus 2.0 Array. KEGG pathway analysis was performed to identify potential gene pathways that may be involved in the pathogenesis of meningiomas. Quantitative real-time PCR (qRT-PCR) was performed to validate the differentially expressed genes in the KEGG pathways. EGFL6 mRNA levels were also determined in brain arachnoidal tissues, meningiomas, and other tumors by qRT-PCR. EGFL6 levels were measured in serum samples from healthy people and patients with various tumors by using ELISA.

Dataset Information

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets