Browse
Submit Data
Databases
API
Help

Dataset Information

4 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Analyses of DNA Methylation Profiling in the Diagnosis of Intramedullary Astrocytomas.

ABSTRACT: Intramedullary astrocytomas (IMAs) consist of a heterogeneous group of rare central nervous system (CNS) tumors associated with variable outcomes. A DNA methylation-based classification approach has recently emerged as a powerful tool to further classify CNS tumors. However, no DNA methylation-related studies specifically addressing to IMAs have been performed yet. In the present study, we analyzed 16 IMA samples subjected to morphological and molecular analyses, including DNA methylation profiling. Among the 16 samples, only 3 cases were classified in a reference methylation class (MC) with the recommended calibrated score (≥0.9). The remaining cases were either considered "no-match" cases (calibrated score <0.3, n = 7) or were classified with low calibrated scores (ranging from 0.32 to 0.53, n = 6), including inconsistent classification. To obtain a more comprehensive tool for pathologists, we used different unsupervised analyses of DNA methylation profiles, including our data and those from the Heidelberg reference cohort. Even though our cohort included only 16 cases, hypotheses regarding IMA-specific classification were underlined; a potential specific MC of PA_SPINE was identified and high-grade IMAs, probably consisting of H3K27M wild-type IMAs, were mainly associated with ANA_PA MC. These hypotheses strongly suggest that a specific classification for IMAs has to be investigated.

SUBMITTER: Lebrun L

PROVIDER: S-EPMC8357340 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Global DNA methylation profiling reveals chromosomal instability in IDH-mutant astrocytomas.

Project description:Diffusely infiltrating gliomas are among the most common central nervous system tumors in adults. Over the past decade, the subcategorization of these tumors has changed to include both traditional histologic features and more recently identified molecular factors. However, one molecular feature that has yet to be integrated is the presence/absence of chromosomal instability (CIN). Herein, we use global methylation profiling to evaluate a reference cohort of IDH-mutant astrocytomas with and without prior evidence of CIN (n = 42), and apply the resulting methylation-based characteristics to a larger test cohort of publicly-available IDH-mutant astrocytomas (n = 245). We demonstrate that IDH-mutant astrocytomas with evidence of CIN cluster separately from their chromosomally-stable counterparts. CIN cases were associated with higher initial histologic grade, altered expression patterns of genes related to CIN in other cancers, elevated initial total copy number burden, and significantly worse progression-free and overall survival. In addition, in a grade-for-grade analysis, patients with CIN-positive WHO grade 2 and 3 tumors had significantly worse survival. These results suggest that global methylation profiling can be used to discriminate between chromosomally stable and unstable IDH-mutant astrocytomas, and may therefore provide a reliable and cost-effective method for identifying gliomas with chromosomal instability and resultant poor clinical outcome.

| S-EPMC8908645 | biostudies-literature

Gene expression profiling and DNA methylation analyses of CTCs.

Project description:A variety of molecular assays have been developed for CTCs detection and molecular characterization. Molecular assays are based on the nucleic acid analysis in CTCs and are based on total RNA isolation and subsequent mRNA quantification of specific genes, or isolation of genomic DNA that can be for DNA methylation studies and mutation analysis. This review is mainly focused on gene expression and methylation studies in CTCs in various types of cancer.

| S-EPMC5528973 | biostudies-other

DNA methylation analysis of paediatric low-grade astrocytomas identifies a tumour-specific hypomethylation signature in pilocytic astrocytomas.

Project description:Low-grade gliomas (LGGs) account for about a third of all brain tumours in children. We conducted a detailed study of DNA methylation and gene expression to improve our understanding of the biology of pilocytic and diffuse astrocytomas. Pilocytic astrocytomas were found to have a distinctive signature at 315 CpG sites, of which 312 were hypomethylated and 3 were hypermethylated. Genomic analysis revealed that 182 of these sites are within annotated enhancers. The signature was not present in diffuse astrocytomas, or in published profiles of other brain tumours and normal brain tissue. The AP-1 transcription factor was predicted to bind within 200 bp of a subset of the 315 differentially methylated CpG sites; the AP-1 factors, FOS and FOSL1 were found to be up-regulated in pilocytic astrocytomas. We also analysed splice variants of the AP-1 target gene, CCND1, which encodes cell cycle regulator cyclin D1. CCND1a was found to be highly expressed in both pilocytic and diffuse astrocytomas, but diffuse astrocytomas have far higher expression of the oncogenic variant, CCND1b. These findings highlight novel genetic and epigenetic differences between pilocytic and diffuse astrocytoma, in addition to well-described alterations involving BRAF, MYB and FGFR1.

| S-EPMC4882864 | biostudies-literature

Integrated DNA methylation analysis identifies topographical and tumoral biomarkers in pilocytic astrocytomas.

