5270 results for "*oma"

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• Genome and transcriptome sequence data from a metastatic non-small cell lung carcinoma patient

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

  Dataset EGAD00001004692

• Genome and transcriptome sequence data from a angiosarcoma patient

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

  Dataset EGAD00001004690

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

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

  Dataset EGAD00001004688

• Genome and transcriptome sequence data from a metastatic rectal adenocarcinoma patient

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

  Dataset EGAD00001004685

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient

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

  Dataset EGAD00001004684

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001004716

• Genome and transcriptome sequence data from a metastatic non-small cell lung adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic non-small cell lung adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004714

• Whole Genome Sequencing of a secondary myelodysplastic syndrome (MDS)

  Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Sample derived from secondary myelodysplastic syndrome (MDS), arising after treatment for medulloblastoma in an 11-year old female Li-Fraumeni syndrome case (LFS-MB1; Rausch et al., 2012; matching WGS data available under EGAS00001000085).

  Dataset EGAD00001000665

• BLUEPRINT: WGBS-seq of multiple myeloma and plasma cells

  Whole-genome Bisulfite sequencing of two multiple myeloma samples and one pooled sample of plasma cells.

  Dataset EGAD00001000672

• Genome-wide analysis of H3K27me3 occupancy and DNA methlytion in pediatric high-grade glioma

  Genome-wide analysis of H3K27me3 occupancy and DNA methylation in K27M-mutant and H3.3-WT primary pediatric high-grade gliomas (pHGGs) as well as pediatric pHGG cell lines. The study aims to elucidate the connection between K27M-induced H3K27me3 reduction and changes in DNA methylation as well as gene expression.

  Dataset EGAD00001000677

• Angiosarcoma follow-up 2 validation study

  A bespoke targeted pulldown experiment will be performed on patients with Angiosarcoma. the resulting products will be sequenced to determine the prevalence of previously found mutations in these patients.

  Dataset EGAD00001000679

• CD74-NRG1 study - RNASeq dataset

  RNAseq data, Publication Fernandez-Cuesta et al., 2014, CD74-NRG1 fusions in lung adenocarcinoma

  Dataset EGAD00001000716

• DIPG_ICR_WGS

  Whole genome sequencing of 20 tumour and normal pairs of diffuse intrinsic pontine glioma (DIPG)

  Dataset EGAD00001000705

• Chordoma Sequencing Project Whole Genome

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000721

• Somatic mutations in angiosarcoma

  Here we present the genomes of three secondary angiosarcomas

  Dataset EGAD00001000735

• Osteosarcoma whole genome rearrangement screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Osteosarcoma 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 EGAD00001000368

• Balanced Brain Tumour Whole Genome Sequencing

  We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Dataset EGAD00001000369

• Sporadic Parathyroid Carcinoma

  This dataset is compromised of 5 sequencing experiments from a single patient with sporadic and recurring parathyroid carcinoma. The samples include whole genome sequence of the primary tumor, the first recurrent tumor and peripheral blood. Whole transcriptome sequence of the first and second recurrent tumors are also included.

  Dataset EGAD00001000370

• Uveal melanoma whole genome sequencing, SNP arrays and RNA-seq

  We conducted whole genome sequencing and DNA SNP array of 12 uveal melanoma genomes and their matched DNA from blood. We also conducted RNA-seq of the 12 tumour samples.

  Dataset EGAD00001000372

• Ewings Sarcoma Rearrangement Screen

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000389

• Chondrosarcoma Validation Study

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from Chondrosarcoma cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.

  Dataset EGAD00001000392

• UK10K_RARE_COLOBOMA REL-2013-04-20

  UK10K_RARE_COLOBOMA REL-2013-04-20

  Dataset EGAD00001000415

• A study of the molecular pathogenesis of Splenic Marginal Zone and Diffuse Large B-Cell Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Dataset EGAD00001000410

• ICGC medulloblastoma whole genome sequencing data, ICGC release 16

  ICGC medulloblastoma whole genome sequencing data, ICGC release 16

  Dataset EGAD00001000816

• Quiescent Sox2+ cells drive hierarchical growth and relapse in Sonic hedgehog subgroup medulloblastoma

  Quiescent Sox2+ cells drive hierarchical growth and relapse in Sonic hedgehog subgroup medulloblastoma

  Dataset EGAD00001000818

• CMF RNA sequencing

  RNA sequencing will be undertaken to reconstruct rearrangements at level of transcription to determine pathogenomic genomic events in chondromyxoid fibroma.

