7825 results for "canc*"

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• SPECTA: NGS Screening Program for Efficient Clinical Trial Access

  SPECTA comprises a network of participating European clinical sites and NGS screening platforms that can screen individual patients for multiple molecular targets and potentially allow the design of trials that will match the specific biology of the diseases affecting specific patients with cancer.

  Dataset EGAD00001000894

• Metastatic Breast Cancer Whole Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000899

• TRACERx pilot study.

  Multi-region Illumina whole-exome and/or whole-genome sequencing on tumor regions collected from early-stage NSCLC patients who underwent definitive surgical resection prior to receiving adjuvant therapy.Detected variants were validated on Ion AmpliSeq™ Custom Panel and/or Comprehensive Cancer Gene Panels.Patients covered by this dataset: L001, L002, L003, L004, L008 and L011.

  Dataset EGAD00001000900

• Targeted gene sequencing of gallbladder cancer

  The dataset includes the targeted gene sequencing data from51 pairs of gallbladder caner tissues and patient-matched normal tissues.

  Dataset EGAD00001000902

• Cancer Cell Line Exome Sequencing

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001039

• Multifocal Breast Project

  Comparison of genomic rearrangements and DNA methylation patterns between different foci of multiple synchronous (multifocal and multicentric) invasive breast cancers.

  Dataset EGAD00001001041

• MDS 5q- exome reads

  Cancer exome reads consisting of FASTQ paired end reads from bone marrow samples

  Dataset EGAD00001001058

• Targeted Pulldown Validation of mutations found in whole genome sequencing

  This experiment is to inform us of the validity of using pre-made library material to perform a bespoke pulldown experiment to validate the mutations found between the whole genome sequencing of the DNA from the same individuals cancer and normal material. This is to identify the valid and informative mutations in cancer genomes.

  Dataset EGAD00001001061

• Angiosarcoma targeted pulldown cancer gene panel

  Extension of angiosarcoma whole genome sequencing study

  Dataset EGAD00001001064

• Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

  Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

  Dataset EGAD00001001066

• Whole exome sequence of biliary tract cancer

  Fastq files of 239 samples of biliary tract cancer

  Dataset EGAD00001001076

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• Cancer-associated genome-wide hypomethylation and copy number aberrations

  Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

  Dataset EGAD00001001093

• Colorectal organoids and tumoroids - pulldown

  Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient.

  Dataset EGAD00001001208

• Reproducibility of variant calls in replicate next generation sequencing experiments

  To examined the reproducibility of nucleotide variant calls in replicate sequencing experiments of the same genomic DNA, we performed targeted sequencing of all known human protein kinase genes (kinome) (~3.3 Mb) using the SOLiD v4 platform. This data set contains 17 breast cancer samples that were sequenced in duplicate (n=14) or triplicate (n=3), in order to assess concordance of all calls and single nucleotide variant (SNV) calls.

  Dataset EGAD00001001209

• PLCRC study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Colorectal cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000947

• Batches 1-3 prostatectomy analysis

  Whole Genome Sequencing Illumina HiSeq data from 95 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). This data is from batches 1 to 3 and is the bulk of the data used in Wedge et al, Nature Genetics 2018 (PMID: 29662167). As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001001116

• WGS and WES of 78 pairs Chinese gastric cancer

  Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

  Dataset EGAD00001001118

• FFPE Normal Panel V3 Cancer Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Dataset EGAD00001001122

• 65 prostate cancer cases transcriptome sequencing

  65 prostate cancer cases transcriptome sequencing

  Dataset EGAD00001000975

• Subclonal diversification of primary breast cancer

  Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

  Dataset EGAD00001000965

• Cancer-Normal chronic myeloid leukaemia sequencing data for "A comparative analysis of algorithms for somatic SNV detection in cancer", Bioinformatics 29 (2013) 2223

  This dataset contains the fastq sequencing data collected from bone marrow DNA of a chronic myeloid leukaemia patient at time of diagnosis.

