10161 results for "cancer rna-seq"

in 62.46 milliseconds.

• mutational landscape of normal human breast

  The accumulation of somatic mutations in the healthy breast throughout life and pregnancy is poorly understood. Here we describe whole genome sequencing analysis of epithelial and stromal compartments from the normal breast. We aimed to study how pregnancy and age affect both the mutational burden and the clonality of the healthy breast, and the subsequent implications on breast cancer risk.

  Study EGAS00001004672

• High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics

  We developed a novel microfluidic platform to automatically barcode genomic DNA from individual cancer cells. Using this approach, we sequenced acute myeloid leukemia (AML) tumors targeting up to 62 loci relevant for the disease from thousands of cells. We predict that our platform will enable analysis of heterogeneity in AML and improve stratification and therapy selection.

  Study phs001627

• Molecular Analysis of Alliance A031201 Study

  This is the first study examining the relationship between clonal hematopoiesis and clinical outcomes in prostate cancer patients. We used a targeted gene sequencing panel to identify patients in the A031201 clinical trial with and without clonal hematopoiesis. We found that clonal hematopoiesis did not affect overall or progression free survival in A031201 but was associated more adverse cardiac events.

  Study phs003717

• Whole genome analysis of pediatric patients with medulloblastoma

  Cancer genomes often contain structural variations (SVs) in non-coding regions, while its impact on tumorigenesis is still unclear. Our goal is to discover genome folding changes resulted from SVs using InfoGenomeR and InfoHiC frameworks, which may reveal novel therapeutic targets. We applied our frameworks to five pediatric patients with medulloblastoma, revealing 3D genome changes of medulloblastoma driver genes.

  Study EGAS00001006653

• A somatic reference standard for cancer genome sequencing with COLO829

  Identification of somatic alterations in cancer has become feasible with the massive adoption of next generation sequencing. However, due to variability in sequencing and informatics pipelines, a common somatic reference is needed. We thus performed paired whole genome sequencing of a metastatic melanoma cell line (COLO829) and a matched lymphoblastoid line (COLO829BL) across three institutions (TGen, Illumina, Genome Sciences Centre at the British Columbia Cancer Agency). We performed a meta-analysis of all data, in combination with the originally reported analysis of these cell lines by Pleasance et al (PMID: 20016485), and report a somatic reference standard based on consensus events. DNA extractions, library preparation, sequencing, and analysis were separately performed at each site. Results were compiled with sequence data previously generated for the cell lines to identify true positive variants, collectively representing a somatic reference standard. Overall, common somatic events include point mutations, small insertion/deletions, and genes affected by concurrent copy number changes. We additionally show divergence of somatic mutations in COLO829 associated with differences in cell line lineage. We present this reference to the community as a standard for enabling interpretation and identification of somatic mutations across institutions and analytical pipelines.

  Study EGAS00001001385

• Nanopore_and_Illumina_sequencing_of_human_glioblastomas

  Liquid biopsy analysis refers to methods designed to detect tumour-specific material (e.g., circulating tumour cells or tumour DNA) in body fluids, such as urine or blood samples. A widely-used liquid biopsy approach consists of genotyping the circulating tumour DNA (ctDNA) through sequencing of plasma/serum DNA. Although useful in the context of metastatic disease (where the concentration of ctDNA is high), current liquid biopsy technologies show limited sensitivity of detection for the early detection of cancer, and low specificity, as cancer-related mutations accumulate in healthy tissues as part of the ageing process, thus making it difficult to distinguish these from tumour mutations, and because sequencing errors and true mutations show overlapping profiles. Therefore, developing liquid biopsy protocols with increased sensitivity and specificity represents an urgent clinical need. Here we harness extrachromosomal circular DNA (eccDNA) elements, which are circular DNA structures physically separated from the chromosomes of up to several Mbp long pervasive in human cancers, for liquid biopsy analysis. In this pilot study we will focus on the analysis of glioblastomas, because there is strong evidence for the presence of eccDNA in these tumour types, and because developing liquid biopsy approaches for brain tumours to reduce the invasiveness of brain tumour biopsies remains an unmet clinical need.

