11925 results for "cancer rna-seq"

in 20.12 milliseconds.

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• Highly complex single-cell mixture of 5 individuals of high cell number

  Mixture of 5 unrelated individuals sequenced by 10x as a scATAC-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile using the De-goulash pipeline. The separation file is submitted as the processed file. The bam are submitted as unprocessed files.

  Dataset EGAD50000000480

• TOTHER3 dataset

  This dataset contains the FASTQ and BAM files for TOTHER3 study. Targeted DNA-Seq experiment were realized with 49 samples. Since this data was obtained with a panel of genes protected by Intellectual Property (IP), these files only contain information to validate the results published and, in consequence, sensible data had to be specifically removed.

  Dataset EGAD50000000562

• Bulk 3' mRNA-Sequencing of human ASC-derived kidney tubuloids

  Bulk 3' mRNA-Seq raw files (FASTQ) from human kidney tubuloids derived from 4 separate donors in collagen-based dome culture and suspension culture. Samples were collected for sequencing on day 7 of passage 3, 4, and 5. Total = 24 samples.

  Dataset EGAD50000002335

• 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

• Tam-seq of tumor samples for HGSOC copy-number signatures study

  This dataset contains targeted amplicon sequencing of DNA extracted from 300 samples of 142 patients (158 methanol-fixed relapse biopsies and 142 FFPE archival diagnostic tissues). Samples were sequenced on Illumina HiSeq 2500 and were aligned to human genome assembly GRCh37 (hg19)to produce 600 bam files (2 technical replicates per sample).

  Dataset EGAD00001004173

• CBD-RAW-SC-ADT: 10X Single-Cell Features Barcode (CITE-seq)

  Raw Illumina sequencing data and CellRanger BAM output files. For further information regarding this dataset, please contact Stephen Sansom at contact@combat.ox.ac.uk.

  Dataset EGAD00001007962

• Mixture of 2 (closer mtDNA)

  Mixture of 2 unrelated individuals (of close mtDNA haplogroup) sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008727

• scRNA-seq of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-10551

  Dataset EGAD00001009386

• Multiple Myeloma ChipSeq data on six histone modifications

  The data contained in this dataset is ChipSeq BAM files aligned to reference genome hg38. The ChipSeq was based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. The samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Dataset EGAD00001008353

• ICGC prostate cancer whole genome mate-pair sequencing

  ICGC prostate cancer whole genome mate-pair sequencing

  Dataset EGAD00001000303

• SNParray copy number dataset

  4 oesophageal cancer derived organoid lines and 2 ovarian cancer derived organoid lines

  Dataset EGAD00010002002

• Amsterdam UMC Head and Neck Cancer Biology and Immunology

  This data access committee oversees data and assesses requests for the Head and Neck Cancer Biology and Immunology lab of Amsterdam UMC, location VUmc.

  Dac EGAC50000000350

• SPECTA Lung cancer DNA FASTQ files

  SPECTA Lung cancer DNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006223

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Dataset EGAD00001006237

• SNP data for Breast cancer PRS

  SNP data for 313 loci required for calculation of the Breast cancer PRS

  Dataset EGAD00001008144

• Ulcerative colitis study - WES data

  Whole Exome Sequencing data of Single crypts, bulk crypt samples, and colitis-associated cancer.

  Study EGAS00001003801

• The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program 'CASCADE'

  Background: Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. The majority of work in this area has targeted primary tumours however, and very few studies have performed comprehensive profiling of advanced disease. Evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease. Methods and Findings: Three patients with ER-positive, HER2-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program. Cases represented a range of management problems in breast cancer, including late relapse after early stage disease; de novo metastatic disease; discordant disease response and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing.Between cases, there were significant differences in mutational burden, driver mutations, mutational processes and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross seeding was found in each case and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases, and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the key role of mutational processes in subclonal evolution.Limitations of this study include the potential for bias introduced by joint analysis of formalin fixed archival specimens with fresh specimens, and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed. Conclusions: This study highlights the variety of mechanisms that shape the genome of metastatic breast cancer, and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

  Study EGAS00001002153

• Genomic and Genetic Characterization of Prostate Tumors Treated with Neoadjuvant Intense Androgen Deprivation Therapy

  The purpose of this study was to develop better ways of detecting prostate cancer before and after pre-operative treatment, and to test the feasibility of multi parametric magnetic resonance imaging (mpMRI) for the localization and detection of focal prostate cancer both before and after pre-operative treatment with ADT and enzalutamide. In this study, patients with intermediate and high risk prostate cancer received six months of neoadjuvant intense androgen deprivation therapy prior to radical prostatectomy. Biopsies were acquired prior to treatment. Tissue from biopsy and radical prostatectomy were subjected to sequencing and analysis for determination of features associated with response or resistance to treatment.

