Search Results - EGA European Genome-Phenome Archive

Whole exome sequencing of pediatric soft tissue sarcoma PDX models

Childhood cancer remains one of the leading causes of death in pediatric patients in Europe. Pediatric sarcomas, comprising soft tissue sarcomas and malignant bone tumors, are a heterogenous group of malignancies, with more than 50 subtypes (WHO classification). Due to low case numbers, studying pediatric sarcomas requires accurate and reliable preclinical models. Here, we established 18 soft tissues sarcoma PDX models, including Ewing Sarcoma, Rhabdmyosarcoma and Osteosarcoma. We characterized these models by Whole Exome Sequencing and assessd the response to a wide range of drugs.

Study EGAS50000000048

Mesothelioma Genomics Study - WGS tumour/normal pairs

Malignant mesothelioma (MM) is an incurable and aggressive tumour that occurs principally in the pleura as a consequence of inhaling asbestos fibres. There are >15,000 cases per annum worldwide, the incidence is increasing and Australia has one of the world's highest incidence rates. Surgery, chemotherapy and radiotherapy (or their combinations) all feature in the clinical management but do not impact significantly on overall survival. This study uses whole genome sequencing (WGS) with the aim of identifying mesothelioma-related genomic alterations and potentially identifying novel treatment strategies.

Study EGAS00001002299

MSK SPECTRUM - SPatiotemporal Evolution of Cancer Traced Using Multimodalities

MSK SPECTRUM is a multi-modal, interdisciplinary prospective study of spatiotemporal determinants of high-grade serous ovarian cancer (HGSOC) evolution, treatment and response. Accounting for ~80% of ovarian cancers, HGSOC is the most lethal gynecological malignancy and is a cancer of major unmet clinical need. Challenges in disease management relate to several unresolved questions about disease biology and diagnostic modalities. Prospective longitudinal collection of tissues and blood from laparoscopic biopsies and debulking surgeries enable multi-modal molecular measurements. The program brings together formidable expertise at Memorial Sloan Kettering Cancer Center (MSKCC) across the disciplines of high-resolution genomics and computer science, radiology and radiomics, surgery, tissue banking and sample preparation, medical oncology, immuno-oncology and high-resolution tissue profiling to generate a comprehensive and integrative dataset that will allow us to address the following major aims: i) characterize malignant and immune diversity at diagnosis, ii) survey the co-evolution of malignant cells and the immune response, and iii) stratify patients on standard-of-care and investigational compounds based on their genomic and transcriptomic signatures and changes to relevant genes (TP53, CCNE1, BRCA1/2, CDK12). The goal is to create a framework to utilize integrated multi-modal data as a route to advanced diagnostics and to ultimately establish a proof-of-concept for integrated diagnostics.

Study phs002857

WGS profiling of pediatric osteosarcoma

Primary pediatric osteosarcoma samples were collected and profiled using WGS. When possible, germline and tumor samples were collected. For some patients, multiple tumor tissues were collected and sequenced. Some of the samples were used to derive PDTX models, which were also profiled with WGS. Paired end sequencing was performed on Illumina HiSeq instruments and FASTQ files reported.

Dataset EGAD00001004537

ATAC-seq in colon normal mucosa

ATAC-seq

Dataset EGAD00001007690

GATCI whole genome sequencing fastqs

Raw whole genome sequencing data (fastq) for the GATCI project

Dataset EGAD00001005926

Acquired Cross-Resistance in Small Cell Lung Cancer Patient-Derived Xenografts

Here we present whole genome sequencing and RNA sequencing of patient-derived xenograft (PDX) models of small cell lung cancer (SCLC). These models were derived at a variety of clinical time points from either biopsy/resection samples, malignant effusions, or circulating tumor cells (CTCs), and grown in the subcutaneous flank of NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl /SzJ) mice. The first analysis published with these data was to determine the genomic and transcriptomic features of PDX models derived after relapse that demonstrated in vivo resistance to multiple chemotherapy regimens (cross-resistance).

Study phs003486

DAC Dr. PORTEU – Gustave Roussy

Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways Data Access Committee Members (Name, Email, Job Title): Principal Investigator PORTEU Françoise (FRANCOISE.PORTEU@gustaveroussy.fr) Head of Bioinformatics platform DELOGER Marc (Marc.DELOGER@gustaveroussy.fr) Data Protection Officer BECHET Clara (Clara.BECHET@gustaveroussy.fr)

Dac EGAC50000000252

Balanced Ependymoma

We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

Dataset EGAD00001000350

Modeling Malignant Progression in Glioma

Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

Study phs002607

Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

Study EGAS00001007877

Paired-end RNA-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

44 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina RNAseq paired-end technology. Dataset contains 44 BAM files aligned to hg19 using Tophat 2.

