7147 results for "canc*"

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• Genome and transcriptome sequence data from an endometrial stromal sarcoma patient

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

  Dataset EGAD00001005899

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (Targeted) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006929

• BAM files ChIP-Seq

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001669

• Whole genome sequencing of a breast cancer cohort with known functional homologous recombination status

  41 breast cancer patients with known functional homologous recombination status (matched normal and tumor genomes, n=82)

  Dataset EGAD00001008027

• Evaluation of capture and amplicon-based targeted sequencing methods on formalin-fixed tumours

  Three capture (Agilent’s SureSelectXT HS, Illumina’s Nextera Rapid Capture Custom, and New England Biolabs’ Next Direct Custom) and one amplicon-based (Qiagen’s Human Breast Cancer Panel) targeted sequencing methods on 6-8 paired blood and FFPE from the Malaysian Breast Cancer Cohort.

  Dataset EGAD00001006879

• Genome and transcriptome sequence data from a metastatic NPC patient

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

  Dataset EGAD00001002020

• Data for the study "Plasma ctDNA is a tumor tissue surrogate and enables clinical-genomic stratification of metastatic bladder cancer"

  Sequencing data from patients with bladder cancer. BAM files from targeted DNA sequencing of bladder cancer driver genes in 344 circulating tumor DNA and tumor tissue samples. BAM files from whole exome sequencing of 49 circulating tumor DNA and tumor tissue samples. Paired FASTQ files from RNA sequencing of 86 tumor tissue samples.

  Dataset EGAD00001006362

• 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

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

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

  Dataset EGAD00001002040

• Single-cell gene expression data from CD8+ T cells from two Austrian COVID19 patients stimulated with wildtype and mutant SARS-Cov-2 peptides

  The data contains single-cell gene sequencing data (10x Genomics) from FACS-purified CD8 T lymphocytes from two Austrian patients. The cells were stimulated with one MHC class I peptides obtained from a common (wild type) variant and an emerging mutant variant of the SARS-Cov-2 virus. Then the samples were multiplexed using hashtag oligos. We provide the raw and aligned sequence data for: i. The single-cell experiments ii. The PCR-amplified samples for enrichment of the hashtag oligo multiplexing barcodes iii. The PCR-amplified samples for enrichment of the T Cell Receptor (TCR) VDJ region for immuno-profiling. The samples and libraries were processed and obtained in collaboration between St. Anna Children's Cancer Research Institute (CCRI), CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the Medical University of Vienna. The cell barcodes and processed data has been submitted to the GEO database with GEO accession GSE166651.

  Dataset EGAD00001006995

• T-WGBS for Naive B Cell

  Tagged-WGBS for 3 Naive B Cell samples of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005966

• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967

• Single cell karyotype sequencing of 7 samples from colorectal cancer (CRC) patients

  Contains data for all cells sequenced for this study. Data is organized as one bam-file per sample. Individual cells can be identified through the CB tag in the bam-files.

  Dataset EGAD00001006438

• hereditary BrEAst Case CONtrol study (BEACCON)

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.

  Dataset EGAD00001007025

• Illumina_WXS_T-XEN-CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from Patient-derived xenograft derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002103

• ENU-LS-411N-TripleTherapy

  BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy.

  Dataset EGAD00001002051

• Genome and transcriptome sequence data from a meningioma patient

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

  Dataset EGAD00001004920

• Sequencing data for oesophageal samples - Killcoyne, Gregson et al (sWGS)

  Data supporting: "Genomic copy number predicts esophageal cancer years before transformation." Killcoyne, Gregson et al. sWGS data 1000 samples BAM files

  Dataset EGAD00001006033

• NICHE - RNA-seq of MMR proficient and MMR deficient early stage colon cancers

  The dataset includes 77 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 39 patients.

  Dataset EGAD00001006042

• NICHE - DNA-seq of MMR proficient and MMR deficient early stage colon cancers

  The dataset includes 174 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 for 39 patients.

  Dataset EGAD00001006041

• Paired-end sequenced plasma DNA samples

  Merged file of low-coverage WGS from 179 plasma DNA samples from non-cancer controls and cancer patients for assessment of size distribution of plasma nuclear DNA fragments.

  Dataset EGAD00001002217

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

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

  Dataset EGAD00001004710

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Pancreatic Organoids (2021-02-02)

  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, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure 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. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006933

• Exome sequencing of replication repair deficient brain cancers

  This dataset contains exome sequencing from replication repair deficient brain tumor samples.

  Dataset EGAD00001006920

• PSCP_bisulphite analysis in hESCs (2018-08-13)

  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/ . This dataset contains all the data available for this study on 2018-08-13.

  Dataset EGAD00001004295