Search Results - EGA European Genome-Phenome Archive

Stage-1 meta-analysis with GC correction

Dataset EGAD00001004800

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

Targeted gene fusion sequencing (Fus-seq) in mesothelioma

This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

Dataset EGAD00001000361

Mucosal Melanoma transcriptomes

This is an RNA sequencing dataset of 101 mucosal melanoma tumors. The original corresponding study is titled "Diversity of the immune microenvironment and response to checkpoint inhibitor immunotherapy in mucosal melanoma" by J.L. Vos et al., published in JCI Insight.

Dataset EGAD50000000892

Genetic architecture of disease in Greenland is shaped by demographic history, fine-structure, and selection - WGS data

This file set has 448 Greenlandic individuals sequenced using Illumina 150 Paired end sequencing and has an average sequencing depth of 35X. The data is unfiltered, in VCF format, and covers 19.751.308 variants.

Dataset EGAD50000000933

Next-generation sequencing-based comprehensive genetic analysis of undiagnosed disease

The purpose of this study is to perform comprehensive genetic analysis using next-generation sequencers to make genetic diagnosis of "undiagnosed diseases".

Study JGAS000522

Department of Human Genetics at Yokohama City University (YCU) — Data Access Committee

The Data Access Committee at Yokohama City University (Department of Human Genetics) is overseeing controlled access to data for our research manuscripts. Access is granted to bona fide researchers in line with the Data Access Agreement and DUO restrictions.

Dac EGAC50000000770

Helleday_HRAS_Project

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

Study EGAS00001000332

Orphan_Tumour_Study___familial_neuroblastoma

The aim of this study is to study the genomes of ultra rare childhood tumours

Study EGAS00001002171

Landscape and significance of multiple mutations in oncogenes.

This study is a comprehensive pan-cancer study of oncogenic multiple mutations (MMs) which includes long-read whole-genome sequencing data (n = 3).

Study EGAS00001003763

Illumina genome sequencing data for HICF2 craniosynostosis families (Genome Medicine)

BAM files for two families recruited to the HICF2 genome sequencing project due to craniosynostosis. One family is a singleton and the other is an affected mother-daughter duo.

Dataset EGAD00001011373

CRU303 GWAS Raw Data Batch 1 Controls

Raw data files of samples in batch 1 of CRU303 GWAS

Dataset EGAD00010001955

CRU303 GWAS Called Data Batch 1

Called genotypes of samples in batch 1 of CRU303 GWAS

Dataset EGAD00010001951

Extrachromosomal DNA Amplification Contributes to Small Cell Lung Cancer Heterogeneity and is Associated with Worse Outcomes

Small-cell lung cancer (SCLC) is a very aggressive neuroendocrine lung cancer often associated with oncogenic MYC amplifications, which are known to drive SCLC heterogeneity marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states. The genetic mechanisms of MYC amplification and phenotypic plasticity between cell states is not known. Using data from cell-lines and a few patient-derived samples along with integrated whole-genome sequencing, long-range optical mapping, single-cell DNA sequencing, and fluorescence in situ hybridization, we have attempted to successfully characterize extrachromosomal DNA (ecDNA) as the primary source of MYC amplifications and driver fusions in SCLC.

Study phs003190

Transcriptome of Chronic Pain and Disease

The Functional Genomics Section (FGS) is a part of the National Institute of Dental and Craniofacial Research (NIDCR) within the National Institutes of Health (NIH). Research at the FGS focuses on understanding the mechanics involved in nociception through both clinical samples from patients with chronic pain and mouse models of pain. Pain is relayed from the periphery to the central nervous system through specialized sensory neurons known as nociceptors. The cell body of nociceptors resides in neuronal structures that branch off of the spinal cord known as dorsal root ganglia (DRG). The DRG is a heterogenous tissue containing not only sensory neurons like nociceptors, but also glial cells, capillaries, fibroblasts, and resident macrophages. The interaction between the nociceptors and these DRG cell types can have a significant role in affecting neuronal hyperexcitability and downstream pain sensitivity. To better understand the cellular factors involved in producing conditions of chronic pain, DRGs from consenting organ donors were collected from individuals experiencing pain disorders such as painful diabetic neuropathy and rheumatoid arthritis. A multi-omics approach is being used to identify molecular mechanisms that lead to pain hypersensitivity in patients with chronic pain.  

Study phs002548

Urethral Microbiome of Adolescent Males

Urethral microbiome of adolescent males is designed to characterize the microbial communities resident in the urethra of young men, to identify differences in these communities as a function of race/ethnicity, circumcision status, sexual exposures, and uro-genital symptoms. We collect detailed sexual behavior and symptoms data using cellular telephones with Internet access. Specimens are routinely collected at monthly intervals, and intermittently following reported symptoms, specific sexual exposures, or identification of a sexually transmitted infection. We also collect periodic samples from the penile coronal sulcus to better characterize its relationship to the urethral micriobial communities. Participants are ages 14 - 17 at enrollment, and prior history of sexual exposure is not required for participation. Parental permission is obtained for each participant. The planned duration of followup is up to 4 years allowing for prospective observation of both physical and behavioral maturation from middle adolescence into young adulthood. The overall objectives of the project are to better characterize the healthy male urethral microbiome, and to use this information to better understand acquisition of urethritis and sexually transmitted infections, as well as chronic genital pain and prostatitis syndromes that become common among young adults.

Study phs000259

An APOBEC Cytidine Deaminase Mutagenesis in Human Cancers

Reprinted from Roberts et al. "An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers", Nature Genetics, 45:970-976, 2013, with permission of Nature Publishing Group: Recent studies indicate that a subclass of APOBEC cytidine deaminases, which convert cytosine to uracil during RNA editing and retrovirus or retrotransposon restriction, may induce mutation clusters in human tumors. We show here that throughout cancer genomes APOBEC-mediated mutagenesis is pervasive and correlates with APOBEC mRNA levels. Mutation clusters in whole-genome and exome data sets conformed to the stringent criteria indicative of an APOBEC mutation pattern. Applying these criteria to 954,247 mutations in 2,680 exomes from 14 cancer types, mostly from The Cancer Genome Atlas (TCGA), showed a significant presence of the APOBEC mutation pattern in bladder, cervical, breast, head and neck, and lung cancers, reaching 68% of all mutations in some samples. Within breast cancer, the HER2-enriched subtype was clearly enriched for tumors with the APOBEC mutation pattern, suggesting that this type of mutagenesis is functionally linked with cancer development. The APOBEC mutation pattern also extended to cancer-associated genes, implying that ubiquitous APOBEC-mediated mutagenesis is carcinogenic.

Study phs000677

Kids First: Whole Genome Sequencing of Nonsyndromic Craniosynostosis

The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Nonsyndromic craniosynostosis (NCS) is a common, major structural birth defect - due to the premature fusion of one or more cranial sutures - that requires extensive surgical correction and is associated with considerable ongoing medical problems and health care costs. Because little is known about the causes of NCS, whole genome sequencing will help advance knowledge of genetic factors contributing to the etiology of NCS. Data from this project will lead to a better understanding of biological processes involved in the etiology of NCS and provide critical insights for development of early diagnostic tools and therapeutic strategies.

Study phs001806

CIDR Whole Exome Sequencing in Joubert Syndrome

The purpose of this study is to identify new genetic causes of neurodevelopmental diseases (NDDs) in the Joubert syndrome (JS) spectrum. Joubert syndrome is a recessive disease characterized by cerebellar vermis hypoplasia. Our currently funded NINDS award entitled "Molecular characterization of Joubert syndrome" seeks to identify new genetic causes through a variety of molecular strategies. Although our previous strategies involved whole genome SNP-scans, followed by candidate gene sequencing to arrive at identification of new JS causes, we have recently moved to Whole Exome Sequencing (WES) as a highly efficient methodology that is optimized for recessive disease. In this pilot project, CIDR has sequenced DNA on probands from 20 inbred families with JS spectrum disorders in which known causes have been excluded, that have not previously undergone genome-wide SNP scans. These paired end reads will be subject to our established bioinformatics pipeline including HOMOZGYOSITY, SNP and INDEL callers in our lab to identify potentially deleterious sequence changes (PDSC). This is followed by analysis to include testing each PDSC for segregation in the whole pedigree, for occurrence in a ethnically-matched cohort, as well as a defined patient cohort patients, in order to validate new NDD genes.