  Study EGAS00001005812

• Germline Mutations and Developmental Mosaicism Underlying EGFR-Mutant Lung Cancer

  We designed this study to examine the etiology of multiple lung tumors in EGFR-mutant non-small cell lung cancer patients who undergo surgical resection. Participants were 52-85 years old never or former smokers, who had at least 2 surgical lung tumor pathology specimens available in the Massachusetts General Hospital biobank, at least one of which had an EGFR mutation by routine clinical genotyping. 10 patients were selected, along with two patients from a family with an inherited EGFR-T790M mutation leading to multiple lung tumors. These patient tumor samples and matched normal lung samples were microdissected to collect DNA.In addition to obtaining clinical histories, we performed whole exome sequencing to evaluate the genetic profile of matched tumor and normal samples. The WES data are available on dbGaP. Our data showed increasing mutational burden and copy number alteration with increasing invasiveness, as compared to normal tissues, for the subset of samples that were assessed for tumor invasiveness. We also observed a range of numbers of shared mutations between tumors in a single patient, indicating different degrees of relatedness between lung tumors. We hope that this resource will help researchers understand non-small cell lung cancer presentations with multiple lung tumors. These data may aid in clinical decision making for such patients.

  Study phs003379

• Scottish High Grade Serous Ovarian Cancer

  Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. On receipt of tumour material the tumour was processed as follows: firstly, the tumour sample was divided into two for DNA and RNA extraction. Slivers of tissue were cut from the front and rear faces of the DNA sample, then fixed in formalin and embedded in paraffin wax. Sections from the front and rear tissues from all samples were examined by H&E staining supplemented by WT1/p53 immunohistochemistry if required. Following pathology review, samples were only included if they met the following criteria: they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using the H&E sections. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality. Only when all 4 quality control requirements were satisfied was the DNA sequenced. The DNA was sequenced at the Glasgow Precision Oncology Laboratories.

  Study EGAS00001004410

• 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

• Targeted gene sequencing of gallbladder cancer

  The dataset includes the targeted gene sequencing data from51 pairs of gallbladder caner tissues and patient-matched normal tissues.

  Dataset EGAD00001000902

• GIST SSGXVIII trial targeted gene sequencing

  Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

  Dataset EGAD00001001427

• Illumina_RNA_T

  RNAseq on Illumina HiSeq2000/2500 of colorectal cancer primary tumor sample

  Dataset EGAD00001002077

• Prostate WGS data (late onset)

  Whole genome sequencing for 12 late onset prostate cancer tumor/control pairs (ICGC)

  Dataset EGAD00001003290

• OT2_Illumina_RNA_MET

  RNAseq on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003364

• 20180208_EGA_Trench_MetCellLine.1

  Illumina platform sequencing data of SureSelect exome libraries prepared from 3 samples from one donor: a normal, primary breast cancer, and cell line derived from metastasis

  Dataset EGAD00001003956

• Organoid Derivation Pilot: RNAseq

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005001

• WES

  WES was performed on 2 TURP, 6 biopsies, 1 CDX, 1 cell line, 6 CTCs, 1 DNA germline and 1WBC from prostate cancer

  Dataset EGAD00001006009

• HiC files for Zhang GenomePaint paper

  HiC files for GenomePaint paper titled "Exploration of coding and non-coding variants in cancer using GenomePaint."

  Dataset EGAD00001006678

• Multi-region WGS of a RET fusion positive cancer

  high depth WGS sequencing of 8 sites of a RET fusion tumour

  Dataset EGAD00001006878

• SAFIR02_Oncoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Dataset EGAD00010002241

• Targeted and shallow whole genome sequencing identifies therapeutic opportunities in p53abn endometrial cancers

  Targeted panel sequencing of 188 formalin-fixed paraffin-embedded p53abn endometrial cancer samples.

  Dataset EGAD00001015349

• BAM/BAI dataset of Colorectal Cancer Synthetic genomes

  This dataset contains binary alignment map (BAM) data with their respective index (BAI) from four patients synthetically generated.

