4982 results for "*oma"

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• scRNA data of neuroblastoma patients

  31 single-cell transcriptomes of neuroblastomas and normal human developing adrenal glands at various stages of embryonic and fetal development

  Dataset EGAD00001006624

• Chip-Seq data of neuroblastoma patients

  144 sample from individuals with ALT-positive neuroblastoma tumors, chip-seq sequencing

  Dataset EGAD00001006625

• hcWGS data of neuroblastoma patients

  238 samples from individuals with ALT-positive neuroblastoma tumors, high coverage whole genome sequencing

  Dataset EGAD00001006626

• Leiomyosarcoma RNA-Seq

  RNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic12 relapses) and 13 tumors treated with radiation(7 primaries, 6 metastatic relapses). RNA-Seq sequencing was performed using established protocols on Illumina HiSeq 2500

  Dataset EGAD00001006628

• WES inform samples

  89 samples of individuals with ALT-positive neuroblastoma tumors, exome sequencing

  Dataset EGAD00001006637

• lcWGS inform data of neuroblastoma patients

  97 samples of individuals with ALT-positive neuroblastoma tumors, low coverage whole genome sequencing

  Dataset EGAD00001006638

• hcWGS inform data of neuroblastoma patients

  63 samples of individuals with ALT-positive neuroblastoma tumors, high coverage whole genome sequencing

  Dataset EGAD00001006639

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643

• 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

• Whole genome sequencing of retinoblastoma reveals the diversity of rearrangements disrupting RB1 and uncovers a treatment related mutational signature

  Background: The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable suggesting alternative pathways to malignancy. Methods: We applied comprehensive whole genome sequencing (WGS) and transcriptomics to sporadic retinoblastomas derived from twenty patients attending our clinic, contrasting these results to that obtained through customary clinical testing. We sought RB1 and other driver mutations, investigated mutation burden, mutational signatures and phylogenetic relatedness in one case of bilateral retinoblastoma. Results: At least one RB1 mutation was identified in all retinoblastomas. We confirmed RB1 mutations previously identified by clinical screening, identified three new RB1 mutations and provided clarity to the mechanism behind a further six mutations. Eight tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Potential driver mutations included mutations in BCOR (5/20) and amplification of MYCN (2/20) and MDM4 (1/20). We show that RB1 mutations are not mutually exclusive of MYCN amplifications, and further reveal that all tumours demonstrate increased MYCN expression suggesting a universal role in retinoblastoma tumorigenesis.  Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. In-keeping with previous WGS of paediatric cancers, the mutation burden in retinoblastomas was extremely low. Mutational signature analysis showed a predominance of signatures associated with cell division and an absence of ultraviolet-related DNA damage. In a tumour exposed to chemotherapy prior to enucleation, a profound platinum-related mutational signature was observed. Conclusions: WGS provides a complete picture of the genomic landscape of retinoblastomas, allowing the discovery of mutations otherwise undetected by conventional clinical screening approaches. The presence of at least one RB1 mutation in all retinoblastomas and the relative paucity of driver mutations in other genes suggests mutations beyond RB1, MYCN and BCOR are rare. Whilst most RB1 mutations are identifiable by clinical screening, the increased resolution and ability to detect otherwise elusive rearrangements of RB1 by WGS, confirming whether they are somatic or germline, has important repercussions on clinical management and advice on recurrence risks.

  Dataset EGAD00001006431

• Breast implant-associated anaplastic large cell lymphoma shallow whole genome sequencing for copy number analysis and Whole exome sequencing data.

  Shallow whole genome sequencing of 29 BIA-ALCL patients for copy number analysis and 24 Alk-negative ALCL samples as control cohort. 7 Whole exome sequencing BIA-ALCL samples.

  Dataset EGAD00001006433

• 20201006_EGA_MELA_CRKL_RNA

  Illumina RNASeq sequencing of tumour samples from 53 cases of cutaneous melanoma and 61 cases of acral melanoma

  Dataset EGAD00001006439

• Whole exome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole exome sequencing reads from 10 normal and 14 cell lines based on Agilent SureSelect XT Human All Exon v6. They are all 2*100bp reads sequenced using Illumina HiSeq4000.

  Dataset EGAD00001006440

• Whole transcriptome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole transcriptome sequencing reads from 8 cell lines based on TruSeq stranded mRNA kit (Illumina). They are all 2*75bp reads sequenced using Illumina NextSeq500.

  Dataset EGAD00001006441

• Whole Exome Sequencing data of glioma from the Chinese Glioma Genome Atlas (CGGA) project

  Glioma is the most common and aggressive brain cancer in adults. While primary glioma has been widely studied, molecular characterization of recurrent glioma is still rare. The high-quality sequencing data that we generated provides a useful resource for the community. The CGGA project contains over 2,000 samples from Chinese cohorts. It totally includes the whole-exome sequencing (286), DNA methylation (159), mRNA sequencing (1,018), mRNA microarray (301) and microRNA microarray (198) and matched clinical data. CGGA removes the barriers to researchers, providing rapid and convenient access to high-quality functional genomic data resources for biological research and clinical applications.