Study phs000382

NHLBI TOPMed: Trans-Omics Analysis for Congestive Heart Failure (TOPCHeF)

Heart failure (HF) is a serious, common, morbid condition that has a huge public health impact. In 2012 alone, there were >1M hospital discharges and >1.7M outpatient visits where HF was the principal diagnosis. HF is the most common hospital discharge diagnosis of the elderly and led to costs in excess of $30B in 2012. Unfortunately, HF therapies have not impacted the 50% 5-year mortality over the past two decades. Our laboratory focuses on cardiomyopathies (CMs) and HF. Dilated cardiomyopathy (DCM) has been a main focus of our laboratory and is the first and third most frequent cause of heart transplantation and HF, respectively. Attention is shifting from the mere identification and cataloging of CM/HF genes and mutations to understanding the molecular and functional cellular processes that drive HF. In this study, we will utilize whole genome sequencing (WGS) and transcriptome analysis of left ventricle samples from adult and pediatric samples from heart banks at the University of Colorado Anschutz Medical Campus and the Children's Hospital Colorado to develop a complete understanding of left ventricular biology and a partial understanding of HF inferred through the lens of a single-chamber perspective.

Study phs002038

Increased mutation accumulation during fetal development in Down syndrome

Children with Down syndrome (DS) show a high incidence of leukemia, which is preceded by transient myeloproliferative disorder (TMD) in neonates. TMD is characterized by mutations in GATA1 that accumulate during fetal development, indicating that additional mutagenesis is required for leukemogenesis. Abnormalities in chromosome numbers can result in a mutator phenotype. However, it is unknown whether a trisomy of chromosome 21 (T21) results in enhanced mutation accumulation during human development. Here, we determined the mutational consequences of a constitutive T21 in DS fetuses compared to disomy 21 cells (D21) of D21 fetuses. We found that D21 fetal HPSCs had a higher somatic mutation rate compared to healthy adults HSPCs. Moreover, we observed an increase in somatic mutation load in T21 cells of DS fetuses, which was already apparent during the first cell divisions of embryogenesis. The mutation load could be explained by processes that are active during normal fetal development and were similar to those observed in TMD blast cells. Our study shows that T21 causes an increase in somatic load in fetal cells of DS fetuses, which may contribute to leukemia development early in life.

Study EGAS00001003982

Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers

Infiltration of human cancers by T cells is generally interpreted as a sign of immune recognition, and there is a growing effort to reactivate dysfunctional T cells at such tumor sites. However, these efforts only have value if the intratumoral T cell receptor (TCR) repertoire of such cells is intrinsically tumor-reactive, and this has not been established in an unbiased manner for most human cancers. To address this issue, we analyzed the intrinsic tumor-reactivity of the intratumoral TCR repertoire of CD8+ T cells in ovarian and colorectal cancer – two tumor types for which T cell infiltrates form a positive prognostic marker. Data obtained demonstrate that a capacity to recognize autologous tumor is limited to approximately 10% of intratumoral CD8+ T cells. Furthermore, in two out of four patient samples tested, no tumor-reactive TCRs were identified, despite infiltration of their tumors by T cells. These data indicate that the intrinsic capacity of intratumoral T cells to recognize adjacent tumor tissue can be rare and variable, and suggest that clinical efforts to reactivate intratumoral T cells will benefit from approaches that simultaneously increase the quality of the intratumoral TCR repertoire.

Study EGAS00001003119

Epigenome wide DNA methylation assay of gingivo-buccal oral squamous cell carcinoma using single base resolution high throughput array

Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out epigenomic (n=87) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India and genome-wide DNA methylation assays were performed. DNA was isolated using DNeasy Blood and Tissue Kit (Qiagen). The purity and concentration was estimated using NanoDrop 2000 (Thermo Fisher Scientific). Approximately 500 ng genomic DNA from each sample was used for sodium bisulfite conversion using the EZ DNA methylation Gold Kit (Zymo Research, USA). Genome-wide DNA methylation was assayed using iScan (Illumina), for paired tumour and adjacent normal samples of 25 patients using the Infinium Human Methylation450 BeadChip and of 62 patients using the Infinium MethylationEPIC BeadChip.