Dataset EGAD00001005387

Sequencing data for oesophageal and related samples - Katz-Summercorn, Jammula et al (RNA)

Data supporting: “Multi-omic cross-sectional cohort study of pre-malignant Barrett’s esophagus reveals structural variation and retrotransposon activity occur early in cancer evolution.” Katz-Summercorn, Jammula et al. RNAseq (BAM files)

Dataset EGAD00001006353

cytogenetically visibile inversions

Pacbio Hifi whole genome sequencing data from six individuals carrying cytogenetically visible inversions. The HiFi data was produced on the PacBio Revio machine, using 1 flowcell per sample. The resulting data was aligned to hg19 using minimap2, and converted into bam using samtools.

Dataset EGAD50000000635

Targeted capture sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

Targeted capture sequencing for 366 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study and 29 samples from a previously uploaded dataset.

Dataset EGAD50000001364

Sporadic and endemic Burkitt lymphoma have frequent FOXO1 mutations but distinct hotspots in the AKT recognition motif

Sample set of 74 whole-exome sequencing samples from sporadic Burkitt lymphoma patients from the UK. 33 of these samples have matched constitutional data, giving a total number of 107 samples

Dataset EGAD00001005105

Sequencing data for oesophageal / related samples - Foley, Shorthouse et al (RNA)

Data supporting: "SMAD4 and KCNQ3 Alterations are Associated with Lymph Node Metastases in Oesophageal Adenocarcinoma" RNAseq (FASTQ files) 6 samples

Dataset EGAD00001011065

Methylation data

To ellucidate methylation activity in mRCC, methylation data was generated as part of the EuroTarget study

Dataset EGAD50000002295

RNA-seq

RNA-seq data

Dataset EGAD00001008959

PacBio medulloblastoma datasets

PacBio data from 5 medulloblastoma tumor-normal pairs. The data consists of BAM files aligned using NGMLR

Dataset EGAD00001010852

TGL49_HBC sWGS

Shallow whole genome sequencing of plasma samples from healthy control patients.

Dataset EGAD00001010000

McGill EMC Release 4 for assay "H3K27ac"

Dataset EGAD00001001298

McGill EMC Release 4 for assay "H3K9me3"

Dataset EGAD00001001299

McGill EMC Release 4 for assay "H3K4me1"

Dataset EGAD00001001296

McGill EMC Release 4 for assay "H3K36me3"

Dataset EGAD00001001295

McGill EMC Release 4 in tissue "kidney"

Dataset EGAD00001001287

McGill EMC Release 4 for assay "H3K4me3"

Dataset EGAD00001001297

McGill EMC Release 4 for assay "H3K27me3"

Dataset EGAD00001001294

Bulk RNA-seq of ATCWGS42 PDX models

This dataset contains bulk RNA-seq dataset for ATCWGS42 PDX models

Dataset EGAD50000002145

snRNA-seq of two samples of ATCWGS42

This dataset contains snRNA-seq data of two samples of ATCWGS42

Dataset EGAD50000002146

Single-cell RNA-Seq of human lymphoma reveals malignant B cell diversity and patterns of T cell immune checkpoint co-expression

Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

Study phs001378

Whole exome sequencing of ETV::RUNX1 positive acute lymphoblastic leukemia

This dataset contains whole exome sequencing of ETV::RUNX1 positive acute lymphoblastic leukemia. Germline and leukemia samples were sequenced in pairs. A total of 94 samples were sequenced and reads were aligned to hg19 genome reference. Aligned bam files are provided in this data set.

Dataset EGAD50000001184

Exome Sequencing of Spanish Patients with rare genetic diseases.

Whole Exome sequencing of a set of Spanish patients suffering rare genetic diseases. The set consists of 3 patients, two were diagnosed with Aniridia (ANI-0006 and ANI-0023) and another one was diagnosed with Retinitis Pigmentosa (RP-0247).

Dataset EGAD00001005498

Baseline and progression dataset

RNAseq FASTq files from 44 pre-treatment (Ven-Obi or Clb-Obi) and 44 paired, post-treatment relapsed CD19+ B cells.

Dataset EGAD00001009419

Digital spatial transcriptomic

Nanostring DSP spatial profiles of 8 patients whose antral sections contained histologically normal, IM, GC, lymphoid aggregates, and stromal regions, representing 480 regions of interest (ROIs) and 76 CD45-segmented areas of illumination (AOIs).

Dataset EGAD00001010174

PCa RNASeq data

RNASeq data from paired malignant/benign prostate tissues

Dataset EGAD00001005931

Different malignant tumor samples including lung cancer, colon cancer and breast cancer.

Genomic DNA was purified from tumor cells and normal cells in cancer patients; We sequenced those genomic DNAs using 10X Genomics sequencing technologies, and analyzed genomic structural variations.

Study JGAS000360

The immunopeptidome landscape associated with T cell infiltration, inflammation and immune-editing in lung cancer

WES sequencing of multiple regions per tumor from 8 lung cancer patients (LUSC, LCNEC and LUAD) and adjacent healthy lung tissue for each patient.

Dataset EGAD00001008950

Whole-Exome Sequences Algerian Imazighen and non-Imazighen

Dataset with 150 whole-exome sequences from Algerian Amazigh (Chaoui and Mozabite) and non-Amazgih saples.

