22994 results for "ega"

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• Single-cell 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 single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015713

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• Ither2 WXS dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010178

• Ither2 RNA-Seq dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010179

• CcRCC_metabolic_heterogeneity

  Heterogeneity is a hallmark of clear cell renal cell carcinoma (ccRCC). In this study, hyperpolarized [1-13C]pyruvate MRI (HP-13C-MRI) was used to probe metabolic heterogeneity non-invasively in 6 ccRCC patients from which 58 tumor and healthy tissues biopsies were acquired postoperatively. MRI parameters were correlated with 146 metabolite concentrations and the expression of 2523 metabolic genes across 34 metabolic pathways. Using metabologram projections and pathway consensus scoring, several metabolic pathways were correlated with the metabolic MRI, including glycolysis, pentose phosphate pathway, and the TCA cycle. A simple thresholding approach applied to the imaging metrics was sufficient to provide meaningful metabolic pathway information. We also show that tissue metabolic heterogeneity increases in regions with higher pyruvate-to-lactate conversion on imaging. These results provide validation of the biological relevance of HP-13C-MRI and support the possibility of its clinical use to improve disease characterization, stratification, targeting of biopsies, and providing novel methods to monitor treatment response.

  Dataset EGAD00001015780

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 6)

  Whole genome sequencing data of 31 high-grade serous carcinoma (HGSC) patients (101 samples) sequenced with HiSeq X Ten and BGISEQ-500

  Dataset EGAD00001010202

• INSPIRE multi-timepoint cfMeDIP dataset

  This dataset contains raw sequencing data from multi-timepoint cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) of plasma samples from the INSPIRE study (NCT02644369). Details about the study, including inclusion/exclusion criteria and interventions are available at https://clinicaltrials.gov/study/NCT02644369. Briefly, five cohorts were included, INS-A (head & neck squamous cell carcinoma), INS-B (triple-negative breast cancer), INS-C (high-grade serous ovarian cancer), INS-D (melanoma), and INS-E (mixed solid tumors). All patients in the study were diagnosed with advanced cancer and received treatment with pembrolizumab. Plasma samples were collected at baseline and every 3 cycles until disease progression, death, loss of follow-up, or completion of the study. Plasma samples were first processed for cell-free DNA mutations and remaining samples were then processed by cfMeDIP-seq, prioritizing baseline and post-cycle 3 samples. In total, data from 204 timepoints from 87 distinct patients are deposited.

  Dataset EGAD00001011312

• Cancer-independent, second somatic NF1 mutation of normal tissues in neurofibromatosis type 1

  Cancer predisposition syndromes mediated by recessive cancer genes generate tumours via somatic variants (second hits) in the unaffected allele. Second hits may or may not be sufficient for neoplastic transformation. Here, we performed whole genome and exome sequencing on 479 tissue biopsies from a child with neurofibromatosis type 1, a multi-system cancer-predisposing syndrome mediated by constitutive monoallelic NF1 inactivation. We identified multiple independent NF1 driver variants in histologically normal tissues, but not in 610 biopsies from two non-predisposed children. We corroborated this finding using targeted duplex sequencing, including a further nine adults with the same syndrome. Overall, truncating NF1 mutations were under positive selection in normal tissues from individuals with neurofibromatosis type 1. We demonstrate that normal tissues in neurofibromatosis type 1 commonly harbour second hits in NF1, the extent and pattern of which may underpin the syndrome's cancer phenotype.

  Dataset EGAD00001015398

• scDNA-seq for 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Dataset EGAD00001015414

• Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

  Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized. Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

  Dataset EGAD00001015357