3794 results for "*oma"

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• RCRF release 1

  Transcriptome sequencing from the Rare Cancer Research Foundation: leiomyosarcoma, large cell neuroendocrine carcinoma, clear cell carcinoma

  Dataset EGAD00001010198

• WES data for study of the microenviroment of angioimmunoblastic T-cell lymphoma

  Exome sequencing data for study of the microenviroment of angioimmunoblastic T-cell lymphoma

  Dataset EGAD00001011581

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• Paired RNA-Seq of Tumor Organoids from glioblastoma, 2 patients, treated with different small molecule inhibitors

  Tumor Organoids from glioblastoma, 2 patients, treated with different small molecule inhibitors. Paired RNA-Seq was done on NovaSeq 6000 with the Illumina TruSeq stranded mRNA Kit. The small inhibitors GW2580, BLZ945 and PLX3397 were used. DMSO was used as control.

  Dataset EGAD00001011274

• Whole genome sequencing of Osteosarcoma clonal evolution

  Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. Here, we conducted longitudinal whole-genome sequencing of 37 tumor samples from eight patients with osteosarcoma that relapsed or became refractory to initial therapy. We found that the chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.

  Dataset EGAD00001011285

• Single RNA-Seq of CD11b Beads selected tumor associated macrophages (TAMs) of 3 gliomablastoma patients treated with small molecule inhibitors

  Single RNA-Seq of CD11b Beads selected tumor associated macrophages (TAMs) of 3 gliomablastoma patients treated with small molecule inhibitors. The sequencing was done on HiSeq 4000 with the SmarTer Ultra Low Input RNA v4 and NEBNext ChIP-Seq Kit. The TAMs were treated with GW2580, BLZ945 and PLX3397 and DMSO as control.

  Dataset EGAD00001011273

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• Evaluating gene expression in aggressive B-cell lymphoma using a quantitative nuclease protection assay

  Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL), comprising 25-30% of all NHL in developed countries with an annual incidence in the USA of 7 cases/100000 persons/year. Collectively, DLBCL is classified based on a common morphological appearance of diffuse growth of large transformed B-cells, immunophenotype, high proliferation rate and aggressive behaviour. Despite these similarities, DLBCLs are a heterogeneous collection of malignancies with distinct clinical and molecular characteristics that do not always correlate with immunohistological features. This gene expression dataset includes transcriptomes of ABC-DLBCLs and of GCB-DLBCLs where cell of origin is determined by the HTG-EdgeSeq quantitative nuclease protection assay. Also included are clonality results from BCR profiling from high-grade B-cell lymphomas sequenced using a NOVA sequencer

  Dataset EGAD00001011309

• Tagged-amplicon deep sequencing

  This dataset contains a collection of tumour samples from high grade serous ovarian carcinoma patients with recurrent disease collected near the point of diagnosis as well as tumour samples collected after patient relapse upon or some time after study entry. Whole blood samples were also collected from patients at study entry for the purpose of germline variant detection. The majority of diagnosis samples were preserved in neutral buffered formalin whereas the majority of post-relapse samples were preserved in universal molecular fixative (UMFIX, Sakura Finetek USA, Inc). DNA was extracted and the tagged-amplicon deep sequencing assay was applied (TAm-Seq, Forshew et al. 2002, Sci Transl Med) with the aid of fluidigm access array technology. Targeted loci were sequenced at very high depths (typically >100X) for the detection of both somatic and germline variants. Sequenced reads were aligned to the GRCh37 reference genome (release hs37d5).

  Dataset EGAD00001011058

• Whole genome sequencing and whole exome sequencing of pediatric osteosarcoma

  Whole genome sequencing and whole exome sequencing of 13 pediatric osteosarcoma patients including 13 primary, 10 metastatic, and 3 relapsed tumors.

  Dataset EGAD00001004482

• ScRNA-seq of 6 human FL

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Dataset EGAD00001007691

• Single-cell RNA-sequencing of H3-K27M diffuse midline glioma.

  Fastq files are deposited for single-cell transcriptomes of patient H3-K27M diffuse midline gliomas, generated using the SMART-seq2 method.

  Dataset EGAD00001011339

• Whole genome sequencing of 78 follicular lymphoma tumours and matched normals

  Whole genome sequencing for tumour/normal matched pairs from 78 samples

  Dataset EGAD00001011343

• CHEWIE ctDNA in Rhabdomyosarcoma

  Targeted DNA based panel of multiple ctDNA samples from 10 patients througout clinical care to assess treatment response. The panel is custom-designed and property of UGS, IC.

  Dataset EGAD00001011127

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 1)

  Whole genome sequencing data of 6 high-grade serous carcinoma (HGSC) patients (11 samples) sequenced with MGISEQ-2000

  Dataset EGAD00001011353

• scRNA-seq, WES, and bulk RNA-seq on longitudinal samples from 7 Lymphoma patients treated with CD20xCD3 bispecific antibodies

  We performed scRNA-seq on 15 fresh lymph node core biopsies from 7 Lymphoma patients treated with CD20xCD3 bispecific antibodies. We also performed whole-exome sequencing (WES) and bulk RNA-seq on formalin-fixed paraffin embedded (FFPE) tumor samples from these patients. WES was additionally performed on matched germline samples (blood) for each patient.

