Search Results - EGA European Genome-phenome Archive

Genomic analysis of patient-derived xenograft models reveals intratumor-heterogeneity in endometrial cancer and can predict tumor growth inhibition with talazoparib

Background: Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprised of four molecular subtypes with differing etiology, prognoses, and response to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. Pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. Methods: Here, we report whole exome or whole genome sequencing of 11 PDX models and the matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. Results: PDX models were successfully generated with similar histomorphology from all four molecular subtypes of EC and uterine carcinosarcomas. We also observed a wide range of inter-tumor and intra-tumor heterogeneity across different PDX lineages, however one arm of most PDX models recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease, however all lacked the HR deficiency genomic signature. Conclusions: EC PDX models represent the four molecular subtypes of disease and can capture intra-tumoral heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi, however, deeper and more durable responses will likely require combination of PARPi with other agents.

Study EGAS00001004666

Characterizing the Role of the Immune Microenvironment in Multiple Myeloma Progression at a Single Cell Level

The plasma cell disease multiple myeloma (MM) is highly dependent on its bone marrow microenvironment (BMME). Early alterations within the bone marrow microenvironment that contribute to the progression of multiple myeloma (MM) from its precursor stages could hold the key to identifying novel therapeutic approaches, yet the intrinsic variability in cellular populations between patients together with differences in sample processing and analysis methods have made it difficult to identify consistent changes between datasets. Here, we used single-cell RNA sequencing of BM cells from precursor stages, monoclonal gammopathy of unknown significance (MGUS), smoldering MM (SMM) and newly diagnosed MM and analyzed our data in combination with a previously published dataset that used a similar patient population and sample processing. Despite vast interpatient heterogeneity, some alterations were seen consistently in both datasets. We identified changes in immune cell populations as disease progressed that were characterized by a substantial decrease in memory and naïve CD4 T cells and an increase in CD8+ effector T cells and T-regulatory cells. These alterations were further accompanied by an enrichment of non-clonal memory B cells and an increase of CD14 and CD16 monocytes in MM compared to its precursor stages. These results provide crucial information of the immune changes associated with the progression to clinical MM and can help to develop immune based strategies for patient stratification and early therapeutic intervention. 

Study phs002756

MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the Mothers and Infants LinKed for Healthy Growth Study (MILk Study), a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject PRJNA1019702.

Study phs003408

Massively parallel nanowell-based single-cell gene expression profiling

Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5184-nanowell-containing microchip to capture ~1300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

Study EGAS00001002320

Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia

Relapse of acute lymphoblastic leukemia (ALL) remains a leading cause of childhood death. Prior studies have shown clonal mutations at relapse often arise from relapse-fated subclones that exist at diagnosis. However, the genomic landscape, evolutionary trajectories and mutational mechanisms driving relapse are incompletely understood. In an analysis of 92 cases of relapsed childhood ALL, incorporating multimodal DNA and RNA sequencing, deep digital mutational tracking and xenografting to formally define clonal structure, we identify 50 significant targets of mutation with distinct patterns of mutational acquisition or enrichment. CREBBP, NOTCH1, and Ras signaling mutations rose from diagnosis subclones, whereas variants in NCOR2, USH2A and NT5C2 were exclusively observed at relapse. Evolutionary modeling and xenografting demonstrated that relapse-fated clones were minor (50%), major (27%) or multiclonal (18%) at diagnosis. Putative second leukemias, including those with lineage shift, were shown to most commonly represent relapse from an ancestral clone rather than a truly independent second primary leukemia. A subset of leukemias prone to repeated relapse exhibited hypermutation driven by at least three distinct mutational processes, resulting in heightened neoepitope burden and potential vulnerability to immunotherapy. Finally, relapse-driving sequence mutations were detected prior to relapse using deep digital PCR at levels comparable to orthogonal approaches to monitor levels of measurable residual disease. These results provide a genomic framework to anticipate and circumvent relapse by earlier detection and targeting of relapse-fated clones.