  Dataset EGAD50000000316

• Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses

  Personalized cancer therapy based on the somatic mutations identified in patient tumors is becoming an increasingly emphasized approach to improve outcomes of patients with cancer. There are also examples of therapeutic vulnerabilities in cancer that result from changes in gene expression that are a direct or indirect result of tumor specific epigenetic perturbations. These genomic and epigenomic changes are ultimately manifest in the tumor proteome and phosphoproteome. In this study, we integrated genomic, epigenomic and proteomic data for rhabdomyosarcoma (RMS) to identify therapeutic vulnerabilities. RMS was selected for this analysis because RAS pathway mutations in rhabdomyosarcoma (RMS) are the most common potentially actionable lesions across pediatric solid tumors. The epigenomic data was useful for identifying deregulated developmental pathways in RMS including the WNT, HH, BMP, adenyl cyclase, p38/MAPK and PI3K pathways. Perturbations in those 6 myogenic signal transduction pathways were also evident in the proteome and phosphoteome data. In addition, the proteomic/phosphoproteomic data revealed that the cell cycle checkpoint, unfolded protein response and RB/E2F pathways were deregulated in RMS relative to normal muscle. Recent success targeting CDK4/6 and MEK in adult cancers with RAS mutations led us to test the value of these targets in RMS tumors. We also targeted the unfolded protein response pathway and cell cycle checkpoint pathway using molecular targeted therapeutics in orthotopic patient derived xenografts. Taken together, these data demonstrate the value of integrating epigenomic and proteomic data to identify tumor vulnerabilities that extend beyond somatic mutations identified in the genome.

  Study EGAS00001002967

• Organoid cultures of early-onset colorectal cancers reveal distinct and rare genetic profiles

  Sporadic early-onset colorectal cancer (EOCRC) has bad prognosis, yet is poorly represented by cell line models. We examine the key mutational and transcriptomic alterations in an organoid biobank enriched in EOCRCs. We established paired cancer (n=32) and normal organoids (n=18) from 20 patients enriched in microsatellite-stable EOCRC. Exome and transcriptome analysis was performed. We observed a striking diversity of molecular phenotypes, including PTPRK-RSPO3 fusions. Transcriptionally, RSPO fusion organoids resembled normal colon organoids and were distinct from APC mutant organoids, with high BMP2 and low PTK7 expression. Single cell transcriptome analysis confirmed the similarity between RSPO fusion organoids and normal organoids, with a propensity for maturation on Wnt withdrawal, whereas the APC mutant organoids were locked in progenitor stages. CRISPR/Cas9 engineered mutation of APC in normal human colon organoids led to upregulation of PTK7 protein and suppression of BMP2, but less so with an engineered RNF43 mutation. The frequent co-occurrence of RSPO fusions with SMAD4 or BMPR1A mutation was confirmed in TCGA database searches. RNF43 mutation was found in organoid from a leukaemia survivor with a novel mutational signature; and organoids with POLE proofreading mutation displayed ultramutation. The cancer organoid genomes were stable over long culture periods, while normal human colon organoids tended to be subject to clonal dominance over time. These organoid models enriched in EOCRCs with linked genomic data fill a gap in existing CRC models and reveal distinct genetic profiles and novel pathway cooperativity.

  Study EGAS00001004063

• Sequence analysis of colorectal serrated lesions

  Recent studies have shown that colorectal serrated lesions, which include sessile serrated adenomas (SSAs) and traditional serrated adenomas (TSAs), are precursors of colorectal cancer. However, the molecular mechanisms underlying the carcinogenesis, particularly in TSAs, remain largely uncharacterized. To clarify their molecular and clinicopathological characteristics, we performed mutation and methylation analyses of cancer-associated genes in 78 serrated lesions, including TSAs, SSAs and microvesicular hyperplastic polyps. Target exon sequence analysis was performed with 39 genes, including genes known to be frequently mutated in colorectal cancers and/or serrated lesions. We also used bisulfite pyrosequencing to assess the methylation status of various cancer-associated genes and marker genes of the CpG island methylator phenotype (CIMP). The prevalence of mutations in genes associated with Wnt signaling was significantly higher in TSAs than SSAs (65% vs. 28%, p < 0.01). Among those, RNF43 mutations were observed in 38% of TSAs and 17% of SSAs. In immunohistochemical studies of 39 serrated lesions, the prevalence of abnormal nuclear ?-catenin accumulation was significantly higher in TSAs (57%) than SSAs (8%) (P = 0.01). SMOC1 methylation was detected in 54% of TSAs but in no SSAs (p < 0.01). Additionally, SMOC1 methylation was more prevalent among TSAs with KRAS mutation (82%) than with BRAF mutation (38%, p = 0.03). Lesions with CIMP-high or RNF43 mutations were detected only in TSAs with BRAF mutation, suggesting two distinct carcinogenic pathways in TSAs. Mutations in genes associated with Wnt signaling play a greater role in the carcinogenesis of TSAs than SSAs.

  Study JGAS000217

• Durable clinical impacts and mechanisms of action and resistance in histone K27 methylation-targeting epigenetic therapy

  Epigenomes allow the rectification of disordered cancer gene expressions, thereby providing new targets for pharmacological interventions in cancer therapy. The clinical utility of targeting histone H3 lysine tri-methylation (H3K27me3) as an epigenetic hallmark has been demonstrated. However, in actual therapeutic settings, the mechanism by which H3K27me3-targeting therapies exert their effects and the response of tumor cells remain unclear. Here we show the potency and mechanisms of action and resistance of a newly developed EZH1/2 dual inhibitor, valemetostat, in the clinical trials of patients with adult T-cell leukemia/lymphoma (ATL). Valemetostat administration reduced the tumor size and demonstrated durable clinical benefits. Integrative single-cell analyses of patients before and after the administration of valemetostat showed that valemetostat abolishes the highly condensed chromatin structure formed by the plastic H3K27me3 and neutralizes multiple gene loci, such as tumor suppressor genes. Nevertheless, subsequent long-term treatment encounters the emergence of resistant clones with reconstructed aggregate chromatin that closely resemble the pre-dose state. The acquired mutations at the EZH2���compound interface result in the propagation of the clones with re-increased H3K27me3. In patients free of this mutation, TET2 mutation or elevated DNMT3A expression causes similar chromatin recondensation through de novo DNA methylation at the H3K27me3-associated regions. We identified subpopulations with distinct metabolic and gene translation characteristics implicated in primary susceptibility until the acquisition of the heritable (epi)mutations. Targeting chromatin homeostasis might provide opportunities for further sustained epigenetic cancer therapies.

  Study JGAS000553

• Liquid Biopsy Versus Tissue Biopsy to Assess Acquired Resistance and Tumor Heterogeneity in Gastrointestinal Cancers

  Tumor heterogeneity can drive the evolution of multiple tumor subclones harboring unique molecular resistance alterations in different metastatic lesions in an individual patient, under the selective pressure of therapy1-3. Studies have suggested that liquid biopsy may better capture the heterogeneity of acquired resistance, but systematic, direct comparisons of post-progression liquid vs. standard single-lesion tumor biopsies are lacking. In a prospective cohort of 44 patients with molecularly-defined gastrointestinal cancers and acquired resistance to targeted therapy, direct comparison of post-progression liquid vs. tumor biopsy revealed that liquid biopsy more frequently identified clinically-relevant resistance alterations and multiple resistance mechanisms, detecting resistance alterations not detected in matched tumor biopsy in 78% of cases. Whole-exome sequencing of serial cell-free DNA, tumor biopsies and rapid autopsy specimens elucidated geographic and evolutionary characteristics of heterogeneity. Our data suggest that acquired resistance is frequently characterized by profound tumor heterogeneity and highlight the potential clinical utility of liquid biopsy. Burrell, R. A. &#38; Swanton, C. Tumour heterogeneity and the evolution of polyclonal drug resistance. Molecular oncology 8, 1095-1111, doi:10.1016/j.molonc.2014.06.005 (2014). Misale, S. et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 486, 532-536, doi:10.1038/nature11156 (2012). Ahronian, L. G. et al. Clinical Acquired Resistance to RAF Inhibitor Combinations in BRAF-Mutant Colorectal Cancer through MAPK Pathway Alterations. Cancer Disco 5, 358-367, doi:10.1158/2159-8290.Cd-14-1518 (2015).

