5246 results for "*oma"

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• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Dataset for H3K27me3 ChIP-seq data for neuroblastoma cell lines (Neuroblastoma_CL)

  Dataset for H3K27me3 ChIP-seq data of 31 neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015809

• Genome and transcriptome sequence data from a suspected radiation induced retroperitoneal sarcoma patient

  Genome and transcriptome sequence data from a suspected radiation induced retroperitoneal sarcoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015854

• RNA-Seq dataset of Targeting the dark proteome to expand the lineage-retained antigen landscape in neuroblastoma

  This dataset contains bulk RNA-sequencing data generated to enable custom transcriptome assembly and to provide expression context for matched ribosome profiling in the discovery of lineage-retained neuroblastoma tumor antigens. RNA was sequenced from 183 neuroblastoma samples comprising cell lines, patient-derived tumor organoids, and primary patient tumors spanning the adrenergic (ADRN) and mesenchymal (MES) lineage states, with 101 samples prepared as rRNA-depleted (total RNA) libraries and 82 samples prepared as poly(A)-selected libraries. Libraries were sequenced paired-end (2x150 bp) on the Illumina NovaSeq 6000 platform. Raw data are provided as paired-end fastq.gz files.

  Dataset EGAD00001016124

• Ribo-Seq dataset of Targeting the dark proteome to expand the lineage-retained antigen landscape in neuroblastoma

  This dataset contains ribosome profiling (Ribo-seq) data generated to map actively translated open reading frames, including non-canonical ORFs from the "dark proteome", in neuroblastoma, supporting the identification of translation-validated tumor antigens. Ribosome-protected mRNA fragments (~28–30 nt) were isolated from 47 neuroblastoma samples comprising cell lines, patient-derived tumoroids, and primary patient tumors spanning the adrenergic (ADRN) and mesenchymal (MES) lineage states. Libraries were prepared following a modified version of the McGlincy & Ingolia 2017 protocol and sequenced single-end (1x50 bp) on the Illumina NextSeq 2000 platform. Raw data are provided as single-end fastq.gz

  Dataset EGAD00001016123

• GBM-Space: Transcriptomic Profiling of Patient-Derived Glioblastoma Cell Lines (Parse Biosciences - Evercode WT)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. This dataset comprises sequencing data from single-cell transcriptomic profiles of patient-derived glioblastoma cell lines (Parse Biosciences Evercode WT v3), towards experimentally validating the malignant cell trajectory from developmental-like to gliosis-hypoxia states.

  Dataset EGAD00001016126

• WGS files for paper titled "Sensitive detection of MYCN amplified neuroblastoma in blood samples with structural variants using whole genome sequencing"

  This dataset contains one long read whole genome sequence tumor sample. 2.5µg of patient DNA was used to prepare SMRTbell sequencing library following the “Preparing whole genome and metagenome libraries using SMRTbell® prep kit 3.0” protocol (PacBio). Sequencing was conducted on PacBio Revio+SPRQ chemistry with 250pM loading concentration, generating 35x mean coverage for the whole genome. Reads were mapped to human genome assembly GRCh37 using pbmm2 v1.17.0 (https://github.com/PacificBiosciences/pbmm2)

  Dataset EGAD00001016133

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Study EGAS00001002049