7790 results for "canc*"

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• Transcriptome profiling by array

  Expression profiling by Nanostring cancer immune

  Dataset EGAD00010001274

• OCAC OncoArray data

  Germline genotype data on 56,479 ovarian cancer cases and controls

  Dataset EGAD00010001192

• ICGC breast cancer sequencing project SNP6 data

  Affymetrix SNP6.0 breast cancer genome sequencing data

  Dataset EGAD00010000915

• BASIS_450k

  BASIS breast cancer DNA methylation Illumina 450k

  Dataset EGAD00010000916

• Genentech_cell_line_SNP

  SNP array data for 668 cancer cell lines

  Dataset EGAD00010000951

• EGAD00010000644

  Affymetrix SNP6.0 cancer cell line exome sequencing data

  Dataset EGAD00010000644

• Breast cancer SNP6 arrays_more

  Affymetrix SNP6.0 array breast cancer data

  Dataset EGAD00010001079

• Blood dataset - Case

  blood-based gene expression from breast cancer cases

  Dataset EGAD00010001063

• Tumor dataset - Case

  tumor-based gene expression from breast cancer cases

  Dataset EGAD00010001064

• Blood dataset - Case-control

  blood-based gene expression from breast cancer cases and age-matched controls

  Dataset EGAD00010001062

• OvCan2

  Digital images of ovarian cancer metastases

  Dataset EGAD00010001099

• OvCan1

  Digital images of ovarian cancer sections

  Dataset EGAD00010000881

• EGAD00010000558

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000558

• EGAD00010000556

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000556

• EGAD00010000554

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000554

• EGAD00010000526

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000526

• EGAD00010000622

  SNP array data for gastric cancer cell lines

  Dataset EGAD00010000622

• EGAD00010000266

  Metabric breast cancer samples (Genotype raw data)

  Dataset EGAD00010000266

• EGAD00010000268

  Metabric breast cancer samples (Expression raw data)

  Dataset EGAD00010000268

• EGAD00010000270

  Metabric breast cancer samples (Images)

  Dataset EGAD00010000270

• EGAD00010000474

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 2 (CC2)

  Dataset EGAD00010000474

• EGAD00010000476

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 1 (CC1)

  Dataset EGAD00010000476

• EGAD00010000478

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 3 (CC3)

  Dataset EGAD00010000478

• EGAD00010000498

  Affymetrix SNP6.0 genotype data for prostate cancer patients

  Dataset EGAD00010000498

• WGS dataset for Genomic rearrangements in Pediatric Cancer

  Dataset EGAD00001008272

• Integrated genomic analysis identifies driver genes and cisplatin-resistant progenitor phenotype in pediatric liver cancer

  Dataset EGAD00001007858

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• Genomic Rearrangements in Pediatric Cancer

  Dataset EGAD00001007701

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Dataset EGAD00001006847

• FFPE cohort with RNA-seq data of tumor samples

  This dataset contains RNA-seq raw data in fastq format from 14 tumor samples. The samples are from primary tumors or metastasis and represent various cancer entities. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006781

• TCR β-chain repertoire characterization of regulatory and conventional T cells in breast tumors from breast cancer patients.

  Dataset EGAD00001006428

• Genomic profiling of patient-derived xenografts and organoids in prostate cancer

  Dataset contains genomic sequencing of 87 samples (blood germline, normal prostate tissues, human tumors, PDOs and PDXs). Sequencing was performed by whole-exome sequencing or targeted sequencing of prostate cancer genes.

  Dataset EGAD00001006403

• Single-cell RNA-Seq of CAF-S1 sub-population of Fibroblast in breast Cancer tumors

  Dataset EGAD00001006163

• RNA-seq data from 70 non-small cell lung cancer (NSCLC)

  Dataset EGAD00001006145

• RNA-seq data from 7 CAF-S1 primary cell lines isolated from breast Cancer

  Dataset EGAD00001006144

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_2020

  Dataset EGAD00001006003

• Exploiting evolutionary steering in cancer therapy

  This dataset contains 9 bam files of exome sequencing for an experiment of evolved resistance. Here a barcoded cell line (HCC827 - POT) has been treated under high concentrations of gefitinib (GEF) and trametinib (TRM) until resistance has evolved, as well as under control conditions (DMSO). The dataset contains exome sequencing of confluent cells for three replicates for each anti-cancer drug as well as two replicates of growth under DMSO conditions. The original barcoded cell line (POT) was also exome sequenced and is included in the cohort. Sequencing was performed on the Illumina NovaSeq platform.