  Study phs001853

• Proteomic Analysis of Non-Muscle Invasive and Muscle Invasive Bladder Cancer Highlights Distinct Subgroups With Metabolic, Matrisomal, and Immune Hallmarks

  We present the proteome biology of bladder cancer based on a cohort comprising treatment-naïve non-muscle invasive (NMIBC, N=17) and treatment-naïve muscle-invasive bladder cancer (MIBC, N=51), as well as neoadjuvant-treated MIBC (N=11); using formalin-fixed, paraffin-embedded samples and data-independent acquisition yielding &gt;8,000 protein identifications. The NMIBC proteome reveals two subgroups that represent cell adhesion or lipid metabolism biology. MIBC, compared to NMIBC, shows an altered metabolic proteome together with enrichment of extracellular matrix (ECM), immune response, and complement proteins; in line with three proteomic MIBC subgroups that represent ECM, metabolic, or immune signatures. The ECM and immune subgroups are enriched for markers of M2-like tumor-associated macrophages and dendritic cells, while markers for natural killer cells are exclusive for the ECM subgroup, and markers for cytotoxic T-cells are a hallmark of the immune subgroup. Infiltration of CD8+ PD1+ positive cytotoxic T cells correlated with PD-L1 expression of MIBC, as demonstrated by multiplex immunofluorescence analysis. The metabolic subgroup presents a comparably immune-depleted microenvironment. YAP1 signaling is particularly prominent in the ECM subgroup. The protein BSCL2 emerges as a prognostic marker for MIBC. We highlight increased endogenous proteolysis in MIBC alongside the upregulation of matrix metalloproteases exceeding the upregulation of their endogenous inhibitors. Genomic panel sequencing underlines prevalent FGFR3 mutations in NMIBC and prevalent TP53 mutations in MIBC, but a genomic underpinning of the MIBC subgroups remains elusive. Proteogenomic analysis yields protein-level evidence for more than 1,300 single amino acid variants. The proteomes of neoadjuvant-treated MIBC resembled treatment-naïve MIBC. Tumor-stroma interaction of MIBC was further investigated by proteomic analysis of patient-derived xenografts of MIBC. Our study adds to the proteome-level understanding of bladder cancer.

  Study EGAS00001007290

• Mutational_signatures_and_clonal_dynamics_in_normal_human_tissues

  Somatic mutations (burdens and signatures) and clonal dynamics in normal human tissues

  Study EGAS00001002471

• V4_Colorectal_panel_test

  Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

  Study EGAS00001001807

• Point-of-care monitoring of head and neck cancer treatment response and recurrence development using nanopore-based ctDNA consensus sequencing

  Study EGAS00001007090

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (WGS)

  Study EGAS00001004756

• Data Access Committee of divisions B060 and B062, German Cancer Research Center (DKFZ)

  Dac EGAC00001000219

• EGAD00010000644

  Affymetrix SNP6.0 cancer cell line exome sequencing data

  Dataset EGAD00010000644

• 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

• BC WGS Dataset 1

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001350

• NSCCG CRC WES

  1006 Familial early onset gemrline CRC patients sequenced by the Molecular and Population Genetics group of the Institute of Cancer Research

  Dataset EGAD00001002204

• Genentech_cell_line_SNP

  SNP array data for 668 cancer cell lines

  Dataset EGAD00010000951

• sWGS of non-cancer controls

  Paired end shallow whole genome sequencing (sWGS) data of cell-free DNA from plasma from self-reporting healthy individuals (MonRec Cohort)

  Dataset EGAD00001005805

• RBWES

  Retinoblastoma is a rare childhood cancer of the retina. We studied retinoblastoma by Whole-Exome-Sequencing.

  Dataset EGAD00001007591

• FunGeST - Functional Genomics from cancer research to personalized medicine

  Dac EGAC00001002924

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015264

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015265

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015267

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015270

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015272

• Genome and transcriptome sequence data from a craniopharyngioma tumor patient

  Genome and transcriptome sequence data from a craniopharyngioma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015273

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015277

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015278

• Genome and transcriptome sequence data from a pineoblastoma tumor patient

  Genome and transcriptome sequence data from a pineoblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015280

• Genome and transcriptome sequence data from a ependymoma tumor patient

  Genome and transcriptome sequence data from a ependymoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015287