Study EGAS00001003896

Allele-specific expression of GATA2 due to epigenetic dysregulation in double mutated CEBPA AML

Transcriptional deregulation is a central event in the development of acute myeloid leukemia (AML). To identify potential disturbances in gene regulation, we conducted an unbiased screen of allele-specific expression (ASE) in 209 AML cases. The gene encoding GATA binding protein 2 (GATA2) displayed ASE more often than any other myeloid or cancer-related gene. GATA2 ASE was strongly associated with CEBPA double mutations (CEBPA DM), with 95% of cases presenting GATA2 ASE. In CEBPA DM AML with GATA2 mutations, the mutated allele was preferentially expressed. We found that GATA2 ASE is a somatic event lost in complete remission, supporting the notion that it plays a role in CEBPA DM AML. Acquisition of GATA2 ASE involved silencing of one allele via promoter methylation, compensated by overactivation of the other allele, thereby preserving expression levels. Notably, promoter methylation was also lost in remission together with GATA2 ASE. In summary, we propose that GATA2 ASE is acquired by epigenetic mechanisms and is a prerequisite for the development of AML with CEBPA DM. This finding constitutes a novel example of an epigenetic hit cooperating with a genetic hit in the pathogenesis of AML.

Study EGAS00001004684

Targeted sequencing data and shallow whole genome sequencing data of Follicular lymphoma.

Contain data of 2 studies 1: 82 nodal stage 1 FL cases and 139 stage III/IV cases 2: 44 watch and wait stage III/IV and 46 Immediate treatment stage III/IV targeted sequencing data of 369 genes and 12 translocation regions whole genome shallow sequencing data

Study EGAS00001005755

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

Study EGAS00001008040

sn-RNAseq profiling of the impact of a cytokine storm model in human cardiac organoids

We developed conditions to model conditions of diastolic dysfunction caused by inflammatory factors in human cardiac organoids. Our organoid model is based on conditions promoting maturation (Mills et al., PNAS, 2017 and Voges et al., In Revision) and incorporating human pluripotent stem cell derived cardiomyocytes, epicardial cells, fibroblasts, endothelial cells and pericytes. Following 15 days of differentiation (Voges et al., Development, 2017) we formed human cardiac organoids incorporating both our multicellular differentiation (Mills et al., PNAS, 2017) and additional endothelial cells (Voges et al., In Revision). After another 12 days of maturation in 5 days maturation medium and 5 days weaning medium (Voges et al., In Revision) human cardiac organoids were either treated with weaning medium or “cardiac cytokine storm” comprised of 100 ng/ml IFNg, 10 ng/ml IL-1 β and 10 µg/ml poly(I:C). After 48 hours human cardiac organoids were harvested and snap frozen in -80C before nuclei isolation and single nuclei RNA sequencing.Pooled hCO (~40) were homogenized in 4 mL lysis buffer (300 mM sucrose, 10 mM Tris-HCl (pH = 8), 5 mM CaCl2, 5 mM magnesium acetate, 2 mM EDTA, 0.5 mM EGTA, 1 mM DTT)(all Sigma-Aldrich) with 30 strokes of a dounce tissue grinder (Wheaton). Large pieces of hCO were allowed to settle and homogenate was passed through pre-wetted 40 µm cell strainers (Becton Dickinson). Remaining hCO material in the douncer was resuspended in 4 mL and the douncing and filtering steps were repeated twice. All steps of the homogenization were performed on ice. The filtered homogenate was centrifuged at 1500 x g for 5 min at 4oC. Nuclei pellets were then re-suspended in PBS. A fraction of resuspended nuclei were then stained with hoechst nuclear stain (1:500 dilution) and counted on a haemocytometer under fluorescent microscope.The nuclei were then re-centrifuged (1500 x g for 5 min at 4°C) and resuspended at a density to load ~5,000 nuclei per sample. Cell were loaded into the Chromium Controller (10X Genomics) for gel bead emulsion (GEM) formation. Library preparation was conducted according to the manufacturer’s recommended protocol using the Chromium Next GEM Single Cell 3’ GEM, Library & Gel Bead Kit v3.1. Libraries were sequenced on the NextSeq 500/550 v2 (Illumina) with 150 bp reads.In the snRNA-seq we note the lower than expected percentage of non-myocytes and the loss of endothelial cells (Mills et al., PNAS, 2017 and Voges et al., In Revision), indicating the protocol requires further optimization for hCO samples.