Study EGAS00001003975

DNA hypermethylation and differential gene expression associated with Klinefelter syndrome

The molecular basis for the phenotypic traits and morbidity in Klinefelter syndrome (KS) are not clarified. As DNA methylation affect gene expression and thereby play a role in disease susceptibility, we performed genome-wide DNA methylation profiling of leucocytes from peripheral blood samples from 67 KS patients, 67 male controls and 33 female controls, in addition to genome-wide RNA-sequencing profiling in a subset of 9 KS patients, 9 control males and 13 female controls. Characterization of the methylome as well as the transcriptome of both coding and non-coding genes identified a unique epigenetic and genetic landscape of both autosomal chromosomes as well as the X chromosome in KS. A subset of genes show significant correlation between methylation values and expression values. Gene set enrichment analysis of differentially methylated positions yielded terms associated with well-known comorbidities seen in KS. In addition, differentially expressed genes revealed enrichment for genes involved in the immune system, wnt-signaling pathway and neuron development. Based on our data we point towards many new candidate genes (AKAP17A, AMOT, APOB, DACT1, DDX58, DOCK7, EIF2S3, FIGNL1, G3BP1, HENMT1, HERC5, IFI44, IFI44L, IFIT1, IFIT3, ISG15, KANK1, LGALS1, NSD1, PEX10, PLSCR1, RSAD2, SHROOM2, SLC25A6, SPEG, SPON2, TXLNG), which may be implicated in the phenotype and further point towards non-coding genes (RP13-216E22.4, RP13-36G14.4, G087825, G088512), which may be involved in X chromosome inactivation in KS and in the regulation of escape genes.

Study EGAS00001002797

Cisplatin increases sensitivity to FGFR inhibition in patient-derived xenograft models of lung squamous cell carcinoma

Lung squamous cell carcinoma (SqCC) is a molecularly complex and genomically unstable disease. No targeted therapy is currently approved for lung SqCC, although potential oncogenic drivers of SqCC have been identified, including amplification of the fibroblast growth factor receptor 1 (FGFR1). Reports from a recently completed clinical trial indicate low response rates in patients treated with FGFR tyrosine kinase inhibitors, suggesting inadequacy of FGFR1 amplification as a biomarker of response, or the need for combination treatment. We aimed to develop accurate models of lung SqCC and determine improved targeted therapies for these tumors. We show that detection of FGFR1 mRNA by RNA in situ hybridisation is a better predictor of response to FGFR inhibition than FGFR1 gene amplification using clinically relevant patient-derived xenograft (PDX) models of lung SqCC. FGFR1-overexpressing tumors were observed in all histological subtypes of non-small cell lung cancers (NSCLC) as assessed on a tissue microarray, indicating a broader range of tumors that may respond to FGFR inhibitors. In FGFR1-overexpressing PDX tumors, we observed increased differentiation and reduced proliferation following FGFR inhibition. Combination therapy with cisplatin was able to increase tumor cell death, and dramatically prolonged animal survival compared to single agent treatment. Our data suggest that FGFR tyrosine kinase inhibitors can benefit NSCLC patients with FGFR1-overexpressing tumors and provides a rationale for clinical trials combining cisplatin with FGFR inhibitors.

