3796 results for "*oma"

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• Leiomyosarcoma Cancer Transcriptome Sequencing

  RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

  Dataset EGAD00001003192

• Constit Genome Sequencing

  WGS blood data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 67 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x.

  Dataset EGAD00001003190

• Leiomyosarcoma Cancer Genome Sequencing

  WGS cancer data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 50x.

  Dataset EGAD00001003191

• Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

  Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

  Dataset EGAD00001003200

• Precursor lesions, clonal architecture and relapse in Wilms nephroblastoma

  Targeted resequencing at high depth (21 genes, 9 chromosomal regions): at least 4 FFPE samples per case and matched germline DNA: * 100 cases with detailed outcome data, including 15 cases with tumour relapse (515 samples) * 40 cases with matched pre-chemotherapy biopsies (240 samples) * 50 nephrogenic rests matched to above cases (50 samples) We expect a proportion (possibly 10%) of cases to be mutationally silent on the above studies, and propose to subsequently carry out integrated whole-genome, methylome and transcriptome studies on matched frozen tissue from these cases

  Dataset EGAD00001003217

• BGISeq-500 sequencing of tumour-normal sample pairs from three mesothelioma patients

  Aligned, merged and deduplicated BAM files from BGISeq-500 sequencing of six samples: matched tumour-normal pairs from three melanoma patients.

  Dataset EGAD00001003221

• HiSeqXTen sequencing of tumour-normal sample pairs from three mesothelioma patients

  Aligned, merged and deduplicated BAM files from HiSeqXTen sequencing of six samples: matched tumour-normal pairs from three melanoma patients.

  Dataset EGAD00001003222

• Poly A transcriptom sequencing of mutifocal hepatocellular carcinoma

  Poly A transcriptome sequence of mutifocal hepatocelular carcinoma

  Dataset EGAD00001003231

• Genetic profiling of mucosal melanoma

  Primary mucosal melanomas (MMs) arise from melanocytes located in mucosal membranes lining the respiratory, gastrointestinal and urogenital tracts. MMs frequently present late and have a poor prognosis; the 5-year survival rate is only 14%. MM makes up only ~1.4% of all melanomas and it is this rarity that makes knowledge of the genetic changes that contribute to its pathogenesis limited to a small number of exome/genome studies and other targeted studies. Thus to investigate the somatic alterations and mutation spectra in MM genomes, we have extracted genomic DNA from formalin-fixed, paraffin-embedded (FFPE) human MMs, and subjected them to whole exome sequencing. Given the propensity of MM to metastasize, we will also be sequencing metastatic MM lesions; primary and metastatic lesions from the same individual represent an excellent opportunity to identify potential drivers of metastasis in MM. Finally we will sequence 'normal' DNA from the same individual, where possible, to exclude germline variations.

  Dataset EGAD00001003237

• Melanoma C32 ENU Resistance to Single Agent Therapy

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

  Dataset EGAD00001003239

• Identification of drug resistance genes in melanoma by mRNA gene expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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 EGAD00001003244

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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 EGAD00001003245

• Genetic Basis of Hepatosplenic T Cell Lymphoma (HSTL)

  Whole exome sequencing of hepatosplenic T cell lymphoma (HSTL) tumors, paired normals, and cell lines, including (1) 68 exome capture, paired-end Illumina Hiseq sequencing, BAM files from HSTL tumor samples, (2) 20 exome capture, paired-end Illumina Hiseq sequencing, BAM files from HSTL paired normal samples, and (3) 2 exome capture, paired-end Illumina Hiseq sequencing, BAM files from HSTL cell lines.

  Dataset EGAD00001003246

• Clonal expansion of mutated cell population in bladder urothelium

  1cm biospies of from patients undergoing bladder cystectomy will be collected. The underlying muscle and stroma will be removed and the remaining epithelia dissected into small sequential areas which will be sent for ultra-deep exome sequencing using a panel of known cancer and viral genes. Sequence analysis using similar methods to Martincorena I et al (Science 2015, 348:880) will provide an idea of the somatic mutational landscape in these patient samples. Individual patient muscle samples will also be sequenced as a reference.