  Dataset EGAD00001006445

• DIPG WES and RNA-Seq

  We characterised H3K27M-mutant diffuse intrinsic pontine glioma (DIPG, n=21) and RNA-Seq (n=26 DIPG, 12 normal brain)

  Dataset EGAD00001006450

• Tumor evolutionary trajectories during the acquisition of invasiveness in early stage lung adenocarcinoma

  Genomic analysis between pre-invasive and invasive components of malignant pulmonary nodule (MPN) facilitates the description of lung adenocarcinoma (LUAD) evolutionary patterns. We conduct an analysis of gene-panel sequencing on 53 T1 stage LUAD cases, which extend the understanding of evolutionary trajectories during invasiveness acquisition in early LUAD.

  Dataset EGAD00001006457

• RRBS analysis to characterize the epigenomic conservation between species in the context of Aging and Cancer.

  This dataset contains Raw Reduced Representation DNA bisulfite-sequencing data obtained from human brain samples corresponding to 3 Young and 3 Old individuals (aging context), and 3 normal and 3 Glioblastoma samples (tumor context). RRBS libraries were prepared at Diagenode SA and samples were sequenced using the Illumina Novaseq6000 sequencing platform.The accompanying samples from this study (mouse tissues) are located at the ENA database under the accession number PRJEB41460.

  Dataset EGAD00001006650

• DKFZ-St.Jude Medulloblastoma - 41 MB germline cases, exome data

  Germline exome tumor/control pairs for 41 medulloblastoma cases, MBG cohort sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006658

• DKFZ-St.Jude Medulloblastoma - 218 CEF control exomes

  218 control exomes, CEF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006659

• DKFZ-St.Jude Medulloblastoma - 8 MB cases, exome/WGS data

  Tumor/Control pairs for 8 medulloblastoma cases, MB cohort, mixed exome and whole genome data, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006660

• DKFZ-St.Jude Medulloblastoma - 70 PAN-GATC control exomes

  Exome controls for 70 individuals, PAN-GATC cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006661

• DKFZ-St.Jude Medulloblastoma - 3 XI046 SF controls, WGS data

  3 control whole genomes, SF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006662

• DKFZ-St.Jude Medulloblastoma - 9 SJMB tumor/control pairs, exome

  9 tumor/control exomes, SJMB samples, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006663

• DKFZ-St.Jude Medulloblastoma - 6 TB control exomes

  6 control exomes, TB cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006664

• DKFZ-St.Jude Medulloblastoma - 225 clinical cases, control exomes with some paired tumor.

  225 clinical cases, control exomes with some paired tumor data, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006665

• Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – patient metatdata (Mutographs)

  Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – patient metatdata (Mutographs)

  Dataset EGAD00001006732

• Fecal 16S rRNA gene sequencing

  Human fecal 16S rRNA gene sequencing data from patients treated with combined anti-CTLA-4 and anti-PD-1 immunotherapy for advanced melanoma.

  Dataset EGAD00001006735

• Fecal whole metagenomic shotgun sequencing data.

  Human fecal WMS data from patients treated with combined anti-CTLA-4 and anti-PD-1 immunotherapy for advanced melanoma.

  Dataset EGAD00001006734

• Proteome data

  Proteome data of neuroblastoma patients

  Dataset EGAD00001006737

• Sequencing data for oesophageal and related samples - Scott et al (WGS, RNA)

  Data supporting: "Evidence that polyploidy in esophageal adenocarcinoma originates from mitotic slippage caused by defective chromosome attachments" Scott et al. WGS and RNAseq sequencing data Organoid, tumour and normal samples BAM files

  Dataset EGAD00001006738

• Whole genome sequencing of EBV Associated Nasopharyngeal Carcinoma

  Whole genome sequencing of EBV Associated Nasopharyngeal Carcinoma

  Dataset EGAD00001006429

• RRBS profiling for a cohort including 88 precancer specimens from 62 resected lung nodules from 39 patients including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) and 39 matched normal lung tissues.

  To study the evolution of DNA methylation at genome level and methylation intra-tumor heterogeneity (ITH) during early lung carcinogenesis, we performed multiregional reduced representation bisulfite sequencing (RRBS) of 127 resected lung samples from 39 patients using single end library Hiseq3000.

  Dataset EGAD00001006367

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• Medulloblastoma whole and focused exome sequencing (n=13 patients, n=37 samples)

  Whole exome sequencing: 24 samples matched tumor-normal and one matched CSF. Focused exome sequencing: 17 samples matched tumor-normal-2 time point CSF.

