4774 results for "*oma"

in 52.14 milliseconds.

• Clinical dataset (new)

  ctDNA guiding adjuvant immunotherapy in urothelial carcinoma (Nature 2021). ABACUS clinical data cut (2020) used in 2021 paper: Clinical data include PCR, RFS_months, RFS_event, and OUTCOME for 40 patients in ABACUS with ctDNA data.

  Dataset EGAD00001007578

• Neuroblastoma WGS samples used for analysis of telomeric sequences

  Paired-end WGS data of 10 neuroblastoma patient samples (5 obtained at diagnosis and 5 matched blood samples as controls) used for analysis of telomeric content and sequence composition. Mean coverage is 11-65x per sample. The remaining patient samples of the dataset can be found under accession numbers EGAS00001001308 and EGAS00001005424 and mappings of the patients IDs in the supplementary material of the publication.

  Dataset EGAD00001009289

• ctDNA dataset

  ctDNA guiding adjuvant immunotherapy in urothelial carcinoma (Nature 2021). ABACUS ctDNA data used in 2021 paper: ctDNA data include TMB_(mut/Mb), cfDNA_extracted_ng, Plasma_Volume_Used_ml, Sample_Call, Sample_Number_Positive_Calls, Sample_Mean_VAF_In_Plasma (%), Sample_MTM_per_mL_In_Plasma across 40 patients in ABACUS.

  Dataset EGAD00001007579

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

  ChIP-Seq data for 4 Multiple Myeloma sample(s). 34 run(s), 28 experiment(s), 28 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 EGAD00001002379

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A95652B

  Dataset EGAD00001009327

• Dataset for Sarcoma-WES linked from study EGAS00001004813

  Sequencing data of 144 sarcoma tumor and control runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

  Dataset EGAD00001010258

• Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

  Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

  Dataset EGAD00001005987

• McGill EMC Community projects Release 7 for cell line "SaOS-2"

  Complete reference epigenome (as defined by IHEC) of a SaOS-2 cell line with osteosarcoma.

  Dataset EGAD00001007678

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• NLG-LBC-05 ctDNA project sequencing data

  Low-pass whole-genome sequencing of pretherapy lymphoma cfDNA and targeted sequencing of cfDNA, tumor tissue and whole-blood samples of NLG-LBC-05 patient samples and cfDNA of nine subjects with no known cancer. Hybrid capture target enrichment; panel target and sequencing information provided in PMID:34932792. FASTQ files provided for targeted sequencing, separate sequencing runs per sample noted with prefix "run" if applicable. Sequences from DTX1 and KLHL6 targets are advised to be excluded from analyses due to PCR/plasmid contaminants of in-house origin.

  Dataset EGAD00001009337

• High-resolution lung adenocarcinoma expression subtypes

  High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

  Dataset EGAD00001009339

• A living biobank of patient-derived ductal carcinoma in situ Mouse-INtraDuctal xenografts identifies factors associated with risk of invasive progression

  Create a living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts to find factors explaining invasive growth. Samples exist of both primary and pdx samples. Invasive growth was scored in the pdx.

  Dataset EGAD00001009336

• RRBS profiling for a cohort including 88 precancer specimens from 62 resected lung nodules from 39 patients including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) and 39 matched normal lung tissues.

  To study the evolution of DNA methylation at genome level and methylation intra-tumor heterogeneity (ITH) during early lung carcinogenesis, we performed multiregional reduced representation bisulfite sequencing (RRBS) of 127 resected lung samples from 39 patients using single end library Hiseq3000.

  Dataset EGAD00001006367

• RNA-seq of human glioblastoma and matched gliomasphere cell lines (BLN panel)

  This dataset contains all RNA-seq runs for the BLN panel of cell lines and matched parental tumors. Tumor/cell line pairs have been authenticated using SNP profiles and all pairs were confirmed. Please note: The dataset also contains raw data from an early primary culture (BLN-1) where no stable cell line could be generated. Please also note different reference genomes.

