4984 results for "*oma"

in 46.81 milliseconds.

• 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

• RNA of peripheral blood for pancreatic cancer and chronic pancreatitis

  Samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer, chronic pancreatitis, or none of these. Please cite this article when using data: Al-Fatlawi, A.; Malekian, N.; García, S.; Henschel, A.; Kim, I.; Dahl, A.; Jahnke, B.; Bailey, P.; Bolz, S.N.; Poetsch, A.R.; Mahler, S.; Grützmann, R.; Pilarsky, C.; Schroeder, M. Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants. Cancers 2021, 13, 2654. https://doi.org/10.3390/cancers13112654

  Dataset EGAD00001006915

• Exploring the heterogeneity of sarcoma using single cell sequencing

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001006786