14977 results for "cancer studies using rna-seq"

in 35.17 milliseconds.

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002998

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003014

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003022

• Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003020

• Genome and transcriptome sequence data from a presumed metastatic lung cancer patient

  Genome and transcriptome sequence data from a presumed metastatic lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003079

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003617

• Whole_Exome_PC9_and_A375

  Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday.

  Study EGAS00001002493

• arrayCGH for copy number profiling on tumor DNA from pediatric cancer tissue samples

  This dataset contains arrayCGH (HumanCytoSNP 850k and HumanCytoSNP v12.1) data from tumor DNA samples of various pediatric cancer entities. Files are provided in IDAT format and as text files processed with GenomeStudio 2.0.

  Study EGAS00001005197

• Genome and transcriptome sequence data from a metastatic cancer to the breast patient

  Genome and transcriptome sequence data from a metastatic cancer to the breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010959

• Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient

  Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010980

• Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient

  Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011037

• Genome and transcriptome sequence data from a non-small cell lung cancer patient

  Genome and transcriptome sequence data from a non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004672

• Genome and transcriptome sequence data from a metastatic transverse colon cancer patient

  Genome and transcriptome sequence data from a metastatic transverse colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004691

• Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002606

• Genome and transcriptome sequence data from a metastatic gastric cancer patient

  Genome and transcriptome sequence data from a metastatic gastric cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004904

• Hereditary Cancer Predisposition Syndromes and Uveal Melanoma

  Uveal melanoma (UM) is a subtype of melanoma characterized by the strong contribution of genetic rather than environmental factors in the pathogenesis of the disease, making it an ideal model disease to study the genetic basis of cancer. The long-term goal of our laboratory is to determine the genes and mechanisms responsible for hereditary cancer predisposition associated with UM. BAP1 has been identified as a candidate gene with definitive association with predisposition to UM. However, pathogenic variants in BAP1 are detected in only a small subset of UM patients even those with strong personal and family history of cancer suggesting the existence of other candidate genes. The goal of this project is to identify novel candidate genes contributing to hereditary predisposition to UM in patients with no detectable germline pathogenic variant in BAP1.

  Study phs001943

• WGS of liver cancer in the Japanese population

  Hepatocellular carcinoma (HCC) is the third leading cancer-related cause of death and the seventh most common form of cancer worldwide, with an estimate of more than 700,000 new cases each year. The most established risk factors of HCC are chronic HBV and HCV infection. HBV infection is responsible for over 50% of the worldwide attributable risk of HCC, especially in East Asia and Africa, while in Japan and several Western countries HCV infection is the most common risk factor for HCC. To gain insights into the molecular alterations of virus-associated HCC, we performed whole genome sequencing (WGS) of 321 HCC tumors from 159 patients. This work was performed as a part of the ICGC (International Cancer Genome Consortium) project.

  Study EGAS00001000678

• The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

  Reactivation of telomerase reverse transcriptase (TERT) expression enables cells to overcome replicative senescence and escape apoptosis, fundamental steps in the initiation of human cancer. Multiple cancer types, including up to 83% of glioblastomas (GBM), harbor highly recurrent TERT promoter mutations of unknown function but specific to two nucleotide positions. We identify the functional consequence of these mutations in GBM to be recruitment of the multimeric GABP transcription factor specifically to the mutant promoter. Allelic recruitment of GABP is consistently observed across four cancer types, highlighting a shared mechanism underlying TERT reactivation. Tandem flanking native ETS motifs critically cooperate with these mutations to activate TERT, likely by facilitating GABP heterotetramer binding. GABP thus directly links TERT promoter mutations to aberrant expression in multiple cancers.

  Study EGAS00001001242

• Evolutionary Origins of Recurrent Pancreatic Cancer

  Surgery is the only curative option for patients with Stage I/II pancreatic cancer, nonetheless most patients will recur after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer we performed whole exome or targeted sequencing of 10 resected primary cancers and their matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease develops from a monophyletic or polyphyletic origin, and this distinction has potential clinical relevance. In all patients, treatment induced genetic bottlenecks led to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In one patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings strongly advocate for routine post-treatment sampling in the management of recurrent pancreatic cancer.

  Study EGAS00001004097

• Myocardial Infarction Genetics Exome Sequencing Consortium: Precocious Coronary Artery Disease Study

  The Precocious Coronary Artery Disease (PROCARDIS) study is an international, multicenter case-control study aimed at discovering the genetic contributors to premature coronary artery disease. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000883

• WES

  Exome Sequencing. 3 ug of genomic DNA from each lymph node sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001005424

• DNA repair in BLM deficient hiPSCs

  We are aiming to investigate repair of a double strand break (DSB) within the genome in the presence and absence of the BLOOM protein. Zinc Finger Nucleases introduce DSBs at specified loci within the genome. Using sequencing we will assess the size of the deletion following repair. Protocol 1. Transfect normal and BLOOM deficient human iPS cells with ZFNs, using AMXA 2. Harvest cells after 5 days 3. Perform column extraction of DNA 4. PCR-amplify the ZFN region 5. Sequence and analyse repair of the DSB This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000819

• Ancient nuclear genomes enable repatriation of Indigenous human remains

  For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.

  Study EGAS00001003359

• Molecular profiling of DLBCL patients treated in the HOVON84 trial

  Using a comprehensive NGS assay for simultaneous screening of mutations, copy number alterations, and translocations, 5 biology-based risk profiles could be reproduced in a Dutch DLBCL population and validated for outcome prediction. This approach will enable application as a diagnostic tool to select DLBCL patients for risk adapted treatment and help to develop biomarker-driven clinical trials for personalized medicine.

  Study EGAS00001003949

• Whole-exome sequencing of intravascular large B-Cell lymphoma

  Intravascular large B-cell lymphoma (IVLBCL) is a unique form of diffuse large B-cell lymphoma (DLBCL) characterized by extranodal cell growth especially in small vessels without systemic lymphadenopathy. The limitation in obtaining sufficient tumor materials hampers understanding the molecular pathogenesis of IVLBCL. We performed whole-exome sequencing of IVLBCL using plasma-derived cell-free DNA (cfDNA) and patient-derived xenograft (PDX) samples.

  Study EGAS00001003970

• Indonesian sea-nomads genomic history

  This study observes the origin of the last living sea nomad group in Indonesia using genome-wide SNP data, and tracks their dispersal in the archipelago. This study involves new samples on not only the sea nomad group, but also surrounding populations where the sea nomad settled. We revealed the scenario of their origin and unique admixture patterns during their dispersal and re-settlement.

  Study EGAS00001002246

• Misoprostol-induced high fever GWAS study

  Genome-wide association (GWAS) meta-analysis study of misoprostol-induced fever was conducted on two South American cohorts (Argentina and Ecuador). DNA was collected from blood of women who were screened for postpartum haemorrhage (PPH) and administered misoprostol were included in the study. Genotypes were acquired from the Global Screening Array (Illumina). Meta-analysis of these cohorts was completed using METAL software.

  Study EGAS00001005455

• NIHR BioResource Common Disease Patients 2016

  NIHR BioResource Common Disease Patients 2016. The dataset includes 13489 samples from blood donors, they were not screened for any particular disease, and therefore they are representative of the general population. Genomic data includes 845487 snps collected using the UK BioBank V1 Affymetrix array. Phenotypic data includes gender, age, ethnicity and disease. According to our internal quality check there are 81 duplicates in this dataset.

  Study EGAS00001004870

• Human pan-genome analysis

  The reference human genome is still incomplete, and several non-reference sequences have derived from diverse populations. With the available of whole genome sequencing data from multiple individuals, we could construct the pan-genome sequence. Here we provide high quality genome sequencing (~30x coverage) from 185 Han Chinese individuals. All samples were sequenced using Illumina HiSeq X10 sequencer and paired-end 150-bp reads were produced.

  Study EGAS00001003657

• Phenotypic characterization and prognostic impact of CD103+ tissue-resident memory T cells in diffuse large B cell lymphoma

  Tissue-resident memory T (TRM) cells are a population of memory T cells that stably occupy tissues and play a key role in immunosurveillance, having been linked to favorable survival outcomes in various solid tumors. While TRM cells have been identified in lymph nodes, their phenotype and prognostic significance in B-cell non-Hodgkin lymphoma (B-NHL), including diffuse large B-cell lymphoma (DLBCL), remains poorly characterized. The frequency of CD103 expressing T cells in patient samples with DLCBL was quantified by immunofluorescence (IF) staining of tissue biopsies (n=306) and flow cytometry (n=252) of cell disaggregates, and linked with clinical outcome. The phenotype of TRM cells was characterized by spectral flow cytometry (n=10 DLBCL and 2 reactive lymph node (rLN) samples) and single-cell RNA sequencing (scRNAseq) (n=12 aggressive B cell lymphomas and 4 rLN samples). An additional 51 samples from an external dataset were included to verify the single cell transcriptome findings. The flow cytometry and scRNAseq findings in DLBCL were extrapolated to additional B-NHL entities. Through analysis of these datasets we were able to characterize CD103+ TRM-like cells in DLBCL and other B-NHL entities and identified them to represent a prognostically favorable population with an activated/cytotoxic T cell phenotype.

  Study EGAS50000000943

• Genetics and therapeutic responses to TIL therapy of pancreatic cancer PDX models

  Pancreatic cancer is the 7th leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet showed encouraging results in pancreatic cancer possibly owing to a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenografts (PDX) models and to assess if autologous tumor-infiltrating lymphocytes (TILs) would have anti-tumoral activity in pancreatic cancer. Tumor biopsies from 29 patients were subcutaneously transplanted into NOG mice. Tumor growths were confirmed in 11 out of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but since stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than PD-L1 were expressed in pancreatic cancers but PD-L1 was rarely expressed. One of the three tumors that did express PD-L1 was an adenosquamous cancer and another had a mismatch repair deficiency. TILs were expanded from six tumors and were injected into NOG or human interleukin-2 transgenic-NOG (hIL2-NOG) mice carrying PDX tumors. Regression of tumors could be verified in hIL2-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model. In conclusion, PDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers, and to evaluate responses to ACT and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

  Study EGAS00001005596

• ALK inhibitors in the context of ALK-dependent cancer cell lines

  ALK inhibitors in the context of ALK-dependent cancer cell lines

  Dataset EGAD00001000078

• Matched breast cancer fusion gene study

  Matched breast cancer fusion gene study

  Dataset EGAD00001000097

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

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

  Dataset EGAD00001000272

• Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Sequencing data for Australian Ovarian Cancer study submitted 20121116

  Dataset EGAD00001000293

• Sequencing data for Australian Pancreatic Cancer study submitted 20130102

  Sequencing data for Australian Pancreatic Cancer study submitted 20130102

  Dataset EGAD00001000323

• Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  Study EGAS00001007298

• Large scale familial CRC exome sequencing study

  The burden of rare disruptive mutations to the heritable risk of colorectal cancer

  Study EGAS00001001666

• panel data of ALK-positiv non-small cell lung cancer patients

  270 samples with ALK-positiv non-small cell lung cancer, targeted sequencing (198 kb panel size)

  Dataset EGAD00001006297

• TP53 in ovarian cancer panel aligned reads Data Access Committee

  TP53 targeted panel aligned reads consisting of BAM paired end reads from ovarian cancer tumor samples Data Access Committee

  Dataset EGAD00001003119

• Whole_Genome_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008277

• Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Dataset EGAD00001012102

• Base-excision repair pathway shapes 5-methylcytosine deamination signatures in pan-cancer genomes

  Transition of cytosine to thymine in CpG dinucleotides is the most frequent type of mutation in cancer. This increased mutability is commonly attributed to spontaneous deamination of 5-methylcytosine (5mC), which is normally repaired by the base-excision repair (BER) pathway. However, the contribution of 5mC deamination in the increasing diversity of cancer mutational signatures remains poorly explored. Here, we integrate mutational signatures analysis in a large series of tumor whole genomes with lineage-specific epigenomic data to draw a detailed view on 5mC deamination in cancer. We uncover tumor type-specific patterns of 5mC deamination signatures in CpG and non-CpG contexts. We demonstrate that the BER glycosylase MBD4 preferentially binds to open chromatin domains, which correlates with lower mutational burden in these domains. We validate our findings by modelling BER deficiencies in isogenic cell models. Overall, we establish MBD4 as the main actor responsible for 5mC deamination repair in humans.