  Dataset EGAD00001005782

• Mapping the breast cancer metastatic cascade onto circulating tumour DNA using genetic and epigenetic clonal tracking

  Dataset EGAD00001005507

• WGS of kidney cancer organoid biobank

  Dataset EGAD00001005319

• RNA-Seq of kidney cancer organoid biobank

  Dataset EGAD00001005318

• Whole Mitochondrial DNA sequencing of Gingivo-buccal Cancer : ICGC-India Project

  This dataset pertains to mitochondrial DNA amplicon sequencing of paired DNA samples from gingivo-buccal oral cancer patients. DNA was isolated from the tumor and blood tissues of 89 patients (178 samples). The sequencing libraries were prepared from whole mitochondrial amplicons using Nextera XT DNA Library Preparation Kit (Illumina) and sequenced in Illumina HiSeq platform. The uploaded BAM files are generated by aligning paired-end reads to the mitochondrial reference sequence (rCRS) using BWA-MEM.

  Dataset EGAD00001004987

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Dataset EGAD00001004585

• Targeted RNA sequencing of breast cancer GWAS loci

  Dataset EGAD00001004498

• Whole Genome Sequencing of Gingivo-buccal Cancer: ICGC-India Project_YR03

  Dataset EGAD00001004478

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_Batch05

  Dataset EGAD00001004430

• TCR β-chain repertoire sequences of regulatory and conventional T cells in peripheral blood from breast cancer patients and healthy individuals

  Dataset EGAD00001004385

• Mutational consequences of precancerous liver disease

  Clonally expanded liver adult stem cell clones of healthy liver and cirrhotic liver (due to alcohol abuse, NASH and PSC), as well as biopsies of liver cancers were subjected to whole genome sequencing to determine the mutational impact of precancerous liver disease

  Dataset EGAD00001004105

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• RNA-SEQ data from 47 CAF (Cancer Associated Fibroblast) samples sorted from fresh breast cancer

  Dataset EGAD00001003808

• RNA-SEQ data from 13 CAF (Cancer Associated Fibroblast) samples sorted from fresh high-grade ovarian carcinoma

  Dataset EGAD00001003460

• The study of response to EGFR Blockade in Colorectal Cancer

  Dataset EGAD00001001628

• The study of response to EGFR Blockade in Colorectal Cancer

  Dataset EGAD00001001674

• Raw sequencing data - Intra-tumor heterogeneity and clonal evolution patterns towards platinum-resistant high-grade serous ovarian cancer

  This dataset includes 69 sampels of whole-exome sequencing data of high-grade serous ovarian carcinoma (HGSOC). We included patients with advanced (International Federation of Gynecology and bstetrics [FIGO] stage IIIeIV) HGSOC for which biopsies were obtained during debulking surgery, the first at initial diagnosis and the second at disease relapse. Where possible, matched normal DNA from each participating patient was obtained from a whole-blood sample. Written informed consent was obtained from all patients and approved by the local ethics committee.

  Dataset EGAD00001001381

• Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

  Dataset EGAD00001001602

• RNA-seq and WGS data of MB-0152

  Identification of fusion transcripts by RNA-sequencing and Whole genome sequencing of a breast cancer patient sample (METABRIC ID MB-0152)

  Dataset EGAD00001003342

• Whole genome sequencing of 63 single cells isolated from bone marrow aspirates of six non-metastatic breast cancer patients after staining for disseminated tumor cells.

  Dataset EGAD00001002745

• Whole exome sequencing of bulk primary tumor (and one lymph node metastasis) and matched blood of six non-metastatic breast cancer patients

  Dataset EGAD00001002746

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR02

  Dataset EGAD00001001060

• Bladder cancer sequencing data

  Dataset EGAD00001001036

• Methylated DNA immunoprecipitation sequencing of untreated and castration resistant prostate cancer

  Methylated DNA immunoprecipitation sequencing of 28 untreated prostate cancers, 11 castration resistant prostate cancers, and 12 benign prostatic hyperplasias.

