Multi-omics RNA profiling of glioblastoma patient tissues
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00010001895 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Background Despite maximal therapy with surgery, chemotherapy and radiotherapy, glioblastoma multiforme (GBM) patients have a median survival of only 15 months. Almost all patients inevitably experience symptomatic tumor recurrence. A hallmark of this tumor type is the large heterogeneity between patients and within tumors itself which relate to failure of standardized tumor treatment. In this study, tissue samples of paired primary and recurrent GBM tumors were investigated to identify individual factors related to tumor progression. Methods Paired primary and recurrent GBM tumor tissues from 8 patients were investigated with a multi-omics approach using transcriptomics, proteomics and phosphoproteomics. Results In the studied patient cohort, large variations between and within patients are observed for all omics analyses. A few pathways affected at the different omics levels partly overlapped if patients are analyzed at the individual level, such as synaptogenesis (containing the SNARE complex) and cholesterol metabolism. Phosphoproteomics revealed increased STMN1(S38) phosphorylation that relates to ERBB4 signaling. A pathway tool has been developed to visualize and compare the different omics datasets per patient and showed potential therapeutic drugs, such as abobotulinumtoxina and afatinib, that target these affected pathways. Afatinib targeting ERBB4 signaling is currently in clinical trials for GBM. Conclusions Large variation on all omics levels exist between and within GBM patients. Therefore, it will be rather unlikely to find a drug treatment that would fit all patients. Instead a multi-omics approach can be used to identify affected pathways on the individual patient level and select potential treatment options.
2020-11-17 | PXD017952 | Pride
Project description:Despite maximal therapy with surgery, chemotherapy and radiotherapy, glioblastoma multiforme (GBM) patients have a median survival of only 15 months. Almost all patients inevitably experience symptomatic tumor recurrence. A hallmark of this tumor type is the large heterogeneity between patients and within tumors itself which relate to failure of standardized tumor treatment. In this study, tissue samples of paired primary and recurrent GBM tumors were investigated to identify individual factors related to tumor progression.
| EGAS00001004345 | EGA
Project description:Although multi-omics studies of glioblastoma (GBM) have improved understanding of its biology nature and accelerated targeted therapy, data for paired adjacent normal tissues remains limited. Here, we report transcriptomes from 2 paired and 1 non-paired tumor and adjacent normal tissues (NAT) of glioblastoma (GBM) patients sequenced using Illumina Novaseq platform, and 150 bp paired-end reads were generated. This dataset provides a resource of paired GBM and normal tissues to identify novel tumor-specific oncogenes or tumor-suppressor genes.
2023-10-01 | GSE184643 | GEO
Project description:A potential new line of anticancer therapy is the use of oncolytic viruses. However, there is a heterogenicity among various types of tumors in response to such treatment. This study is aimed at identifying molecular mechanisms that confer sensitivity to viral infection. We investigated type I interferon responses in human glioblastoma cell line DBTRG-05MG (resistant to viral infection) and osteosarcoma cell line HOS (sensitive to viral infection). We applied a multi-omics approach with included transcriptome, proteome and editome analysis of these cell lines before and after interferon treatment.
2022-02-01 | GSE166877 | GEO
Project description:Longitudinal multi-omics profiling of prediabetes
| PRJNA497499 | ENA
Project description:Longitudinal multi-omics profiling of prediabetes
| PRJNA497500 | ENA
Project description:Although multi-omics studies of glioblastoma (GBM) have improved understanding of its biology nature and accelerated targeted therapy, data for paired adjacent normal tissues (NAT) remains limited. Here, we report proteomes from 3 paired of tumor tissues and NATs of glioblastoma (GBM) patients using liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based label-free quantification. This dataset provides a resource of paired GBM and normal tissues to identify novel tumor-specific oncogenes or tumor-suppressor genes.
2021-09-24 | PXD028730 | iProX
Project description:Joint profiling of chromatin accessibility and gene expression from the same single cell provides critical information about cell types in a tissue and cell states during a dynamic process. These emerging multi-omics techniques help the investigation of cell-type resolved gene regulatory mechanisms. Here, we developed in situ SHERRY after ATAC-seq (ISSAAC-seq), a highly sensitive and flexible single cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single cell. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from thousands of nuclei from the mouse cerebral cortex, we uncovered major and rare cell types together with their cell-type specific regulatory elements and expression profiles. Finally, we revealed distinct dynamics and relationships of transcription and chromatin accessibility during an oligodendrocyte maturation trajectory.
2022-06-15 | E-MTAB-11264 | biostudies-arrayexpress
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.
2018-07-09 | E-MTAB-6127 | biostudies-arrayexpress