  Dataset EGAD00001000967

• Distinct evolutionary trajectories of primary high grade serous ovarian cancers revealed through spatial mutational profiling

  High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to emergence of treatment-resistant sub-clones. We sought to measure the degree of genomic diversity within primary, untreated HGSC to examine the natural state of tumor evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on thirty-one spatially and temporally separated HGSC tumor specimens (six patients) including ovarian masses, distant metastases, and fallopian tube lesions. We found widespread intra-tumoral variation in mutation, copy number, and gene expression profiles, with key driver alterations in genes present in only a subset of samples (e.g. PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range: 10.2% to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology with common etiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating diversity arises at early stages of tumorigenesis. Our results reveal that HGSC exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug resistance mechanisms.

  Dataset EGAD00001000974

• Harnessing transposons for drug resistance gene discovery in cancer

  This study involves a forward genetic screen to identify common insertion sites in drug resistant clones. We will be utilising piggybac transposon systems in order to generate multiple drug resistant clones in a range of human cancer cell lines.

  Dataset EGAD00001000980

• 65 prostate cancer cases wgs sequencing

  65 prostate cancer cases wgs sequencing

  Dataset EGAD00001000983

• Metastatic Prostate Follow Up

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000988

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• 65 prostate cancer cases wgs sequencing

  65 prostate cancer cases wgs sequencing

  Dataset EGAD00001001004

• Exome sequencing

  Exome sequencing of peripheral blood from 4 individuals of a family with familial colorectal cancer type X

  Dataset EGAD00001001009

• Somatic cancer gene mutation screening

  Sequencing of colorectal tumors and normal tissue using Ion AmpliSeq Cancer Hotspot Panel V2

  Dataset EGAD00001001010

• Genentech gastric cell line sequencing

  RNAseq and exome sequencing data of gastric cancer cell lines.

  Dataset EGAD00001001013

• Lung Multi-site Targeted Sequence Capture

  DNA extracted from multiple biopsies taken from different areas of primary lung tumours will be subjected to targeted re-sequencing and analysed in order to assess intra-tumour heterogeneity with respect to mutations in a selection of cancer related genes.

  Dataset EGAD00001001017

• Metastatic breast cancer targeted gene screen (2014-09-24)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2014-09-24

  Dataset EGAD00001001018

• OncoCis: Annotation of cis-regulatory mutations in cancer

  RNA-seq dataset used for the validation of CDK6 cis-regulatory mutation annotated by OncoCis. NB bam files for manuscript A_Proteomic_Chronology_of_Gene_Expression_through_the_Cell_Cycle_in_Human_Myeloid_Leukemia_Cells are now available at the following link:http://www.ebi.ac.uk/ena/data/view/ERP008483

  Dataset EGAD00001001019

• ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001230

• ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001231

• ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001232

• ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001233

• ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001234

• smRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  smRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001226

• Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001227

• Whole genome shotgun sequencing assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Whole genome shotgun sequencing assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001228

• ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001229

• ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001235

• Prognostic factors in prostate cancer: deep sequencing pilot project TAPG

  This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

  Dataset EGAD00001001237

• Chordoma Extension (known cancer genes)

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001239

• WGS of Asian lung cancers

  VCF files of somatic variants from tumor-normal pairs of Asian lung cancer patients

  Dataset EGAD00001001240

• WES of HCC

  WES of HCC by HiSeq 2000,total 71 samples including Hepatocellular carcinoma cell lines and nornal sample(Peripheral Blood or the adjacent tissues of cancer)

  Dataset EGAD00001001249

• Capture Hi-C

  Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci.