  Dataset EGAD00001002893

• 24 Chordoma samples (WES,WGS)

  Case series of the rare tumor entity chordoma. 9 cases sequenced with Whole Exome Sequencing (WES) and 2 cases sequenced with Whole Genome Sequencing (WGS) were recruited from the personalized oncology program NCT-MASTER/DKTK-MASTER at the German Cancer Research Center. One of the WES patients was re-sequenced at a later time point when he relapsed, this resequencing was done by WGS. Therefore there are 11 patients, one of which with two samples, all of which were sequenced with matched normal controls, amounting to a total number of 24 NGS samples.

  Dataset EGAD00001004825

• Single-cell mRNA-sequencing to generate a transcriptomic atlas of RMS

  Single-cell mRNA-sequencing to generate a transcriptomic atlas of soft tissue sarcoma tumors

  Dataset EGAD00001009385

• 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

• Single Cell Genome Sequence for DLP+ library A96205B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A96205B

  Dataset EGAD00001009471

• Whole Genome Sequencing of low-grade ovarian serous carcinoma

  Whole genome sequencing of 14 cases of low-grade ovarian serous carcinoma with matched normal DNA

  Dataset EGAD00001009626

• 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

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

  Dataset EGAD00001007754

• Genomic profiling of patient-derived xenograft models of myxoid liposarcoma either sensitive or resistant to trabectedin

  The dataset consists of two patient-derived xenograft model of myxoid liposarcoma one sensitive and one resistant to trabectedin. Both models underwent the same treatment schedule with trabectedin (tree time points and one treatment with doxorubicin). We performed genomic profiling using Agilent OneSeq assay.

  Dataset EGAD00001005099

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• McGill EMC Community projects Release 7 for cell line "lung epithelial"

  Complete reference epigenome (as defined by IHEC) of a lung epithelial cell line with non-small Cell Lung Adenocarcinoma

  Dataset EGAD00001007679

• 10x Genomics Single Cell Gene Expression for SA1049AX1XB01417

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009121

• 10x Genomics Single Cell Gene Expression for SA1053FX1XB01611

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009128

• 10x Genomics Single Cell Gene Expression for SA1051DX1XB01482

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009133

• Medulloblastoma Nanopore whole genome sequencing 3 samples

  ONT (PromethION) sequencing of chromothriptic medulloblastoma. Three samples: blood, primary tumor, and relapse tumor. Includes a fourth low-coverage run that multiplexes blood and primary tumor.

  Dataset EGAD00001009411

• Single cell CNV and ATAC profiling of multiple myeloma

  Patient-derived samples were profiled using 10X genomics single-cell CNV and single-cell ATAC kits.

  Dataset EGAD00001007788

• Sequencing data for oesophageal and related samples - OACs 496 release (WGS)

  Data from 496 OCCAMS (Oesophageal Cancer Clinical And Molecular Stratification) cases. WGS BAM files 496x oesophageal adenocarcinoma samples 496x normal samples

  Dataset EGAD00001007785

• RNAseq data for Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Dataset EGAD00001008458

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  mRNA capture sequencing data (FASTQ files) of 28 FFPE sarcoma tumors

  Dataset EGAD00001007696

• Genomic analysis for intrahepatic cholangiocarcinoma

  Intrahepatic cholangiocarcinomas (iCCs) are characterized by their rarity, difficulty in diagnosis, and overall poor prognosis. We performed comprehensive genomic characterization of treatment-naive iCC. This study reports a large-scale genomic analysis of iCC. The findings could assist in patient stratification with iCCs and in developing rational therapeutic strategies.

  Dataset EGAD00001008557

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• Acquired RAD51C promoter methylation loss causes PARP inhibitor resistance in high grade serous ovarian carcinoma

  Analysis of RAD51C promoter methylation using targeted bisulfite sequencing (amplicon sequencing) in ovarian cancer pre-clinical models and patient samples.

  Dataset EGAD00001007799

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Melanoma post mortem analysis

  We have been applying whole genome and transcriptome sequencing across metastases collected during post mortem. Herein we show the findings for the first such patient.

  Dataset EGAD00001005072

• Genomic Analysis of Focal Nodular Hyperplasia with Associated Hepatocellular Carcinoma Unveils its Malignant Potential

  Whole exome sequencing of FNH and two HCC compartments from a single patient, along with matched germline.