  Dataset EGAD00001011350

• Single-cell RNA-seq data of angioimmunoblastic T-cell lymphoma

  Single-cell RNA-seq data of angioimmunoblastic T-cell lymphoma

  Dataset EGAD00001011361

• WES raw data set for the study "Genomic profiling of localized (lFL) and systemic follicular lymphoma (sFL) reveals novel insights into FL pathogenesis"

  221 patient samples including 164 initial tumor (TI) samples (53/164 fresh frozen TI samples, and 111/164 formalin-fixed paraffin-embedded (FFPE) TI samples), 22 paired matched normal samples, and 35 unpaired normal samples from healthy donors; FASTQ file format, Agilent SureSelect Human All Exon V6 Kit (Agilent Technologies, Inc., Santa Clara, California, USA)

  Dataset EGAD00001011369

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 2)

  Whole genome sequencing data of 35 high-grade serous carcinoma (HGSC) patients (112 samples) sequenced with Illumina Novoseq 6000

  Dataset EGAD00001011368

• OncoScan SNP data set for systemic follicular lymphoma (sFL)

  122 unpaired initial tumor samples (122 FFPE samples) of sFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002592

• OncoScan SNP data set for localized follicular lymphoma (lFL)

  149 unpaired initial tumor samples (133/149 FFPE and 16/149 fresh frozen samples) of lFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002593

• Complex structural variation patterns in pediatric solid tumors WGS

  Paired tumor-normal whole genome sequencing data from primary tumors of patients diagnosed with neuroblastoma, Ewing sarcoma, Wilms tumor, hepatoblastoma and rhabdomyosarcoma

  Dataset EGAD00001011378

• HDAC inhibitor quisinostat in synovial sarcoma cell lines

  An RNA Seq study of the effects of HDAC inhibitor Quisinostat on six different synovial sarcoma cell lines

  Dataset EGAD00001003810

• Genetic landscape of hepatocellular carcinoma

  Genetic landscape of hepatocellular carcinoma

  Dataset EGAD00001000131

• A new subgroup of hepatocellular adenomas with sonic hedgehog pathway activation

  Using sequencing and gene expression analyses, we identified a subgroup of HCA characterized by fusion of the INHBE and GLI1 genes and activation of sonic hedgehog pathway. Molecular subtypes of HCAs associated with different patients’ risk factors for HCA, disease progression, and pathology features of tumors. This classification system might be used to select treatment strategies for patients with HCA. Related Publication: Molecular Classification of Hepatocellular Adenoma Associates With Risk Factors, Bleeding, and Malignant Transformation Nault, Jean-CharlesLaurent, Christophe et al. Gastroenterology , Volume 152 , Issue 4 , 880 - 894.e6 http://dx.doi.org/10.1053/j.gastro.2016.11.042

  Dataset EGAD00001003092

• RNA-seq of Liver Cancer

  The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003993

• WGS/RNA-seq pair of an inflammatory hepatocellular adenoma (IHCA)

  This study contain the WGS and RNA-seq aligned bam files for this particular inflammatory hepatocellular adenoma sample.

  Dataset EGAD00001004141

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (35-80%). Recurrent clonal AAV2 insertions are associated with the pathogenesis of rare human hepatocellular carcinoma (HCC) developed on normal liver. This study aimed to characterize the natural history of AAV infection in the liver and its consequence in tumor development. In silico analyses using viral capture data explored viral variants and new clonal insertions. Clonal AAV insertions were positive selected during HCC development on non-cirrhotic liver challenging the notion of AAV as a non-pathogenic virus.

  Dataset EGAD00001004484

• Exome sequencing of advanced hepatocellular carcinoma

  The aim of our project is to decipher the genomic of advanced hepatocellular carcinoma using whole exome sequencing. To this purpose, we aim to compare genetic landscape of advanced hepatocellular carcinoma with early tumor in order to understand the mechanisms of tumor progression. This work will also help to identify new therapeutic targets potentially useful to treat patients at advanced stage. This dataset contain whole exome sequencing aligned reads for 41 tumor with matched normal samples

  Dataset EGAD00001004555

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Dataset EGAD00001007762

• VRK3 depletion in Pontine Diffuse Midline Glioma DMG-K27 altered cells

  In order to investigate possible mechanisms underlying the phenotype of cell fitness decline observed following decrease of VRK3 in pontine DMG-K27 altered cells 7, we examined differences in global gene expression. RNA-seq was performed 44h and 60h post-transduction with two distinct shRNAs targeting VRK3 to be able to evaluate the early impact of VRK3 knock-down (KD) in four independent in vitro models of DMG

  Dataset EGAD00001010097

• Low-coverage whole-genome sequencing of cancer and healthy plasma circulating DNA

  Plasma samples from patients with melanoma (stage II/III/IV) and breast cancer (stage IV) as well as healthy individuals were subjected to low-coverage whole-genome sequencing (less than 10x average depth). This dataset contains raw fastq files from 39 breast cancer, 127 melanoma and 42 healthy control plasma samples.