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015288

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015290

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015293

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015294

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015300

• Population Architecture Using Genomics and Epidemiology (PAGE): Epidemiologic Architecture for Genes Linked to Environment (EAGLE) - BioVU Cancer Project

  As part of Population Architecture using Genomics and Epidemiology PAGE study (Phase I), the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE I) project accessed both epidemiologic- and clinic-based collections. The epidemiologic-based collection of EAGLE I included the National Health and Nutritional Examination Surveys (NHANES), ascertained between 1991-1994 (NHANES III), 1999-2002, and 2007-2008. NHANES is a population-based cross-sectional survey now conducted every year in the United States to assess the health status of Americans at the time of ascertainment and to assess trends over the years of survey. Genetic NHANES consists of 19,613 DNA samples linked to thousands of variables including demographics, health and lifestyle variables, physical examination variables, laboratory variables, and exposures. NHANES is diverse with almost one-half of the samples (46.4%) coming from self-reported Mexican Americans and non-Hispanic blacks. In contrast to NHANES, BioVU is a clinic-based collection of &#62;150,000 DNA samples from Vanderbilt University Medical Center linked to de-identified electronic medical records (EMRs). Approximately 12% of BioVU&#39;s overall DNA sample collection is from African American, Hispanic, and Asian patients. The overall goals of PAGE I and EAGLE I were broad and several-fold: Replicate genome-wide association study (GWAS)- identified variants in European Americans; Identify population-specific and trans-population genotype-phenotype associations; Identify genetic and environmental modifiers of these associations. NHANES is an excellent resource for the study of quantitative traits associated with common human diseases. However, given that the age range of NHANES spans childhood to late adulthood and not all diseases are surveyed, NHANES is less useful for the study of adult-onset diseases such as major cancers. Therefore, under American Recovery and Reinvestment Act (ARRA) funding, EAGLE as part of PAGE I defined eight major cancers sites for genetic analysis in BioVU, Vanderbilt&#39;s biorepository linked to de-identified EMRs. The eight major cancers defined for this study included melanoma, breast, ovarian, prostate, colorectal, lung, endometrial, and Non-Hodgkin&#39;s lymphoma (NHL). Cancer cases were defined using a combination of ICD-9 codes and tumor registry entries. Controls include BioVU participants without cancer and encompassing the age and gender distributions of cancer cases. Targeted genotyping of GWAS-identified variants for these diseases (124 SNPs) and ancestry informative markers (128 AIMs) was performed by the Center for Human Genetics Research Vanderbilt DNA Resources Core. After quality control, a total of 116 cancer-associated SNPs and 122 AIMs were available for downstream analyses.

  Study phs000559

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• EGAD00010000268

  Metabric breast cancer samples (Expression raw data)

  Dataset EGAD00010000268

• Illumina_WXS_MET-CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002096

• EPO2_Illumina_WXS_XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample (EPO2_cohort)

  Dataset EGAD00001003363

• ParityImmune

  Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC)

  Dataset EGAD00010001412

• Organoid Derivation Project WGS: Release 1

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005000

• WGS of kidney cancer organoid biobank

  Dataset EGAD00001005319

• Organoid Derivation Project WGS: Release 2

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005955

• Organoid Derivation Project TGS: Release 2

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001004999

• Organoid Derivation Project TGS: Release 3

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Dataset EGAD00001005958

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015296

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015302

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015309

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015316

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015332

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015337

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015338

• BROCA cancer panel sequencing for 15 samples

  BROCA panel sequencing using the BROCA-HR v8 and BROCA-GO v1 versions of the gene panel

  Dataset EGAD50000000035

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 4 Shwachman-Diamond syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 4 Shwachman-Diamond syndrome (SDS) cases. This data set, comprising 4 SDS cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 3 Diamond-Blackfan anemia (DBA) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002660

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 3 Diamond-Blackfan anemia cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 3 Diamond-Blackfan anemia (DBA) cases. This data set, comprising 3 DBA cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 4 Shwachman-Diamond syndrome (SDS) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition, this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002661

• Target-capture sequencing of FFPE tumor samples from patients diagnosed with NKTL

  211 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing. FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip.