  Dataset EGAD00001007702

• Neuroblastoma WGS samples used for detection of seismic amplification

  Paired-end WGS data of 27 neuroblastoma patient samples (10 obtained at diagnosis, 6 at relapse and 11 matched blood samples as controls) used for detection of complex "seismic" amplification. Mean coverage is 24-55x per sample. The remaining patient samples of the dataset can be found under accession number EGAS00001001308.

  Dataset EGAD00001007807

• Mantle cell lymphoma primary cases RNAseq data

  Dataset includes fastq transcriptomic sequencing files from 8 conventional (SOX11+) and 4 non-nodal (SOX11-) mantle cell lymphoma (MCL) primary cases. RNA-sequencing has performed from peripheral blood and lymph node diagnostic samples.

  Dataset EGAD00001009422

• SOX11+ and SOX11- mantle cell lymphoma cell lines RNAseq data

  Fastq transcriptomic sequencing files from Z138 SOX11+ and JVM2 SOX11- mantle cell lymphoma (MCL) cell lines upon SOX11 knock out (KO) and ectopic overexpression, respectively. Dataset includes 3 samples of Z138-SOX11KO, 3 of Z138 control, 3 of JVM2 control and 3 of JVM2-SOX11 MCL cell lines.

  Dataset EGAD00001009421

• Melanoma microRNA profiling

  This dataset includes microRNA profiling of 61 early-passage metastatic melanoma cell lines. The data are provided as single-end small RNA seq fastq files.

  Dataset EGAD00001006269

• Comprehensive RNA repository of tissue and plasma from patients with esophageal cancer or precursor lesions

  A comprehensive RNA repository (both coding and non-coding) from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were collected. This dataset includes both mRNA and small RNA sequencing data (fastq.gz files) of all tissue and plasma samples. In total,102 RNA-seq libraries from 51 samples (17 plasma and 34 tissue samples) were sequenced (plasma mRNA libraries were sequenced twice).

  Dataset EGAD00001006857

• Deep targeted DNA sequencing dataset for the study "Molecular characteristics in Burkitt lymphoma over age groups"

  We performed deep targeted DNA sequencing with a panel of 134 selected cancer-related genes previously identified to be recurrently mutated in BL/B-AL. A Nextera rapid capture custom kit was designed using the Illumina DesignStudio. For every gene, all regions in which previous mutations had been described were covered. For 40 of these genes, the entire coding sequence was covered. Targeted deep sequencing was performed on a MiSeq-Sequencer using MiSeq Reagent Kit v2 (300 cycle) with 24 samples per run. There are 396 samples in this targetedDNAseq-dataset with 298 tumors (288 patients and 10 cell lines) and 98 normals. There are 132 female, 262 male, and 2 unknown gender samples in this dataset.

  Dataset EGAD00001007708

• Genome and transcriptome sequence data from a uveal melanoma patient

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

  Dataset EGAD00001010956

• Cohort of NGS lymphoma samples used as control

  Control cohort of lymphoma samples sequenced with a hybrid capture panel designed to be able to detect translocations and mutations in lymphoma samples. used in the paper "Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing"

  Dataset EGAD00001007711

• Single Cell Genome Sequence for DLP+ library A118814B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1162B passage 1 on DLP+ library A118814B

  Dataset EGAD00001009443

• Single Cell Genome Sequence for DLP+ library A118784A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118784A

  Dataset EGAD00001009436

• Single Cell Genome Sequence for DLP+ library A118808B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096C passage 1 on DLP+ library A118808B

  Dataset EGAD00001009441

• Single Cell Genome Sequence for DLP+ library A118816A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118816A

  Dataset EGAD00001009444

• Single Cell Genome Sequence for DLP+ library A118857B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1184D passage 1 on DLP+ library A118857B

  Dataset EGAD00001009445

• Single Cell Genome Sequence for DLP+ library A95668A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A95668A

  Dataset EGAD00001009447

• 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

• Single Cell Genome Sequence for DLP+ library A95717A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096A passage 1 on DLP+ library A95717A

  Dataset EGAD00001009450

• SF10679

  SF10679 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location: Frontal Age: 43. Sex: Male.

  Dataset EGAD00001006312

• Single Cell Genome Sequence for DLP+ library A96142B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A96142B

  Dataset EGAD00001009455

• scRNAseq of neuroblastoma PDX and cell lines

  This dataset contains the 22 bam files coresponding to the scRNAseq done in PDX models and cell lines.

