8252 results for "canc*"

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• CPC-GENE Prostate Cancer Heterogeneity Study

  Raw sequence data, fastq format

  Dataset EGAD00001002885

• 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

• Whole genome sequencing of matched esophageal tumor-normal samples

  The dataset includes whole genome sequencing (WGS) data on ten matched esophageal tumor-normal pairs. WGS was performed by the cancer sequencing service of CG with an average read coverage of approximately 50-fold. Illumina HiSeq2000 instrument was used to perform the sequencing.

  Dataset EGAD00001004832

• Korean Advanced Thyroid Cancer Dataset

  Massively-parallel DNA sequencing of 113 advanced thyroid cancers and Massively-parallel RNA sequencing of 25 advanced thyroid cancers

  Dataset EGAD00001004845

• Amplicon sequencing of adenoma to carcinoma paired samples from colon

  Colorectal cancer panel sequencing of 100 adenoma and carcinoma samples . Cancer Hot Spot panel sequencing of 7 samples from one poly.

  Dataset EGAD00001004848

• Genentech gallbladder cancer study - exome

  Genentech gallbladder cancer study - exome

  Dataset EGAD00001004853

• Genentech gallbladder cancer study - RNA-seq

  Genentech gallbladder cancer study - RNA-seq

  Dataset EGAD00001004854

• Genentech gallbladder cancer study - whole genome sequencing

  Genentech gallbladder cancer study - whole genome sequencing

  Dataset EGAD00001004855

• TONIC study RNASeq

  Transcriptome sequencing of 97 matched TNBC breast cancer metastasis samples obtained from 50 unique patients assayed at two timepoints: at baseline (directly after patient randomization), and post-induction treatment or control waiting period. The included raw transcriptome sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004858

• TONIC study Whole Exome Sequencing

  Paired-end whole exome sequencing of 50 TNBC breast cancer metastasis samples and matched normal samples obtained from 50 unique patients assayed at study baseline (directly after patient randomization). The included raw sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004857

• Preferential infiltration of unique Vγ9Jγ2‐Vδ2 T cells into glioblastoma multiforme

  Glioblastoma multiforme (GBM) is clinically highly aggressive as a result of evolutionary dynamics induced by cross-talk between cancer cells and a heterogeneous group of immune cells in tumor microenvironment. The brain harbors limited numbers of immune cells with few lymphocytes and macrophages; thus, innate‐like lymphocytes, such as γδ T cells, have important roles in antitumor immunity. Here, we characterized GBM‐infiltrating γδ T cells, which may have roles in regulating the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor‐infiltrating and blood‐circulating γδ T cells from four patients were analyzed by next-generation sequencing-based T-cell receptor (TCR) sequencing in addition to mutation and immune profiles in four GBM cases. In all tumor tissues, abundant innate and effector/memory lymphocytes were detected, accompanied by large numbers of tumor‐associated macrophages and closely located tumor‐infiltrating γδ T cells, which appear to have anti-tumor activity. The immune-related gene expression analysis using the TCGA database showed that the signature gene expression extent of γδ T cells were more associated with those of cytotoxic T and Th1 cells and M1 macrophages than those of Th2 cells and M2 macrophages. Although the most abundant γδ T cells were Vγ9Vδ2 T cells in both tumor tissues and blood, the repertoire of intratumoral Vγ9Vδ2 T cells was distinct from that of peripheral blood Vγ9Vδ2 T cells and was dominated by Vγ9Jγ2 sequences, not by canonical Vγ9JγP sequences that are mostly commonly found in blood γδ T cells. Collectively, unique GBM‐specific TCR clonotypes were identified by comparing TCR repertoires of peripheral blood and intra‐tumoral γδ T cells. These findings will be helpful for the elucidation of tumor-specific antigens and development of anticancer immunotherapies using tumor-infiltrating γδ T cells.

  Dataset EGAD00001004862

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867

• Genetic alterations in benign breast biopsies of subsequent breast cancer patient

  This dataset consists of amplicon sequencing of fibrocystic breast tissues, subsequent cancer tissue and germline control of 17 patients. The target genes include all exons of 27 protein-coding genes and 2 non-coding genes, as well as mutation hotspots in three cancer genes, frequently mutated in breast cancer. Ion AmpliSeq libraries were generated and sequenced on the Ion S5 XL system.

  Dataset EGAD00001004874

• Proteogenomic Landscape of Curable Prostate Cancer

  Aligned RNA-seq sequences in this dataset are from the Proteogenomic Landscape of Curable Prostate Cancer study

  Dataset EGAD00001004875

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

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

  Dataset EGAD00001004903

• Targeted analysis of chondrosarcoma cancer genes (2019-04-01)

  Targeted analysis of chondrosarcoma cancer genes . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004877

• Evolution of the cancer epigenome in myeloproliferative neoplasms. (2019-04-01)

  Evolution of the cancer epigenome in myeloproliferative neoplasms. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004879

• Genetic vulnerability of knockout cancer lines (2019-04-01)

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004881

• Exome sequencing of synchronous colorectal cancers

  The data consists of 47 exome-sequenced synchronous colorectal cancers from 23 patients. The exomes of corresponding normal samples were used to remove germline variants. All patients are Finnish (white Caucasian). All except one patient (sync_11 who belongs to a LS family) were assumed sporadic. The sequence data was produced with Illumina HiSeq 4000.

  Dataset EGAD00001004884

• Somatic mutations in twin breast cancers (2019-04-03)

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004890

• Whole Exome PC9 and A375 (2019-04-03)

  Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004891

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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 2019-04-03.

  Dataset EGAD00001004893

• Clonal haematopoiesis in patients with AAA (2019-04-03)

  Recent advances in genomics have demonstrated that clonal haemopoiesis driven by leukaemia associated somatic mutations is a relatively common phenomenon that increases in frequency with advancing age. Whilst individuals with clonal haemopoiesis have an increased risk of developing haematological malignancies, they also have an increased mortality from other causes. Additionally, certain mutations are almost exclusively seen in individuals aged 70 years or older, whilst others are seen in individuals with non-haematological cancers including breast and ovarian. Recently, clonal haemopoiesis was found to be associated with a significantly increased risk of atherosclerotic cardiovascular disease. This association is thought to be causative with clonally-derived macrophages showing elevated expression of several chemokine and cytokine genes that contribute to atherosclerosis. Another vascular pathology, abdominal aortic aneurysm (AAA), increases with age and shares risk factors with atherosclerosis (including smoking, male sex, high cholesterol). However, the impact of these risk factors and the overlap between AAA and atherosclerosis is poorly understood. To investigate a possible link between clonal haemopoiesis and AAA, we will study DNA samples from 300 patients with AAA and up to 200 controls for evidence of clonal haemopoiesis. This will be done using target DNA enrichment with biotinylated RNA baits followed by high throughput sequencing. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004895

• Predictor_RIO_TNBC (2019-04-03)

  In this study, samples fom a window study of the PARP inhibitor rucaparib in patients with primary triple negative or BRCA1/2 related breast cancer (RIO trial) will be investigated. Samples will undergo whole genome sequence and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004894

• Multi-Region WES of Metastatic Colorectal Cancer

  In order to reconstruct the evolutionary history of metastatic colorectal cancer, we performed whole-exome sequencing of 12 metastatic colorectal cancer patients for whom the primary tumor and matched distant metastases to the brain (n=10) and liver (n=2). For 8 of the 12 patients, multiple regions (n=3-7) of the primary tumor and distant metastases were sequenced.

  Dataset EGAD00001004896