EPIC-based DNA methylation analysis of glioblastoma stem cells.
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PROVIDER: PRJNA675826 | ENA |
REPOSITORIES: ENA
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Project description:EPIC-based DNA methylation analysis of glioblastoma stem cells and H9NSC (HOXA-AS2 depletion or overexpression)
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Project description:Infinium® HumanMethylation450 BeadChip and EPIC arrays were run with the aim of using the methylation profiles (n=986 in total) for sarcoma subtype classification (Paper: Lyskjær et al, 2021, DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the ‘DKFZ sarcoma Classifier’ ). 500ng of DNA from fresh frozen (FT) or formalin-fixed paraffin-embedded (FFPE) tumour samples were bisulfite converted using the Zymo EZ DNA methylation Gold kit (Zymo Research Corp. Irvine, USA) before hybridisation to the Infinium HumanMethylation450 or EPIC beadchip arrays (Illumina, San Diego, CA) by UCL Genomics. All bisulfite-converted FFPE samples were restored with the Infinium FFPE DNA Restore kit (Illumina).
2021-05-01 | E-MTAB-9875 | biostudies-arrayexpress
Project description:In human, the 39 coding HOX genes and 18 referenced non-coding antisense transcripts are arranged in four genomic clusters named HOXA, B, C, and D. This highly conserved family belongs to the homeobox class of genes that encode transcription factors required for normal development. Therefore, HOX gene deregulation might contribute to the development of many cancer types. Here, we study HOX gene deregulation in adult glioma, a common type of primary brain tumor. We performed extensive molecular analysis of tumor samples, classified according to their isocitrate dehydrogenase (IDH1) gene mutation status, and of glioma stem cells. We found widespread expression of sense and antisense HOX transcripts only in aggressive (IDHwt) glioma samples, although the four HOX clusters displayed DNA hypermethylation. Integrative analysis of expression-, DNA methylation- and histone modification signatures along the clusters revealed that HOX gene upregulation relies on canonical and alternative bivalent CpG island promoters that escape hypermethylation. H3K27me3 loss at these promoters emerges as the main cause of widespread HOX gene upregulation in IDHwt glioma cell lines and tumors. Our study provides the first comprehensive description of the epigenetic changes at HOX clusters and their contribution to the transcriptional changes observed in adult glioma. It also identified putative "master" HOX proteins that might contribute to the tumorigenic potential of glioma stem cells.
2021-03-09 | GSE161175 | GEO
Project description:Intra-Tumor DNA Methylation Heterogeneity in Glioblastoma; Implications for DNA Methylation-based Classification
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Project description:Glioblastoma multiform account for about half of all gliomas and are the most deadly and aggressive forms. Its therapeutic resistance and tumor relapse rely on a subpopulation of cells, the so-called Glioma-stem Cells (GSCs). Here, we investigated for the role of the long non-coding RNA HOXA-AS2 in GSC biology by conducting descriptive and functional analyses of glioma samples classified according to their isocitrate dehydrogenase (IDH1) gene mutation status, and of glioma stem cells. We found that HOXA-AS2 is overexpressed only in aggressive (IDHwt) glioma and GSC. Sh-RNA-based depletion of HOXA-AS2 affects GSC both at the cellular and molecular levels with a decrease in proliferation and altered expression of several hundreds of their genes. Integrative analysis revealed that these changes is expression are not associated to changes in DNA methylation or chromatin signature at the promoter of most deregulated genes following HOXA-AS2 silencing in GSC, supporting a post-transcriptional regulation. In addition, transcription factor motif enrichment and correlation analyses sustained that HOXA-AS2 affect, directly or indirectly, expression of key transcription factors of GCS biology, including E2F8, E2F1, STAT1 and ATF3 to, in fine, contributes to their pathological status by promoting proliferation and modulating the inflammation pathway of Glioma Stem Cell.
2022-04-15 | GSE199032 | GEO
Project description:Background: Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium Methylation EPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price. Methods: Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000ng), medium (300-1000ng), and low (150ng-300ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array. Results: After quality control, an average of 3,708,550 CpG sites per sample was detected by MC-seq with DNA quantity >1000ng. Reproducibility of MC-seq detected CpG sites was high with strong correlation estimates for CpG methylation among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98~0.99). However, methylation for a small proportion of CpGs (N=235) differed significantly between the two platforms, with differences in beta values of greater than 0.5. Conclusions: Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.
2020-06-11 | GSE152245 | GEO
Project description:Transcriptome and EPIC-based DNA methylation analysis of glioblastoma stem cells and H9NSC (HOXA-AS2 depletion or overexpression), and chromatin states in glioblastoma stem cells (HOXA-AS2 depletion)
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Project description:DNA Methylation (EPIC) from the Grady Trauma Project
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Project description:DNA methylation analysis in oropharyngeal cancer [EPIC array]
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Project description:Background: A feature of glioblastoma (GBM) is the cellular and molecular heterogeneity, both within and between tumors. This variability results in a risk for sampling bias and potential tumor escape from future targeted therapy. Heterogeneous gene expression within GBM is well documented, but little is known regarding the epigenetic heterogeneity. We therefore aimed to profile the intra-tumor DNA methylation heterogeneity in GBM. Methods: 3-4 biopsies per tumor from spatially separated regions were collected from 12 GBM patients. We performed genome-wide DNA methylation analysis (~850,000 CpG sites) and compared inter- and intra-tumor variation. Results: All samples were classified as GBM IDH wt or IDH mutated by DNA methylation profiling, but the GBM subtype differed within five tumors. Some GBM samples exhibited higher DNA methylation differences within tumors than between, and many CpG sites (mean: 17,000) had different methylation levels within the tumors. Conclusions: We demonstrated that intra-tumor DNA methylation heterogeneity is a feature of GBM. Although all biopsies were classified as GBM IDH wt/mutated by DNA methylation analysis, the assigned subtype differed in samples from the same patient. The observed DNA methylation heterogeneity within tumors is important to consider for methylation-based biomarkers and future improvements in stratification of GBM patients.
2019-02-27 | GSE116298 | GEO