  Dataset EGAD00001000824

• Osteosarcoma RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Dataset EGAD00001000826

• Small cell carcinoma of the ovary, hypercalcemic type, displays frequent inactivating germline and somatic mutations in SMARCA4

  Small cell carcinoma of the ovary of hypercalcemic type (SCCOHT) is an extremely rare, aggressive cancer affecting children and young women. We identified germline and somatic inactivating mutations in the SWI/SNF chromatin-remodeling gene SMARCA4 in 75% (9/12) of SCCOHT patients in addition to SMARCA4 protein loss in 82% (14/17) of SCCOHT tumors, but in only 0.4% (2/485) of other primary ovarian tumors. These data implicate SMARCA4 in SCCOHT oncogenesis.

  Dataset EGAD00001000850

• Whole genome sequence of condrosarcoma

  Fastq files of 10 samples of condrosarcoma

  Dataset EGAD00001000873

• Indel/point mutation of chondrosarcoma

  Indel/point mutation of chondrosarcoma

  Dataset EGAD00001000874

• Mutational Signatures of relapse in rectal cancer FFPE samples in the CR07 clinical trial

  The CRO7 clinical trial recruited patients with clinically operable rectal adenocarcinoma. Patients were randomized to either pre-operative short course surgery followed by chemo-radiotherapy only in those patients at high risk of local relapse. Patients in both arms the received standard %-FU based adjuvant chemotherapy as per local policy. We intend to use FFPE derived DNA from the primary tumours to identify patterns of mutations or copy number alterations that are predictive of local or distant relapse.

  Dataset EGAD00001000875

• RNA-Seq files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  RNA-Seq files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Dataset EGAD00001000878

• HCC.GNE exome dataset

  Exome read sequences for 30 tumor-normal pairs for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma".

  Dataset EGAD00001000885

• Whole genome data for study EGAS00001000824 (Diverse modes of genomic alterations in hepatocellular carcinoma)

  Whole genome data (Complete genomics platform) for the study EGAS00001000824

  Dataset EGAD00001001034

• RNAseq - Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting.

  Dataset EGAD00001001050

• Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting.

  Dataset EGAD00001001046

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - mobile_elements

  Samples from Edwards et al 2015 - doi:10.1186/s12864-015-1685-z

  Dataset EGAD00001001048

• Whole Exome Sequencing files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Whole Exome Sequencing files accompanying Genetic landscape of pediatric Rhabdomyosarcoma

  Dataset EGAD00001001059

• Chondromyxoid fibroma

  Chondromxoid fibroma is a benign tumour of bone with unknown underlying pathogenesis. To determine pathognomic genomic event in chondromyxoid fibroma whole genome sequencing will be undertaken to reconstruct rearrangements and find underlying mutations.

  Dataset EGAD00001001063

• Angiosarcoma targeted pulldown cancer gene panel

  Extension of angiosarcoma whole genome sequencing study

  Dataset EGAD00001001064

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 100

  Samples from the "100" project that are in the ICGC PanCancer project.

  Dataset EGAD00001001071

• DLBCL Discovery (FF) Cohort

  miRNA-seq Cohort of 92 Fresh Frozen Diffuse Large B-cell Lymphoma Patient Samples

  Dataset EGAD00001001074

• DLBCL Validation (FFPE) Cohort

  miRNA-seq Cohort of 140 Formalin Fixed Paraffin Embedded Diffuse Large B-cell Lymphoma Patient Samples

  Dataset EGAD00001001073

• Genomic Analysis of Hurthel Cell (Oncocytic) Thyroid Carcinoma

  This dataset includes 2 pairs of tumour/normal whole genome sequence data as well as MEN1 gene targeted sequencing of an additional 87 specimens.