  Dataset EGAD00001007870

• RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  Dataset EGAD00001006329

• 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

• Single Cell Genome Sequence for DLP+ library A96189A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049C passage 1 on DLP+ library A96189A

  Dataset EGAD00001009465

• RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

  RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

  Dataset EGAD00001007874

• Single Cell Genome Sequence for DLP+ library A96194A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053B passage 1 on DLP+ library A96194A

  Dataset EGAD00001009468

• BLUEPRINT release August 2016, ChIP-Seq for Burkitt Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Burkitt Lymphoma sample(s). 13 run(s), 13 experiment(s), 13 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 EGAD00001002329

• Single Cell Genome Sequence for DLP+ library A96194B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053E passage 1 on DLP+ library A96194B

  Dataset EGAD00001009469

• Single Cell Genome Sequence for DLP+ library A96200B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052D passage 1 on DLP+ library A96200B

  Dataset EGAD00001009470

• Single Cell Genome Sequence for DLP+ library A96206B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050F passage 1 on DLP+ library A96206B

  Dataset EGAD00001009472

• Single-cell RNA sequencing generated from 11 glioma patient samples

  This dataset includes paired-end fastq files from 6 IDH-mutant, 5 IDH-wild-type glioma patient samples of unmatched initial and recurrent timepoints profiled using single-cell RNA sequencing.

  Dataset EGAD00001007772

• Single Cell Genome Sequence for DLP+ library A96222A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1105, patient SA1103, patient SA1106, patient SA1104 on DLP+ library A96222A

  Dataset EGAD00001009478

• Single Cell Genome Sequence for DLP+ library A96207A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96207A

  Dataset EGAD00001009473

• Alveolar Rhabdomyosarcoma sequencing data

  This dataset contains samples from 9 patients with alveolar rhabdomyosarcoma. 9 samples have whole exome data (one has multiple). 6 samples have RNAseq data (one has multiple). 6 samples have matched normals dna sequence data

  Dataset EGAD00001007778

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Dataset EGAD00001009427

• Genomic characterization of co-existing biliary tract intraepithelial neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer

  Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we performed whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients.

  Dataset EGAD00001007792

• Embryonal Rhabdomyosarcoma sequencing data

  This dataset contains samples from 9 patients with embryonal rhabdomyosarcoma. 9 samples have whole exome tumor data (one has multiple). 7 samples have tumor RNAseq data. 1 sample has matched normal dna sequence data

  Dataset EGAD00001007939

• Single Cell Genome Sequence for DLP+ library A108847B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1182E passage 1 on DLP+ library A108847B

  Dataset EGAD00001009429

• Single Cell Genome Sequence for DLP+ library A108765A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1181A passage 1 on DLP library A108765A

  Dataset EGAD00001009428

• Small-molecule inhibitors in melanoma - Kenski / Kong - WES (2019-04-11)

  Small-molecule inhibitors targeting the most commonly activated pathway in melanoma, MAPK pathway (either alone or in combination) are already given to melanoma patients for few years, and initially reduce tumour burden dramatically, eventually melanomas become resistant and tumours progress while on treatment. Resistance to this treatment occurs by acquisition of additional mutations or other alterations that affect the mitogen-activated protein kinase (MAPK) pathway by either direct or indirect signalling. Many resistance mechanisms somehow lead to reactivation of extracellular signal-regulated kinase (ERK), thereby restoring signalling of the oncogenic BRAF/MEK/ERK pathway. In addition, PI3K pathway activation contributes to resistance to BRAF inhibition. Less frequent but equally important to the phenomenon of targeted drug resistance is the observation that B15-20% of BRAF mutant melanoma patients fail to respond to BRAF inhibition already early on treatment, owing to intrinsic resistance. These patients have little therapeutic options, unless immunotherapy can be given. To better understand the resistance mechanisms in MAPK inhibitor-treated melanoma patients and melanoma biology, our lab generated a big panel of MAPK inhibitor resistant melanoma cell lines by continuous drug exposure. The understanding of the genetic landscape and gene expression as well as cross resistance to other treatment regimens, and other aspects of melanoma biology such as phenotype switch, will allow us to better exploit new therapeutic strategies for melanoma patients. . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004952