Project description:Pilocytic astrocytoma (PA) is the most common glioma in pediatric patients and occurs in different locations. Chromosomal alterations are mostly located at chromosome 7q34 comprising the BRAF oncogene with consequent activation of the mitogen-activated protein kinase pathway. Although genetic and epigenetic alterations characterizing PA from different localizations have been reported, the role of epigenetic alterations in PA development is still not clear. The aim of this study was to investigate whether distinctive methylation patterns may define biologically relevant groups of PAs. Integrated DNA methylation analysis was performed on 20 PAs and 4 normal brain samples by Illumina Infinium HumanMethylation27 BeadChips. We identified distinct methylation profiles characterizing PAs from different locations (infratentorial vs supratentorial) and tumors with onset before and after 3 years of age. These results suggest that PA may be related to the specific brain site where the tumor arises from region-specific cells of origin. We identified and validated in silico the methylation alterations of some CpG islands. Furthermore, we evaluated the expression levels of selected differentially methylated genes and identified two biomarkers, one, IRX2, related to the tumor localization and the other, TOX2, as tumoral biomarker.

| S-EPMC5862617 | biostudies-literature

Adult intracranial ependymoma-relevance of DNA methylation profiling for diagnosis, prognosis, and treatment.

Project description:BackgroundA methylation-based classification of ependymoma has recently found broad application. However, the diagnostic advantage and implications for treatment decisions remain unclear. Here, we retrospectively evaluate the impact of surgery and radiotherapy on outcome after molecular reclassification of adult intracranial ependymomas.MethodsTumors diagnosed as intracranial ependymomas from 170 adult patients collected from 8 diagnostic institutions were subjected to DNA methylation profiling. Molecular classes, patient characteristics, and treatment were correlated with progression-free survival (PFS).ResultsThe classifier indicated an ependymal tumor in 73.5%, a different tumor entity in 10.6%, and non-classifiable tumors in 15.9% of cases, respectively. The most prevalent molecular classes were posterior fossa ependymoma group B (EPN-PFB, 32.9%), posterior fossa subependymoma (PF-SE, 25.9%), and supratentorial ZFTA fusion-positive ependymoma (EPN-ZFTA, 11.2%). With a median follow-up of 60.0 months, the 5- and 10-year-PFS rates were 64.5% and 41.8% for EPN-PFB, 67.4% and 45.2% for PF-SE, and 60.3% and 60.3% for EPN-ZFTA. In EPN-PFB, but not in other molecular classes, gross total resection (GTR) (P = .009) and postoperative radiotherapy (P = .007) were significantly associated with improved PFS in multivariable analysis. Histological tumor grading (WHO 2 vs. 3) was not a predictor of the prognosis within molecularly defined ependymoma classes.ConclusionsDNA methylation profiling improves diagnostic accuracy and risk stratification in adult intracranial ependymoma. The molecular class of PF-SE is unexpectedly prevalent among adult tumors with ependymoma histology and relapsed as frequently as EPN-PFB, despite the supposed benign nature. GTR and radiotherapy may represent key factors in determining the outcome of EPN-PFB patients.

| S-EPMC10326475 | biostudies-literature

DNA methylation methods: Global DNA methylation and methylomic analyses.

Project description:DNA methylation provides a pivotal layer of epigenetic regulation in eukaryotes that has significant involvement for numerous biological processes in health and disease. The function of methylation of cytosine bases in DNA was originally proposed as a "silencing" epigenetic marker and focused on promoter regions of genes for decades. Improved technologies and accumulating studies have been extending our understanding of the roles of DNA methylation to various genomic contexts including gene bodies, repeat sequences and transcriptional start sites. The demand for comprehensively describing DNA methylation patterns spawns a diversity of DNA methylation profiling technologies that target its genomic distribution. These approaches have enabled the measurement of cytosine methylation from specific loci at restricted regions to single-base-pair resolution on a genome-scale level. In this review, we discuss the different DNA methylation analysis technologies primarily based on the initial treatments of DNA samples: bisulfite conversion, endonuclease digestion and affinity enrichment, involving methodology evolution, principles, applications, and their relative merits. This review may offer referable information for the selection of various platforms for genome-wide analysis of DNA methylation.

| S-EPMC7914139 | biostudies-literature

Distinct DNA Methylation Patterns of Subependymal Giant Cell Astrocytomas in Tuberous Sclerosis Complex.