Study EGAS00001002423

Whole Tumor spatial heterogeneity in metastatic melanoma

Heterogeneous inter-tumoral responses, sustained periods of apparent clinical benefit despite lack of objective response to various therapies, and even spontaneous remission are well known within a subpopulation of advanced melanoma patients. The molecular and cellular dynamics facilitating long-term survival remain poorly defined, particularly in the current era ofexposure to multiple potentially active therapies. We studied an exceptional case of long-term survival in a patient with non-responding metastatic melanoma in order to characterize the clonal and microenvironmental factors.We performed immunogenomic analysis of 3 metachronous tumors, and of 67 intratumor sub-regions of one metastatic lesion, usingwhole exome sequencing, RNA-sequencing, immunohistochemistry, and T cell receptor sequencing. Longitudinal analysesidentified mutations in severalknownresistance genes affecting distinctmetastases. Intra-tumoral immune signatures revealed spatially-distinct pockets of immune activation and suppression throughout the metastasis. A specific T cell VBeta CDR3 rearrangement was identified as both dominant and recurrent not only across multiple spatial points within a single tumor mass, but also across metachronous tumors spanning the patient’s disease course. Immunophenotyping of this T cell population with single-cell sequencingsuggestedrepeatedT-cell priming events leading to the persistence of both activated and exhausted T cells bearing this same TCR-Beta at any given time.Our findings highlight genomic and immune heterogeneityin metastatic disease, extending to the intra-tumoral leveland provide a rationale for integrative spatiotemporal analysis of metastatic lesions in the context of immune checkpoint blockade.

Study EGAS00001003292

Characterization of HCV-specific CD4 T cells during DAA-Therapy

Background: Chronic HCV-infection is characterized by a severe impairment of HCV-specific CD4 T cell help that is driven by chronic antigen stimulation. We aimed to study the fate of HCV-specific CD4 T cells after viral elimination. Methods: HCV-specific CD4 T cell responses were longitudinally analyzed using MHC class II tetramer-technology, multicolor flow cytometry and RNA sequencing in a cohort of chronically HCV-infected patients undergoing therapy with direct-acting antivirals. In addition, HCV-specific neutralizing antibodies and CXCL13 levels were analyzed. Results: We observed that the frequency of HCV-specific CD4 T cells increased within two weeks after initiation of DAA therapy. Multicolor flow cytometry revealed a downregulation of exhaustion and activation markers and an upregulation of memory-associated markers. While cells with a Th1 phenotype were the predominant subset at baseline, cells with phenotypic and transcriptional characteristics of follicular T helper cells increasingly shaped the circulating HCV-specific CD4 T cell repertoire, suggesting antigen-independent survival of this subset. These changes were accompanied by a decline of HCV-specific neutralizing antibodies and the germinal center activity. Conclusion: We identified a population of HCV-specific CD4 T cells with a follicular T helper cell signature that is maintained after therapy-induced elimination of persistent infection and may constitute an important target population for vaccination efforts to prevent re-infection and immunotherapeutic approaches for persistent viral infections.

Study EGAS00001003950

Gene Expression in an African American Schizophrenia Dataset

Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain largely undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using RNAseq on lymphoblastoid cell lines from schizophrenia cases and controls of African American ancestry. Genes related to immune processes were enriched in the genes differentially expressed in the schizophrenia cases. Approximately half of the differentially expressed genes in this African American dataset were also differentially expressed by affection status in our previously studied European ancestry dataset (PMID: 28418402).

Study phs002842

Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers: multi-timepoint exome sequencing of a single patient's disease

This dataset is a time-series of EGFR-mutant NSCLC clinical specimens from an individual patient profiled using tumor-based whole exome sequencing and the data is in BAM format. DNA was extracted from FFPE for primary tumor and frozen tumor tissue samples and matched non-tumor tissue using the Qiagen Allprep DNA/RNA Mini Kit. The library preparation protocol was based on the Agilent SureSelect Library Prep and Capture System. DNA was resuspended in a low TE buffer and sheared (Duty Cycle 5%; Intensity 175; Cycles/Burst: 200; Time: 300s, Corvaris S2 Utrasonicator). Bar-coded exome libraries were prepared using the Agilent Sure Select V5 library kit per manfucaturer’s specifications. The libraries were run on the HiSeq2500. Raw paired end reads (100bp) in FastQ format generated by the Illumina pipeline were aligned to the full hg19 genomic assembly obtained from USCS, gencode 14, using bwa version 0.7.12. Picard tools version 1.117 was used to sort, remove duplicate reads and generate QC statistics. Tumor DNA was sequenced to median depth of 303X (range 114.39-383.41) and the matched germline DNA to average depth of 231.65.