  Study EGAS50000000536

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - RNAseq

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000977

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - WES

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000976

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty__WG_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003311

• GENOMIC MUTATION LANDSCAPE OF SKIN CANCERS FROM DNA REPAIR-DEFICIENT XERODERMA PIGMENTOSUM PATIENTS

  Xeroderma pigmentosum (XP) is a genetic disorder caused by mutations in genes of the Nucleotide Excision Repair (NER) pathway (groups A-G) or in Translesion Synthesis (TLS) DNA polymerase η (group V). XP is associated with an increased skin cancer risk, reaching, for some groups, several thousand-fold compared to the general population. Here, we analyzed 38 skin cancer genomes from five XP groups. We found that the activity of NER determines heterogeneity of the mutation rates across skin cancer genomes and that transcription-coupled NER extends beyond the gene boundaries reducing the intergenic mutation rate. Mutational profile in XP-V tumors revealed the role of polymerase η in the error-free bypass of (i) rare TpG and TpA DNA lesions, (ii) 3’ nucleotides in pyrimidine dimers, and (iii) TpT photodimers. Our study unravels the genetic basis of skin cancer risk in XP and provides insights into the mechanisms reducing UV-induced mutagenesis in the general population.

  Study EGAS00001006732

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty__Exome_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003313

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty___WG__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003524

• MutWP5__CRUK_Mutographs_of_Cancer__BRCA_Carriers___Exome__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003526

• Somatic_mutation_and_clonal_evolution_normal_breast_tissue_WGS

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development.

  Study EGAS00001002857

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Reduction_Mammoplasty___Exome__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003527

• MutWP5__CRUK_Mutographs_of_Cancer__BRCA_Carriers___WG__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003523

• MutWP5__CRUK_Mutographs_of_Cancer__Cancer_Mastectomy__Exome__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003528

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  Phytocannabinoids Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) have been demonstrated to exhibit anti-cancer activity in preclinical models of brain cancer leading to new clinical trials for adults with glioblastoma. We describe here the first report that has investigated a role for THC and CBD in paediatric brain cancer. Cannabinoids had cytotoxic activity against medulloblastoma and ependymoma cells in vitro, functioning in part through the inhibition of cell cycle progression and the induction of autophagy. Despite these effects in vitro, when tested in orthotopic mouse models of medulloblastoma or ependymoma, no impact on animal survival was observed. Furthermore, cannabinoids neither enhanced nor impaired conventional chemotherapy in a medulloblastoma mouse model. These data show that while THC and CBD do have some effects on medulloblastoma and ependymoma cells, are well tolerated and have minimal adverse effects, they do not appear to elicit any survival benefit in preclinical models of paediatric brain cancer.

  Study EGAS00001004963

• PanCuRx Translational Research Initiative

  The goal of the PanCuRx TRI is to seek solutions to the high fatality rate of pancreatic adenocarcinoma (PDAC), the most common type of pancreatic cancer, by generating new knowledge about the genetics and biology of the disease, mechanisms of how tumours grow and tailored treatment options. PDAC is the fourth leading cause of cancer death in Canada and is expected to become the second-leading cause of cancer death within the next decade. The current five-year survival rate of eight per cent is the lowest of all epithelial cancers. There are major clinical challenges to treating the disease, including the fact that PDAC spreads to other parts of the body early so surgical removal of the tumour benefits few patients, that PDAC has proven relatively resistant to systemic therapies such as chemotherapy and that there has been limited benefit from the use of newer molecular targeted agents. The PanCuRx team has created the world’s first resource of tumour-purified PDAC whole genomes; more than 500 PDAC samples, with combined clinical annotation, have been successfully sequenced and analyzed at the Ontario Institute for Cancer research in Toronto. The resulting clinical genomic resource created from this data has led to multiple new findings that have established a framework to better understand PDAC biology and lays the foundation for new genomic approaches to better understanding the disease. The team also launched a clinical trial called COMPASS (Comprehensive Molecular Characterization of Advanced Ductal Pancreas Adenocarcinoma for Better Treatment Selection: A Prospective Study), which is recruiting patients with advanced PDAC (both locally advanced and metastatic) at The Princess Margaret Cancer Centre (PM) in Toronto. The study uses the molecular results from individual patient tumours to guide selection of better second line treatment on a case-by-case basis. The primary objective of the initial study was to assess the feasibility of collecting tumour materials from patients with advanced PDAC and delivering results within 56 days of biopsy. Having achieved this objective, the trial has expanded to other cancer centres across Canada. Pancreatic cancer is one of the most deadly forms of cancer and outcomes have not improved in four decades. The PanCuRx initiative is providing a better understanding of the disease and actively applying new knowledge to cancer patients through clinical trials. This knowledge will help to improve quality of life and prolong survival for pancreatic cancer patients worldwide.