Study EGAS00001005174

CRU303 GWAS Raw Data Batch 1 Cases

Raw data files of samples in batch 1 of CRU303 GWAS

Dataset EGAD00010001954

A common single nucleotide variant in T is strongly associated with chordoma

Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics.

Dataset EGAD00001000226

Genomic characterization of co-existing biliary tract intraepithelial neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer

Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we performed whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients.

Dataset EGAD00001007792

Transcriptome of (peripheral blood), from donor Sample A, replicate 1 FACS processing technical replicates

FACS processing technical replicates

Dataset EGAD00001010086

The Role of E2F4 in Controlling Resistance to Irinotecan (CPT-11) in Human Colon Cancer

This study reports the results of RNA sequencing (RNA-seq) experiments performed on three isogenic clones of the human HT29 colon cancer cell line, genetically engineered to achieve the selective inactivation of the adenovirus early 2 (E2) gene transcription factor 4 (E2F4) protein, a key functional component of the multimeric transcriptional repression complex known as the dimerization partner (DP), retinoblastoma-like (RB-like), E2F and multi-vulva class B (MuvB) complex (DREAM). In previous studies, we identified E2F4 as a key regulator of colorectal cancer (CRC) resistance to irinotecan (CPT-11), a cytotoxic agent that stands at the backbone of multiple chemotherapy regimens for the treatment of metastatic CRCs. The molecular mechanisms linking E2F4 to irinotecan resistance, however, remain poorly understood. The present study was designed to identify which genes are under the transcriptional control of E2F4, either at baseline or following exposure to SN38 (i.e., the active metabolite of irinotecan, generated in vivo by biotransformation in the liver) in order to clarify the role played by E2F4 in shaping colon cancer resistance to chemotherapy. The cell line used for this study (HT29) is aneuploid and contains three copies of the E2F4 gene, because of a trisomy of chromosome 16, where the E2F4 gene is located (Kawai et al., Genes, Chromosomes & Cancer, 34:1-8, 2002; PMID: 11921276). HT29 cells were infected with lentivirus vectors encoding for CRISPR/Cas9 constructs designed to selectively inactivate the E2F4 gene, using three distinct guide-RNAs (gRNAs), each targeting a different sequence within the proximal exons of the E2F4 gene (exon 1, exon 2). Lentivirus-infected cells were sub-cloned by single-cell fluorescence-activated cell sorting (FACS), based on the differential expression of a fluorescent reporter (EGFP) expressed in tandem with the gRNAs. Isogenic clones (EGFP+) were then screened to identify those with a tri-allelic knock-out, as revealed by both genetic sequencing of the E2F4 gene (revealing the presence of three distinct frameshift mutations) and Western blot (revealing complete loss of E2F4 protein expression). The study includes twelve (n=12) RNA-seq experiments, representative of 3 experimental replicates (i.e., three distinct isogenic clones of the HT29 cell line, each displaying complete loss of E2F4 expression) and 3 negative controls (i.e., three independent preparations of the parent HT29 cell line, infected with a lentivirus vector encoding for a non-targeting gRNA) exposed to 2 distinct in vitro cell culture conditions: a) treatment with SN38 resuspended in dimethyl sulfoxide (DMSO); or b) treatment with DMSO alone (negative control). The in vitro treatment regimen used for SN38 (32 nM, 24 hours) was designed so that the exposure to SN38 experienced in vitro by HT29 cells would mirror the exposure to SN38 experienced in vivo by malignant tissues, as measured, for example, in metastatic CRC patients receiving a standard dose of irinotecan (180 mg/m2) administered by intravenous infusion over 90 minutes (Deyme et al., Cancer Chemotherapy and Pharmacology, 88:247-258, 2021; PMID: 33912999).

Study phs003560

NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in GLAUGEN Samples

This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the GLAUGEN (Glaucoma Gene Environment) initiative have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the GLAUGEN description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the GLAUGEN study. From the MEEI, 50 patients were selected from POAG pedigrees, to include all the probands genotyped by CIDR and are currently undergoing exome sequencing, and to include additional genotyped probands who belong to pedigrees of sufficient size and structure that parent of origin effects could be evaluated. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000308 (Geneva - Glaugen GWAS Study).

Study phs000461

Genetic defects in familial renal disorders

Several different genes cause, when mutated, increased urinary phosphate excretion and hypophosphatemia leading to rickets/osteomalacia; however, the majority of phosphate-wasting disorders has not yet been defined at the molecular level. Identification of phosphate-regulating genes has provided important novel insights into the mechanism contributing to phosphate homeostasis, which remains incompletely understood. We therefore pursue exome-wide nucleotide sequence analysis to define the underlying mutations, which is expected to provide novel insights into the regulation of this important mineral. Virtually nothing is known about the genetic mutations that cause non-syndromic structural abnormalities involving the urinary tract, which represent about 50% of the causes of end-stage renal disease (ESRD). The completion of the human genome project and the technological advances that allow low cost whole exome sequencing have now made it feasible to readily search for the cause of different inherited disorders in humans, particularly if clinical information and genomic DNA is available from larger kindreds with multiple affected members that can be used for mapping the disease-causing genetic locus. Furthermore, catalogs were generated that document the expression profiles of numerous genes during embryonic, fetal, and postnatal development, thereby supporting the exploration of kidney involvement in animal models of different diseases and in human genetic syndromes. We therefore plan to define the mechanisms leading to inherited disorders of the urogenital tract and the kidneys by establishing the causative genetic defects through a combination of genetic mapping and whole exome sequencing. Hajdu-Cheney Syndrome (HCS) is a rare autosomal-dominant skeletal disorder characterized by severe osteoporosis, acroosteolysis of the distal phalanges, renal cysts and other abnormalities. Our goal is to identify the genetic cause of HCS using exome sequencing. Opsismodysplasia is a very rare recessive spondylometaphyseal dysplasia characterized by delayed epiphyseal ossification, shortness of bones and sometimes low serum phosphate levels. Discovery of the causing mutation will give us insights into the pathogenesis of this often lethal disease.

Study phs000477

CaBagE: a Cas9-Based Background Elimination Strategy for Targeted, Long-Read DNA Sequencing

While repeat-expansion polymorphisms are known to underlie several developmental and neurological disorders, technological limitations have inhibited the ability to resolve accurate genotypes for these variants. A pertinent example is the (CCCCGG)n repeat expansion in C9orf72 that segregates with up to 40% of familial amyotrophic lateral sclerosis (ALS) cases. There is a clear relationship between this repeat expansion and neurodegeneration. However, widely-used short-read sequencing is ill-suited to characterize the C9orf72 repeat expansion due to polymerase slippage over low complexity sequences and the inherently limited mapping/haplotype resolution of redundant short sequences. Consequently, researchers and physicians must rely on crude variant characterization methods (e.g. Southern blots), which limit direct genotype-phenotype associations and create challenges for the diagnosis of disease in patients with atypical clinical presentation. In contrast, ultra-long (e.g., 10-150kb) sequencing reads generated by Oxford Nanopore Technologies (ONT) enable direct measurement of loci containing complex structures without being subject to amplification or alignment bias. We are therefore developed a molecular and computational framework for targeted sequencing and quantification of pathogenic repeat expansions by combining Cas9 and amplification-free sequence capture methods with Nanopore long-read sequencing technology. First, extracted high molecular weight DNA is bound by Cas9 on either side of a DNA target. Bound Cas9 protects the target DNA from challenge by processive exonucleases. Unprotected (off-target) DNA is degraded with exonucleases and the remaining sample is sequenced using the ONT MinION sequencer. Then, base-called reads are aligned to the target locus and repeat copy number genotypes are estimated using a Gaussian Mixture Model. We applied this molecular and computational framework to 2 ALS patients with C9orf72 repeat expansions with biospecimens available from the NINDS collection from Coriell. Genotype estimates produced with CaBagE were commensurate with genotypes derived from repeat-primed PCR for each individual.

Study phs002368

Molecular Etiology of Early-Onset Dystonia

Primary torsin dystonias (PTD) are a group of movement disorders characterized by twisting muscle contractures, where dystonia is the only clinical sign (except for tremor) and there is no evidence of neuronal degeneration or an acquired cause. Eleven genes have been mapped for primary dystonia including DYT1 (TOR1A), DYT2, DYT4 (TUBB4A), DYT6 (THAP1), DYT7, DYT13,, DYT17, DYT21, CIZ1, DYT24 (ANO3), and DYT25 (GNAL); however, only 3 genes (TOR1A, THAP1, and GNAL) have mutations in early onset dystonia patients. Each is inherited as an autosomal dominant trait but with reduced penetrance, meaning that individuals can carry the mutation but do not show clinical symptoms. The most common form of PTD is adult onset focal accounting for about 90% of all cases of dystonia with a prevalence estimated at 30/100,000 in the general population. A small percentage of focal cases are due to mutations in CIZ1, ANO3, THAP1, TUBB4A, and GNAL, but the vast majority is unaccounted for and is most likely multigenic or multifactorial. In this grant, focusing on early onset PTD, we will uncover genes that influence the penetrance of DYT1 (TOR1A) dystonia through GWAS and exome sequencing studies. We will identify other genes for early onset PTD using exome sequencing and determine whether variants within the identified early onset PTD genes or the pathways associated with these genes contribute to susceptibility in the most prevalent form of PTD, focal dystonia, using a case:control association study. The proposed research will identify novel PTD risk factors and genes, which in turn should reveal shared and intersecting pathways leading to a better understanding of the molecular basis of PTD and provide the underpinnings for developing new treatments. Additionally, insight into the factors that modulate disease penetrance would be a first step in determine whether these could be modified leading to a reduced incidence of the disease.

Study phs001733

International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

Oral cavity squamous cell carcinoma (OSCC) is the major subtype (~90%) of oral cancer, which is leading cancer with high mortality worldwide. The environmental risk factors associated with OSCC are quite different in Taiwan as compared to other populations. In most non-Taiwanese populations, OSCC is often associated with tobacco chewing, cigarette smoking, alcohol drinking, or human papillomavirus (HPV) infection. In Taiwan, in contrast, the OSCC occurs mainly in males aged 30 years or older who have habitual betel nut chewing, cigarette smoking, and alcohol drinking. To uncover molecular mechanisms and identify new therapeutic strategies of oral squamous cell carcinoma, this study recruited 112 treatment-naïve OSCC patients and generated multi-omics data, including WES, RNA-Seq, TMT-labeled proteomes, and phosphoproteomes from paired normal/tumor tissues. We have investigated our multi-omics data, covering molecular characterizations such as mutation signatures, impacts of mutations on RNA/protein/phosphoprotein, RNA-protein correlation, somatic copy number alteration, and the relationship with RNA & protein, proteome, and phosphoproteome analysis (T vs NAT), novel peptides (somatic variants, neoantigens, CT antigens, T cell receptors, etc.), as well as molecular subtyping (& pathway analysis). Notably, we have discovered a higher frequency of APOBEC3B deletion polymorphism in the Taiwanese population, and APOBEC3A is a potential prognostic biomarker. Our proteogenomic data enable us to further stratify patients into four groups based on APOBE3A expression level, which is found inversely correlated with EGFR expression. Therefore, the patients with high EGFR and low APOBEC3A expression may benefit from anti-EGFR therapy, while those with low EGFR and high APOBEC3A expression may benefit from immunotherapy. To clarify if there is an interaction between genetic polymorphisms and betel nut chewing habit in Taiwanese OSCC, we plan to concurrently evaluate the effect of habitual betel nut chewing on the gene mutation pattern, the dysregulated protein/phosphoproteins as novel biomarkers and/or therapeutic targets, and the molecular subtyping of patients for effective treatments. 