Project description:Tuberous sclerosis complex (TSC) is a monogenic disorder caused by mutations in either the TSC1 or TSC2 gene, two key regulators of the mechanistic target of the rapamycin complex pathway. Phenotypically, this leads to growth and formation of hamartomas in several organs, including the brain. Subependymal giant cell astrocytomas (SEGAs) are low-grade brain tumors commonly associated with TSC. Recently, gene expression studies provided evidence that the immune system, the MAPK pathway and extracellular matrix organization play an important role in SEGA development. However, the precise mechanisms behind the gene expression changes in SEGA are still largely unknown, providing a potential role for DNA methylation. We investigated the methylation profile of SEGAs using the Illumina Infinium HumanMethylation450 BeadChip (SEGAs n = 42, periventricular control n = 8). The SEGA methylation profile was enriched for the adaptive immune system, T cell activation, leukocyte mediated immunity, extracellular structure organization and the ERK1 & ERK2 cascade. More interestingly, we identified two subgroups in the SEGA methylation data and show that the differentially expressed genes between the two subgroups are related to the MAPK cascade and adaptive immune response. Overall, this study shows that the immune system, the MAPK pathway and extracellular matrix organization are also affected on DNA methylation level, suggesting that therapeutic intervention on DNA level could be useful for these specific pathways in SEGA. Moreover, we identified two subgroups in SEGA that seem to be driven by changes in the adaptive immune response and MAPK pathway and could potentially hold predictive information on target treatment response.

| S-EPMC9560915 | biostudies-literature

DNA methylation profiling in nanochannels.

Project description:We report the profiling of the 5-methyl cytosine distribution within single genomic-sized DNA molecules at a gene-relevant resolution. This method linearizes and stretches DNA molecules by confinement to channels with a dimension of about 250×200 nm(2). The methylation state is detected using fluorescently labeled methyl-CpG binding domain proteins (MBD), with high signal contrast and low background. DNA barcodes consisting of methylated and non-methylated segments are generated, with both short and long concatemers demonstrating spatially resolved MBD binding. The resolution of the technique is better than 10 kbp, and single-molecule read-lengths exceeding 140 kbp have been achieved.

| S-EPMC3161501 | biostudies-other

Copy Number Profiling of Brazilian Astrocytomas.

Project description:Copy number alterations (CNA) are one of the driving mechanisms of glioma tumorigenesis, and are currently used as important biomarkers in the routine setting. Therefore, we performed CNA profiling of 65 astrocytomas of distinct malignant grades (WHO grade I-IV) of Brazilian origin, using array-CGH and microsatellite instability analysis (MSI), and investigated their correlation with TERT and IDH1 mutational status and clinico-pathological features. Furthermore, in silico analysis using the Oncomine database was performed to validate our findings and extend the findings to gene expression level. We found that the number of genomic alterations increases in accordance with glioma grade. In glioblastomas (GBM), the most common alterations were gene amplifications (PDGFRA, KIT, KDR, EGFR, and MET) and deletions (CDKN2A and PTEN) Log-rank analysis correlated EGFR amplification and/or chr7 gain with better survival of the patients. MSI was observed in 11% of GBMs. A total of 69% of GBMs presented TERT mutation, whereas IDH1 mutation was most frequent in diffuse (85.7%) and anaplastic (100%) astrocytomas. The combination of 1p19q deletion and TERT and IDH1 mutational status separated tumor groups that showed distinct age of diagnosis and outcome. In silico validation pointed to less explored genes that may be worthy of future investigation, such as CDK2, DMRTA1, and MTAP Herein, using an extensive integrated analysis, we indicated potentially important genes, not extensively studied in gliomas, that could be further explored to assess their biological and clinical impact in astrocytomas.

| S-EPMC4938641 | biostudies-literature

DNA methylation and cancer diagnosis.

Project description:DNA methylation is a major epigenetic modification that is strongly involved in the physiological control of genome expression. DNA methylation patterns are largely modified in cancer cells and can therefore be used to distinguish cancer cells from normal tissues. This review describes the main technologies available for the detection and the discovery of aberrantly methylated DNA patterns. It also presents the different sources of biological samples suitable for DNA methylation studies. We discuss the interest and perspectives on the use of DNA methylation measurements for cancer diagnosis through examples of methylated genes commonly documented in the literature. The discussion leads to our consideration for why DNA methylation is not commonly used in clinical practice through an examination of the main requirements that constitute a reliable biomarker. Finally, we describe the main DNA methylation inhibitors currently used in clinical trials and those that exhibit promising results.

| S-EPMC3742286 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data