  Dataset EGAD00001001243

• BASIS RNAseq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001264

• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• Lung Progression versus Regression Whole Genome Sequencing

  Around 50 samples of pre-invasive lung cancer lesions showing subsequent clinical and pathological progression or regression

  Dataset EGAD00001001271

• Fastq data for ChIP-Seq (H3K9me3) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (H3K9me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001408

• Fastq data for ChIP-Seq (H3K4me3) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (H3K4me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001407

• Fastq data for ChIP-Seq (Input) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (Input) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001409

• Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients

  Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients

  Dataset EGAD00001001421

• ESGI-Exome sequencing in Circulating Tumor Cells to determine therapy related markers

  The objectives of this project are the identification of markers related to cancer therapy resistance in the blood of breast cancer patients and to study the genetic changes in cancer cells during this development of resistance. Whole genome amplified DNA from Circulating Tumor Cells (CTCs), selected during the course of systemic treatment from blood of metastatic breast cancer patients, will be exome sequenced . The patients selected for this study did not respond to therapy.

  Dataset EGAD00001001425

• TGS - Comprehensive Molecular Characterization of Colorectal Cancer Metastases (2015-07-02)[MOSAIC]

  Systematic next generation sequencing efforts are beginning to define the genomic landscape across a range of primary tumours, but we know very little of the mutational evolution that contributes to disease progression. We therefore propose to obtain a comprehensive description of genomic, transcriptomic and epigenomic changes in a cohort of matched primary and metastatic colorectal cancers, and additionally to explore the extent to which those mutations identified as recurrent in the metastatic setting are able to subvert normal biological processes using both genetically engineered mouse models and established cancer cell lines. This study will enable us to define to what extent primary tumour profiling can capture the biological processes operative in matched metastases as well as the significance of intratumoural heterogeneity. This dataset contains all the data available for this study on 2015-07-02.

  Dataset EGAD00001001426

• GIST SSGXVIII trial targeted gene sequencing

  Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

  Dataset EGAD00001001427

• Anaplastic Meningioma V3 cancer gene panel

  Investigation into causal genes underlying anaplastic meningioma

  Dataset EGAD00001001430

• Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001435

• Colorectal organoids and tumour tissue

  Whole genome sequencing of single cell derived organoids from normal colon tissue and colorectal cancer.

  Dataset EGAD00001001447

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• Chugai colorectal organoid sequencing

  Genomic and transcriptomic characterization of drug-resistant colon cancer stem cell lines.

  Dataset EGAD00001001446

• Feasibility of targeted capture sequencing in FFPE cancer specimens 2

  Testing the feasibility of genome-scale sequencing in routinely collected formalin-fixed paraffin-embedded (FFPE) cancer specimens versus matched fresh-frozen samples using targeted pulldown capture prior to Illumina sequencing.

  Dataset EGAD00001001448

• ChIP sequencing in Cancer Cell Lines

  The project is to evaluate the genomic binding sites of the histone demethylase JARID1C. This gene was recently identified in CGP as a novel recessive cancer gene in human renal cell carcinoma.

  Dataset EGAD00001001453

• RNAseq - Colorectal organoids and tumoroids (2015-08-05)

  Transcriptome sequencing of tumour tissue, adjacent normal tissue and derived organoids/tumoroids from colorectal cancer. This dataset contains all the data available for this study on 2015-08-05.

  Dataset EGAD00001001459

• CPC-GENE Prostate Cancer Heterogeneity Study

  Aligned Sequence (bam format), Duplicates removed

  Dataset EGAD00001001329

• mFAST-SeqS of plasma-DNA

  Sequence data from L1-amplicon libraries prepared from plasma-DNA from a set of 24 female controls and 18 male controls without malignant disease and samples from patients breast (n= 28) and prostate cancer patients (n=61).

  Dataset EGAD00001001314

• Genome and transcriptome sequence data from a metastatic colorectal carcinoma patient

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

  Dataset EGAD00001001307

• Genome and transcriptome sequence data from a primary unknown cancer patient

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

  Dataset EGAD00001001308

• Genome and transcriptome sequence data from an appendix cancer patient

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

  Dataset EGAD00001001309

• Genome and transcriptome sequence data from a peritoneal mesothelioma patient

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

  Dataset EGAD00001001310

• Genome and transcriptome sequence data from a peritoneal mesothelioma patient

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

  Dataset EGAD00001001311

• Fastq data for whole genome bisulfite sequencing for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for whole genome bisulfite sequencing assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001312

• Deep Sequencing of somatic cancer mutations

  We enriched a panel of cancer associated genes using the Custom Sure Select Target Enrichment Kit. Identified mutations were validated with deep sequencing in order to assess mutated allele frequencies more accurately.