• Sequencing data for oesophageal and related samples - Ng, Contino et al (WGS)

  Data supporting "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. WGS (BAM files) 383 oesophageal adenocarcinoma samples 383 normal samples

  Dataset EGAD00001007808

• Single Cell Genome Sequence for DLP+ library A95717B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050D passage 1 on DLP+ library A95717B

  Dataset EGAD00001009489

• Functional dissection of inherited non-coding variation influencing multiple myeloma risk

  This dataset contains ATAC sequencing of plasma cells from multiple myeloma (MM) patients. The data was used to investigate genotype-specific chromatin accessibility quantitative trait locus (caQTL) using caQTLseg (https://github.com/abhisheknrl/caQTLseg). This dataset contains 161 bam files.

  Dataset EGAD00001007814

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell

  Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell. Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell. Libraries were sequenced on a HiSeqTM4000 Illumina machine using 75bp paired-end reads

  Dataset EGAD00001007822

• 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 EGAD00001008942

• Whole genome sequencing (bam files) of 5 samples of myxofibrosarcoma and 5 matched pairs

  Myxofibrosarcoma (MFS) is a rare subtype of sarcomas in the elderly, whose genetic basis is poorly understood. To elucidate it, the whole genome sequence was performed.

  Dataset EGAD00001007825

• Whole genome sequencing and somatic mutation profiles and whole genome transcription files of pediatric medulloblastoma

  Fastq, Mutect (SNVs), Platypus (indels), and InfoGenomeR (SVs and CNAs) calls from whole genome sequencing data and fastq files of whole genome transcription data of five patients with pediatric medulloblastoma.

  Dataset EGAD00001009507

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Small RNA sequencing data (TruSeq small RNA library preparation kit v2) from serum samples and tumor tissue of orthotopically injected mice (SH-SY5Y cell line) and unengrafted mice, treated with idasanutlin, temsirolimus and vehicle control.

  Dataset EGAD00001009625

• 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 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 EGAD00001002621

• Medulloblastoma cfDNA low-coverage WGS

  Whole genome sequencing of cell free DNA from CSF across timepoints from medulloblastoma clinical trial patients.

  Dataset EGAD00001008277

• Ewings sarcoma sequencing data

  This dataset contains samples from 5 patients with ewings sarcoma. 5 samples have whole exome tumor data. 1 sample has tumor RNAseq data. 4 samples have matched normal dna sequence data

  Dataset EGAD00001008282

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• SF6420

  Oligodendroglioma (WHO gr. 2)

  Dataset EGAD00001008306

• SF7233

  Astrocytoma (WHO gr. 2)

  Dataset EGAD00001008305

• Osteosarcoma sequencing data

  This dataset contains samples from 13 patients with osteosarcoma. 13 samples have whole exome tumor data. 12 samples have tumor RNAseq data. 3 samples have matched normal dna sequence data

  Dataset EGAD00001008117

• Whole transcriptome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole transcriptome sequencing reads from 8 cell lines based on TruSeq stranded mRNA kit (Illumina). They are all 2*75bp reads sequenced using Illumina NextSeq500.

  Dataset EGAD00001006441

• WGS and WES data for manuscript titled: ctDNA as a biomarker of progression in oesophageal adenocarcinoma

  WGS and WES data for manuscript titled: ctDNA as a biomarker of progression in oesophageal adenocarcinoma

  Dataset EGAD00001008554

• Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – filtered vcf files

  Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence – filtered vcf files

  Dataset EGAD00001008339

• Genetic landscape of SMM

  Identifying high risk smoldering myeloma patients and progression mechanism is a prerequisite to implement effective inception strategies and curve myeloma related morbidity and mortality. We hypothesize that genomics may help identify determinants of progression that may help predict outcome and offer effective chemo preventive targets. Eighty-two patients underwent a custom targeted panel sequencing with an additional capture for the translocation loci. These results were compared to 223 newly diagnosed patients (EGAS00001003223 and EGAD00001004117) and 17 MGUS and 10 early myeloma patients. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads. Overall, these data highlight the importance of dysregulation of the MAPK pathway in the progression to MM.

  Dataset EGAD00001005285

• 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