Search Results - EGA European Genome-Phenome Archive

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

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

Colorectal cancer methylation profiling

4 AC samples, each with adenoma, carcinoma and normal colon tissue (12 samples in total) were analysed on the Infinium MethylationEPIC BeadChip for copy number alteration analyses.

Dataset EGAD00010001691

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

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

20190219_EGA_MelanomaOnTreatment

Illumina platform sequencing data for matched tumour-normal DNA samples from 77 melanoma patients participating in a study investigating response to immunotherapy. Selected cases also have RNA sequencing of the tumour.

Dataset EGAD00001004869

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

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

Whole exome sequencing of human and mouse sarcoma samples for personalized therapy

Whole exome sequencing of human and mouse sarcoma samples for creation of personalized therapy options. Tissues were sequenced directly; no interventions or alterations were made to the tissue samples

Dataset EGAD00001004885

Exome sequencing of matching primary tumor and venous tumor thrombus (VTT) renal cell carcinoma (RCC) samples

We performed multiregion whole exome sequencing of a total of 37 samples from five consecutive patients (normal tissue, n=5; primary tumors, n=16; tumor thrombi, n=16) to >35-fold target coverage. Matching primary tumor and venous tumor thrombus samples were analyzed. Four patients had a clear cell RCC, one patient had a poorly differentiated type II papillary RCC (RCC-VTT-04). The latter patient had a friable thrombus, the others were of solid consistency.

Dataset EGAD00001004887

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

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

Dataset EGAD00001004899

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

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