3773 results for "*oma"

in 104.60 milliseconds.

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004651

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the stomach patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the stomach patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004652

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004653

• Genome and transcriptome sequence data from a breast invasive ductal carcinoma patient

  Genome and transcriptome sequence data from a breast invasive ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004654

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the pancreas patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the pancreas patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004663

• Genome and transcriptome sequence data from a neuroendocrine carcinoma patient

  Genome and transcriptome sequence data from a neuroendocrine carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004664

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004716

• Genome and transcriptome sequence data from a metastatic non-small cell lung adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic non-small cell lung adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004714

• RMS_Infinium450K

  Infinium 450K in Rhabdomyosarcoma

  Dataset EGAD00010000897

• Copy number profiling of primary samples and cell lines of retinoblastoma

  Illumina SNP-arrays for matching retinoblastoma-blood pairs and retinoblastoma cell lines.

  Dataset EGAD00010000908

• Glioblastoma CRISPR Screen (2016-06-02)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2016-06-02.

  Dataset EGAD00001002158

• 33 Paired (Normal-Tumor1-Tumor2) MM whole-exome data

  Samples were sequenced from 33 multiple myeloma patients including tumor presentation and relapse samples and a matched patient control sample. Tumor DNA was isolated from CD138-positive plasma cells. Control DNA originated from peripheral blood leukapheresis products collected after induction therapy. Libraries were prepared using the SureSelectQXT sample prep kit and the SureSelect Clinical Research Exome kit (Agilent), with additional baits covering the Ig and MYC loci. Paired-end sequencing was performed to an average sequencing depth of 118× on a HiSeq2500 (Illumina).

  Dataset EGAD00001002165

• Clear cell renal cell carcinoma (HIPO-045)

  Exome from EGAS00001001861

  Dataset EGAD00001002166

• Leiden_melanomafamilies

  Around 10% of patients who present in melanoma clinics have a first degree relative with a previous diagnosis of melanoma. While around 3% have three or more relatives who have been diagnosed with the disease. In this project we will whole genome sequence patients from large Dutch familial melanoma pedigrees to identify mutations in genes that drive melanomagenesis. The identification of these genes will facilitate the management of familial melanoma patients and their families.

  Dataset EGAD00001002186

• Barcelona kids with melanoma

  This set of samples is composed of eight young people (7-16 years old) that have developed melanoma with first-degree relatives that have also developed cancer, which suggests a genetic component to their disease. Here we want to sequence these samples in order to find the causative mutations. As these samples do not carry any of the high-penetrance mutations known to date, finding the genes(s) responsible will offer new insights into the genetic mechanisms underlying predisposition to melanoma.

  Dataset EGAD00001002198

• Merged analysis-ready bam files: HiSeq sequencing of matched tumour/normal DNA samples from Pancreatic Ductal Adenocarcinoma cases

  Additional sequencing data for 173 donors in EGAS00001000154, a study of Pancreatic Ductal Adenocarcinoma. WGS libraries were used for high-cellularity cases, WXS sequencing to high depth on low-cellularity cases. HiSeq 2xxx platform was used in all cases. The analysis files associated with this dataset are merged, de-duplicated bams aligned against GRCh37, one tumour and one normal bam per donor.

  Dataset EGAD00001002192

• EATL-II whole-exome sequencing profile

  Enteropathy-associated T-cell lymphoma (EATL), a rare and aggressive intestinal malignancy of intraepithelial T lymphocytes, comprises two disease variants (EATL-I and EATL-II) differing in clinical characteristics and pathological features. Here we report findings derived from whole exome sequencing of 15 EATL-II tumor-normal tissue pairs.

  Dataset EGAD00001002220

• PSCP_mutation analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002231

• PSCP_bisulphite analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. 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 EGAD00001002235

• Melanoma C32 ENU resistance to Combination Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Dataset EGAD00001002234

• RNA expression profiling of melanoma patient-derived xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growth 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 EGAD00001002230

• BAP1 sequence of uveal melanoma and mesothelioma samples

  Detection of BAP1 mutations in DNA from uveal melanoma and mesothelioma samples.

  Dataset EGAD00001002229

• Gencode_550K

  Lymphoma samples using HumanOmni

  Dataset EGAD00010000949

• Gencode_500K

  Lymphoma samples using 450k

  Dataset EGAD00010000948

• Gencode_15K

  Lymphoma samples using CytoSNP

  Dataset EGAD00010000947

• Transcriptome/Exome for glioblastoma intra-tumoral heterogeneity

  Total of 49 tumor specimens from 20 patients were subjected for whole-exome and/or whole-transcriptome sequencing including matched normal/blood. Tumor samples are acquired based on 4 categories; 1) locally adjacent tumors, 2) multifocal/multicentric tumors, 3) 5-ALA (+/-) tumors and 4) Longitudinal tumors.

