Dataset Information

Human meningioma fixed tumour tissue: training set

ABSTRACT: Background: Meningiomas account for about 27% of primary brain tumors, making them one of the most common brain tumor. They are most common in people between the ages of 40 and 70 and are more common in women than in men. Most meningiomas (90%) are categorized as benign tumors, with the remaining 10% being atypical or malignant. Multiple classifications exist today, but the most commonly used is the World Health Organization’s (WHO) which classifies meningiomas into three histological grades: grade I (benign), grade II (atypical), and grade III (anaplastic) in accordance with the clinical prognosis. Most of these subtypes behave similarly, however anaplastics are the most aggressive. The ability to distinguish benign from atypical and anaplastic tumors is important because of its impact on treatment decisions. A molecular based classification system has the likelihood of being a better prognostic indicator and is useful for identifying alterations in pathways and networks that drive tumor progression and growth. The information obtained can potentially be translated into more effective and less toxic targeted therapies. We tested a method for genome wide expression profiling of formalin-fixed, paraffin-embedded tissues. We applied the method to the analysis of the clinical outcome of meningioma tumor. Materials and Methods: The training set consisted of tissue samples from 63 patients who were consecutively treated with surgery for meningioma between 1990 and 2005. For each patient data on clinical outcomes and formalin-fixed, paraffin-embedded blocks of tumor were available. The validation set included tissue samples from 189 patients with meningioma who consecutively underwent surgery between 1992 and 2006. We used a custom 60-mer amino modified oligo- array, containing 912 probes, a lot of which specific for genes commonly altered in cancer. Functional annotation was performed by means of gene set enrichment analysis (GSEA, www. broad.mit.edu/gsea/). Survival analyses were performed with the use of the log-rank test and Cox regression modeling. All analyses were performed with the use of GenePattern. Results: We investigated whether gene-expression profiles of meningioma tumors were associated with the clinical outcome. Using a standard leaveone- out cross-validation procedure, we found the meningioma signature to be significantly correlated with survival (P = 0.0001). The survival correlated signature contained 219 genes and was tested in the validation set. Conclusion: These results support the validity of the survival signature and highlight the potential role of tumoral meningioma tissue in predicting the outcome for patients with meningioma tumors.

ORGANISM(S): Homo sapiens

PROVIDER: GSE16153 | GEO | 2011/05/11

SECONDARY ACCESSION(S): PRJNA122827

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Meningiomas account for about 27% of primary brain tumors, making them one of the most common brain tumor. They are most common in people between the ages of 40 and 70 and are more common in women than in men. Most meningiomas (90%) are categorized as benign tumors, with the remaining 10% being atypical or malignant. Multiple classifications exist today, but the most commonly used is the World Health Organization’s (WHO) which classifies meningiomas into three histological grades: grade I (benign), grade II (atypical), and grade III (anaplastic) in accordance with the clinical prognosis. Most of these subtypes behave similarly, however anaplastics are the most aggressive. The ability to distinguish benign from atypical and anaplastic tumors is important because of its impact on treatment decisions. A molecular based classification system has the likelihood of being a better prognostic indicator and is useful for identifying alterations in pathways and networks that drive tumor progression and growth. The information obtained can potentially be translated into more effective and less toxic targeted therapies. We tested a method for genome wide expression profiling of formalin-fixed, paraffin-embedded tissues. We applied the method to the analysis of the clinical outcome of meningioma tumor. Materials and Methods: The training set consisted of tissue samples from 63 patients who were consecutively treated with surgery for meningioma between 1990 and 2005. For each patient data on clinical outcomes and formalin-fixed, paraffin-embedded blocks of tumor were available. The validation set included tissue samples from 189 patients with meningioma who consecutively underwent surgery between 1992 and 2006. We used a custom 60-mer amino modified oligo- array, containing 912 probes, a lot of which specific for genes commonly altered in cancer. Functional annotation was performed by means of gene set enrichment analysis (GSEA, www. broad.mit.edu/gsea/). Survival analyses were performed with the use of the log-rank test and Cox regression modeling. All analyses were performed with the use of GenePattern. Results: We investigated whether gene-expression profiles of meningioma tumors were associated with the clinical outcome. Using a standard leaveone- out cross-validation procedure, we found the meningioma signature to be significantly correlated with survival (P = 0.0001). The survival correlated signature contained 219 genes and was tested in the validation set. Conclusion: These results support the validity of the survival signature and highlight the potential role of tumoral meningioma tissue in predicting the outcome for patients with meningioma tumors.

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.

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 TGFβ 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.

Dataset Information

Human meningioma fixed tumour tissue: training set

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets