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• Comparison of 3 protocols for deriving pancreatic progenitors from hPSC with RNA-seq and ATAC-seq

  Several distinct differentiation protocols for deriving pancreatic progenitors (PP) from human pluripotent stem cells have been described but it remains to be shown how similar the PP are across protocols, and how well they resemble their in vivo counterparts. Here we evaluated three differentiation protocols; performed RNA and ATAC-seq on isolated PP derived with these, and compared them to fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PP, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PP through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols, and provides a valuable resource for exploring human pancreatic development.

  Study EGAS00001003513

• Drug Perturbation of Primary Lymphoma Patient Samples and RNA Sequencing

  This submission contains 3'-end-based shallow-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule drugs (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). The samples were sequenced after 48 hours. The total data set consists of 1476 RNA sequencing samples from 6 batches (pilot, batch 1, batch 1 replicate, batch 2, batch 3, batch 4).

  Study EGAS50000001500

• Incentives and Case Management to Improve Cardiac Care: Healthy Lifestyle Program (HeLP)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this study.Objectives: The HeLP study assessed how early case management, financial incentives contingent on cardiac-rehabilitation attendance, or both impacted adherence to cardiac rehabilitation among patients with lower socioeconomic status (SES) who had a cardiac-rehabilitation-qualifying diagnosis. Background:Cardiovascular disease (CVD) is the leading cause of death in the United States. Regular attendance at cardiac rehabilitation (CR) is the number one recommendation for patients who have experienced a recent cardiac event. CR is a secondary prevention outpatient program involving an individually tailored structured exercise program along with counseling and encouragement regarding lifestyle changes to reduce the recurrence of major cardiac events.Despite the benefits of CR attendance, enrollment and adherence to the program are low. This is particularly true of individuals of lower socioeconomic status (SES), who also generally suffer a higher burden from CVD on account of higher-risk cardiac profiles. As these profiles are the result of modifiable behavior targeted by CR (i.e., smoking, obesity, lack of physical activity), methods of increasing CR attendance among this population are necessary.Case management and financial incentives contingent on CR attendance are two potential strategies for addressing this issue. Previous studies have shown how trained case managers can support and assist patients with attending CR and improving their cardiac health, and how financial incentives can promote various types of health-related behavior. The purpose of the present study was to evaluate how these two interventions, individually and in tandem, fared at improving CR adherence among individuals of lower SES specifically. Participants:A total of 314 participants were screened, and 209 were randomized. All consented to have their data shared for research purposes. Design:Eligible patients were approached either while still in the hospital or during initial visits to CR. After obtaining informed consent, clinical and demographic characteristics (i.e., age, sex, education, race and ethnicity, smoking status, and CR-qualifying diagnosis) and depressive symptoms were collected. Participants then were randomized 2:3:3:3 to usual care (UC), case management starting in hospital (CM), financial incentives for attending CR (FI), or financial incentives plus case management (FICM). For all participants regardless of condition, an appropriate referral for CR was confirmed after randomization. Over the course of the study participants completed three assessments – one at intake, one after four months, and one after one year. Clinical (i.e., cardiorespiratory fitness, body composition, and cardiac-related quality of life) and sociocognitive (i.e., Beck Depression Inventory, Achenbach System of Empirically Based Assessment, and Behavior Rating Inventory of Executive Function) measures were obtained at each assessment. Participants randomized to the UC condition were contacted weekly by study staff for adverse event checks, but received no additional intervention. Participants randomized to the CM condition were immediately assigned a case manager. Case managers met with their participants, usually within 24 hours of consent while they were still in the hospital, to introduce themselves during an initial check-in. Within the first week of consent they completed a longer, more thorough initial needs assessment with their participant and established behavioral goals. For the next 16 weeks, case managers met with their participants at least once a week, typically over the phone, to discuss progress on these goals and address any problems or barriers that had arisen. Case managers also were available via phone outside of these regular meetings during normal working hours and Saturday mornings. Participants randomized to the FI condition could earn money for completing an initial CR orientation and attending CR sessions. Twenty dollars could be earned for completing the CR orientation session. CR attendance was reinforced on an escalating schedule starting at $10. Payments increased by $2 for each successive session attended, and capped out at a maximum of $40 per session. Unexcused absences resulted in the incentives for that session not being earned, and the potential earnings for the next scheduled session being reset to $10. Successful participation of two consecutive sessions following the reset resulted in the incentives being returned to the amount prior to the reset. In total, participants could earn $1220 for attending the initial orientation and all 36 sessions of CR. The primary outcome of interest was the percentage of participants who completed at least 30 sessions of CR. Secondary outcomes included the number of sessions completed, cardiorespiratory fitness (peak VO2 and estimated metabolic equivalents (METs)), body composition (waist circumference and BMI), depression scores, and both general and cardiac-related qualify of life. Conclusions:The two interventions involving financial incentives (i.e., financial incentives alone and financial incentives plus case management) significantly improved CR adherence compared to usual care. Subsequent analyses revealed that the combination of financial incentives and case management led to greater improvements in CR attendance than financial incentives alone.

  Study phs003737

• Novel mutational mechanisms and drivers in Pancreatic Neuroendocrine Tumours

  Pancreatic neuroendocrine tumours (PanNETs) are increasing in prevalence due to earlier detection, consequently creating challenges in clinical care, as current classification permits unsatisfactory therapeutic stratification. We performed whole genome sequencing of 102 primary PanNETs and defined the genomic events underlying their pathogenesis. We describe the mutational signatures they harbour, including a novel G:C>T:A Base-Excision-Repair-deficiency signature due to MUTYH inactivation. We uncover a larger than expected proportion of germline mutations in clinically sporadic PanNETs. These include previously unreported mutations in DNA repair genes MUTYH, CHEK2, BRCA2, and PALB2, which together with MEN1 and VHL occur in 16% of patients. Somatic mutations (point mutations and structural rearrangements) commonly occurred in genes involved in 4 main pathways: chromatin remodelling, DNA damage repair, activation of mTOR signalling (including novel EWSR1 gene fusions) and telomere maintenance. Aberrations in these mechanisms are associated with subtypes of PanNET with potential clinical application for prognostic and therapeutic stratification.

  Study EGAS00001001732

• Ovarian Cancer Organoid Biobank - RNASeq data

  Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004509

• MGMT genomic rearrangements contribute to chemotherapy resistance in gliomas

  Temozolomide (TMZ) is an oral alkylating agent used for the treatment of glioblastoma and is now becoming a chemotherapeutic option in patients diagnosed with high-risk low-grade gliomas. The O-6-methylguanine-DNA methyltransferase (MGMT) is responsible for the direct repair of the main TMZ-induced toxic DNA adduct, the O6-Methylguanine lesion. MGMT promoter hypermethylation is currently the only known biomarker for TMZ response in glioblastoma patients. Here we show that a subset of recurrent gliomas carry MGMT genomic rearrangements that lead to MGMT overexpression, independently from changes in its promoter methylation. By leveraging the CRISPR/Cas9 technology we generated some of these MGMT rearrangements in glioma cells and demonstrated that they lead to TMZ resistance both in vitro and in vivo. Lastly we showed that such fusions can be detected in tumor-derived exosomes and could potentially represent an early detection marker of tumor recurrence in a subset of patients treated with TMZ.

