Towards an integrated cellular and molecular classifier for glioblastoma
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ABSTRACT:
PROVIDER: PRJNA1237898 | ENA |
REPOSITORIES: ENA
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Project description:The recognition of tumor heterogeneity has highlighted the necessity of examining tumor samples through the lens of single-cell genomics. In glioblastoma (GBM), a highly heterogeneous tumor, single-cell analysis is critical to assist in assessing tumor composition and in the longitudinal analysis of response to therapies. However, single-cell genomic approaches face practical challenges for broad implementation, underscoring the importance of developing deconvolution methods that may assist in the interpretation of bulk profiles and can be deployed at scale. Bulk DNA methylation data, a stable and widely used diagnostic tool in gliomas and central nervous system tumors, provides a promising substrate for deconvolution. However, the limited availability of cell state-specific references in DNA methylation, coupled with low-coverage single-cell DNA methylation data, poses significant challenges. We present a hierarchical non-negative matrix factorization approach to deconvolute bulk DNA methylation profiles, initially resolving cell types and subsequently refining cell states within a cell type. By integrating multi-omics single-cell data, we mapped DNA methylation components to their transcriptional counterparts, enabling accurate predictions of transcriptional cellular composition from bulk DNA methylation. This methodology allows the decomposition of GBM bulk DNA methylation into glial, immune, neuronal, and malignant cell types, with further distinction into malignant stem-like and malignant differentiated cell states. Our findings reveal that low cancer cell fractions can distort classification, prompting the development of an in-silico purification method to enhance diagnostic accuracy. Additionally, we provide a framework to assist in quantifying the influences of the immune micro-environment on GBM bulk classification, unmasking the underlying genetic heterogeneity and tumor subtype. Our work provides a blueprint to reconcile DNA methylation, bulk transcription-based and single-cell classifications of GBM.
2025-03-26 | GSE292314 | GEO
Project description:We over-expressed an epigenetic regulator in a glioblastoma (GBM) primary culture from an adult patient. These GBM cells have cancer stem cell phenotypes, as they have self-renewal properties and tumor initiation potential when transplanted in immunocompromised mice. ATAC-seq was performed on cells over-expressing the epigenetic regulator and control cells expressing EGFP. ATAC-Seq on glioblastoma cells that over-express EGFP or an epigenetic regulator.
2015-12-08 | E-GEOD-67633 | biostudies-arrayexpress
Project description:Unsupervised clustering and epigenetic classification of single cells
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Project description:Epigenetic characterization of glioblastoma stem cells
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Project description:DNA methylation-based classification of human central nervous system tumors
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Project description:We over-expressed an epigenetic regulator in a glioblastoma (GBM) primary culture from an adult patient. These GBM cells have cancer stem cell phenotypes, as they have self-renewal properties and tumor initiation potential when transplanted in immunocompromised mice. An epigenetic regulator (ER) was over-expressed in the GBM primary culture G514NS. EGFP was expressed from the same vector backbone as a control. N = 3 biological replicates for each of EGFP- and ER-overexpressing cells. Please note that complete data output (with 74,342 data rows) from Partek analysis contains several identifiers which are not represented in the GPL17586, and therefore is linked as Series supplementary file.
2015-11-11 | E-GEOD-63296 | biostudies-arrayexpress
Project description:EPIMETRIC (EPIgenetic MEthylation-based Algorithm for Respiratory Illness Classification - COPD)
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Project description:Epigenetic profiling for the molecular classification of metastatic brain tumors
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Project description:Cancer-specific coding mutations can create neoantigens that can be presented on the cell surface of tumors to trigger immunogenic clearance1–4. However, current cancer vaccine approaches have not been universally effective5; this is especially true in tumors with a low mutational burden which, in turn, carry a low conventional neoantigen load6. Transposable elements (TEs) make up approximately 50% of the human genome and have been discovered to provide cryptic promoters, which can be reactivated with epigenetic manipulations to generate TE-gene chimeric transcripts that can be translated into noncanonical peptides7. Here, we focus on glioblastoma, an aggressive brain cancer with low mutation burden, to explore whether epigenetic therapy can induce TE-chimeric antigens (TEAs) to appreciably increase the antigen repertoire that can be targeted with immunotherapy. We perform comprehensive epigenetic and transcriptomic profiling of three patient-derived glioblastoma stem cell lines (GSCs) and, more importantly, astrocyte and fibroblast primary cell lines that are either proliferating or quiescent, treated with epigenetic therapy drugs to identify treatment-induced TEA (TI-TEA) candidates that are preferentially expressed in cancer cells. Although we verify TI-TEAs are indeed presented on HLA molecules in GSCs thus are promising cancer vaccine candidates, many TEs were also transcriptionally activated in proliferating primary cell lines after epigenetic therapy. This work presents a cautionary but optimistic tale for future efforts in harnessing TI-TEAs for targeted immunotherapy approaches.
2024-06-05 | PXD039893 | Pride
Project description:Glioblastoma (GBM) is an incurable brain tumor carrying a dismal prognosis, which displays considerable heterogeneity. We have recently identified recurrent H3F3A mutations affecting two critical positions of histone H3.3 (K27, G34) in one-third of pediatric GBM. Here we show that each of these H3F3A mutations defines an epigenetic subgroup of GBM with a distinct global methylation pattern, and are mutually exclusive with IDH1 mutation (characterizing a CpG-Island Methylator Phenotype (CIMP) subgroup). Three further epigenetic subgroups were enriched for hallmark genetic events of adult GBM (EGFR amplification, CDKN2A/B deletion) and/or known transcriptomic signatures. We also demonstrate that the two H3F3A mutations give rise to GBMs in separate anatomic compartments, with differential regulation of OLIG1/2 and FOXG1, possibly reflecting different cellular origins. To further dissect the biological differences between epigenetic glioblastoma subgroups, we looked at the transcriptomic profiles of glioblastoma samples. 46 glioblastoma samples from patients of various ages were selected for RNA extraction and hybridization on Affymetrix Affymetrix Human Genome U133 Plus 2.0 Arrays.
2012-10-16 | E-GEOD-36245 | biostudies-arrayexpress