  Study EGAS00001002543

• CAGE-seq analysis of osteoblast derived from cleidocranial dysplasia human induced pluripotent stem cells

  Non-coding RNAs (ncRNAs) comprise a major portion of transcripts and serve an essential role in biological processes. Although the importance of major transcriptomes in osteogenesis has been extensively studied, the function of ncRNAs in human osteogenesis remains unclear. Previously, we developed hiPSCs from patients with cleidocranial dysplasia (CCD) caused by runt-related transcription factor 2 (RUNX2) haploinsufficiency. To gain insight into ncRNAs in osteogenesis, we surveyed differential ncRNA expression profiling and promoter differences of RUNX2 using patient-specific iPSCs and cap analysis gene expression (CAGE) technology to define the promoter landscape. Revertant iPSCs (Rev1 iPSCs) edited by CRISPR/Cas9 system to harbor mutation-corrected RUNX2 exhibited increased proximal promoter expression of RUNX2, while CCD iPSCs did not. We identified 2271 ncRNA genes with altered expression levels before and after differentiation, 31 of which showed at least 20-fold higher expression in Rev1 iPSCs. Bioinformatic analysis also categorized AC007392.3, LINC00379, RP11-122D10.1, and RP11-90J7.2 as enhancer regulatory regions, and HOXA-AS2, MIR219-2, and RP11-834C11.3 as dyadic regulatory regions of these ncRNAs. In addition, two miRNAs, termed MIR199A2 and MIR152, were found to have high enrichment of osteogenic-related terms. Upon further examination of the role of MIR152 on osteoblast differentiation, we found that MIR152 knockdown induced upregulation of ALP and COL1A1 in Saos-2 cells. Thus, ncRNAs were found to regulate the osteogenic differentiation potentials of hiPSCs that are used for bone regeneration and repair owing to their differentiation potentials. These data allow understanding ncRNA profiles of hiPSCs during osteogenesis.

  Study JGAS000248

• Genetic Analysis of Substance Use Disorder Using the Indiana Biobank Data

  The goal of this study is to identify genes related to substance use disorders. The study participants were selected from the Indiana Biobank. The Indiana Biobank provides centralized processing and storage of specimens that are linked to participants' electronic medical information. Cases were defined as having any type of substance use disorders by using ICD9/10 codes, including alcohol, cannabis, cocaine, opioid, nicotine, and other substances. Controls were defined as not having any type of substance use disorders. The Indiana Biobank is part of the Indiana Clinical and Translational Sciences Institute (CTSI), a state-wide research partnership among Indiana University, Purdue University, and the University of Notre Dame.

  Study phs003025

• Pilot study of adoptive cell therapy using cultured tumor infiltrating lymphocytes for Japanese melanoma patients refractory to immune-checkpoint inhibitors

  To evaluate feasibility of the adoptive cell therapy (ACT) using tumor infiltrating lymphocytes (TIL) in Japanese melanoma patients who failed the immune checkpoint inhibitors (ICIs) and investigate the immune components and immunologic milieu within the pretreatment tumor and expanded TILs from there.?Three patients whose clinical subtype were mucosal, superficial spreading, and acral melanoma were treated and the all completed the TIL-ACT. Clinical response were one short-partial response, one relatively long-stable disease, and one progression disease. Whole-exome and transcriptional analysis of pretreatment tumor revealed the various?immunophenotypes including tumor mutation burden with immunogenic neoantigens and upregulation of immunosuppressive gene signatures.

  Study JGAS000249

• BLUEPRINT Gene expression analysis during human B-cell differentiation using the Affymetrix Human Genome U219 Array

  We performed gene expression analysis using the Affymetrix Human Genome U219 Array of 9 subpopulations covering the complete B-cell maturation program: hematopoietic progenitor cells (HPC); pre-B-I cells (preB1C); pre-B-II cells (preB2C); naive B cells from peripheral blood (naiBC); naive B cells from tonsil (t-naiBC); germinal center B cells (gcBC); plasma cells from tonsil (t-PC); memory B cells from peripheral blood (memBC) and plasma cells from bone marrow (bm-PC). All the samples were isolated from healthy donors and, with the exception of bm-PC (only 1 replicate), we used 3 to 11 biological replicates of each subtype.

  Study EGAS00001001197

• EGAD00010000768

  Replication data for HipSci normal samples using both HumanCoreExome-12_v1 and HumanOmni2.5-8 BeadChips

  Dataset EGAD00010000768

• Helleday_HRAS Project

  This experiment is looking at the mutational signatures generated by engineered HRAS mutations by using whole genome sequence generated on massively parallel next generation sequencers.

