High copy number variation burdens in cranial meningiomas from patients with diverse clinical phenotypes characterized by hot genomic structure changes
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ABSTRACT:
PROVIDER: PRJNA615929 | ENA |
REPOSITORIES: ENA
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Project description:Meningiomas, as the most common primary tumor of the central nervous system, are known to harbor genomic aberrations that associate with clinical phenotypes. Here we performed genome-wide genotyping for cranial meningiomas in 383 Chinese patients and identified 9,821 copy number variations (CNVs).
2020-03-28 | GSE147673 | GEO
Project description:Meningiomas, as the most common primary tumor of the central nervous system, are known to harbor genomic aberrations that associate with clinical phenotypes. Here we performed genome-wide genotyping for cranial meningiomas in 383 Chinese patients and identified 9,821 copy-number variations (CNVs). Particularly, patients with diverse clinical features had distinct tumor CNV profiles. CNV burdens were greater in high-grade (WHO grade II and III) samples, recurrent lesions, large tumors (diameter >4.3 cm), and those collected from male patients. Nevertheless, the level of CNV burden did not relate to tumor locations, peritumoral brain edema, bone invasion, or multiple lesions. Overall, the most common tumor CNVs were the copy-number gain (CNG) at 22q11.1 and the copy-number losses (CNLs) at 22q13.2, 14q11.2, 1p34.3, and 1p31.3. Recurrent lesions were featured by the CNLs at 1p31.3, 6q22.31, 9p21.3, and 11p12, and high-grade samples had more CNVs at 4q13.3 and 6q22.31. Meanwhile, large tumors were more likely to have the CNVs at 1p31.3 and 1p34.3. Additionally, recurrence prediction indicated the CNLs at 4p16.3 (p = 0.009, hazard ratio = 5.69) and 10p11.22 (p = 0.037, hazard ratio = 4.53) were candidate independent risk factors.
| S-EPMC7457130 | biostudies-literature
Project description:Genome-wide genotyping analysis identified copy number variations in cranial meningiomas in Chinese patients, and demonstrated diverse CNV burdens among individuals with diverse clinical features.
2020-04-06 | PRJEB37584 | EVA
Project description:Spinal meningiomas account for 1.2-12% of all meningiomas and 25-45% of all spinal tumours. About 20% of intracranial, but also 4.6% of spinal meningiomas recur and require additional treatment. The classification of intracranial meningiomas has evolved considerably in recent years and uses genetic [1,2,4] as well as epigenetic parameters [3,5] in order to more precisely predict the patients’ prognosis and to lay the ground for therapeutic regiments that are adapted to the aggressiveness of a patient’s tumor. On the other hand, spinal meningiomas are missing in many of the large cohorts that were gathered for the molecular profiling of meningiomas. Also, they have never been thoroughly analyzed separately, and their classification still relies on histopathological findings solely. We analysed 65 tumour samples from 63 patients, who had histologically proven spinal meningioma to perform genetic and epigenetic profiling. Clinical features are described in Supplementary Table 1, online resource. T-distributed Stochastic Neighbor Embedding (t-SNE) analysis of genome-wide DNA methylation data shows that most spinal meningiomas separate from cranial meningiomas (Fig. 1A&B) and form two distinct clusters.
2022-10-12 | GSE212449 | GEO
Project description:Meningiomas are typically considered a benign tumor that can be cured by complete surgical resection; however, a percentage of patients have recurrent disease, even after apparently complete resections. These patients require additional surgeries, radiation therapy, chemotherapy, or a combination of all three. The ability to recognize these patients prior to recurrence would promote earlier use of adjuvant therapy, thus improving overall patient outcome. Unfortunately, identification of meningiomas with this more aggressive phenotype is difficult, and standard histopathological techniques rarely suffice. The identification of genetic and molecular parameters that can help to define these more aggressive tumors would improve prognostication and treatment planning for patients with meningiomas. 1. Establish gene profiles for benign (grade 1) and aggressive (grades 2 and 3) meningiomas. 2. Determine if there are particular expression profiles that can help differentiate between benign and aggressive meningiomas. 3. Determine if there is/are specific gene(s) whose expression is/are altered in benign vs aggressive tumors. 4. Determine if there is a correlation between specific genetic abnormalities in these tumors (as analyzed by fluorescent in situ hybridization; FISH) and gene expression profiles. Our overall hypothesis is that there are molecular and biochemical changes that can be used to identify meningiomas that will have a more aggressive clinical course. Specific Aims 1 and 2: RNA from flash frozen or RNA-later preserved tissue (from all three grades of meningiomas) has been used for RNA isolation using standard protocols. RNA quantity has been determined using a RiboGreen RNA quantitation Kit (Molecular Probes), and RNA quality has been demonstrated using standard formaldehyde gels. These samples will be sent to the NINDS/NIMH microarray consortium for Affymetrix microarray analyses. Data analysis will be done using GeneSpring software (Silicon Genetics, Inc.) with assistance from consortium personnel. Specific Aim 3: Differentially expressed genes identified through microarray analyses will be analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Real time qRT-PCR is a standard technique used in our laboratory for gene expression analysis. Specific Aim 4: FISH analyses of paraffin-embedded tissue has been completed for 77 tumors. We have frozen tissue from a number of these patients. RNA from these samples will be used for microarray analyses (Specific Aims 1-3). The results of Speicifc Aims 1 and 2 will affect how we perform our correlation analyses. This will be done with the assistance of contracted statistical personnel.