  Dataset EGAD00001002248

• Single-cell Transcriptome for glioblastoma intra-tumoral heterogeneity

  Single-Cell RNA Sequencing of 355 cells isolated from 7 tissue fragments of 3 patients corresponding to locally adjacent tumor, multifocal with recurrence and sections segregated by a marker of tumor cellularity (5-ALA).

  Dataset EGAD00001002249

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq EAC expression data - Publication Secrier & Li et al., 2016, Nature Genetics

  Dataset EGAD00001002260

• Exome-sequencing of human B cell lymphoma cell lines

  26 cell lines derived from human Diffuse Large B Cell lymphomas (DLBCL) or Burkit Lymphomas (BL) were subjected to whole exome sequencing. Exome capture was carried out using the SeqCap EZ Exome Library 2.0 kit (Roche/Nimblegen) and 100 bp single-read sequencing was performed on a HiSeq2500 (Illumina). 82% of the coding region was covered at least 30x.

  Dataset EGAD00001002262

• BLUEPRINT release August 2016, ChIP-Seq for Activated B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Activated B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 12 run(s), 12 experiment(s), 12 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002307

• BLUEPRINT release August 2016, ChIP-Seq for Burkitt Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Burkitt Lymphoma sample(s). 13 run(s), 13 experiment(s), 13 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002329

• BLUEPRINT release August 2016, RNA-Seq for Mantle Cell Lymphoma, on genome GRCh38

  RNA-Seq data for 5 Mantle Cell Lymphoma sample(s). 5 run(s), 5 experiment(s), 5 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002336

• BLUEPRINT release August 2016, ChIP-Seq for Multiple Myeloma, on genome GRCh38

  ChIP-Seq data for 4 Multiple Myeloma sample(s). 34 run(s), 28 experiment(s), 28 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002379

• BLUEPRINT release August 2016, ChIP-Seq for Mantle Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 5 Mantle Cell Lymphoma sample(s). 35 run(s), 35 experiment(s), 35 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002397

• BLUEPRINT release August 2016, RNA-Seq for Multiple Myeloma, on genome GRCh38

  RNA-Seq data for 14 Multiple Myeloma sample(s). 14 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002401

• TFL unique case study

  Whole exome sequencing of a normal sample, primary tumor sample, and relapse tumor sample of a transformed non-Hodgkins follicular lymphoma patient with extraordinary response to treatment.

  Dataset EGAD00001002707

• BLUEPRINT release August 2016, Bisulfite-Seq for Mantle Cell Lymphoma, on genome GRCh38

  Bisulfite-Seq data for 5 Mantle Cell Lymphoma sample(s). 65 run(s), 5 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002505

• BLUEPRINT release August 2016, ChIP-Seq for Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 10 run(s), 10 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002506

• BLUEPRINT release August 2016, Bisulfite-Seq for Multiple Myeloma, on genome GRCh38

  Bisulfite-Seq data for 5 Multiple Myeloma sample(s). 63 run(s), 7 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002521

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002546

• BLUEPRINT ChIP-Seq from two mantle cell lymphoma patients

  BLUEPRINT ChIP-Seq from two mantle cell lymphoma patients

  Dataset EGAD00001002655

• Genome and transcriptome sequence data from a Ewing sarcoma patient

  Genome and transcriptome sequence data from a Ewing sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002552

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002541

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002587

• Genome and transcriptome sequence data from a squamous cell carcinoma of vulva patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of vulva patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002586

• Genome and transcriptome sequence data from a vulvar metastatic melanoma patient

  Genome and transcriptome sequence data from a vulvar metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002584

• Genome and transcriptome sequence data from a retroperitoneal leiomyosarcoma patient

  Genome and transcriptome sequence data from a retroperitoneal leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002583

• Genome and transcriptome sequence data from a squamous cell carcinoma of anal canal patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of anal canal patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002582

• Genome and transcriptome sequence data from a carcinoma of left lower outer quadrant patient

  Genome and transcriptome sequence data from a carcinoma of left lower outer quadrant patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002579

• Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002577

• Genome and transcriptome sequence data from a ductal carcinoma of left breast patient

  Genome and transcriptome sequence data from a ductal carcinoma of left breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002574

• Genome and transcriptome sequence data from an infiltrating ductal carcinoma of right breast patient