  Dataset EGAD00001006387

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• EPC (eccrine porocarcinoma) WES samples

  Whole-exome sequencing (WES) in a well-characterized sample of 14 matched EP tumour/healthy surrounding tissue samples. The sequencing was done with paired EXOME sequencing on Illumina HiSeq 4000 using Agilent SureSelect XT HS + Human All Exon V7.

  Dataset EGAD00001006395

• WES raw data for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 123 patient samples including 38 normal (22 paired normal and 16 unpaired), 85 tumor-initial, FASTQ file types, Agilent SureSelect Human All Exon V6 Kit

  Dataset EGAD00001006400

• Cam_121 RNA-Seq data

  This dataset contains RNA-Seq data from 204 primary melanomas and 177 regional lymph nodes. More details can be found in the manuscript: "Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study"

  Dataset EGAD00001006401

• Sequencing files for 7 melanoma patients

  Files from whole exome sequencing of matched normals and multiple tumors from 7 melanoma patients. The tumors include primary tumors and distant metastases.

  Dataset EGAD00001006410

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• Co-amplification of MYC and CCNE1 in aggressive childhood osteosarcoma

  Osteosarcoma, the most common primary malignant tumour of bone, affects children and adults alike. No fundamental biological differences between paediatric and adult osteosarcoma are known. Here, we apply multi-region whole genome sequencing to an index case of a four-year old child whose aggressive tumour harboured high level, focal amplifications of MYC and CCNE1 connected by translocations. We re-analysed copy number readouts of 258 cases of high-grade osteosarcoma from three different cohorts and identified an additional three cases with MYC and CCNE1 co-amplification, confined to children and associated with aggressive disease. Examining the age distribution of MYC and CCNE1 amplicons across all cases revealed a significant enrichment of focal MYC amplification in children, whereas CCNE1 amplification is not strictly restricted to children. Our findings indicate that amplification of the MYC oncogene, known to be associated with a poor outcome, delineates a variant of osteosarcoma specific to childhood. When co-amplified with CCNE1, it may herald an aggressive disease course.

  Dataset EGAD00001006859

• rna-seq data of multiple myeloma patients

  6 samples from individuals with multiple myeloma with selective elimination of immunosuppressive T cells, rna sequencing

  Dataset EGAD00001006866

• CASCADE Metastatic Melanoma Rapid Autopsy sequencing data

  Sequence data (paired-end FASTQ format) for 209 samples from 73 sample sites, from 7 individuals. Samples include primary melanomas, metastatic tumours and ctDNA

  Dataset EGAD00001006867

• Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – sequence data (Mutographs)

  Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – sequence data (Mutographs)

  Dataset EGAD00001006868

• RNA-seq dataset for Mutation-specific non-canonical pathway of PTEN as a distinct therapeutic target for glioblastoma

  RNA-seq dataset for Mutation-specific non-canonical pathway of PTEN as a distinct therapeutic target for glioblastoma

  Dataset EGAD00001006877

• THE GENOMIC LANDSCAPE OF ACTINIC KERATOSIS

  Actinic keratoses (AK) are lesions of epidermal keratinocyte dysplasia and are precursors for invasive cutaneous squamous cell carcinoma (CSCC). Identifying the specific genomic alterations driving progression from normal skin-AK-invasive CSCC is challenging due to the massive ultraviolet radiation-induced mutational burden characteristic at all stages of this progression. Here, we report the largest AK whole exome sequencing study to date and perform mutational signature and candidate driver gene analysis on these lesions. We demonstrate in 37 AK, from both immunosuppressed and immunocompetent patients, that there are significant similarities to CSCC in terms of mutational burden, copy number alterations, mutational signatures and patterns of driver gene mutations. We identify 44 significantly mutated AK driver genes and confirm that these genes are similarly altered in CSCC. We identify the azathioprine mutational signature in all AK from patients exposed to the drug, providing further evidence for its role in keratinocyte carcinogenesis. CSCC differ from AK in having higher levels of intra-sample heterogeneity. Alterations in signaling pathways also differ, with immune-related signaling and TGF-β signaling significantly more mutated in CSCC. Integrating our findings with independent gene expression datasets confirms that dysregulated TGF-β signaling may represent an important event in AK-CSCC progression.

  Dataset EGAD00001006894

• scRNA-seq of relapsed/refractory multipe myeloma with 10x Chromium (3´ v2)

  This dataset includes 87 scRNA-seq samples of bone marrow aspirates of 20 relapsed/refractory patients generated with the 3´(v2) kit of the 10x Chromium platform. Bone marrow cells have been sorted using CD138 +/- fractions using magnetic beads for plasma cell enrichment and processed independently. For 14/20 patients multiple treatment timepoints are available that includes samples before treatment and at relapse during treatment.

  Dataset EGAD00001006903