  Dataset EGAD00001000302

• Yemen_Somali.Omni5

  The individuals were assayed for genome-wide SNP genotypes using the Illumina Human Omni5 Bead Chip (Illumina), which surveys 4,284,426 single nucleotide markers regularly spaced across the genome

  Dataset EGAD00010001651

• KuwaitPopGenetics

  Genome-wide Genotyping of 620 Arab individuals using Illumina iSelect platform with HumanOmniExpress bead chips

  Dataset EGAD00010002063

• MethylationEPIC_850K

  This dataset includes IDAT files from 160 samples (57 primary prostate cancers, 95 proste-derived brain metastases, and 7 normal tissues). The samples were profiled using the Illumina Infinium MethylationEPIC BeadChips (850K)

  Dataset EGAD00010002372

• ctDNA raw data (BAMs)

  Raw data of ctDNA profiling using the PredicineWES+ or PredicineBEACON assay in patients enrolled in divarasib phase I GO42144 study.

  Dataset EGAD50000000530

• WGS

  Our cohort represents infants with ALL in whom KMT2Ar was not detected by FISH or by standard cytogenetics. Whole-genome sequencing (WGS) was performed using Illumina’s HiSeqX to a depth of >30X.

  Dataset EGAD50000000594

• WGS data of multiple myeloma

  Dataset containing WGS data from 4 patients with 17 samples with multiple myeloma. The sequencing was always paired and performed using Illumina NovaSeq 6000

  Dataset EGAD50000000437

• GCAT| SNParray coreSpain V3 TopMed

  4988 samples issued from GCAT cohort, genotyped with MEGAex-Infinium Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed r2.

  Dataset EGAD00010002749

• Methylation profiling of CDS and ES tumor samples

  Methylation profiling of 9 CDS and ES tumor samples, using the approach described in "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  Dataset EGAD00010002760

• Single Cell-Derived chemoradiotherapy-treated colonies.

  60X WGS of single cell-derived colonies of DHL4 cells treated with platinum or RT (or unexposed control). 16 bam files aligned using MGP1000 pipeline (GRCh38).

  Dataset EGAD50000001461

• GCAT| SNParray GSA TopMed

  2746 samples issued from GCAT cohort, genotyped with GSA Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed.

  Dataset EGAD00010002758

• WES of Multiple myeloma/MGUS cases (germline) - Fastq files

  WXS - Exome capture using the Twist Human Core Exome Kit on germline DNA, paired-end (2x100bp) sequencing on a NovaSeq system. Number of samples: 295

  Dataset EGAD50000001799

• HICHIP_TALL_t_14_16_translocation

  For patient P01, HiChIP experiment for was performed using the Arima-HiC+ kit (A510008, Arima genomics) according to the manufacturer’s protocols.

  Dataset EGAD50000002167

• Somatic MT SNV calls

  Filtered somatic MT SNV (heteroplasmy) calls detected using mitoCaller (v1.0)

  Dataset EGAD00001007871

• Mucoepidermoid Carcinoma

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001003958

• Whole genome sequencing of chronic lymphocytic leukemia

  Whole genome sequencing of chronic lymphocytic leukemia, 49 CLL/control pairs, sequenced on HiSeq X Ten with DNA prepared using Illumina TruSeq DNA Nano.

  Dataset EGAD00001009638

• Cell line sequencing data

  SmMIP libraries using bulk cell line DNA and DNA mixes were generated in replicates and were sequenced on the NovaSeq SP platform (Illumina)

  Dataset EGAD00001007790

• Live slow-frozen human tumor tissues scRNA

  Bam files of 17 samples from 11 different patients. The scRNAseq data were obtained using the 10X 3' Gene Expression kit.

  Dataset EGAD00001009284

• Endometriosis

  Whole exome sequencing data for matched normal and endometriosis samples. Samples were prepared using Agilent Sureselect capture kit, and sequenced on an Illumina HiSeq 2500. The submitted files are in BAM format.