Dataset EGAD00001003769

Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma WES

Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

Dataset EGAD00001014789

Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyoma WES

Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

Dataset EGAD00001014787

National Cancer Institute Clinical and Laboratory Analysis of Familial Cancer

The purpose of this study is to continue the analysis begun on 09C0079 which was focused on identification of the genetic mutation associated with a new gastric polyposis syndrome, Gastric Adenocarcinoma and Proximal Polyposis of the Stomach (GAPPS). GAPPS, first described in 2012, is an autosomal dominant gastric polyposis syndrome that confers a substantial risk for gastric adenocarcinoma. The GAPPS phenotype consists of a carpeting of greater than 100 fundic gland polyps (FGPs) in the oxyntic mucosa of the gastric body and fundus, with antral sparing with some FGPs displaying high-grade dysplasia. This is in contrast to sporadic FGPs that are benign, most often are not associated with high-grade dysplasia though low-grade dysplasia has been reported, and are fewer in number. Gastric FGPs have been found to be associated with Familial Adenomatous Polyposis (FAP) and attenuated FAP, which is an autosomal dominant condition associated with germ line mutations in APC which confers a phenotype consisting of multiple (>100) adenomatous polyps in the colon and rectum developing after the first decade of life. FGPs are reported to occur in 12-84% of patients with FAP, whereas sporadic FGPs are identified in ~5% of patients undergoing upper gastrointestinal endoscopy. Gastric adenocarcinoma arising from FGPs in individuals with FAP have been reported. Other manifestations of FAP and AFAP include polyps in the upper gastrointestinal tract, congenital hypertrophy of retinal pigment epithelium, osteomas and epidermoid cysts, supernumerary teeth, desmoid formation, and other malignancies such as thyroid, small bowel cancer, hepatoblastoma, and medulloblastoma. Thus far there are no reports in GAPPS of polyposis arising in the esophagus, gastric antrum, pylorus, small intestine, or colon.

Study phs001935

Evolutionary dynamics of residual disease in human glioblastoma

Glioblastoma is the most common and aggressive adult brain malignancy against which conventional surgery and chemoradiation provide limited benefit. Even when a good treatment response is obtained, recurrence inevitably occurs either locally (c.80%) or distally (c.20%), driven by cancer clones that are often genomically distinct from those in the primary tumour. Glioblastoma cells display a characteristic infiltrative phenotype, invading the surrounding tissue and often spreading across the whole brain. We hypothesised that cancer cells responsible for relapse reside in two compartments of residual disease that are left behind after treatment: the infiltrated normal brain parenchyma, and the sub-ventricular zone (SVZ). In this model, residual disease subclones diverge early during glioblastoma evolution, may remain dormant in the normal parenchyma and are responsible for recurrence. To test our hypothesis, we performed whole-exome sequencing of 69 multi- region samples collected using fluorescence-guided resection from 11 patients, including the infiltrating tumour margin (M) and the SVZ for each patient, as well as matched blood. We used a phylogenomic approach to dissect the spatio-temporal evolution of each tumour and unveil the relation between residual disease and the main tumour mass. We also analysed two patients with paired primary-recurrence samples with matched residual disease. Our results suggest that the infiltrative phenotype is an early evolutionary trait of glioblastoma, giving rise to the tumour mass detected at surgery. After treatment, the same infiltrative clone may seed the growth of a recurrent tumour, thus representing the ‘missing link’ between the primary tumour and recurrent disease. These results are consistent with recognised clinical phenotypic behaviour and suggest that more specific therapeutic targeting of cells in the infiltrated brain parenchyma may improve patient’s outcome.

Study EGAS00001003043

1 Intratumoral genetic heterogeneity and clonal evolution following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal tumors.

Purpose: Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment forpatients with locally advanced rectal cancer. However, little is known about the effect of nCRT in the mutational landscape and intratumoral genetic heterogeneity (ITGH) of rectal tumors. Moreover, response to nCRT vary substantially among patients and the genetic determinants of treatment response are not fully understood. Here, we sought to determine the impact of nCRT in the mutational landscape and ITGH of rectal tumors and to identify putative drivers of therapeutic resistance. Patients and Methods: We analyzed whole-exome sequencing (WES) and clinical data from 79 primary non-treated rectal cancers obtained from The Cancer Genome Atlas (TCGA). We also compared the mutational landscape of a matched set of peripheral blood cells, irradiated tumor-adjacent colonic mucosa and pre and post-treatment tumor samples to determine the iatrogenic effects of nCRT and its impact in tissue genetic heterogeneity. Finally, we performed WES of 7 matched pre and post-treatment tumor samples to examine how nCRT affects the clonal architecture of rectal tumors. Results: We show that rectal tumors exhibit remarkable ITGH, which increases with disease progression. We also show that nCRT, per se, does not introduce novel somatic mutations, nor alters the clonal architecture of the irradiated colonic mucosa. Instead, we show that it acts as a potent selective pressure, favoring the expansion of tumor cell subpopulations more prone to resist therapy and increasing ITGH in the residual tumor. Conclusion: Our results reveal the highly heterogeneous and dynamic clonal architecture of rectal tumors undergoing nCRT. Our results also uncover putative genetic determinants of response to nCRT and a possible role for ITGH in predicting treatment outcome.

Study EGAS00001003250

Projects

Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, the EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags CANDLE | CANDLE project aims to conceptualise and advance the development of National Cancer Data Nodes (NCDNs) in European countries. These NCDNs will boost the reuse of cancer data for research, innovation and policy making, in order to improve diagnostics and treatment for cancer patients, as well as prevention and early detection. 2025-2028 Cancer Horizon Europe DOCUMENTATION EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS SenSec | This project aims to establish a mechanism for orchestrating secure access to sensitive data hosted by the EGA, whether in Central EGA or any Federated Node, from Galaxy, a popular open-source, community-driven VRE (Virtual Research Environment) for bioinformatics analysis. Building on a previous prototype that enabled Galaxy users within Trusted Research Environments (TREs) to decrypt sensitive data for workflow execution without sharing private encryption keys, SenSec will expand this prototype into a comprehensive solution for secure data analysis in Galaxy, facilitating encrypted data access and transfer from FEGA/EGA repositories to designated TREs. 2025-2026 Genomic and health data; trusted research environment ELIXIR ACCESS DATA ANALYSIS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE SYNTHIA | The aim of SYNTHIA is to deliver validated, reliable tools and methods for synthetic data generation (SDG). The tools will cover multiple data types including lab results, clinical notes, genomics, imaging and m-health data. SYNTHIA also hopes to make possible the generation of longitudinal data. 2024-2029 Genomic and health data; multi-omics; AI solutions Innovative Health Initiative (IHI) DATA ANALYSIS DATA MANAGEMENT INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; disease prevention; AI/ML solutions Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE Completed projects Project Duration Domain Funder Tags EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarato | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundacio La Marato de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research ? informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

Documentation about/projects-and-funders/projects

Identification of Recurrent NAB2-STAT6 Gene Fusions in Solitary Fibrous Tumor by Integrative Sequencing

Transcriptome sequencing of solitary fibrous tumors / hemangiopericytomas from a variety of anatomic sites revealed recurrent gene fusions between two genes, NAB2 and STAT6. All SFTs examined exhibited an in-frame fusion transcript encoding a fusion protein containing the EGR1 interaction domain of NAB2 with the transcriptional activation domain of STAT6. Functional testing of the fusion alleles confirmed the conversion of the wt NAB2 repressor into a transcriptional activator. A range of individual fusion junctions can be detected by next-generation sequencing acro the sample set, highlighting the suitability of this method in the diagnostic characterization of SFTs. This study indentified the pathognomonic alteration in solitary fibrous tumors and illuminates a pathway towards targeted therapeutics for this cancer.

Study phs000567

Whole-Exome Sequencing and Targeted DNA Sequencing of Matched Ocular Melanocytosis and Uveal Melanoma

Ocular melanocytosis is the most important predisposing condition for the eye cancer uveal melanoma (UM). Here we used whole-exome and deep targeted sequencing to identify for the first time a clonal Gq pathway mutation in ocular melanocytosis, which gave rise to UM. Additionally, we elucidated the order in which canonical genetic aberrations were acquired during tumor evolution. These findings provide a mechanistic explanation for the well-known clinical association of ocular melanocytosis with UM, and they provide new insights into UM tumor evolution. Reprinted from: Durante MA, Field MG, Sanchez MI, Covington KR, Decatur CL, Dubovy SR, Harbour JW. Genomic evolution of uveal melanoma arising in ocular melanocytosis, with permission from Cold Spring Harbor Molecular Case Studies.

Study phs001835

Development of Novel Chondrosarcoma Organoid Models for Drug Discovery

Chondrosarcoma is a rare and aggressive malignant bone tumor characterized by resistance to conventional chemotherapy and radiotherapy. Its pathogenesis remains poorly understood, although recurrent mutations such as IDH1 have been implicated in tumor development. We treated patients with chondrosarcoma at the Osaka International Cancer Institute and established two organoid cultures from resected tumor specimens using a modified air-liquid interface method. After serial passaging, the organoids were successfully xenografted into NOD-scid IL2Rgnull (NSG) mice. The established organoids retained key histological features and genetic characteristics of the original tumors. These organoid models provide a novel and reliable platform for studying the biology of chondrosarcoma and may facilitate the development of effective therapeutic strategies for this treatment-resistant tumor.

Study JGAS000834

Genomic subtypes and cellular phenotypes of high-grade endometrial carcinoma

Based on the mechanism of carcinogenesis, endometrial cancer (EC) is classified into two major types, Type I and Type II. Type I EC is characterized by G1/G2 histology, accounting for about 80% of all uterine carcinomas. On the other hand, Type II EC, which often develops after menopause, is estrogen-independent and consists of serous and clear cell carcinomas. G3 EC is often classified as a Type II EC, but the pathogenesis is thought to be a mixture of estrogen-dependent and estrogen-independent carcinogenesis. We will conduct an integrative genomic analysis to clarify the pathogenesis of Type II EC and redefine its classification by combining genomic status with cell phenotypes reflected in gene expression profiles.

Study JGAS000753

Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___DNA_sequencing

This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

Study EGAS00001003517

Targeting PTPRK-RSPO3 colon tumours promotesdifferentiation and loss of stem-cell function

Colorectal cancer remains a major unmet medical need, promptinglarge-scale genomics efforts in the field to identify moleculardrivers for which targeted therapies might be developed. Wepreviously reported the identification of recurrent translocationsin R-spondin proteins present in a subset of colorectal tumours.Here we show that targeting RSPO3 in PTPRK-RSPO3-fusion positivehuman tumour xenografts inhibits tumour growth andpromotes differentiation. Notably, genes expressed in the stem-cellcompartment of the intestine were among those most sensitive toanti-RSPO3 treatment. This observation, combined with functionalassays, suggests that a stem-cell compartment drives PTPRK-RSPO3colorectal tumour growth and indicates that the therapeutictargeting of stem-cell properties within tumours may be a clinicallyrelevant approach for the treatment of colorectal tumors.

Study EGAS00001001462

Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___single_cell_RNA_sequencing

This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

Study EGAS00001003519

A PROSTATE TUMORGRAFT PANEL TO ACCELERATE PRECISION MEDICINE

The management of advanced prostate cancer (PCa) has strongly evolved in the last decade with the introduction of the next generation of androgen receptor pathway inhibitors which have considerably improved patient outcomes. Most recently, the investigation of genomic landscape has provided targetable molecular alterations such as homologous gene DNA repair defects correlated with response to PARP inhibitors. Despite these significant advances, while localized PCa is generally associated with favorable outcome, metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

Study EGAS00001007033

9337 results for "cancer rna-seq"

in 49.02 milliseconds.