Dataset EGAD00001010846

Gabriella Miller Kids First Pediatric Research Program in Enchondromatoses and Related Malignant Tumors

Chondrosarcoma is a malignant tumor that originates from cartilaginous cells. It is the third most common primary malignancy of bone after myeloma and osteosarcoma. It accounts for about 20% of bone tumors and is diagnosed in approximately 600 patients each year in the United States. Up to 40% of the chondrosarcomas arise from an enchondroma. Enchondromas are benign, intramedullary cartilaginous tumors of bone. They can be solitary or multiple and are present in >3% of the population. Enchondromatosis refers to a group of diseases characterized by multiple enchondromas including metachondromatosis (MC), Ollier disease (OD), and Maffucci syndrome (MS) among others. All have skeletal abnormalities with or without associated vascular anomalies that can cause severe limb deformities during early childhood. The risk for chondrosarcoma is up to 30% in OD and MS. Currently, the only treatment for patients with these disorders is surgical; there is no effective pharmacologic therapy. The molecular bases of these two conditions is not well understood.

Study phs001987

An Ultrasensitive Method for Detection of Cell-Free RNA

Our study describes the development of a novel method for cell free RNA (cfRNA) analysis called RARE-Seq (Random priming & Affinity capture of cell-free RNA fragments for Enrichment analysis by Sequencing). We find RARE-Seq improves the limit of detection for tumor-naïve cancer detection while maintaining high specificity. We explore the potential utility of RARE-Seq in diverse clinical applications, including non-invasive ctRNA genotyping, treatment resistance monitoring, and molecular characterization of non-malignant conditions.

Study phs004091

RNAseq profiling of pediatric osteosarcoma

Primary pediatric osteosarcoma samples were collected and profiled using RNAseq. When possible, germline and tumor samples were collected. For some patients, multiple tumor tissues were collected and sequenced. Some of the samples were used to derive PDTX models, which were also profiled with RNAseq. Paired end sequencing was performed on Illumina HiSeq instruments and FASTQ files reported.

Dataset EGAD00001004538

H3K27ac ChIP-seq in Insulinomas

H3K27ac ChIP-seq datasets in human insulinoma samples

Dataset EGAD50000000461

WGS_TALL_t_14_16_translocation

WGS data for patients with t(14;16) translocated T-ALL.

Dataset EGAD50000001782

Anaplastic_Meningioma_WGS_X10

Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

Study EGAS00001000859

Cell-free DNA fragmentation patterns and personalized sequencing reveal circulating tumor DNA in urine and plasma of glioma patients

Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy as levels in body fluids are low. We determined the glioma-derived DNA fractions in tumor biopsies, in cerebrospinal fluid (CSF), plasma and urine samples, using deep sequencing of personalized capture panels. By sequencing cfDNA across thousands of mutations identified individually in each patient’s matched tumor we detected tumor-derived DNA in plasma (10/12) and urine samples (8/11). The median tumor fraction was 6.4x10-3 in CSF, 3.1x10-5 in plasma and 4.7x10-5 in urine. We identified a shift in the size distribution for mutant cfDNA fragments in these body fluids. Next, we analyzed cfDNA fragment sizes with paired-end shallow whole genome sequencing (WGS) in urine samples from 35 patients with gliomas, 8 individuals with non-malignant brain disorders, and 26 controls (n=69 individuals, 96 samples). cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (t-test, p=1.7x10-2) and compared to urine of controls (t-test, p=5.2x10-9). The proportion of DNA fragments <60 bp was higher in glioma patients urine and could be used for classification (AUC=0.93). Machine learning models integrating fragment lengths could identify urine samples from glioma patients (AUC=0.97 in cross-validation).

Study EGAS00001004355

Bulk RNA-seq osteosarcoma

We profiled 23 patient osteosarcoma tumor samples by bulk RNA-seq. The raw fastqs are provided.

Dataset EGAD00001011371

Linking genes, genomic instability and molecular subgroups in medulloblastoma

Brain tumors are the second most common pediatric cancer and carry the highest mortality rates in this age group. Medulloblastoma is the most frequent malignant brain tumor of childhood. Recent studies indicate that medulloblastoma comprises at least four sub-entities (SHH-signaling, WNT-signaling, Group-C, Group-D) that differ in molecular alterations, cell of origin, clinicopathological features and outcome. Further characterization of the entire spectrum of genomic alterations underlying the formation of these distinct groups is urgently needed to identify diagnostic and prognostic biomarkers for clinical management and uncover novel therapeutic targets.

Study EGAS00001000085

Clones derived from early passage tumoroids of colorectal cancer

We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

Dataset EGAD50000000152

Genomic characterization of CNA-quiet oral cancer

Low-coverage whole genome sequencing and targeted (30 gene panel) deep sequencing of oral cancer. Note that the targeted deep sequencing is not actually amplicon sequencing but hybrid capture sequencing, which was not available as on option.

Dataset EGAD50000000790

16452 results for "sec+and+unspecified+malignant+neoplasm"

in 19.60 milliseconds.