5032 results for "*oma"

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• Genome and transcriptome sequence data from a NUT midline carcinoma tumor patient

  Genome and transcriptome sequence data from a NUT midline carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015325

• Genome and transcriptome sequence data from a diffuse midline glioma, H3K27 mutant tumor patient

  Genome and transcriptome sequence data from a diffuse midline glioma, H3K27 mutant patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015326

• Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour tumor patient

  Genome and transcriptome sequence data from a CNS non-germinoma germ cell tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015327

• Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015329

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015330

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015332

• Genome and transcriptome sequence data from a pIlomyxoid astrocytoma tumor patient

  Genome and transcriptome sequence data from a pIlomyxoid astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015333

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015335

• Genome and transcriptome sequence data from a high-grade glioma, glioblastoma tumor patient

  Genome and transcriptome sequence data from a high-grade glioma, glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015336

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015337

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015338

• RNAseq Atlas in HCC tumors

  The atlas provides a comprehensive exploration of genetic and transcriptomic landscapes within HCC, offering insights into key genomic alterations and gene expression patterns. The integration of DNA sequencing and RNAseq data enhances our understanding of the molecular complexity underlying HCC, potentially paving the way for targeted therapeutic strategies and biomarker discovery in the context of hepatocellular carcinoma.

  Dataset EGAD00001015341

• Exome Atlas in HCC tumors

  The atlas provides a comprehensive exploration of genetic and transcriptomic landscapes within HCC, offering insights into key genomic alterations and gene expression patterns. The integration of exome sequencing and RNAseq data enhances our understanding of the molecular complexity underlying HCC, potentially paving the way for targeted therapeutic strategies and biomarker discovery in the context of hepatocellular carcinoma.

  Dataset EGAD00001015342

• FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

  This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

  Dataset EGAD00001015356

• 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

• Activation of Wnt/β-catenin signalling by mutually exclusive FBXW11 and CTNNB1 hotspot mutations drives salivary gland basal cell adenoma - WES

  Wnt signalling must be 'just right' to promote tumour growth. Basal cell adenoma (BCA) and basal cell adenocarcinoma (BCAC) of the salivary gland are rare tumours that can be difficult to distinguish from each other and other salivary gland tumour subtypes. Due to their rarity, the genomic profiles of BCA and BCAC have not been explored. Using whole-exome and transcriptome sequencing of BCA and BCAC cohorts, we identify a novel recurrent FBXW11 missense mutation (p.F517S) in BCA, that was mutually exclusive with the previously reported CTNNB1 p.I35T gain-of-functon (GoF) mutation. These driver events collectively accounted for 94% of BCAs. In vitro, mutant FBXW11 had a dominant negative affect, characterised by defective binding to β-catenin and the accumulation of β-catenin in cells. This was consistent with the nuclear expression of β-catenin observed in BCA cases harbouring the FBXW11 p.F517S mutation and activation of the Wnt/β-catenin pathway and defines a novel mechanism of Wnt pathway control. The genomic profiles of BCAC were distinct from BCA, with hotspot DICER1 and HRAS mutations and putative driver mutations affecting PI3K/AKT and NF-κB signalling pathway genes. A single BCAC, which may represent a malignant transformation of BCA, harboured the recurrent FBXW11 mutation. These findings have important implications for the diagnosis and treatment of BCA and BCAC, which, despite histopathologic overlap, may be unrelated entities.

  Dataset EGAD00001015365

• Activation of Wnt/β-catenin signalling by mutually exclusive FBXW11 and CTNNB1 hotspot mutations drives salivary gland basal cell adenoma - RNA

  Wnt signalling must be 'just right' to promote tumour growth. Basal cell adenoma (BCA) and basal cell adenocarcinoma (BCAC) of the salivary gland are rare tumours that can be difficult to distinguish from each other and other salivary gland tumour subtypes. Due to their rarity, the genomic profiles of BCA and BCAC have not been explored. Using whole-exome and transcriptome sequencing of BCA and BCAC cohorts, we identify a novel recurrent FBXW11 missense mutation (p.F517S) in BCA, that was mutually exclusive with the previously reported CTNNB1 p.I35T gain-of-functon (GoF) mutation. These driver events collectively accounted for 94% of BCAs. In vitro, mutant FBXW11 had a dominant negative affect, characterised by defective binding to β-catenin and the accumulation of β-catenin in cells. This was consistent with the nuclear expression of β-catenin observed in BCA cases harbouring the FBXW11 p.F517S mutation and activation of the Wnt/β-catenin pathway and defines a novel mechanism of Wnt pathway control. The genomic profiles of BCAC were distinct from BCA, with hotspot DICER1 and HRAS mutations and putative driver mutations affecting PI3K/AKT and NF-κB signalling pathway genes. A single BCAC, which may represent a malignant transformation of BCA, harboured the recurrent FBXW11 mutation. These findings have important implications for the diagnosis and treatment of BCA and BCAC, which, despite histopathologic overlap, may be unrelated entities.

  Dataset EGAD00001015366

• Dataset for "Characterizing the cfDNA fragmentome in patients with hepatocellular carcinoma"

  The dataset includes 63 BAM files from Oxford Nanopore PromethION whole-genome sequencing, generated by base calling POD5 files with Dorado (super-accurate, modified base model v5.0.0_5mCG_5hmCG@v3) and aligning reads to the hg19 reference genome.

  Dataset EGAD00001015823

• 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

• snRNA sequencing of high-grade pancreatic neuroendocrine carcinoma (panNEC)

  High-grade pancreatic neuroendocrine carcinoma (panNEC) is a rare, aggressive cancer with limited tissue availability. Single-nucleus transcriptomics of five large-cell panNECs revealed two interesting neuroendocrine cell states: one highly proliferative with an aberrant brain-specific neuronal differentiation program and another stress-responsive state enriched for heat stress, hypoxia, and glycolysis. Our findings suggest potential therapeutic vulnerabilities, highlighting the need to evaluate the efficacy of combination therapies.

  Dataset EGAD00001016154

• GBM-Space: Whole Genome Sequencing of Laser Capture Microdissected Glioblastoma (LCM-WGS)

  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 contains whole genome sequencing (WGS) data generated from regions of interest (ROIs) collected via laser capture microdissection (LCM), towards identifying copy number alterations and subclones directly at the DNA level.

  Dataset EGAD00001016155

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• WGS dataset of Hepatoblastoma tumoroid biobank as a key resource for tumour genetics

  WGS dataset of Hepatoblastoma tumoroid biobank with WGS of tumor and matched tumoroids

  Dataset EGAD00001015671