  Dataset EGAD00001004964

• Mucoepidermoid carcinoma- normals

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001004946

• 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 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 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 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 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 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 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 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 Completed projects Project Duration Domain Funder Tags 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 LaMarató | 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 Fundació La Marató 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

• Breast Cancer Histology Images

  Fresh frozen breast cancer H&E tissue images collected and annotated by the International Cancer Genome Consortium (ICGC), that included the BASIS collaboration. Associated with whole genome sequence data as originally described by Nik-Zainal et al, Nature, 2016 (DOI: 10.1038/nature17676) and deposited with ID EGAS00001001178

  Dataset EGAD00010001911

• Germline Genetic Variants in Cancer-Susceptibility Genes in Patients with Osteosarcoma

  We conducted whole-exome sequencing of germline DNA from patients with osteosarcoma to estimate the frequency of pathogenic/likely pathogenic germline genetic variants in known cancer-susceptibility genes in a large population of osteosarcoma patients unselected for family history.

  Study phs002444

• EOSC4Cancer Synthetic Colorectal Cancer Genomic data

  In this study there are stored the synthetic datasets produced by partners involved in EOSC4Cancer. The study contains independent datasets available for the research community. The synthetic genomes have been created trying to mimic real cancer data.

  Study EGAS50000000190

• Whole exome sequencing of uterine cervical cancer

  We conducted whole-exome sequencing of cervical tissue samples to evaluate HLA loss of heterozygosity (LOH) and B2M gene mutations, which are key mechanisms of immune evasion that allow cancer cells to escape T-cell recognition and antigen presentation.

  Study JGAS000824

• Clinical Utility of Breast cancer Research by Inocras, Catholic university hospital and Samsung medical center

  Breast cancer remains a major global challenge. To comprehensively characterize its genomic landscape and clinical significance, we analyzed whole genome sequences from 1,364 clinically annotated breast cancers, integrating transcriptome data from most of the tumors.

  Study EGAS50000001062

• Intrapatient tumor heterogeneity and clonal evolution in metastatic salivary gland cancer: an autopsy study

  This data contains DNA sequencing data of an autopsy study in patients with salivary gland cancer. Whole-genome sequencing was performed on multiple spatially separated tumor samples per patient (4-7 per patient) and healthy control samples.

  Study EGAS50000001420

• Clinical data of liver cancer patients from EuCanImage - Use case 1 Synthetic

  This study is part of EuCanImage project. It contains the standardized clinical information following FHIR model. The data was collected together with MRI of patients diagnosed with liver cancer (HCC) and controls (non-HCC). All data is synthetic.

  Study EGAS50000001444

• Prediction of response to preoperative chemoradiotherapy in rectal cancer based on whole-exome sequencing and transcriptomic analysis

  Accumulating evidence suggests that radiotherapeutic success has an immune-associated component. We aimed to investigate the immunogenomic profiles associated with response to preoperative chemoradiotherapy (CRT) in patients with locally advanced rectal cancer.

  Study JGAS000158

• Clinical Utility of Breast cancer Research by Inocras, Catholic university hospital and Samsung medical center

  Breast cancer remains a major global challenge. To comprehensively characterize its genomic landscape and clinical significance, we analyzed whole genome sequences from 1,364 clinically annotated breast cancers, integrating transcriptome data from most of the tumors.

  Study EGAS50000001377

• HER2_positive_Breast_Cancer_

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

  Study EGAS00001000042

• Matched_Pair_Cell_Line_Tumour_RNAseq

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

  Study EGAS00001000434

• Triple_Negative_Breast_Cancer_sequencing

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

  Study EGAS00001000161

• SPECTA__NGS_Screening_Program_for_Efficient_Clinical_Trial_Access

  SPECTA comprises a network of participating European clinical sites and NGS screening platforms that can screen individual patients for multiple molecular targets and potentially allow the design of trials that will match the specific biology of the diseases affecting specific patients with cancer.

  Study EGAS00001000728

• Genome and transcriptome sequence data from a metastatic non-small cell lung cancer patient

  Genome and transcriptome sequence data from a metastatic non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003717

• Genome and transcriptome sequence data from a metastatic non-small cell lung cancer patient

  Genome and transcriptome sequence data from a metastatic non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003650

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  The dataset for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer includes 106 bam files from whole exome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include matched tumor/normal samples from non-small cell lung cancer patients treated with immunotherapy.

  Dataset EGAD00001005796

• Genome and transcriptome sequence data from a metastatic non-small cell lung cancer patient

  Genome and transcriptome sequence data from a metastatic non-small cell lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004626

• Genome and transcriptome sequence data from a squamous cell carcinoma of unknown primary cancer patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of unknown primary cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002624