2008-06-12 | E-GEOD-4039 | biostudies-arrayexpress
Project description:Meningiomas are the most common primary brain tumor. Though typically benign with a low mutational burden, histopathologic analysis has poor predictive value for malignant behavior and there are no proven chemotherapies. Although DNA methylation patterns distinguish subgroups of meningiomas and have higher predictive value for tumor behavior than histologic classification, little is known about differences in DNA methylation between meningiomas and surrounding normal dura tissue. Using multimodal studies of meningioma/dura pairs, we identified 4 distinct DNA methylation patterns. Diffuse DNA hypomethylation of malignant meningiomas readily facilitated their identification from lower grade tumors by unsupervised clustering. All clusters and 12/12 meningioma-dura pairs exhibited hypomethylation of the gene promoters of a module associated with the craniofacial patterning transcription factor FOXC1 and its upstream lncRNA FOXCUT. Furthermore, we identified an epigenetic continuum of increasing hypermethylation of polycomb repressive complex target promoters with increased histopathologic grade suggesting progressive epigenetic dysregulation is associated with increasing tumor aggressiveness. These findings are a starting point for future investigations of the role of epigenetic dysregulation of FOXC1 and cranial patterning genes in early stages of meningioma formation as well as studies of the utility of polycomb inhibitors for treatment of aggressive meningiomas.
2023-06-22 | GSE178139 | GEO
Project description:Meningiomas are the most common primary brain tumor. Though typically benign with a low mutational burden, histopathologic analysis has poor predictive value for malignant behavior and there are no proven chemotherapies. Although DNA methylation patterns distinguish subgroups of meningiomas and have higher predictive value for tumor behavior than histologic classification, little is known about differences in DNA methylation between meningiomas and surrounding normal dura tissue. Using multimodal studies of meningioma/dura pairs, we identified 4 distinct DNA methylation patterns. Diffuse DNA hypomethylation of malignant meningiomas readily facilitated their identification from lower grade tumors by unsupervised clustering. All clusters and 12/12 meningioma-dura pairs exhibited hypomethylation of the gene promoters of a module associated with the craniofacial patterning transcription factor FOXC1 and its upstream lncRNA FOXCUT. Furthermore, we identified an epigenetic continuum of increasing hypermethylation of polycomb repressive complex target promoters with increased histopathologic grade suggesting progressive epigenetic dysregulation is associated with increasing tumor aggressiveness. These findings are a starting point for future investigations of the role of epigenetic dysregulation of FOXC1 and cranial patterning genes in early stages of meningioma formation as well as studies of the utility of polycomb inhibitors for treatment of aggressive meningiomas.
2023-06-22 | GSE176457 | GEO
Project description:Copy number variants (CNVs) are among the largest genetic variants, yet CNVs have not been effectively ascertained in most genetic association studies. Here we ascertained protein-altering CNVs from UK Biobank whole-exome sequencing data (n = 468,570) using haplotype-informed methods capable of detecting subexonic CNVs and variation within segmental duplications. Incorporating CNVs into analyses of rare variants predicted to cause gene loss of function (LOF) identified 100 associations of predicted LOF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 conferred one of the strongest protective effects of gene LOF on hypertension risk (odds ratio = 0.86 (0.82-0.90)). Protein-coding variation in rapidly evolving gene families within segmental duplications-previously invisible to most analysis methods-generated some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.
| S-EPMC11018521 | biostudies-literature
Project description:This SuperSeries is composed of the following subset Series: GSE16581: Genomic landscape of meningiomas: gene expression GSE16583: Genomic landscape of meningiomas: genotyping Refer to individual Series
2010-12-01 | E-GEOD-16584 | biostudies-arrayexpress
Project description:Meningiomas represent one of the most common and clinically heterogeneous brain tumor types that only modestly correlate with histopathologic features. While emerging molecular profiling efforts have linked specific genomic drivers to distinct clinical patterns, the proteomic landscape of meningiomas remains largely unexplored. We utilize mass spectrometry to profile a clinically well-annotated cohort (n=69) of meningiomas stratified to span all three World Health Organization (WHO) grades and various degrees of clinical aggressiveness. In total, we quantify 3042 unique proteins and compare the patterns across different clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic (n=106 proteins, Welch’s t-test, P<0.01) and pathway-level (e.g. Notch and PI3K/AKT/mTOR) differences between convexity and skull base meningiomas. Supervised comparative analyses of different pathological grades revealed distinct patterns between benign (WHO Grade I) and atypical/malignant (WHO Grade II and III) meningiomas with classic oncogenes often enriched in higher grade lesions. Independent of WHO grade, clinically aggressive meningiomas, that rapidly recurred, also had distinctive protein patterns that converged on mRNA processing and impaired activation of the extracellular matrix naba matrisome complex. Larger sized meningiomas, and those with previous radiation exposure, also had distinct protein profiles. Collectively, we highlight distinct clinically-dependent proteomic patterns of meningiomas that may help better predict outcome and guide the development of more personalized and directed therapies.
2019-05-30 | PXD012923 | Pride