  Dataset EGAD00001001085

• BLUEPRINT release August 2014, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000934

• Whole Genome Sequencing of acral melanoma

  Whole Genome Sequencing of 5 acral melanomas and matched normal samples

  Dataset EGAD00001000944

• Divergent clonal selection dominates medulloblastoma at recurrence

  Divergent clonal selection dominates medulloblastoma at recurrence

  Dataset EGAD00001000946

• Skin Adenocarcinoma Genome Sequencing

  DCC Project Code: SKCA-BR Skin Adenocarcinoma - BR Brazil

  Dataset EGAD00001001100

• Identification of drug resistance genes in melanoma

  Our aim is to analyze the genome of human melanoma cell lines and short term culture from human melanoma samples in order to identify genes that confer drug resistance to clinically relevant targeted therapies. We will perform whole-exome sequencing, copy number variation analysis and methylome analysis in a collection of human melanoma cell lines and short term culture that will be then screened for drug sensitivity/resistance through a library of clinically relevant drugs and drug combinations. By the combined analysis of the genomic lesion and the drug sensitivity/resistance profile of different cell lines, we will look for genes whose mutation is associated to the sensitivity or resistance to a specific drug in different samples.

  Dataset EGAD00001001124

• BLUEPRINT release January 2015, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001152

• High grade serous ovarian carcinoma sample

  Multi-region whole genome sequencing of an high grade serous ovarian carcinoma sample for characterization of genomic intra-tumoural heterogeneity.

  Dataset EGAD00001000978

• HIPO blastemal Wilms (nephroblastoma) exome sequencing samples

  HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving DNA alterations

  Dataset EGAD00001000995

• Carcinosarcoma Exome Sequencing Data

  Whole exome sequencing data from tumor and normal samples from carcinosarcoma (malignant mixed mullerian tumor) patients

  Dataset EGAD00001000987

• HIPO blastemal Wilms (nephroblastoma) WGS sequencing samples

  HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving chromosomal aberrations

  Dataset EGAD00001000994

• HIPO blastemal Wilms (nephroblastoma) CHIP sequencing samples

  HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving events caused by differential SIX1 binding of the SIX1 Q177R mutatns

  Dataset EGAD00001000992

• HIPO blastemal Wilms (nephroblastoma) RNA sequencing samples

  HIPO blastemal Wilms (nephroblastoma) characterisation of tumor driving gene expression events

  Dataset EGAD00001000993

• Chronic lymphocytic leukemia driven by paradoxical ERK activation during BRAF inhibitor treatment

  Whole-exome sequencing of a chronic lymphocytic leukemia (CLL) developed during vemurafenib treatment of a patient with malignant melanoma. Peripheral blood mononuclear cells were separated by Ficoll gradient centrifugation. DNA was extracted from highly purified (>97%) CD19+CD5+ cells obtained from the patient while being under BRAF inhibition versus CD14+ germline control cells (>90% purity). No alterations that could be linked to aberrant RAS activity or paradoxical RAF/MEK/ERK signaling could be identified in the CLL, which shows characteristic copy number alterations.

  Dataset EGAD00001000997

• Myeloma Follow up Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Dataset EGAD00001000998

• Spatial and temporal evolution of distal 10q deletion, a prognostically unfavorable event in diffuse low-grade gliomas

  Background: The disease course of patients with diffuse low-grade glioma is notoriously unpredictable. Temporal and spatially distinct samples may provide insight into the evolution of clinically relevant copy number aberrations (CNAs). The purpose of this study is to identify CNAs that are indicative of aggressive tumor behaviour and can thereby complement the prognostically favorable 1p/19q co-deletion. Results: Genome-wide, 50 base pair single-end, sequencing was performed to detect CNAs in a clinically well-characterized cohort of 98 formalin-fixed paraffin-embedded low-grade gliomas. CNAs are correlated with overall survival as an endpoint. Seventy-five additional samples from spatially distinct regions and paired recurrent tumors of the discovery cohort were analysed to interrogate the intratumoral heterogeneity and spatial evolution. Loss of 10q25.2-qter is a frequent subclonal event and significantly correlates with an unfavorable prognosis. A significant correlation is furthermore observed in a validation set of 126 and confirmation set of 184 patients. Loss of 10q25.2-qter arises in a longitudinal manner in paired recurrent tumor specimens, whereas the prognostically favorable 1p/ 19q co-deletion is the only CNA that is stable across spatial regions and recurrent tumors. Conclusions: CNAs in low-grade gliomas display extensive intratumoral heterogeneity. Distal loss of 10q is a late onset event and a marker for reduced overall survival in low-grade glioma patients. Intratumoral heterogeneity and higher frequencies of distal 10q loss in recurrences suggest this event is involved in outgrowth to the recurrent tumor.

