5246 results for "*oma"

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• 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

• Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Dataset EGAD00001000807

• 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

• 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

• 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

• 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

• Divergent clonal selection dominates medulloblastoma at recurrence

  Divergent clonal selection dominates medulloblastoma at recurrence

  Dataset EGAD00001000946

• 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

• 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

• 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 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

• 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

• 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

• 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 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

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

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

  Dataset EGAD00001004891

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

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

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

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

  Dataset EGAD00001004898

• 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

• Melanoma - Exome sequencing

  whole exome sequencing of tumor- as well as PBMC-derived DNA of five melanoma patients for identification of naturally presented patient-specific neoepitopes

  Dataset EGAD00001002731

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Dataset EGAD00001002738

• Melanoma Germlines subset for BAP1

  These samples comprise both melanoma cases and controls sequenced for a selection of loci linked to disease susceptibility. These bams are a subset of the sequencing restricted specifically to the GRCh37 coding areas of the BAP1 gene.

  Dataset EGAD00001002743

• BLUEPRINT release August 2016, Bisulfite-Seq for Mantle Cell Lymphoma, on genome GRCh38

  Bisulfite-Seq data for 5 Mantle Cell Lymphoma sample(s). 65 run(s), 5 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002505

• BLUEPRINT release August 2016, ChIP-Seq for Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 10 run(s), 10 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002506

• BLUEPRINT release August 2016, Bisulfite-Seq for Multiple Myeloma, on genome GRCh38

  Bisulfite-Seq data for 5 Multiple Myeloma sample(s). 63 run(s), 7 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002521

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

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

  Dataset EGAD00001002537

• WGS, RNA-seq and methyl-seq data for multiple tumour clones from a single glioblastoma case.

  10 bams of WGS data from HiSeqXTen platform; 10 bams of RNA-seq data from HiSeq2500 platform; 7 bams of TruSeq Methyl Capture EPIC sequencing data from HiSeq4000 platform

  Dataset EGAD00001004773

• Sequencing data for oesophageal and related samples - Mourikis et al (WGS)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. WGS (BAM files) 521 samples

  Dataset EGAD00001004775

• Sequencing data for oesophageal and related samples - Mourikis et al (RNA)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. RNAseq (BAM files) 137 samples

  Dataset EGAD00001004776

• Targeted bisulfite sequencing

  Raw reads from targeted bisulfite sequencing. The SureSelect Methyl-Seq target enrichment system (Agilent Technologies, Inc., CA, USA) was used to prepare bisulfite sequencing libraries from blood DNA samples of lymphoma patients (Ly1, Ly2), healthy family members (Ly8, Ly9, Ly10, Ly11, Ly12, Ly13 and Ly14), baseline controls (Control1-5), DNMT3A mutation carriers (Id5, Id7, Id9, Id11) and their age-matched controls (Id6, Id8, Id10, Id12). In addition, blood DNA sample of a patient (HLRCC_N7) with germline fumarate hydratase (FH) mutation is included. Illumina paired-end sequencing for targeted libraries from Ly1, Ly2, Ly8, Ly9, Ly10 and Ly11 was done at Karolinska Institutet using 100 base-pair read length and the HiSeq2000 platform. Illumina paired-end sequencing for targeted libraries from Ly12, Ly13, Ly14, and DNMT3A mutation carriers and their age-matched controls was done as a service at BGI (BGI Tech Solutions Co., Ltd., China) using 126 base-pair read length and the HiSeq2500 platform.

  Dataset EGAD00001004785

• Whole genome sequencing informs treatment decision of end-stage metastatic cutaneous angiosarcoma in a patient with Xeroderma Pigmentosum

  Whole genome sequencing (WGS) detects all mutations in a cancer. “Mutational signatures” are patterns of mutations that report the DNA damage and subsequent DNA repair processes that have occurred in cancers. We present a patient with Xeroderma Pigmentosum that developed metastatic angiosarcoma, unresponsive to all lines of sarcoma therapy. Primary tumour WGS revealed a hypermutated tumour, including clonal ultraviolet light-induced mutational patterns (Signature 7) and subclonal signatures of activating mutations of DNA Polymerase-epsilon (POLE)(Signature 10). These signatures are associated with response to immune-checkpoint blockade. Immunohistochemistry confirmed high PD-L1 expression in metastatic deposits. The patient was commenced on anti-PD-L1 therapy and has responded.

  Dataset EGAD00001004786

• Genome and transcriptome sequence data from an adenomacarcinoma of vulva patient

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

  Dataset EGAD00001002590

• Genome and transcriptome sequence data from a leiomyosarcoma patient

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

  Dataset EGAD00001002593

• 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 EGAD00001002594

• 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 EGAD00001002595

• Genome and transcriptome sequence data from a porocarcinoma patient

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

  Dataset EGAD00001002596

• Genome and transcriptome sequence data from an invasive ductal carcinoma of left breast patient

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

  Dataset EGAD00001002601

• 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 EGAD00001002602

• Genome and transcriptome sequence data from a clear cell carcinoma of ovary patient

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

  Dataset EGAD00001002604

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

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

  Dataset EGAD00001002606

• Genome and transcriptome sequence data from a pleomorphic spindle cell sarcoma patient

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

  Dataset EGAD00001002608

• Genome and transcriptome sequence data from an invasive carcinoma of left breast patient

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

  Dataset EGAD00001002610

• Genome and transcriptome sequence data from a breast carcinoma patient

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

  Dataset EGAD00001002613

• Genome and transcriptome sequence data from an esophageal adenocarcinoma patient

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

  Dataset EGAD00001002612

• Genome and transcriptome sequence data from an endometrial carcinoma patient

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

  Dataset EGAD00001002633

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

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

  Dataset EGAD00001002630

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

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

  Dataset EGAD00001002628

• Genome and transcriptome sequence data from an adenoid cystic carcinoma of the trachea patient

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

  Dataset EGAD00001002627

• 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 EGAD00001002626