  Dataset EGAD00001001313

• ICGC Korean Breast Cancer Project

  A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing.

  Dataset EGAD00001001322

• Her2 BC WGS dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001334

• Triple Negative BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001335

• Xenograft BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001336

• BASIS BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001337

• BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001338

• Triple Negative BC RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001339

• Breast RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001340

• BASIS RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001341

• WGS on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of fifteen samples, tumour and whole blood, from the four initial patients.

  Dataset EGAD00001001343

• WGS on patients 5-7, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of six samples, tumour and whole blood, from the three additional patients whose somatic variants were examined in depth.

  Dataset EGAD00001001344

• RNA-seq on patients 1-4, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. RNA-seq of twelve samples, tumour and benign tissue, from the four initial patients.

  Dataset EGAD00001001345

• Cell Line Dataset

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001349

• BC WGS Dataset 1

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001350

• BC WGS Dataset 3

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001351

• BC WGS Dataset 4

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001353

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• CGP CORE CELL LINES - RNA-seq

  Genomic characterisation of a large series of cancer cell lines.

  Dataset EGAD00001001357

• The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

  Dataset contains Exome-seq and RNA-seq from 2 GBM patients, as well as RNA-seq from the derived cultured cells (GNS).

  Dataset EGAD00001001359

• Cooperative activity of BRAF F595L and mutant HRAS in histiocytic sarcoma provides new insights into oncogenic BRAF signaling

  Mutations that activate the RAF-MEK-ERK signaling pathway, in particular BRAFV600E, occur in many cancers, and mutant BRAF-selective inhibitors have clinical activity in these diseases. Activating BRAF alleles are usually considered to be mutually exclusive with mutant RAS, whereas inactivating mutations in the D594F595G596 motif of the BRAF activation segment can coexist with oncogenic RAS and cooperate via paradoxical MEK/ERK activation. We determined the functional consequences of a largely uncharacterized BRAF mutation, F595L, which was detected along with an HRASQ61R allele by clinical exome sequencing in a patient with histiocytic sarcoma and also occurs in epithelial cancers, melanoma, and neuroblastoma, and investigated its interaction with mutant RAS. We demonstrate that, unlike previously described DFG motif mutants, BRAFF595L is a gain-of-function variant with intermediate activity towards MEK that does not act paradoxically, but nevertheless cooperates with mutant RAS to promote oncogenic signaling. Of immediate clinical relevance, BRAFF595L shows divergent responses to different mutant BRAF-selective inhibitors, whereas signaling driven by BRAFF595L with and without mutant RAS is efficiently blocked by pan-RAF and MEK inhibitors. Mutation data from primary patient samples and cell lines show that BRAFF595L, as well as other BRAF mutations with intermediate activity, frequently coincide with mutant RAS in a broad spectrum of cancers. These data define a novel class of activating BRAF mutations that cooperate with oncogenic RAS in a non-paradoxical fashion to achieve an optimal level of MEK-ERK signaling, extend the spectrum of patients with systemic histiocytic disorders and other malignancies who are candidates for therapeutic blockade of the RAF-MEK-ERK pathway, and underscore the value of comprehensive genetic profiling for understanding the signaling requirements of individual cancers.

  Dataset EGAD00001001384

• BASIS WGBS

  Whole-genome bisulfite sequencing (WGBS) on 30 breast cancer cases from the BASIS project.

  Dataset EGAD00001001388

• Characterization and clinical relevance of the genomic alterations defining invasive lobular breast cancer

  Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications.Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates.Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively.Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment.

  Dataset EGAD00001001395

• Fastq data for smRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for smRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001401

• Fastq data for whole genome shotgun sequencing for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for whole genome shotgun sequencing assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001400