3794 results for "*oma"

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• Genome and transcriptome sequence data from a gliomatosis cerebri anaplastic astrocytoma tumor patient

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

  Dataset EGAD00001015292

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

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

  Dataset EGAD00001015307

• 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

• G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

  Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

  Dataset EGAD00001007860

• CRUK Accelerator: oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Whole exome and RNASeq raw sequencing data for a cohort of 7 male patients with oesophageal adenocarcinoma. Median age at diagnosis was 68. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001008489

• 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

• 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

• Genome and transcriptome sequence data from a infantile fibrosarcoma tumor patient

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

  Dataset EGAD00001015263

• Genome and transcriptome sequence data from a relapsed osteosarcoma tumor patient

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

  Dataset EGAD00001015311

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• Machine Learning Guided Signal Enrichment for Plasma Tumor-burden Monitoring Dataset

  Includes 4 Datasets: 1. 35 Control Plasma WGS samples sequenced on NovaSeq V1.0 Chemistry at the New York Genome Center. Denoted by CTRL-2XX naming scheme. 2. Plasma WGS from 17 patients with Small Cell Lung Cancer. Samples extracted at either Pretreatment or Postoperative at weeks 2 or 3. Denoted by SCLC-XX naming scheme. 3. Plasma WGS from a synthetic mixing study of a high-burden melanoma plasma sample with plasma bag, at estimated tumor concentrations of 10e-3, 10e-4, 10e-5, and 10e-6 for 2 replicates. Denoted by SM-repX naming scheme. 4. Assorted Plasma, Tumor, and Normal WGS from patients with NSCLC expressing high-burden for use in model training. Denoted by NSCLC-2XX naming scheme.

  Dataset EGAD00001011352

• 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 - 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

• Healthy_pleura

  EPIC methylation data of pleural mesothelioma samples and healthy pleura samples

  Dataset EGAD00010002656

• Pleural_mesothelioma

  EPIC methylation data of pleural mesothelioma samples and healthy pleura samples

  Dataset EGAD00010002657

• 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

• Multiregional non-invasive genetic characterization of MM

  Genomic characterization (through whole-exome sequencing) of circulating tumor cells, bone marrow clonal plasma cells and extramedullary plasmacytomas from multiple myeloma patients.

  Dataset EGAD00001006028

• Methylation array data of thymic epithelial tumors (TC, NET, THYM)

  Methylation microarray data (Illumina 850K) of 52 thymic epithelial tumors. 13 patients with thymoma A and B, 32 thymic carcinoma (TC) and 7 neuroendocrine tumors of the thymus (NET).

  Dataset EGAD00010002355

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014789

• Single-nuclei gene-expression analysis of pheochromocytoma and paraganglioma links tumor subtypes with tumor microenvironment

  This dataset contains raw sequencing reads in FASTQ format from single-nuclei (30 samples) and bulk tissue (40 samples) transcriptome sequencing of pheochromocytoma and paraganglioma tissue specimens. Additionally, data from single-nuclei sequencing of two normal adrenal medulla specimens is included.

  Dataset EGAD00001008403

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014787

• NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

  T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

  Dataset EGAD00001015255

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015377

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015379

• A5_SDHB_PCPG_Methylation

  Illumina Infinium MethylationEPIC Array profiling of 93 pheochromocytoma and paraganglioma tumours with and a germline SDHB mutation

  Dataset EGAD00010002667