  Dataset EGAD00001000610

• ICGC prostate cancer MBD sequencing (DNA methylation)

  Dataset EGAD00001000632

• Whole exome sequencing of metastatic breast cancer

  Dataset EGAD00001000836

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

  Dataset EGAD00001000856

• Combination therapies for personalized cancer medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Dataset EGAD00001000869

• SYSCOL Human colorectal cancer project pilot RNA-seq and germline genotyping

  Genotyping by array and Transcriptome profiling by high-throughput sequencing

  Dataset EGAD00001000880

• Novel driver variants in the histone 3.3 genes, H3F3A and H3F3B, define bone and cartilage cancer sub-types

  A selection of human cancers harbours somatic driver mutations in genes encoding histones, most notably childhood brain tumours with K27M substitutions of the histone 3.3 gene, H3F3A. We performed whole genome sequencing of the benign cartilage tumour, chondroblastoma, and targeted sequencing of histone 3.3 genes, H3F3A and H3F3B, in seven further skeletal tumour types. We identified an exceptionally high prevalence of novel histone 3.3 driver mutations at glycine 34 and at lysine 36. Histone 3.3 gene mutations were found in 91% in giant cell tumours of bone (48/53), mainly H3F3A G34W variants, and in 92% of chondroblastoma (73/79), predominantly K36M mutations in H3F3B. H3F3B is paralogous to the cancer gene H3F3A. However, H3F3B driver variants have not previously been reported in human cancer. Our observation demonstrate remarkable tumour-specificity of mutations, with respect to which histone 3.3 gene and residue is mutated, indicating that the advantage these mutations confer is tumour dependent. Moreover, tumour-specific mutation of H3F3A and H3F3B suggests, that although both genes encode identical proteins, they are likely non-redundant and employed differentially during skeletal development.

  Dataset EGAD00001000646

• Signatures of mismatch repair deficiency in cancer genomes

  DNA replication errors occurring in mismatch repair (MMR) deficient cells persist as mismatch mutations and predispose to a range of tumors. Here, we sequenced the first whole-genomes from MMR-deficient endometrial tumors.

  Dataset EGAD00001000641

• Primary Lung Cancer whole genome study

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung 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 EGAD00001000388

• Whole exome sequencing of gallbladder cancer

  The dataset includes the whole exome sequencing data from32 pairs of gallbladder caner tissues and patient-matched normal tissues.

  Dataset EGAD00001000901

• Subclonal diversification of primary breast cancer

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

  Dataset EGAD00001000898

• ICGC Prostate Cancer Whole Genome Sequencing

  To characterize the subclonal genomic architecture of androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of 51 tumours from 10 patients to an average sequencing depth of 55x, including multiple metastases from different anatomic sites in each patient and, in five cases, the prostate tumour. Noncancerous DNA from blood or other tissue is used as reference comparison for each patient. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) rapid autopsy study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, some of the studies using these data include: Gundem et al, Nature 2015 (PMID: 25830880). Additional EGAD00001000891 sample metadata is contained in Supplementary Information in this report.Tubio et al, Science 2014 (PMID: 25082706) Behjati et al, Nature Comm 2015 (PMID: 27615322) Wedge et al, Nature Genetics 2018 (PMID: 29662167)Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)Rodriguez-Martin et al, Nature Genetics 2020 (PMID: 32024998)Woodcock et al, Nature Comm 2020 (In Press)

  Dataset EGAD00001000891

• Exome sequencing of patients with Ewings sarcoma

  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 EGAD00001000333

• Breast Cancer FRT RNA seq

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

  Dataset EGAD00001000338

• Somatic mutations, clonal architecture and genomic evolution in multiple myeloma

  Multiple myeloma is an incurable plasma cell malignancy whose molecular pathogenesis is incompletely understood. We used whole exome sequencing, copy number profiling and cytogenetic to analyses 84 samples from 67 patients with myeloma. In addition to known myeloma genes, we identify new candidate genes, including truncations of SP140, ROBO1 and FAT3 and clustered missense mutations in EGR1. We find oncogenic mutations in cancer genes not previously implicated in myeloma, including SF3B1, PI3KCA and PTEN. We define diverse processes contributing to the mutational repertoire, including kataegis and somatic hypermutation. Most cases have at least one cluster of subclonal variants, including subclonal driver mutations, implying on-going tumor evolution. Serial samples revealed diverse patterns of clonal evolution, including linear evolution, differential clonal response and branching evolution. Our findings reveal the myeloma genome to be heterogeneous across patients and, within individual patients, to exhibit diversity in clonal admixture and dynamics in response to therapy.