  Dataset EGAD00001005303

• T-VEC CBCL scRNA

  We are presenting raw and processed data of our study where we analyze fine-needle aspirate (FNA) samples of primary cutaneous B-cell lymphoma patients undergoing oncolytic virotherapy (https://clinicaltrials.gov/ct2/show/NCT03458117). We are uploading single cell RNA-sequencing and immune repertoire profiling data of 29 FNA samples from four pCBCL patients. The four patients have three different subtypes of primary cutaneous B-cell lymphoma: pCDLBCL-LT, pCFCL and pCMZL. The samples are taken at different time points following T-VEC injection (from baseline up to 91 days after injection). We are uploading the sequences in BAM format and the outputs of the cellranger pipeline (count matrices and filtered VDJ contigs) in CSV format.

  Dataset EGAD00001006829

• MPM cell lines

  RNA-sequencing data for 12 MPM cell lines treated with 0.1% DMSO or 1 µM palbociclib for 9-10 days. Experiment was performed in duplicates for sensitive cells (MPM08, MPM21, MPM38, MPM57, MPM59, Meso11, Meso13, Meso34 and Meso56) and only once for resistant cells (MPM31, MPM34 and MPM36) except for Meso11 which was done in triplicates. For Meso11, Meso13, Meso34 and Meso56, a drug washout of 48 hours was also performed. 4 MPM cell lines (MPM31, MPM34, MPM59 and MPM66) were also analyzed in untreated condition. 2 FASTQ files for each sample (n=56) (paired)

  Dataset EGAD00001008741

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  In this study we performed whole genome sequencing on matched tumor-normal CD138+ bone marrow mononuclear cells from 60 patients with newly diagnosed multiple myeloma treated with daratumumab, carfilzomib, lenalidomide, and dexamethasone (NCT03290950-MANHATTAN trial). In addition, we performed 5’-single-cell RNA-sequencing (10X Genomics) coupled with V(D)J sequencing and capture of the surface protein markers (TotalSeq-C, Biolegend) of the CD138- bone marrow mononuclear cells to interrogate the composition of the immune microenvironment at baseline and after eight cycles of induction therapy in 22 patients with newly diagnosed multiple myeloma. Samples were multiplexed using hashtag oligo.

  Dataset EGAD00001011132

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Dataset EGAD50000000087

• MDS_Sequential_Treatment_Validation

  Validations of variants identified by exome sequencing in sequential samples derived after treatment cycle with AZA.

  Study EGAS00001000703

• Targeted_sequencing_of_in_vitro_colonies___bulks

  In this study we will perform targeted sequencing on the bulk samples of in vitro colonies

  Study EGAS00001003175

• V2_Colorectal_panel_test

  Targeted gene screen of cell line tumour samples for testing the new V2 Colorectal gene panel.

  Study EGAS00001001806

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___POL___WGS

  Somatic mutations (burdens and signatures) and clonal dynamics in individuals with germline DNA polymerase mutations.

  Study EGAS00001003682

• EGAD00010000558

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000558

• 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

• ICGC Korean Breast Cancer Project

  A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing.

  Dataset EGAD00001001322

• Illumina_WGS_MET-CELL

  Whole-genome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002085

• Illumina_WXS_MET

  Whole-exome sequencing on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample

  Dataset EGAD00001002095

• Illumina_WXS_T-CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002100

• NanoString gene expression of PBMC from bladder cancer and RCC patients

  This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts

  Dataset EGAD00001005976

• Lung cancers from admixed Latin American populations (1)

  Raw data from cancer panel sequencing of lung adenocarcinomas from admixed Latin American populations. Predominantly samples carrying known oncogene mutations (n=581).

  Dataset EGAD00001006552

• RPPA analysis + clinical data

  RPPA analysis from FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer.

  Dataset EGAD00001008507

• The CCA Genome Core is responsible for archiving the sequencing data generated by the Cancer Centre Amsterdam (CCA).

  Dac EGAC00001000181

• Cell_lines_with_telomere_fusion_induced_rearrangements

  Whole-genome somatic rearrangement and point mutation analysis in cell lines with induced telomere fusions.

  Study EGAS00001001059

• Genome and transcriptome sequence data from a CNS sarcoma tumor patient

  Genome and transcriptome sequence data from a CNS sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015268

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015279

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015283