  Dataset EGAD00001001000

• Seminoma exome sequencing

  Exome sequencing data for 8 pairs of seminomas and matched normal

  Dataset EGAD00001001002

• Whole genome sequence of hepatocellular carcinoma (RCAST)

  Fastq files of 52 samples of hepatocellular carcinoma(RCAST, THCC)

  Dataset EGAD00001001024

• Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Dataset EGAD00001001210

• BLUEPRINT transcriptional profiling of normal and neoplastic plasma cells

  RNAseq profile of purified plasma cells from multiple myeloma patients and tonsils of healthy donors

  Dataset EGAD00001001212

• Myeloma Targeted Follow-up Study

  Targeted sequencing follow-up of genomic lesions in multiple myeloma.

  Dataset EGAD00001001215

• Chordoma Extension Study

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001238

• Chordoma Extension (known cancer genes)

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001239

• 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

• Mesothelioma Whole Genomes

  Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project.

  Dataset EGAD00001001265

• Primary angiosarcoma Whole Genome Sequencing

  Whole genome sequencing of primary angiosarcoma

  Dataset EGAD00001001266

• 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

• Whole-exome sequencing of adult T-cell leukemia/lymphoma

  Whole-exome sequencing of 81 tumor/normal pairs of adult T-cell leukemia/lymphoma

  Dataset EGAD00001001410

• RNA sequencing of adult T-cell leukemia/lymphoma

  RNA sequencing of 57 tumor samples of adult T-cell leukemia/lymphoma as well as 3 samples of HTLV-1 carrier and 3 samples of healthy volunteers.

  Dataset EGAD00001001411

• Whole genome sequencing of adult T-cell leukemia/lymphoma.

  Whole genome sequencing of 48 tumor/normal pairs obtained from adult T-cell leukemia/lymphoma. This data set includes 11 full-pass WGS and 37 low-pass WGS data.

  Dataset EGAD00001001412

• Transcriptome and Exome from longitudinal samples of human glioblastoma

  We obtained paired longitudinal specimens from a total of 38 glioblastoma (GBM) patients (34 primary and 4 secondary GBM patients). Treatment-naive initial tumors were available for 35 cases; for the other 3 cases, we used the first available recurrent tumors in lieu of initial tumors. Tumor specimens were subjected to whole-exome sequencing (27 of 38 cases, with the matched normal/blood for 22 of the 27 cases) and transcriptome sequencing (30 of 38 cases).

  Dataset EGAD00001001424

• Anaplastic Meningioma V3 cancer gene panel

  Investigation into causal genes underlying anaplastic meningioma

  Dataset EGAD00001001430

• 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

• Deep sequencing of melanoma for driver mutations

  Deep sequencing of melanoma for driver mutations

  Dataset EGAD00001001445

• Anaplastic Oligodendroglioma AO Exome-seq data

  Anaplastic oligodendrogliomas (AOs) are rare primary brain tumors which are generally incurable, with heterogeneous prognosis and few treatment targets identified. Most oligodendrogliomas have chromosome 1p/19q co-deletion and IDH mutation. We analyzed 51 AOs by whole-exome sequencing, identifying previously reported frequent somatic mutations in CIC and FUBP1. We also identified recurrent mutations in TCF12 and in an additional series of 83 AO. Overall 7.5% of AO are mutated for TCF12, which encodes an oligodendrocyte-related transcription factor. 80% of TCF12 mutations identified were in either the bHLH domain, which is important for TCF12 function as a transcription factor, or were frame shift mutations leading to TCF12 truncated for this domain. We show that these mutations compromise TCF12 transcriptional activity and are associated with a more aggressive tumor type. Our analysis provides further insights into the unique and shared pathways driving AO.

  Dataset EGAD00001001452

• 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

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 100_all_samples

  All samples from the "100" project

  Dataset EGAD00001001457

• CBP has opposing functions during cerebellar development and is a targetable tumor suppressor at late stages of medulloblastoma initiation

  CBP has opposing functions during cerebellar development and is a targetable tumor suppressor at late stages of medulloblastoma initiation

  Dataset EGAD00001001461

• Whole exome sequencing dataset in follicular lymphoma without evidence of transformation

  Whole exome sequencing data of 5 patients diagnosed with FL that had undergone several relapse episodes without evidence of transformation

  Dataset EGAD00001001301

• The UCSF Low Grade Glioma Genome Project #2"

  Dataset contains WES data from 3 astrocytoma patients: blood as control, primary tumor and recurrent tumor

  Dataset EGAD00001001305

• RNA Seq Data

  Human melanoma samples were collected pre, on, and progression on BRAF inhibitor therapy. RNA was extracted and run on RNA-seq. This has provided insights into different categories of BRAF inhibitor resistance mechanisms.

