4924 results for "*oma"

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• Acral Melanoma PDXs from the admixed Brazilian Population - Patient Derived Xenograft samples VCF files with somatic SNV and INDELs - Whole exome sequencing data

  Raw, flagged and annotated VCF files with somatic calls made with CavEMan and Pindel for Patient Derived Xenograft samples. Variant effect prediction was run with Ensembl VEP v103. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015749

• 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 EGAD00001010316

• 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 EGAD00001010317

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

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

  Dataset EGAD00001003669

• 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

• Mechanism and targeted therapy of Vemurafenib-Resistant Hairy-Cell Leukemia

  The discovery of the BRAF V600E mutation in almost all cases of hairy-cell leukemia has led to the widespread adoption of the BRAF inhibitor vemurafenib for treatment of chemotherapy-resistant cases. Impressive responses are reported; however, acquired resistance is common. Whilst diverse mechanisms of vemurafenib resistance have been elucidated in melanoma, the basis of resistance in HCL is unclear. Here we apply whole genome and deep targeted sequencing to investigate resistance mechanisms and potential therapeutic strategies in a patient with aquired resistance to vemurafenib.

  Dataset EGAD00001003924

• Mapped RNA-Seq data

  Mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma.

  Dataset EGAD00001001939

• 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 EGAD00001002046

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• Multiple Myeloma Diagnosis to Relapse study samples (2016-01-27)

  The study will investigate serial samples from the same patient taken at the time of MGUS or SMM diagnosis, and later at the time of evolution towards MM. Samples will be sequenced by whole genome along with a matched normal to obtain the highest possible amount of information toinvestigate genomic changes at disease evolution. This dataset contains all the data available for this study on 2016-01-27.

  Dataset EGAD00001001898