  Genome and transcriptome sequence data from an infiltrating ductal carcinoma of right breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002572

• Genome and transcriptome sequence data from an adenocarcinoma of lung patient

  Genome and transcriptome sequence data from an adenocarcinoma of lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002564

• Genome and transcriptome sequence data from a follicular lymphoma patient

  Genome and transcriptome sequence data from a follicular lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002563

• Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma patient

  Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002589

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002593

• Genome and transcriptome sequence data from a peritoneal mesothelioma patient

  Genome and transcriptome sequence data from a peritoneal mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002594

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002595

• Genome and transcriptome sequence data from a porocarcinoma patient

  Genome and transcriptome sequence data from a porocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002596

• Genome and transcriptome sequence data from a pancreatic ductal adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic ductal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002597

• Genome and transcriptome sequence data from a medullary thyroid carcinoma patient

  Genome and transcriptome sequence data from a medullary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002599

• Genome and transcriptome sequence data from an invasive ductal carcinoma of left breast patient

  Genome and transcriptome sequence data from an invasive ductal carcinoma of left breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002601

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002602

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002606

• Genome and transcriptome sequence data from a pleomorphic spindle cell sarcoma patient

  Genome and transcriptome sequence data from a pleomorphic spindle cell sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002608

• Genome and transcriptome sequence data from an invasive carcinoma of left breast patient

  Genome and transcriptome sequence data from an invasive carcinoma of left breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002610

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002611

• Genome and transcriptome sequence data from a thymic carcinoma patient

  Genome and transcriptome sequence data from a thymic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002614

• Genome and transcriptome sequence data from a breast carcinoma patient

  Genome and transcriptome sequence data from a breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002613

• Genome and transcriptome sequence data from an esophageal adenocarcinoma patient

  Genome and transcriptome sequence data from an esophageal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002612

• Genome and transcriptome sequence data from a multifocal hepatocellular carcinoma patient

  Genome and transcriptome sequence data from a multifocal hepatocellular carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002644

• Genome and transcriptome sequence data from a metastatic small cell carcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from a metastatic small cell carcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002641

• Genome and transcriptome sequence data from a clival chordoma patient

  Genome and transcriptome sequence data from a clival chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002640

• Genome and transcriptome sequence data from an endometrial carcinoma patient

  Genome and transcriptome sequence data from an endometrial carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002633

• Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002630

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002626

• Genome and transcriptome sequence data from a squamous cell carcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002624

• Genome and transcriptome sequence data from a metastatic colorectal adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002622

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002621

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002648

• Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002647

• Genome and transcriptome sequence data from an epithelioid mesothelioma patient

  Genome and transcriptome sequence data from an epithelioid mesothelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002646

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas: RNAseq variants

  Variants called from RNA-seq data of meningioma tumors.

  Dataset EGAD00001002649

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas: Somatic exome variants

  Somatic variants called from whole-exome sequencing of meningioma-blood pairs

  Dataset EGAD00001002650

• dataset1

  BLUEPRINT DNA Methylation 450K data of mantle cell lymphoma

  Dataset EGAD00010001012

• Melanoma - Exome sequencing

  whole exome sequencing of tumor- as well as PBMC-derived DNA of five melanoma patients for identification of naturally presented patient-specific neoepitopes

  Dataset EGAD00001002731

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Dataset EGAD00001002738

• Melanoma Germlines subset for BAP1

  These samples comprise both melanoma cases and controls sequenced for a selection of loci linked to disease susceptibility. These bams are a subset of the sequencing restricted specifically to the GRCh37 coding areas of the BAP1 gene.

  Dataset EGAD00001002743

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002891

• RNA-seq of human glioblastoma and matched gliomasphere cell lines (BLN panel)

  This dataset contains all RNA-seq runs for the BLN panel of cell lines and matched parental tumors. Tumor/cell line pairs have been authenticated using SNP profiles and all pairs were confirmed. Please note: The dataset also contains raw data from an early primary culture (BLN-1) where no stable cell line could be generated. Please also note different reference genomes.

  Dataset EGAD00001002893

• WGS, RNA-seq and methyl-seq data for multiple tumour clones from a single glioblastoma case.