  Dataset EGAD00001003250

• Identification of drug resistance genes in melanoma by Exome Sequencing

  The cell lines in this study are a combination of internally sequenced (cosmic) and externally sequenced cell lines known to be “double-wild-type” (lacking BRAF and NRAS somatic mutations). These sequences were realigned in this data set for consistency.

  Dataset EGAD00001003260

• Whole-genome sequencing (WGS) data of Gastric adenocarcinoma and adjacent normal tissues

  High-coverage WGS sequencing of DNA samples from 90pairs GCs was performed on the Illumina HiSeq X Ten System.

  Dataset EGAD00001003269

• Pseudomyxoma peritonei exome sequencing vcf-files

  Dataset EGAD00001003297

• RNASeq on HiSeq platform of 95 pancreatic adenocarcinoma cases

  BAM outputs from RSEM (https://deweylab.github.io/RSEM/) analysis of RNASeq sequencing on HiSeq platform of tumour samples from 95 pancreatic adenocarcinoma cases.

  Dataset EGAD00001003298

• WGS of T-cell and NK-cell lymphoma for ICGC (NKTL-SG)

  WGS of T-cell and NK-cell lymphoma The tumor samples were sequenced with Illumina HiSeq 2500 platform and the resulting FASTq files have been uploaded.

  Dataset EGAD00001003271

• Melanoma_SNP6

  Melanoma cell lines CNV by SNP6

  Dataset EGAD00010001216

• Whole Exome and Target Sequencing Data in 75 Samples from 5 Hepatocellular Carcinoma Patients.

  Whole Exome and Target Sequencing Data in 75 Samples from 5 Hepatocellular Carcinoma Patients. The sequencing was performed by Illumina HiSeq 4000. Background and aims: Intratumoral heterogeneity (ITH) challenges identifying mutations with target therapy potential whereas circulating cell-free DNAs (cfDNAs) could reflect nearly the entire mutation spectrum in given tumors. We investigated how to minimize the limit of ITH for profiling hepatocellular carcinoma (HCC).Methods: Thirty-two multi-regional HCC samples from five patients were subjected to whole exome sequencing (WES) and targeted deep sequencing (TDS). ITH extent was measured by the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Matched cfDNAs were also analyzed by WES and TDS. Profiling efficiencies of single tumor specimen and cfDNA were compared and the one better depicted mutational landscape was selected to screen therapeutic targets.Results: We found variable extents of ITH in HCCs and observed branched and parallel evolution patterns. ITH level decreased at higher sequencing depth of TDS than that measured by WES (28.1% vs 34.9%, P < 0.01) but it remained unchanged upon additional samples analyzed. TDS of single tumor specimen detected an average of 70% the total mutations in HCC. Although more mutations were detected in cfDNA under TDS than WES, an average of 47.2% total HCC mutations uncovered by cfDNA suggested tissue outperform cfDNA and the latter may serve as alternative in profiling HCC genome. Consequently, TDS of single tumor tissue in 66 patients and cfDNAs in four unresectable HCCs identified 38.6% (26/66 and 1/4) patients bearing therapeutic targets.Conclusions: TDS of single tumor specimen could largely circumvent ITH to uncover mutations indicative of target therapy in HCC.

  Dataset EGAD00001003278

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279

• Genomics of enteropathy-associated T cell lymphoma (EATL)

  Whole exome sequencing of enteropathy-associated T cell lymphoma (EATL) tumors and paired normals, as well as RNA-sequencing of EATL tumors: including (1) 69 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples, (2) 36 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL paired normal samples, and (3) 32 RNAseq, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples.

  Dataset EGAD00001003284

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Dataset EGAD00001003324

• RNA-Seq and WXS from 6 glioblastoma patients

  RNA-Seq and WXS from 6 glioblastoma patients

  Dataset EGAD00001003293