  Study phs001938

• Integrative Analysis of Lung Adenocarcinoma in EAGLE (Version 2)

  We performed a comprehensive analysis of intratumor heterogeneity of somatic mutations in cancer driver genes, copy number aberrations and DNA methylation in 292 tumor samples from 84 lung adenocarcinoma (LUAD) patients from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. SNVs of 37 established lung cancer driver genes were profiled by deep target sequencing in 180 tumor samples and 55 blood samples and 1 buccal sample from 56 subjects. Somatic copy number alterations were profiled using SNP arrays in 268 tumor samples from 80 subjects. DNA methylation levels were profiled with methylation arrays in 205 tumor samples and 74 normal tissue samples from 68 subjects.

  Study phs001169

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__WG_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from lung tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will deeply sample from individuals with smoking-related lung diseases (COPD, pulmonary fibrosis, lung cancer) and those without smoking history. This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003502

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  Introduction Immune checkpoint blockade (ICB) immunotherapy has revolutionized cancer treatment, demonstrating exceptional clinical responses in a wide range of cancers. Despite the success, a significant proportion of patients still fail to respond, highlighting the existence of unappreciated mechanisms of immunotherapy resistance. Delineating such mechanisms is paramount to minimize immunotherapy failures and optimize the clinical benefit. Methods In this study, we treated tumour-bearing mice with PD-L1 blockage antibody (aPD-L1) immunotherapy, to investigate its effects on cancer-induced emergency myelopoiesis, focusing on bone marrow HSPCs. We examined the impact of aPD-L1 treatment on HSPC quiescence, proliferation, transcriptomic profile, and functionality. Results Herein, we reveal that aPD-L1 in tumour-bearing mice targets the hematopoietic stem and progenitor cells (HSPCs) in the bone marrow (ΒΜ), mediating their exit from quiescence and promoting their proliferation. Notably, disruption of the PDL1/PD1 axis induces transcriptomic reprogramming in HSPCs, observed in both individuals with Hodgkin lymphoma (HL) and tumour-bearing mice, shifting towards an inflammatory state. Furthermore, HSPCs from aPDL1-treated mice demonstrated resistance to cancer-induced emergency myelopoiesis, evidenced by a lower generation of MDSCs compared to control-treated mice. Discussion: Our findings shed light on unrecognized mechanisms of action of ICB immunotherapy in cancer, which involves targeting of BM-driven HSPCs and reprogramming of cancer-induced emergency myelopoiesis.

  Study EGAS00001007873

• Deep multi-region whole-genome sequencing reveals heterogeneity and gene-by-environment interactions in treatment-naive, metastatic lung cancer

  Our understanding of genomic heterogeneity in lung cancer is largely based on the analysis of early-stage surgical specimens. Here we used endoscopic sampling of paired primary and intrathoracic metastatic tumors from 11 lung cancer patients to map genomic heterogeneity inoperable lung cancer with deep whole-genome sequencing. Intra-patient heterogeneity in driver or targetable mutations was predominantly in the form of copy number gain. Private mutation signatures, including patterns consistent with defects in homologous recombination, were highly variable both within and between patients. Irrespective of histotype, we observed a smaller than expected number of private mutations, suggesting that ancestral clones accumulated large mutation burdens immediately prior to metastasis. Single-region whole-genome sequencing of from 20 patients showed that tumors in ever-smokers with the strongest tobacco signatures were associated with germline variants in genes implicated in the repair of cigarette-induced DNA damage. Our results suggest that lung cancer precursors in ever-smokers accumulate large numbers of mutations prior to the formation of frank malignancy followed by rapid metastatic spread. In advanced lung cancer, germline variants in DNA repair genes may interact with the airway environment to influence the pattern of founder mutations, whereas similar interactions with the tumor microenvironment may play a role in the acquisition of mutations following metastasis.

  Study EGAS00001003830