  Dataset EGAD00001011817

• Multiregional single cell RNA sequencing of human renal cell carcinoma

  The dataset comprises of 5' single cell RNA sequencing with TCR enrichment with 10x Genomics' Chromium technology of multiregional biopsies of human renal cell carcinomas. Biopsies from different tumour regions, the tumour-normal interface, normal kidney, normal adrenal, metastatic regions, peri-nephric fat, and peripheral blood were sequenced from 12 patients with kidney tumours.

  Dataset EGAD00001008030

• Germline BAMs from patients with both uveal and cutaneous melanoma

  Germline BAMs from blood/saliva samples from patients diagnosed with both uveal and cutaneous patients. Reads have been aligned, deduplicated and recalibrated.

  Dataset EGAD00001011676

• Dataset for RNA and Exome sequencing of Glioblastoma samples

  This dataset contains RNA Seq, 10x scRNA Seq and Exome sequencing of glioblastoma samples. Sequencing was performed on a Illumina NovaSeq 6000 and Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD00001012235

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Dataset EGAD00001006427

• MutWP1 CRUK Grand Challenge Mutographs of Cancer Colorectal

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Dataset EGAD00001007510

• Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma

  Whole genome, exome and RNA sequencing of TFCP2-rearranged rhabdomyosarcoma, 86 samples of paired fastq files, sequenced on: Illumina HiSeq 2500 using Agilent SureSelect WGS, Illumina HiSeq 2500 using Illumina TruSeq RNA, Illumina HiSeq 2500 using Agilent SureSelect v5 WES (+UTRs), Illumina HiSeq 4000 using Agilent SureSelect WGS, Illumina HiSeq 4000 using Illumina TruSeq stranded mRNA Kit, Illumina HiSeq 4000 using Agilent SureSelect v5 WES stranded mRNA Kit, Illumina NovaSeq 6000 using Illumina TruSeq Stranded mRNA, Illumina NovaSeq 6000 using Illumina TruSeq Nano DNA, Illumina HiSeq X Ten using TruSeq Nano DNA.

  Dataset EGAD00001010108

• Methylation profiling of sarcoma and TFCP2-rearranged rhadomyosarcoma samples

  Methylation profiling of 345 sarcoma and TFCP2-rearranged rhadomyosarcoma samples, using the approach described "Genomic, transcriptomic, functional, and mechanistic characterization of rhabdomyosarcoma with FUS-TFCP2 or EWSR1-TFCP2 fusions"

  Dataset EGAD00010002451

• PRADO trial - Personalized response-directed surgery and adjuvant therapy after neoadjuvant ipilimumab plus nivolumab in stage III melanoma

  The dataset includes RNA sequencing data on PRE- treatment biopsies of lymph node metastasis (n=80) The technology used for sequencing is llumina HiSeq 2500

  Dataset EGAD00001012116

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

  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 EGAD00001014788

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

  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 EGAD00001014790

• Amplicon Sequencing for 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

  BAMs from deep sequencing using a custom panel for the study 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

  Dataset EGAD00001015012

• Genome and transcriptome sequence data from a multifocal glioblastoma multiforme tumor patient

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

  Dataset EGAD00001015281

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• Whole genome sequencing of Multiple Myeloma CD138positive bone marrow plasma cells and saliva control samples

  Whole genome paired sequencing of Multiple Myeloma CD138positive bone marrow plasma cells and saliva control samples (6 tripletts, tumor1, tumor2, saliva control) from 6 patients. WGS was done on HiSeq X-Ten or Novaseq 6000 with Illumina TruSeq Nano DNA.

  Dataset EGAD00001008618

• Bone marrow microenvironment of 6 newly diagnosed myeloma patients using 10X Genomics scRNA- and TCR-sequencing

  10X Genomics scRNA- and TCR-sequencing (Chromium Next GEM Single Cell 5’ Reagent Kit v1.1) was performed on the plasma cell depleted mononuclear fraction of bone marrow aspirates from 6 patients with newly diagnosed multiple myeloma. Generated gene expression libraries were paired-end sequenced on the NovaSeq 6000 S2. Generated V(D)J libraries were paired-end sequenced on the NextSeq 550.

  Dataset EGAD00001009270

• WGS and RNA-Seq data of 2 additional patients of newly diagnosed multiple myeloma (NDMM)

  For WGS DNA of tumor or control samples was prepared for paired sequencing using the Illumina TruSeq DNA Nano Kit and sequenced on NovaSeq 6000. For RNA-Seq the sequencing Kit Illumina TruSeq stranded mRNA was used with the same sequencer. There are 4 samples for WGS (18 runs) and 4 samples for RNA (4 runs) available.

  Dataset EGAD00001009627

• Genome and transcriptome sequence data from a progressive facial plexiform neurofibroma tumor patient

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

  Dataset EGAD00001015282