  Dataset EGAD00001006281

• Bleomycin Induced Pneumonitis WGS dataset

  This is whole genome sequencing data from a cohort of 18 patients with germ cell tumours or Hodgkin Lymphoma, who developed clinically significant bleomycin-induced pneumonitis despite low clinical risk. DNA was extracted from whole blood, and 150-base paired-end reads were generated on an Illumina NovaSeq 6000 instrument to a minimum 30x depth. Sequence reads were aligned to the GRCh38 reference with BWA MEM, and germline variants were called following GATK best practice procedures. The dataset comprises per-sample read alignment files in BAM format, and a joint-called germline variant file in VCF format.

  Dataset EGAD50000002221

• Spatiotemporal evolution and inter-patient heterogeneity in primary and recurrent/metastatic head and neck squamous cell carcinoma

  Head and neck cancer squamous cell carcinomas (HNSCCs) are heterogeneous in terms of origin and aetiology. In addition, there is uncertainty about the spatiotemporal genetic evolution from initial diagnosis to recurrence/metastasis (R/M) after primary treatments and further disease progression following systemic treatment. Changes in the genetic profile have implications on the selection of appropriate treatments for patients, especially in the era of targeted therapies and immunotherapies. Here, we analysed a cohort of 11 HNSCC patients with metachronous R/M, among whom nine had paired primary and R/M samples suitable for next-generation sequencing (multiple R/M samples collected at different time points were available for some of the patients). At the genomic level, the R/M samples shared a fraction of the somatic single nucleotide variants (SNVs) with the index primary tumours, but they also acquired many additional mutations, while losing only a few others. A similar behaviour was also observed when examining the changes of mutational signatures between primary and R/M samples. Overall, R/M appeared thus more genetically diverse than the respective primary tumours. The transcriptomic analysis showed that R/M samples had lower immune cell infiltration and several genes related to immune response were significantly downregulated compared to the primary samples. Our results underline the importance of analysing multiple samples per patient to obtain a more complete picture of the patient’s tumour and advocates a re-biopsy in the event of R/M and treatment failure, in order to select the most appropriate therapeutic strategy.

  Study EGAS00001007464

• Establishment of Human Trophoblast Stem Cells from Term Smooth Chorion

  Human trophoblast stem (TS) cells, which were established from blastocysts and first-trimester placental villi, can differentiate into the all trophoblastic subtypes, extravillous trophoblast (EVT) cells and syncytiotrophoblast (ST) cells. We newly generated human TS cells from the term smooth chorion (Ch-TS cells). They has the potential to differentiate into both ST and EVT cells as same as human TS cells derived from early placental villi. The transcriptomic profile of Ch-TS cells is also similar to conventional human TS cells.