  Dataset EGAD00001001306

• 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

• Whole genome sequencing of adult t-cell leukemia/lymphoma

  Whole genome sequencing of single adult t-cell leukemia/lymphoma case

  Dataset EGAD00001001326

• 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

• Genomic Analysis of Anaplastic Thyroid Carcinoma

  This dataset includes WGS & WTS alignment data generated from 1 ATC tumor, its matched peripheral blood specimen and 3 authenticated ATC cell lines, THJ-16T, THJ-21T and THJ-29T. In addition, it includes WTS data from extra 4 unique anaplastic cell lines, ACT-1, C643, HTh7 and T238.

  Dataset EGAD00001001321

• Exome sequencing of EBV-driven lymphoma

  Exome sequencing of a case of lethal EBV-driven LPD

  Dataset EGAD00001001347

• 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

• 463 newly diagnosed patients paired samples (Tumor/Normal)

  463 newly diagnosed patients from the UK Myeloma XI clinical trial (NCT01554852) underwent whole exome sequencing plus targeted capture of the IGH/K/L and MYC loci. 200 ng of DNA were processed using NEBNext DNA library prepartion kit and hybridised to the SureSelect Human All Exon V5 Plus. Four samples were pooled and run on one lane of a HiSeq 2000 using 76-bp paired end reads. DNA from CD138+ selected bone marrow cells (myeloma tumour) as well as peripheral white blood cells were analysed and somatic mutations detected.

  Dataset EGAD00001001358

• Neuroblastoma relapse trio series from the AMC

  The majority of neuroblastoma patients have tumors that initially respond to chemotherapy, but a large proportion of patients will experience therapy-resistant relapses. The molecular basis of this aggressive phenotype is unknown. Whole genome sequencing of 23 paired diagnostic and relapsed neuroblastomas showed clonal evolution from the diagnostic tumor with a median of 29 somatic mutations unique to the relapse sample. Eighteen of the 23 relapse tumors (78%) showed RAS-MAPK pathway mutations. Seven events were detected only in the relapse tumor while the others showed clonal enrichment. In neuroblastoma cell lines we also detected a high frequency of activating mutations in the RAS-MAPK pathway (11/18, 61%) and these lesions predicted for sensitivity to MEK inhibition in vitro and in vivo. Our findings provide a rationale for genetic characterization of relapse neuroblastoma and show that RAS-MAPK pathway mutations may function as a biomarker for new therapeutic approaches to refractory disease.

  Dataset EGAD00001001360

• TRACERx esophageal adenocarcinoma multi-region NGS

  This dataset contains whole exome data from 8 esophageal adenocarcinoma tumors, that has been subjected to multiregion sequencing, ranging from 3-8 regions per tumor. In total, 40 tumor samples and 8 normal blood samples have been sequenced on Illumina HiSeq 2500 at a median dept of 90x.

  Dataset EGAD00001001364

• Mechanisms of patient response to Dabrafenib in Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)*NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]*CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Dataset EGAD00001001375

• 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

• CRISPR screen M14, NCI-H3122

  Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung

  Dataset EGAD00001001389

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - barretts_1

  Samples from Ross Innes et. al 2015 - doi:10.1038/ng.3357

  Dataset EGAD00001001394

• MethylCap-seq based DNA methylation profiles of 65 glioblastoma and 5 non-tumoral tissues

  Data represent genome-wide DNA methylation profiles obtained by MethylCap-seq (Diagenode’s MethylCap-kit based purification followed by Illumina GAIIx sequencing), for 70 brain tissue samples, including 65 glioblastoma samples and 5 non-tumoral tissues (obtained from epilepsy surgery).

  Dataset EGAD00001001399

• BLUEPRINT release August 2015, ChIP-Seq for Multiple myeloma, on genome GRCh38

  ChIP-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001592