  Dataset EGAD00001000339

• Monotherapy Breast Cancer

  These samples are from locally advanced breast cancers that have been treated with epirubicin monotherapy before surgery. We will sequence some samples from patients with good response to the therapy and some with poor response to the therapy.

  Dataset EGAD00001000349

• Transcriptome Sequencing of Cancer Cell Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Dataset EGAD00001000359

• Targeted gene fusion sequencing (Fus-seq) in mesothelioma

  This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

  Dataset EGAD00001000361

• Lung Plasma rearrangement screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from lung 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 EGAD00001000367

• A common single nucleotide variant in T is strongly associated with chordoma

  Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics.

  Dataset EGAD00001000226

• Testing the feasibility of genome scale sequencing in routinely collected FFPE cancer specimens versus matched fresh frozen samples

  Testing the feasibility of genome scale sequencing in routinely collected FFPE cancer specimens versus matched fresh frozen samples

  Dataset EGAD00001000255

• OICR PANCREATIC CANCER DATASET

  OICR PANCREATIC CANCER DATASET

  Dataset EGAD00001000262

• ICGC Prostate Cancer Whole Genome Sequencing

  A small subsample of EGAD00001000689. Please do not use.

  Dataset EGAD00001000263

• Genetic mechanisms of resistance to chemotherapy in breast cancer

  Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is toidentify genetic mechanisms causing some breast cancer patients not torespond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment. In the project wewill perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where allpatients have recieved treatment with epirubicin monotherapy before surgical removal of alocally advanced breast tumour, and where all patients have beensubjected to objective evaluation of the response to thetherapy. Subsequent to sequencing, we will analyse the data andcompare with the clinical data for each patient (object response totherapy). The main aim being to identify mutations that are associatedwith resistance to epirubicin. Identification of mutations with strongpredictive value, may have a direct impact on cancer treatment sinceit opens the possibility for genetic testing of a tumour, and desicionon which drug is likely to work best, prior to treatment start.

  Dataset EGAD00001000264

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  Dataset EGAD00001000272

• Breast Cancer Exome Sequencing

  Breast Cancer Exome Sequencing

  Dataset EGAD00001000110

• Mutational landscapes of primary triple negative breast cancers - Exomes

  Mutational landscapes of primary triple negative breast cancers - Exomes

  Dataset EGAD00001000113

• Mutational landscapes of primary triple negative breast cancers - WGS

  Mutational landscapes of primary triple negative breast cancers - WGS

  Dataset EGAD00001000115

• Breast Cancer Whole Genome Sequencing

  Breast Cancer Whole Genome Sequencing

  Dataset EGAD00001000121

• HER2 positive Breast Cancer

  HER2 positive Breast Cancer

  Dataset EGAD00001000126

• Breast Cancer Matched Pair Cell Line Whole Genomes

  Breast Cancer Matched Pair Cell Line Whole Genomes

  Dataset EGAD00001000130

• Mutational landscapes of primary triple negative breast cancers - RNA seq

  Mutational landscapes of primary triple negative breast cancers - RNA seq

  Dataset EGAD00001000132

• The landscape of cancer genes and mutational processes in breast cancer

  The landscape of cancer genes and mutational processes in breast cancer

  Dataset EGAD00001000133

• Mutational processes moulding the genomes of 21 breast cancers

  The expression data for this study can be found here: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1088/and its SNP6 data can be found here:http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1087/

  Dataset EGAD00001000138

• Triple Negative Breast Cancer Whole Genomes

  Triple Negative Breast Cancer Whole Genomes

  Dataset EGAD00001000141

• Lung Cancer Whole Genomes

  Lung Cancer Whole Genomes

  Dataset EGAD00001000144

• Matched Pair Cancer Cell line Whole Genomes

  Matched Pair Cancer Cell line Whole Genomes

  Dataset EGAD00001000145

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  Dataset EGAD00001000149

• Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Massive genomic rearrangement acquired in a single catastrophic event during cancer development

  Dataset EGAD00001000002

• CLL cancer Sample Sequencing

  CLL cancer Sample Sequencing

  Dataset EGAD00001000004

• Various Cancer Fusion Gene Sequencing

  Various Cancer Fusion Gene Sequencing

  Dataset EGAD00001000005