  Study JGAS000777

• 'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

  Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

  Study EGAS00001007347

• Programmatic submission based on XML

  Programmatic submissions (XML based) For further information please check our Submission FAQs, submission quickguide as well as submission terms! Introduction Besides the Submitter Portal tool, EGA supports programmatic sequence and clinical data metadata submissions. If you are not sure what this means, you may want to explore our brief metadata introduction. Programmatic submissions are recommended for array-based submission. Moreove, it may be of help if your submission is recurrent or it is difficult to manage manually due to its sheer size. Otherwise, we highly recommend using the Submitter Portal to perform submissions. In this page we will guide you through the required steps to programmatically submit data to the EGA. Programmatic submissions require your metadata to be structured for an easy and straightforward validation and archival. It basically consists in formatting your metadata as Extensible markup language (XML) files and submitting them to the EGA using the WEBIN Before submitting metadata to the EGA, it is important to ensure that the information in your XML files is compliant with our standards. You can see further details on how these standards are maintained at EGA at our EGA Schemas documentation page. Using WEBIN, you can validate your XML files against EGA's schemas to ensure that your metadata is compliant before submission. WEBIN services WEBIN production service WEBIN test service We advise you to submit your metadata to the test service when submitting to the production service for the first time. The test service is identical to the production service except that all submissions will be discarded in the following 24 hours. This allows you to learn about the submission process without having to worry about data being submitted. Authentication Authentication is required each time a submission is made. The submission service uses HTTPS protocol for metadata encryption and identification to provide a secure submission environment. Data file upload Both Runs and Analyses reference files (e.g. FASTQ need to be uploaded to the EGA before these metadata objects are submitted. In other words, if you submit a Run that references a file that we cannot find associated with your account, the metadata submission will fail. See further details on how to upload your files in our File Upload documentation. Metadata model of the EGA Our metadata model is formed by multiple metadata objects. Check further details in our documentation at our EGA Schema documentation page. Working with EGA XMLs files Now that the basic concepts of the EGA metadata have been described, you can start preparing your programmatic submission through XML. Here you will find the guidance on how to prepare the XML files. Programmatic Submission Tutorial Video Take a look at the Programmatic Submission Tutorial Video, which explains the workflow of a programmatic submission and goes over an example metadata submission. Programmatic Submission Tutorial Video. When building your XML files, we recommend using text editors (e.g.Sublime Text or VisualStudio) that allow you to visualise the structure of the XML with ease. Furthermore, these editors constantly check the consistency of the XML structure. Alternatively, and if the submission consists of a big number of objects (specially analyses), you may find the tool star2xml handy. This tool allows for a direct conversion between metadata in a tabular format (e.g. a spreadsheet) into XMLs. Identifying objects: Aliases and center names Every EGA object must be uniquely identified within the submission account using their alias attribute. The aliases can be used in submissions to make references between EGA objects. Let us dig into EGA's use of aliases and center names: alias: every object should have a name that is unique within your submission account. Once submitted successfully, every alias will be assigned a unique and permanent accession (EGA ID). refname: when an object references another by its alias, the alias of the referenced object goes into the "refname" attribute of the referencing object. For example, if a sample has the alias "sample1", and an experiment uses this sample, then the experiment's "EXPERIMENT/SAMPLE/refname" attribute should be "sample1". center_name: The "center_name" attribute is required within the submission XML and, if not provided when the object is submitted, it will be automatically filled using your default EGA account center_name. This element is the "controlled vocabulary acronym or abbreviation that is provided to the account holder when the account is first generated". If the submitter is brokering a submission for another institute, the submitter should use their special broker account name in broker_name while the data centre acronym remains in center_name. Log-in details should have been provided when you requested a submission account. Please contact our Helpdesk team if you have any questions. run_center: Many submitting centers contract out the actual sample sequencing to another center. In these cases, the sequencing center should be acknowledged in the run_center attribute. Again, this is controlled vocabulary and the acronym should be sought from EGA helpdesk before submitting. Please contact our Helpdesk team if you have any questions. Prepare your XMLs The goal of this section is to provide sufficient information to be able to create the metadata XML documents required for programmatic submissions. Please note, the EGA utilises the XML schemas maintained at the European Nucleotide Archive (ENA). It is important due to the fact that by using a similar system, some pieces of documentation from the ENA's programmatic submission can also help you with your programmatic submission to the EGA. For example, you can submit programmatically without using a Submission XML by following the steps at Submission actions without submission XML. A submission does not have to contain all different types of XMLs. For example, it is possible to submit only a few samples; or a study that is later to be referenced. You can submit each object one by one, or submit all in a batch: you choose what method of submission works best for you. We do recommend, nevertheless, that you submit the objects to be referenced (e.g. samples or studies) first, and the objects that reference these (e.g. experiments or datasets) afterwards. You can see a graphical view of these objects and their relationships at our EGA Schemas page. Independently of the submission scenario, you will always require a Dataset XML. The entity of a dataset is what is used to control access to the given data, in the form of runs or analyses. In other words, when a requester is granted access, it is through the dataset and the objects (e.g. runs or analyses) that the dataset contains, granting access to them in one go. Given the nature of the EGA, a dataset XML will always be required for the data access. First, we will differentiate between submissions of "raw" and "processed" data: Runs and Analyses, respectively. Run data submissions Raw data derives from instruments "as is". For example, a plain sequence file (e.g. FASTQ or unaligned BAM files) would be considered raw data. A typical raw (unaligned) sequence read submission consists of 8 XMLs: Submission Study Sample Experiment Run DAC Policy Dataset When technical reads (e.g. barcodes, adaptors or linkers) are included in the submitted raw sequences, a spot descriptor must be submitted to describe the position of the technical reads so that they can be removed. The following data files can be submitted without providing spot descriptor information in the experiment/run XML: BAM files (single reads) SFF files (single reads without barcodes) FastQ files (single reads without any technical reads) Complete Genomics files Analysis data submissions Processed data is, in some way, refined raw data. This includes raw data that has been processed by some form of analysis method (e.g. alignment, noise reduction, etc.). For example, an aligned sequence (e.g. BAM file), that was created using raw FASTQ files, would be a processed file. This category includes most types of data: sequence alignment files (e.g. BAM or CRAM), clinical data (e.g. phenopackets), sequence variation files (e.g. VCF), sequence annotation, etc. A typical EGA analysis data submission consists of 7 EGA XML: Submission Study Sample Analysis DAC Policy Dataset We accept three different types of analysis data submissions: BAM files (for multiple read alignments) VCF files (for sequence variations) Phenotype files (in any format) In anycase, keep in mind that samples must be created in order to be referenced in the analyses. In other words, the provenance of the information within the BAM, VCF and phenotype files Example XMLs Below you can find a non-extensive list of example XMLs with descriptive fields (i.e. explaining what to provide in each field). Furthermore, you can also find real examples (i.e. the true value of the provided fields) in our GitHub repository. Submission XML The submission XML is used to validate, submit or update any number of other objects. The submission XML refers to other XMLs. New submissions use the ADD action to submit new objects. Object updates are done using the MODIFY action and objects can be validated using the VERIFY action. Descriptive submission XML example True values submission XML example Study XML The study XML is used to describe the study containing a title, a study type and abstract as it would appear in a publication. Descriptive study XML example True values study XML example Please use the following notation within the property "STUDY_LINKS" when including PubMed citations in the Study XML: <STUDY_LINKS> <STUDY_LINK> <XREF_LINK> <DB>PUBMED</DB> <ID>18987735</ID> </XREF_LINK> </STUDY_LINK> </STUDY_LINKS> Sample XML The sample XML is used to describe the samples used to obtain the data, whether they were sequenced, measured in any other way, or have an associated phenotype. The mandatory fields include information about the taxonomy of the sample, sex, subject ID and phenotype. For example, the mandatory attribute fields for each sample would look like these, within the array of "SAMPLE_ATTRIBUTES": <SAMPLE_ATTRIBUTES> <SAMPLE_ATTRIBUTE> <TAG>subject_id</TAG> <VALUE>free text!</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>sex</TAG> <VALUE>female/male/unknown</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>phenotype</TAG> <VALUE>Free text, EFO terms (e.g. EFO:0000574) are recommended</VALUE> </SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTES> Sample is one of the most important objects to be described biologically, it is highly recommended that “TAG-VALUE” pairs are generated as SAMPLE_ATTRIBUTES to describe the sample in as much detail as possible. For example, were we to give the population ancestry of the sample, we could add a new attribute to the array, in which, for example, we would indicate that the sample derives from an individual of "Mende in Sierra Leone" (MSL), with an african ancestry: <SAMPLE_ATTRIBUTE> <TAG>Population</TAG> <VALUE>MSL</VALUE> </SAMPLE_ATTRIBUTE> Given that VALUE and TAG are free text, the combinations are limitless in order to give you full flexibility on the information you want to provide. We recommend you use the Experimental Factor Ontology (EFO) to describe the phenotypes of your samples. You can provide more than one phenotype by adding more items to the array of SAMPLE_ATTRIBUTES. Phenotypes considered essential for understanding the data submission should be provided. Each phenotype described should be listed as a separate sample attribute <SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTE>. There is no limit to the number of phenotypes that can be submitted. If a suitable EFO accession cannot be found for your phenotype attribute, please consider using another controlled ontology database (e.g. HPO, MONDO, etc.) before using free text. Descriptive sample XML example True values sample XML example Experiment XML The experiment XML is used to describe the experimental setup, including instrument platform and model details, library preparation details, and any additional information required to correctly interpret the submitted data. Where any of these values differ between runs, a new experiment object must exist, since runs are grouped by experiments. Each experiment references a study and a sample by alias, or if previously-submitted, by accession. Pooled data must be demultiplexed by barcode for submission. Descriptive experiment ( Illumina paired read ) XML example True values experiment ( Illumina paired read ) XML example Run XML The run XML is used to associate data files with experiments and typically comprises a single data file (e.g. a FASTQ file). Please note that pooled samples should be de-multiplexed prior submission and submitted as different runs. Descriptive run XML example True values run XML example Analysis XML Given that an analysis can be used to submit any type of processed data to the EGA, we will list below an example of each of the three most common types of analysis XMLs submitted to the EGA: sequence alignments (e.g. BAM files); sequence variation (e.g. VCF files); and clinical metadata or phenotypes (e.g. phenopackets). Regardless of the type of processed data submitted in the analysis, the analysis must be associated with a Study and can reference multiple types of other objects, from samples to experiments, if they are available at the EGA. Just like with Runs, whenever a file is submitted to the EGA through an analysis object, the file MD5 checksums must be present, in order for the EGA to validate file integrity upon transfer. This also includes index files when applicable (e.g. .bai.md5 files). Ideally, any analysis that uses a reference sequence for some kind of alignment (e.g. BAM, CRAM or VCF files), would contain metadata about the alignment, such as INSDC reference assemblies and sequences, by either using accessions (e.g. CM000663.1) or common labels (e.g. GRCh37). Read alignment (BAM) Analysis XML The Analysis can be used to submit BAM alignments to EGA. Only one BAM file can be submitted in each analysis and the samples used within the BAM read groups must be associated with Samples. Descriptive bam alignments XML example True values bam alignments XML example Sequence variation (VCF) Analysis XML The Analysis can be used to submit VCF files to EGA. Only one VCF file can be submitted in each analysis and the samples used within the VCF files must be associated with Samples. Download analysis XML (VCF) Phenotype files The Analysis XML can be used to submit phenotype files to the EGA. Only one phenotype file can be submitted in each analysis and the samples used within the phenotype files must be associated with EGA Samples. Download analysis XML (Phenotype) DAC XML The DAC XML describes the Data Access Committee (DAC) affiliated to the data submission. The DAC may consist of a group or a single individual and is responsible for the data access decisions based on the application procedure described in the POLICY.XML. As with any other object, if it was already submitted to the EGA, there is no need to submit it again: you can reference an existing object within the EGA. Hence, A DAC XML does not need to be provided if your submission is affiliated to an existing EGA DAC.. Further information on DACs can be found here, and you can always contact our Helpdesk team if you have further inquiries. Descriptive dac XML example True values dac XML example Policy XML The Policy XML describes the Data Access Agreement (DAA) to be affiliated to the named Data Access Committee. Descriptive policy XML example True values study XML example Dataset XML The dataset XML describes the data files, defined by the Run.XML and Analysis.XML, that make up the dataset and links the collection of data files to a specified Policy. The dataset xml is commonly the last metadata object to be submitted, since it references multiple other entities. Please consider the number of datasets that your submission consists of. For example, a case-control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Descriptive dataset XML example True values dataset XML example Validating and submitting your EGA Validating EGA's XMLs through Webin After you have ensured that the XMLs are properly formatted and contain all the required information. You can proceed to validate and submit your data. Use the curl command to validate your XML file: Once you have prepared your XML file and asserted you have access to Webin, you can validate your XML file programmatically against EGA's schemas using the curl command. There are multiple ways in which you can validate your XMLs. This variety has to do with the fact that: (1) there are 2 instances of Webin (test and production); and (2) that validation is a default step during submission. In other words, any time that you submit your data through Webin, it will be validated automatically before being accepted. This allows for 4 possible routes of validation, all having the same validation result: validating or submitting to either the production service or the test service of Webin. For example, directly validating a "study" object XML in the testing service (wwwdev…) would look like the following: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" In this command, you would need to replace <USERNAME> and <PASSWORD> with your EGA account username and password, respectively. You would also replace <INPUT_FILE> with the path to your XML file. A mock example would look like the following: curl -u ega-test-data@ebi.ac.uk:egarocks -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" The validation attempt can have different results depending on the given arguments: If your XML file is valid according to EGA's schemas, you will see a message indicating that your XML file is compliant. For example, see below for our mock example, where the "success" was "true" (i.e. no validation errors found). Nevertheless, notice how the "<STUDY accession=" is empty: it is because we were simply validating, so the study did not get an accession or ID. <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:19:28.850+01:00" submissionFile="submission-EBI-TEST_1681222768850.xml" success="true"> <STUDY accession="" alias="Mock example" status="PRIVATE"/> <SUBMISSION accession="" alias="SUBMISSION-11-04-2023-15:19:28:840"/> <MESSAGES> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If there are any errors or warnings, the tool will display them, allowing you to correct them before submitting your data to EGA. For example, in the following response, it is said that the object we were trying to submit was already existing, and therefore the "success" was "false". <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:12:35.609+01:00" submissionFile="submission-EBI-TEST_1681222355609.xml" success="false"> <STUDY alias="Example!_Human Microbiome Project SP56J" status="PRIVATE" holdUntilDate="2023-03-11Z"/> <SUBMISSION alias="SUBMISSION-11-04-2023-15:12:35:576"/> <MESSAGES> <ERROR>In study, alias: "Example!_Human Microbiome Project SP56J". The object being added already exists in the submission account with accession: "ERP127584".</ERROR> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If the curl command retrieves no response at all, please double check if your username and password are correctly provided. Also notice the "ACTION=..." argument passed to the Curl command. This specifies the action to take during the call to Webin, so we do not need a "Submission" XML just for a validation attempt. See more at submission actions without submission XML. Furthermore, validation of multiple files or objects (e.g. sample, experiment, study…) can be done in a single command by adding more arguments (i.e. '-F'). For example: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" -F "SAMPLE=@sample.xml" -F "DATASET=@dataset.xml" As mentioned above, beside "validate" action in the test environment, you can also validate your metadata by three other methods: "Validate" in the production server. From our example above, you simply need to take the "dev" away from the URL. curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the development server. From our example above, you would simply need to replace the action: from "validate" to "add". Whatever is submitted to this service will be discarded in 24h, so whether something gets submitted or not would not matter in the long run. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the productionserver. A combination of the previous two methods, which would render this attempt into a submission. This path is just to be taken when you are sure your metadata is compliant and what you want to submit. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" What happens after the submission of a dataset XML? Once you have completed the registration of your dataset/s please contact our Helpdesk Team to provide a release date for your study. Please note that all datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitter or DAC contact contact the EGA Helpdesk for the study to be released. We strongly advise you not to delete your data until EGA Helpdesk confirms that your data has been successfully archived.

  Documentation submission/metadata/submission/programmatic-submission-xml

• The African American Breast Cancer Epidemiology and Risk (AMBER) Consortium Study

  The AMBER Consortium Study was formed to pool interview data, questionnaire data, and biological samples from epidemiological studies of breast cancer in African-American women to discover the potential causes of early-onset and aggressive breast cancer in African-American women. AMBER is funded through a Program Project grant from the National Cancer Institute. Genetic data submitted to dbGaP come from participants in the Carolina Breast Cancer Study, Women&#39;s Circle of Health Study, and Black Women&#39;s Health Study. The P01 consists of four scientific projects; the aims include follow-up on previous GWAS findings for breast cancer susceptibility in AA women as well as investigation of SNPs in candidate genes in biologically plausible pathways. These SNPs were genotyped using DNA from 3130 African-American women with breast cancer and 3700 controls. Descriptions of the original studies that provided the data and samples for this collaborative study are given below. The Carolina Breast Cancer Study (CBCS): a North Carolina population-based case-control study of breast cancer, conducted in three phases. The current study phase, phase 3 (years 2008-2014), includes women residents in 44 counties. CBCS phases 1 and 2 were conducted in 24 counties. Breast cancer cases are identified using Rapid Case Ascertainment in cooperation with the NC Central Cancer Registry. Controls were identified for phases 1 and 2 only (1993-1996 and 1996-2001), using Division of Motor Vehicles lists for women under age 65 and Health Care Financing Administration lists for women 65 and older. Randomized recruitment was used to oversample AA women and women under age 50. In-depth interviews are conducted by study nurses in participants&#39; homes to obtain information on potential risk factors for breast cancer. DNA samples have been obtained from most participants. Overall response rates for Phases 1 and 2 were 74% for AA cases and 54% for AA controls. Phase 3, conducted in 44 counties from 2008-2014, includes cases only. The response rate for AA cases in Phase 3 was 70.5%. The Women&#39;s Circle of Health Study (WCHS): a multi-site case-control study in New York City (NYC) and New Jersey (NJ) aimed at evaluating risk factors for early and aggressive breast cancer in women of AA and EA ancestry. Recruitment in NYC took place between January 2002 and December 2008 and involved hospital-based ascertainment of cases, while controls were identified through random digit dialing (RDD). Recruitment at the NJ site started in March 2006 and is ongoing. Phase I of the study ended in April 2012 and covered seven counties in NJ. WCHS2 includes two additional counties. Cases in NJ were identified from 2006 to 2012 by the NJ State Cancer Registry using rapid case ascertainment. Controls were initially recruited though RDD (2006 to 2010) and later through community-based efforts (2009-2012). In-person interviews ascertained data on established and suspected risk factors for breast cancer. DNA samples were obtained. Among eligible AA women, 75% in NY and 54% in NJ completed an interview and provided a biologic specimen. Black Women&#39;s Health Study (BWHS): an ongoing prospective cohort study of health and illness among U.S. black women, with a focus on cancer. The study began in 1995 when 59,000 AA women 21-69 years of age from across the United States completed a 14-page postal health questionnaire. The median age at entry was 38, and participants were residents of 17 states in mainland U.S.: Northeast, 28%; South, 30%; Midwest, 23%; West, 19%. The baseline questionnaire elicited information on a wide range of variables, including demographic factors, use of medical care, family history of breast cancer, reproductive and medical history, cigarette and alcohol use, weight, height, waist and hip circumference, medication use, diet, and exercise. Biennial follow-up questionnaires ascertain new cases of breast cancer and other illnesses and update covariate information. Medical record and cancer registry data are sought for all participants who report a diagnosis of breast cancer. As of 2014, approximately 80% of the baseline cohort have completed follow-up. DNA samples were obtained from about 50% of participants. BWHS data for the AMBER consortium were prepared as a nested case-control study, with controls frequency-matched to cases on year of birth, geographic region, and most recent questionnaire completed prior to the end of the at-risk period.

  Study phs000669

• Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dac EGAC50000000578

• Single cell targeted DNA-sequencing (and antibody sequencing) of high hyperdiploid B-ALL

  This dataset contains all sequencing data of the publication "Single-cell DNA and Surface Protein Characterization of High Hyperdiploid Acute Lymphoblastic Leukemia at Diagnosis and During Treatment". We provide both the raw fastq-files as well as the processed data in the form of .h5 files. There are 13 patients: XJ176, XH135, XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162, XF98, XG111 and XG115. Of 9 patients, also follow-up samples during/after treatment were sequenced: XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162 and XG111. To identify the cell types and distinguish between normal and leukemic cells, cell surface proteins were also captured for 6 samples: XF98, XG111 (at diagnosis and during treatment), XG115, XI162 (after treatment) and XJ175 (after treatment). All samples were processed on the MissionBio platform with a custom amplicon panel, and DaB-seq for the combined targeted DNA and protein sequencing.

  Dataset EGAD50000000829

• Characterization of a human iPSC-derived islet differentiation model

  To explore the contribution of islet development to T2D pathogenesis, we characterised the transcriptomes of 3 human iPSC lines (from independent donors) differentiated along the islet development lineage. Whole transcriptome RNA-seq was performed at 7 developmental stages: definitive endoderm, primitive gut tube, posterior foregut (PF), pancreatic endoderm, endocrine progenitors, endocrine-like cells, and beta-like cells (BLC). Differentially-expressed (ΔExp) genes were assigned to the stage in which they were most upregulated (versus baseline iPSC profile), and used to assess the enrichment of T2D GWAS genes, as well as to predict the upstream transcription factors at each developmental stage.We found 9409 ΔExp genes across all stages, including known markers of islet development (NEUROG3, INS). Genes ΔExp in the most-differentiated (BLC) stage were significantly enriched for genes within the 99% credible sets of T2D GWAS loci. Despite this enrichment in BLC only, over 70% of genes mapping within the credible sets were ΔExp before this stage, highlighting the relevance of key T2D GWAS genes in islet development: e.g. expression of TCF7L2 peaked during the PF stage (log2FC=1.2; q=8.5×10-10). REST and LMNA are also highlighted by the analyses as having a potential function in islet development, considering their pattern of expression and those of the genes they regulate. Transcriptomic signatures derived from this iPSC differentiation model highlight T2D-associated GWAS loci, monogenic diabetes genes and potential master regulators of gene networks with plausible function in islet development. All these provide clues for developmental mechanisms contributing to T2D diabetes pathology.

  Study EGAS00001002721

• Kids First: Whole Genome Sequencing Studies of Multiplex Nonsyndromic Cleft Lip/Palate Families

  Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect that affects approximately 135,000 newborns worldwide, and imposes significant medical, psychosocial and financial burdens to affected individuals and their families. Genetic variation in numerous genes has been associated with NSCLP, however the exact mechanisms by which they contribute to the condition remain largely unknown. Here, we will use whole genome sequencing and robust analytical approaches to systematically evaluate the causes of NSCLP in 923 individuals from large multigenerational families.

  Study phs002626

• Intraductal transplantation models of human pancreatic ductal adenocarcinoma reveal progressive transition of molecular subtypes

  Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past few decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated. However, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present an orthotopic xenotransplantation model of human patient-derived PDAC organoids in which organoids are grafted via direct injection into the pancreatic duct of immunocompromised (NSG) mice. Tumors that arise from these intraductally grafted organoids (IGOs) enable the distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively, depending on which organoid they originate from. RNA-sequencing was used to characterize the tumors that resulted from IGO xenografts, and to compare the fast- and slow-progressing IGO tumors. Tumors generated using a traditional orthotopic xenograft model, in which organoids are injected into the parenchyma of the pancreas (i.e. orthotopically grafted organoids, or OGOs), were also sequenced for comparison with the IGO tumors. To further characterize the model, laser-capture microdissection followed by RNA-sequencing was used to compare intraductal to invasive lesions resulting from IGOs. To better understand the connection between KRAS signaling and the fast-progressing phenotype, RNA-sequencing was used to compare cultured organoids in which oncogenic KRAS (GeneID: 3845) was hyperactivated to control organoids, and to compare laser-capture microdissected lesions derived from IGOs of KRAS-hyperactivated organoids to lesions derived from control organoids. To ascertain copy number, low-coverage, whole genome DNA-sequencing was performed on organoids cultured in vitro, and on laser-capture microdissected lesions derived from IGO tumors.

  Study phs002045

• Pediatric Whole Genome Sequencing Diagnostic Utility

  The standard of care for first-tier clinical investigation of the etiology of congenital malformations and neurodevelopmental disorders is chromosome microarray analysis (CMA) for copy number variations (CNVs), often followed by gene(s)-specific sequencing searching for smaller insertion-deletions (indels) and single nucleotide variant (SNV) mutations. We compared diagnostic rate of WGS to CMA and targeted gene testing of 100 patients referred to The Hospital for Sick Children Genetics clinic in 2014. WGS identified genetic variants meeting clinical diagnostic criteria in 34% of cases, representing a 4-fold increase in diagnostic rate over CMA (8%) (p-value = 1.42e-05) alone and &gt;2-fold increase in CMA plus targeted gene sequencing (13%) (p-value = 0.0009). WGS identified all rare clinically significant CNVs that were detected by CMA. In an additional 26 patients, WGS revealed indel and missense mutations presenting in a dominant (63%) or a recessive (37%) manner. We found four subjects with mutations in at least two genes associated with distinct genetic disorders, including two cases harboring a pathogenic CNV and SNV. When considering medically actionable secondary findings in addition to primary WGS findings, 38% of patients would benefit from genetic counselling.

  Study EGAS00001001623

• OAK clinical data

  Relevant clinical data for OAK including treatment arm, histology, overall survival, progression-free survival, and best confirmed overall response.

  Dataset EGAD00001008549

• POPLAR clinical data

  Relevant clinical data for POPLAR including treatment arm, histology, overall survival, progression-free survival, and best confirmed overall response.

  Dataset EGAD00001008548

• FinHer Breast Cancer Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Dataset EGAD00001000871

• JMML targeted sequencing (2013)

  Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic myeloproliferative neoplasm of early childhood initiated by germline or somatic RAS-activating mutations (Chang, Dvorak et al. 2014). Clinical evolution is heterogeneous, with acute myeloid leukemia (AML) transformation in 1/3 of cases and frequent relapses after hematopoietic-stem-cell transplantation (HSCT), although some patients experience spontaneous remission (Locatelli, Nollke et al. 2005; Matsuda, Shimada et al. 2007; Takagi, Piao et al. 2013; Locatelli and Niemeyer 2015). The initiating lesion incompletely predicts outcome, suggesting the involvement of additional mutations. Genetic profiling of a large JMML cohort (n=118), including whole-exome sequencing (WES) in 30 cases, uncovered additional genetic abnormalities in 56 cases (47%). Somatic events were rare (0.38/case/Mb) and restricted to sporadic (47/78; 60%) or NF1-associated (8/8; 100%) JMML. Multiple concomitant genetic hits were identified targeting the RAS pathway in 13/78 (17%), RAC2D63V, which activates the PI3K/PDK1/AKT and the mTORC2 pathways, and a novel pathway for JMML, the polycomb repressive complex 2 (PRC2), in 26/78 (33%) of the sporadic JMML cases. Interestingly, PRC2 imbalance was recently shown to synergize with RAS activation (De Raedt, Beert et al. 2014). JMML outcome was associated to the mutational profile, suggesting a dose-dependent effect for RAS-pathway activation, distinguishing very aggressive JMML rapidly progressing to AML.

  Study EGAS00001001324

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• National Human Genome Research Institute (NHGRI) GENEVA Genome-Wide Association Study of Venous Thrombosis (GWAS of VTE)

  Overview: Our overall long-term goal is to determine risk factors for the complex (multifactorial) disease, venous thromboembolism (VTE), that will allow physicians to stratify individual patient risk and target VTE prophylaxis to those who would benefit most. In this genome-wide association case-control study (1300 cases and 1300 controls) we hope to identify susceptibility variants for VTE. Mutations within genes encoding for important components of the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways are risk factors for VTE. We hypothesize that other genes within these four pathways or within other pathways also are VTE disease-susceptibility genes. Therefore, we performed a genome wide association (GWA) screen and analysis using the Illumina 660W platform to identify SNPs within 1,300 clinic-based, non-cancer VTE cases primarily from Minnesota and the upper Midwest USA, and 1300 clinic-based, unrelated controls frequency-matched on patient age, gender, myocardial infarction/stroke status and state of residence. This is a subset of a slightly larger candidate gene study using 1500 case-control pairs to identify haplotype-tagging SNPs (ht-SNPs) in a large set of candidate genes (n~750) within the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways. Study Populations. Cases. VTE cases were consecutive Mayo Clinic outpatients with objectively-diagnosed deep vein thrombosis (DVT) and/or pulmonary embolism (PE) residing in the upper Midwest and referred by Mayo Clinic physician to the Mayo Clinic Special Coagulation Laboratory for clinical diagnostic testing to evaluate for an acquired or inherited thrombophilia, or to the Mayo Clinic Thrombophilia Center. Any person contacted to be a control but discovered to have had a VTE was evaluated for inclusion as a case. Cases were primarily residents from Minnesota, Wisconsin, Iowa, Michigan, Illinois, North or South Dakota, Nebraska, Kansas, Missouri and Indiana. A DVT or PE was categorized as objectively diagnosed when (a) confirmed by venography or pulmonary angiography, or pathology examination of thrombus removed at surgery, or (b) if at least one non-invasive test (compression duplex ultrasonography, lung scan, computed tomography scan, magnetic resonance imaging) was positive. A VTE was defined as: Proximal leg deep vein thrombosis (DVT), which includes the common iliac, internal iliac, external iliac, common femoral, superficial [now termed "femoral"] femoral, deep femoral [sometimes referred to as "profunda" femoral] and/or popliteal veins. (Note: greater and lesser saphenous veins, or other superficial or perforator veins, were not included as proximal or distal leg DVT). Distal leg DVT (or "isolated calf DVT"), which includes the anterior tibial, posterior tibial and/or peroneal veins. (Note: gastrocnemius, soleal and/or sural [e.g., "deep muscular veins" of the calf] vein thrombosis was not included as distal leg DVT). Arm DVT, which includes the axillary, subclavian and/or innominate (brachiocephalic) veins. (Note: jugular [internal or external], cephalic and brachial vein thrombosis was not included in "arm DVT"). Hepatic, portal, splenic, superior or inferior mesenteric, and/or renal vein thrombosis. (Note: ovarian, testicular, peri-prostatic and/or pelvic vein thrombosis was not included). Cerebral vein thrombosis (includes cerebral or dural sinus or vein, saggital sinus or vein, and/or transverse sinus or vein thrombosis). Inferior vena cava (IVC) thrombosis Superior vena cava (SVC) thrombosis Pulmonary embolism Patients with VTE related to active cancer, antiphospholipid syndrome, inflammatory bowel disease, vasculitis, a rheumatoid or other autoimmune disorder, a vascular anomaly (e.g., Klippel-Tr&#233;naunay syndrome, etc.), heparin-induced thrombocytopenia, or a mechanical cause for DVT (e.g., arm DVT or SVC thrombosis related to a central venous catheter or transvenous pacemaker, portal and/or splenic vein thrombosis related to liver cirrhosis, IVC thrombosis related to retroperitoneal fibrosis, etc.), with hemodialysis arteriovenous fistula thrombosis, or with prior liver or bone marrow transplantation were excluded. Controls. A Mayo Clinic outpatient control group was prospectively recruited for this study. Controls were frequency-matched on the age group (18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+ years), sex, myocardial infarction/stroke status, and state of residence distribution of the cases. We selected clinic-based controls using a controls&#39; database of persons undergoing general medical examinations in the Mayo Clinic Departments of General Internal Medicine or Primary Care Internal Medicine. Additionally persons undergoing evaluation at the Mayo Clinic Sports Medicine Center, and the Department of Family Medicine were screened for inclusion as controls. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to venous thrombosis through large-scale genome-wide association studies of 1,300 clinic-based, VTE cases and 1300 clinic-based, unrelated controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000289

• Renal Cell Carcinoma Tumors From S-TRAC trial (NCT00375674) Whole Transcriptome Sequencing

  We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and other factors such as immune response and that tumor environment may be of greater importance.

  Study EGAS00001006528

• Renal Cell Carcinoma Tumors From S-TRAC trial (NCT00375674) Exome Sequencing

  We report a comprehensive genomic and transcriptomic analysis of tumor samples from 171 patients at high risk for recurrent renal cell carcinoma post nephrectomy from the S-TRAC trial (NCT00375674). We identify gene expression signatures, including STRAC11 (derived from the sunitinib-treated population). The overlap in key elements captured in these gene expression signatures, which include genes representative of the tumor stroma microenvironment, regulatory T cell, and myeloid cells, suggests they are likely to be both prognostic and predictive of the anti-angiogenic effect in the adjuvant setting. These signatures also point to the identification of potential therapeutic targets for development in adjuvant renal cell carcinoma, such as MERTK and TDO2. Finally, our findings suggest that while anti-angiogenic adjuvant therapy might be important, it may not be sufficient to prevent recurrence and other factors such as immune response and that tumor environment may be of greater importance.

  Study EGAS00001006529

• Center for Common Disease Genomics [CCDG] - Cardiovascular ATVB: Atherosclerosis Thrombosis and Vascular Biology

  Italian Atherosclerosis Thrombosis and Vascular Biology study is a prospective, nationwide, case-control study involving 125 coronary care units in Italy. The cases were patients who were hospitalised for a first MI before the age of 45 years and underwent coronary angiography. Acute MI was defined as resting chest pain lasting more than 30 minutes, accompanied by persistent electrocardiographic changes, and confirmed by an increase in total creatine kinase or in the MB fraction to more than twice the upper normal limits. The controls were healthy subjects without a history of thromboembolic disease who were unrelated to the patients, but individually matched with them by age, gender and geographical origin. They were enrolled from among the blood donors or staff of the same participating hospitals. Recruitment of cases and controls took place between 1994 and 2007. This site hosts data from ~60 whole exomes.

  Study phs001592

• Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

  A dataset of ER+PR+ breast tumor samples that were analyzed in order to identify mutation enrichment in cis-regulatory elements and cistrome. The repository includes sequencing data from 88 patients. 26/88 were sequenced using ATAC-seq

  Dataset EGAD00001007650

• GA4GH

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

  Documentation about/projects-and-funders/ga4gh

• Exome-sequencing of human B cell lymphoma cell lines

  26 cell lines derived from human Diffuse Large B Cell lymphomas (DLBCL) or Burkit Lymphomas (BL) were subjected to whole exome sequencing. Exome capture was carried out using the SeqCap EZ Exome Library 2.0 kit (Roche/Nimblegen) and 100 bp single-read sequencing was performed on a HiSeq2500 (Illumina). 82% of the coding region was covered at least 30x.

  Dataset EGAD00001002262

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  Study on RNA-seq data from tumor tissue samples of primary tumors of advanced clear cell renal cell carcinoma patients enrolled in the NIVOREN GETUG-AFU-26 trial who consented to and participated in the translational program. The goal of this study was to assess previously published gene expression signatures and evaluate their association with the benefit and/or resistance to nivolumab, as well as their association with circulating soluble factors.

  Study EGAS50000001057

• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• Germline Genetics of Myelodysplastic Syndromes (MDS) and Acute Myeloid Leukemia (AML)

  Myelodysplastic syndromes (MDS) are part of a heterogeneous and overlapping group of clonal diseases that arise in the hematopoietic stem or progenitor cells and also include acute myeloid leukemia (AML), myeloproliferative neoplasms (MPN), and the hybrid MDS/MPN entities. Individuals with MDS have a high risk of progressing to leukemia, with approximately 30% expected to develop AML. This study evaluates genetic susceptibility to myeloid malignancy using data from population-based case control studies of myelodysplastic syndromes and acute myeloid leukemia in adults (ages 18-85 years) and pediatric MDS cases with banked samples at the Center for International Blood and Marrow Transplant Research (CIBMTR). Adult cases were identified through the Minnesota Cancer Reporting System and controls were recruited from the State Driver's License/Identification Card list. DNA samples were collected via mouthwash collection kits (AML cases and controls) or Oragene saliva collection kits (adult MDS cases and controls). Pediatric MDS samples were banked at CIBMTR prior to receipt of a transplant and DNA was extracted from isolated T cells or whole blood samples. Genotyping data were generated using the Illumina Global Diversity array and quality control and genotype calling was conducted using established best practices. Our primary analyses investigated the contribution of genetic variation to MDS risk and evaluated the role of the killer cell immunoglobulin receptors (KIR) on incidence and survival.

  Study phs002962

• Screening_for_human_epigenetic_variation_at_CpG_islands

  Many human characteristics, including susceptibility to disease, are determined genetically. An unexplored alternative to such genetic determination concerns epigenetic mechanisms such as DNA methylation. CpG islands (CGIs) are generally constitutively hypomethylated, however there are circumstances in which they become heavily methylated and, when coincident with a gene promoter, this invariably causes transcriptional silencing. CGI methylation occurs in normal tissues during processes such as X-inactivation, but abnormal patterns of methylation have also been implicated in disease. The vast majority of evidence relates to cancer, where silencing of multiple genes in this way appears to be a causal contributor to the cancer state. To address the role and extent of CGI methylation in ‘normal’ and diseased cells we applied MBD-affinity purification in conjunction with next generation sequencing in a panel of human brain autopsy samples. These samples represent a panel of individuals as well as specific brain regions and neurological pathologies.

  Study EGAS00001000074

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  Fifty percent of diffuse large B-cell lymphoma (DLBCL) cases lack cell-surface expression of the class-I major histocompatibility complex (MHC-I), thereby escaping immune recognition by cytotoxic T cells. In order to comprehensively identify the mechanisms involved in MHC-I loss, we first performed immunophenotypic analysis of both MHC class-I and -II in 657 cases across the spectrum of B-NHL, revealing that loss of MHC-I, but not MHC-II, is preferentially restricted to DLBCL. We then used whole exome and targeted deep-sequencing to examine genes involved in MHC-I expression in 74 DLBCL samples representative of MHC-I positive and negative cases. We show here that somatic biallelic or monoallelic inactivation of B2M and/or HLA-I is present in 80.9% (34/42) of MHC-I negative tumors. Furthermore, 68.8% (22/32) of MHC-I positive DLBCLs also harbored monoallelic HLA-I genetic alterations (MHC-I positivemono) that lead to allelic imbalance, suggesting allele-specific inactivation. Both MHC-I negative and MHC-I positivemono cases showed a significantly higher mutational burden as well as a higher number of inferred neo-antigens, suggesting co-selection of HLA-I loss and sustained neo-antigen production. Interestingly, the analysis of &amp;gt; 500.000 individuals in two databases revealed homozygosity of germline HLA-I genes in 26-38% of DLBCL patients, a frequency significantly higher than that observed in any other cancer type. In mice, germinal-center B cells lacking HLA-I expression did not progress to lymphoma and were counterselected in the context of oncogene-driven lymphomagenesis, suggesting that additional events are needed to license immune evasion. These results suggest a multi-step process of HLA-I loss including both germ-line and somatic events in DLBCL development, and have direct implications for the pathogenesis and immunotherapeutic targeting of this disease.

  Study EGAS00001005054

• The Mutational Landscape of CTCL and Sezary Syndrome

  Sezary syndrome is a leukemic and aggressive form of cutaneous T-cell lymphoma (CTCL) resulting from the malignant transformation of skin-homing central memory CD4+ T cells. To identify new genetic alterations involved in Sezary syndrome and CTCL transformation we performed whole-exome sequencing of tumor-normal sample pairs from 26 Sezary syndrome and 16 CTCL patients. These analyses revealed a distinctive pattern of somatic copy number alterations in Sezary syndrome including highly prevalent recurrent chromosomal deletions involving the TP53, RB1, PTEN, DNMT3A, and CDKN1B tumor suppressor genes. Mutation analysis identified a broad spectrum of somatic mutations involving key genes involved in epigenetic regulation (TET2, CREBBP, MLL3, BRD9, SMARCA4 and CHD3) and signaling, including mutations in MAPK1, BRAF, CARD11 and PRKG1 driving increased MAPK, NFKB and NFAT activity upon T-cell receptor stimulation. Collectively, our findings provide new insights into the genetics of Sezary syndrome and CTCL and support the development of personalized therapies targeting key oncogenically activated signaling pathways for the treatment of these diseases.

  Study phs000994

• Precision Medicine for ABCA4 Disease: Modifier Alleles

  Genetic variation affecting the structure and function of the ABCA4 protein gives rise to a broad collection of genetically and clinically heterogeneous diseases, collectively known as ABCA4 disease, which are characterized by both phenotypic overlap and variable penetrance and expressivity. These include autosomal recessive Stargardt disease, cone-rod dystrophy, occult maculopathy, bull's eye macular dystrophy, retinitis pigmentosa-like retinal dystrophy, etc. Some phenotypic variation can be attributed to variability of highly penetrant ABCA4 mutations; however, much of the heterogeneity cannot be explained by ABCA4 mutations alone. The concept of Precision Medicine requires, by definition, identification of all genetic variation contributing to specific disease phenotypes. The main goal of this study is to identify all genetic variation resulting in phenotypes compatible with ABCA4 disease, which, in addition to biallelic disease-causing variants in the ABCA4 locus, include cis- and trans-acting modifiers and mutations in genes other than ABCA4.The study was carried out by performing whole exome sequencing (WES) of affected individuals to identify causal and modifying genetic variation for patients with macular dystrophies compatible with ABCA4 disease. All samples were sequenced with the IDT's Exome Research Panel Version 1 with SeqCap EZ Exome v2 and SeqCap EZ Exome v3 capture kits. Samples were sequenced on Illumina next-generation sequencing machines (San Diego, CA, USA) using DRAGEN Bio-IT Platform v. 2.5.1 (Illumina) to align reads to the Genome Reference Consortium Human Build 37, calling variants in accordance with the Genome Analysis Tool Kit (GATK, v.4.0.2.1) Best Practices Workflow, using ATAV (v.7.0.16) variant-calling pipeline. Variants for analysis were restricted to the consensus coding sequencing public transcripts (CCDS release 20) plus 2 base pair (bp) intronic extensions. Variants were annotated using ClinEff (DnaMiner) with Ensembl-HGRCh37.73 annotations.This set of WES data from unrelated patients of different racial and ethnic backgrounds can be stored and shared through dbGaP. These data provide information on frequencies of disease-causing variants in genes other than ABCA4 in patients with macular dystrophies. These also provide frequencies of selected pathogenic and none-pathogenic variants in different ethnicities.

  Study phs002393

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• Everything you need to know about Federated EGA Affiliates: Q&A

  Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

  Blog fega-affiliates-q&a

• Immunogenomics of colorectal cancer response to immune checkpoint blockade

  Molecular and cellular determinants of response to immune checkpoint inhibitors are mostly unknown. Here we use whole exome, RNA and T cell receptor sequencing, imaging mass cytometry, immunohistochemistry and PD1-PDL1 interaction detection to profile 543 regions from 16 colorectal cancers (CRCs) subsequently treated with Pembrolizumab or Nivolumab. Independent of treatment response, CRCs express low levels of PD1 and PDL1 proteins and form less PD1-PDL1 complex than other cancers. Non hypermutated CRCs have no benefit from treatment, show WNT activation and low T cell infiltrates. Among hypermutated CRCs, those with durable benefit have clonal immunogenic alterations, clonally expanded T cells and potential for immune escape through dysfunctional antigen presentation. Responsive tumours are enriched in PD1-expressing cytotoxic and proliferating CD8 T cells and PDL1-expressing antigen presenting macrophages, which form high-density clusters of interacting cells. Our study shows that immune checkpoint inhibitors are most effective in highly infiltrated CRCs where they may release the interactions between macrophages and CD8 T cells thus promoting their priming and expansion in intra-tumour niches.

  Study EGAS00001004438

• Mechanism and Response of Thymoglobulin in Patients with Myelodysplastic Syndrome (MDS)

  In people with MDS, the bone marrow stops making healthy blood cells and instead produces poorly functioning, malformed, and immature blood cells. This can lead to anemia resulting from too few healthy red blood cells, infection resulting from too few healthy white blood cells, and bleeding resulting from too few healthy platelets. The exact cause of MDS remains unknown, but it may be caused by abnormal autoimmune activity in which activated T cells, a type of white blood cell, prevent normal bone marrow production. ATG, a medication that inhibits immune function, can restore normal blood production in some people with MDS, but it is not known how this happens and why it does not happen in all MDS patients. The purpose of this study is to examine the effects of ATG in adults with MDS and to determine which individuals with MDS are most likely to benefit from treatment with ATG. Based on disease severity and likely disease progression, participants will be separated into either a high-risk group or a low-risk group. Participants will be hospitalized for a 4-day period during which they will receive daily infusions of ATG. Oral prednisone will be given 2 days before hospitalization, throughout hospitalization, and then for 14 days after hospitalization to limit the side effects of ATG. Antihistamines and acetaminophen will also be given during hospitalization to reduce the chances of an allergic reaction to ATG. After discharge, all participants will attend monthly study visits that will include blood collection, review of disease symptoms, and evaluation of medication response. At Week 16, participants in the high-risk group will undergo additional blood collection, a bone marrow biopsy, and a thorough evaluation of disease progression and the effects of MDS on daily living abilities. Participants in the low-risk group will undergo these same procedures at Week 24. Follow-up for all participants may last up to 2 years.

  Study phs000697

• Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

  Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

  Study EGAS00001006490

• The Gene Partnership (TGP) - eMERGE Data

  The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children&#39;s Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants&apos; preferences; results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children&#39;s Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

  Study phs000495

• Tumor-associated preferred end coordinates and somatic variants as signatures of circulating tumor DNA

  Cell-free DNA fragmentation is a nonrandom process. We showed that cell-free DNA fragments with ends at certain genomic coordinates had higher likelihoods of being derived from hepatocellular carcinoma. Other coordinates were associated with cell-free DNA molecules originating from the liver. Quantitative assessment of cell-free DNA molecules bearing these respective groups of end signatures correlated with the amounts of tumor-derived or liver-derived DNA in plasma. There were millions of tumor-associated plasma DNA end coordinates across the genome. Due to their high prevalence, they were more readily detectable than somatic mutations as a cancer signature in plasma. Hence, detection of tumor-associated plasma DNA ends may offer a cost-effective means of capturing evidence for the presence of cancer through liquid biopsy assessment.

  Study EGAS00001003160

• Congenital anosmia 2

  Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). Here we obtained genomic DNA from families with multiple individuals with anosmia, suggesting they are congenital. These include those inherited in a manner consistent with dominant and recessive alleles. We have sequenced the exomes of both affected and unaffected family members on the Illumina platform.

  Dataset EGAD00001002228

• Efficacy of nivolumab in pediatric cancers with high mutation burden and mismatch-repair deficiency

  Purpose: Checkpoint-inhibitors have limited efficacy for children with unselected solid and brain tumors. We report the first prospective pediatric trial (NCT02992964) using nivolumab exclusively for refractory non-hematological cancers harboring tumor mutation burden (TMB) ≥5 mutations/megabase (mut/Mb) and/or mismatch-repair deficiency (MMRD). Patients and methods: Twenty patients were screened, and ten ultimately included in the response cohort of whom nine had TMB &gt;10mut/Mb (three initially eligible based on MMRD) and one patient had TMB between 5-10 mut/Mb. Results: Delayed immune responses contributed to best overall response of 50%, improving on initial objective responses (20%) and leading to 2-year overall survival (OS) of 50% (95% CI; 27, 93). Four children, including three with refractory malignant gliomas are in complete remission at a median follow-up of 37-months (range: 32.4-60), culminating in 2-year OS of 43% (95% CI; 18.2, 100). Biomarker analyses confirmed benefit in children with germline MMRD, microsatellite instability, higher activated and lower regulatory circulating T-cells. Stochastic mutation accumulation driven by underlying germline MMRD impacted the tumor microenvironment, contributing to delayed responses. No benefit was observed in the single patient with a MMR-proficient tumour and TMB 7.4 mut/Mb. Conclusions: Nivolumab resulted in durable responses and prolonged survival for the first time in a pediatric trial of refractory hypermutated cancers including malignant gliomas. Novel biomarkers identified here need to be translated rapidly to clinical care to identify children who can benefit from checkpoint-inhibitors, including for upfront management of their cancers.

  Study EGAS00001007393

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926