  10 bams of WGS data from HiSeqXTen platform; 10 bams of RNA-seq data from HiSeq2500 platform; 7 bams of TruSeq Methyl Capture EPIC sequencing data from HiSeq4000 platform

  Dataset EGAD00001004773

• Targeted bisulfite sequencing

  Raw reads from targeted bisulfite sequencing. The SureSelect Methyl-Seq target enrichment system (Agilent Technologies, Inc., CA, USA) was used to prepare bisulfite sequencing libraries from blood DNA samples of lymphoma patients (Ly1, Ly2), healthy family members (Ly8, Ly9, Ly10, Ly11, Ly12, Ly13 and Ly14), baseline controls (Control1-5), DNMT3A mutation carriers (Id5, Id7, Id9, Id11) and their age-matched controls (Id6, Id8, Id10, Id12). In addition, blood DNA sample of a patient (HLRCC_N7) with germline fumarate hydratase (FH) mutation is included. Illumina paired-end sequencing for targeted libraries from Ly1, Ly2, Ly8, Ly9, Ly10 and Ly11 was done at Karolinska Institutet using 100 base-pair read length and the HiSeq2000 platform. Illumina paired-end sequencing for targeted libraries from Ly12, Ly13, Ly14, and DNMT3A mutation carriers and their age-matched controls was done as a service at BGI (BGI Tech Solutions Co., Ltd., China) using 126 base-pair read length and the HiSeq2500 platform.

  Dataset EGAD00001004785

• Whole genome sequencing informs treatment decision of end-stage metastatic cutaneous angiosarcoma in a patient with Xeroderma Pigmentosum

  Whole genome sequencing (WGS) detects all mutations in a cancer. “Mutational signatures” are patterns of mutations that report the DNA damage and subsequent DNA repair processes that have occurred in cancers. We present a patient with Xeroderma Pigmentosum that developed metastatic angiosarcoma, unresponsive to all lines of sarcoma therapy. Primary tumour WGS revealed a hypermutated tumour, including clonal ultraviolet light-induced mutational patterns (Signature 7) and subclonal signatures of activating mutations of DNA Polymerase-epsilon (POLE)(Signature 10). These signatures are associated with response to immune-checkpoint blockade. Immunohistochemistry confirmed high PD-L1 expression in metastatic deposits. The patient was commenced on anti-PD-L1 therapy and has responded.

  Dataset EGAD00001004786

• Whole genome sequencing data of lung adenocarcinomas

  This dataset includes the whole-genome sequencing data from a study entitled "Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma". Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X Ten machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

  Dataset EGAD00001004793

• RNA-seq dataset of lung adenocarcinomas

  This dataset includes the RNA-seq data from a study entitled "Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma". PolyA tails were captured by Oligo-dT beads, and sequencing run was made in HiSeq 2500 machines. Paired-end FASTQ files are provided in our dataset.

  Dataset EGAD00001004794

• Frequent germline mutations of HAVCR2 in sporadic subcutaneous panniculitis-like T-cell lymphoma.

  Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of peripheral T-cell lymphoma affecting younger cases and associated with hemophagocytic lymphohistiocytosis. To clarify the molecular pathogenesis of SPTCL, we analyzed paired tumor and germline DNAs from 13 patients by whole exome sequencing.

  Dataset EGAD00001004795

• 24 Chordoma samples (WES,WGS)

  Case series of the rare tumor entity chordoma. 9 cases sequenced with Whole Exome Sequencing (WES) and 2 cases sequenced with Whole Genome Sequencing (WGS) were recruited from the personalized oncology program NCT-MASTER/DKTK-MASTER at the German Cancer Research Center. One of the WES patients was re-sequenced at a later time point when he relapsed, this resequencing was done by WGS. Therefore there are 11 patients, one of which with two samples, all of which were sequenced with matched normal controls, amounting to a total number of 24 NGS samples.

  Dataset EGAD00001004825

• Methylation

  Meningioma Methylation

  Dataset EGAD00010001687

• Genomic stratification and liquid biopsy in a rare adrenocortical carcinoma (ACC) case, with dual lung metastases

  Dataset consisting of three WGS BAM files, representing the two dual lung metastases with matched germline control, for a 37 year old female patient, with primary adrenocortical carcinoma. Work conducted at Garvan Institute of Medical Research, Sydney, Australia.

  Dataset EGAD00001004833

• Presentation and relapse myeloma

  Series of 56 paired presentation, relapse and control samples from newly diagnosed, uniformly treated myeloma patients. Deep of treatment response and maintenance allocation (active observation or lenaldiomide) was determined for all. All samples underwent whole exome sequencing with additional baits to cover the myc and immunoglobulin loci. There are 168 (56 presentation, 56 relapse and 56 control) samples in this study. 131 are available as part of this dataset. The remaining 37 are available with dataset accession id EGAD00001001358.

  Dataset EGAD00001004846