Study phs002580

McGill Epigenomics Mapping Centre

The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

Study EGAS00001000995

Effects of interferon-gamma treatment on human small intestinal organoids generated from healthy donors

The intestine is vulnerable to interferon-gamma as intestinal epithelial stem cells undergo cell death when exposed to interferon-gamma. Here, we developed a novel human intestinal organoid-based 3D model system to study the effects of interferon-gamma-induced intestinal epithelial damage at the RNA level. We treated organoids with 10 ng/mL for either 6 or 18h. Knowledge generated with this dataset is relevant for a variaty of intestinal pathologies with an immune component, for instance graft-versus-host disease.

Study EGAS50000000083

Washington University PDX Development and Trial Center

This data set is a collection of patient specimens from common and rare cancers that have been developed into patient-derived xenograft (PDX) models at the Washington University PDX Development and Trial Center (WU-PDTC). The goal of the PDTC is to develop and characterize PDX models, gaining insight into tumor biology, and validating biomarkers across all major tumor types. Pre-clinical experiments in these PDX models will be used to advance our ability to predict clinical responses to new molecularly targeted agents under development.

Study phs002305

NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy

The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study.

Study phs001293

Bladder Chemotherapy Responders

Cisplatin-based chemotherapy is the standard of care for patients with muscle invasive urothelial carcinoma. Pathologic downstaging to pT0/pTis after neoadjuvant cisplatin-based chemotherapy is associated with improved survival, and some patients with metastatic disease achieve complete responses to these therapies. However, the molecular determinants of cisplatin response are incompletely understood. We performed whole exome sequencing on tumor and germline DNA from patients with muscle invasive or metastatic urothelial carcinoma who received cisplatin-based chemotherapy to identify somatic mutations that occurred preferentially in cisplatin responders.

Study phs000771

Genome Wide Association Study of Chronic TMD: Discovery Phase

The OPPERA project is investigating effects of genetic, physiological, psychological and clinical factors on the risk of developing painful temporomandibular disorder (TMD). This case-control study is a discovery-phase genome wide association study that aims to identify commonly-occurring genetic variants associated with chronic TMD. It represents the first step in a series of studies that seek to identify the genetic background of TMD. For related phenotype and targeted genotype data, please see additional studies from the OPPERA project at dbGaP phs000761).

Study phs000796

African American Adolescent Idiopathic Scoliosis Whole Genome and Whole Exome Study

Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. The causes of scoliosis are only now being discovered yet are important for predicting outcome and need for surgery. Prior studies have investigated the causes of scoliosis, including common and rare variant risk factors, but have mostly used populations consisting of Asian or European ancestry. It is essential that we determine what the risk factors are in all populations so that we can delivery equitable care to all individuals.

Study phs003136

High-throughput determination of the antigen specificities of T cell receptors in single cells

High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.

Study phs001678

Characterization of copy number quiet oral cancer

Copy number quiet head and neck squamous cell carcinoma are a distinct subset with relatively good prognosis. Previous work has indicated this subset is most commonly found in the oral cavity and is highly enriched for HRAS and CASP8 mutations. TP53 mutations are much less common than in CNA-quiet oral cancers. In this study we corroborate the validity of CNA-quiet tumors as a distinct subset in a large OSCC cohort and further chart clinical, genomic, and immunological characteristics of this subset.

Study EGAS50000000558

Observational studies using advanced analytical techniques to understand the biological functions of kidney component cells

The purpose of this study is to establish a foundation for understanding the functions of kidney component cells and the biology of renal disease. Single cell and spatial transcriptome analyses of human kidney component cells will be performed to analyze the gene expression profiles of those cells and explore their relationship between the gene expression profiles and clinical parameters. The research foundation established here is worthwhile for understanding disease mechanisms in the kidney or discovering novel therapeutic drugs for renal disease.

Study JGAS000736

Transcriptome and epigenomic landscape of cytotrophoblasts from normal and HDP placentas

Hypertensive isorders of pregnancy (HDP) is a severe pregnancy-related disorder that poses significant risks to both maternal and fetal health. Dysfunctional placental development is one of the major contributors to the onset of HDP. In this study, we investigated the gene expression and epigenomic modifications in cytotrophoblasts from normal and HDP placentas. The information obtained in this study contributes to the growing body of knowledge aimed at improving the diagnosis, management, and treatment of HDP.

Study JGAS000667

PEVOsq

The PEVOData PEVOsq basket trial is an open-label, multi-center, phase II trial investigating the combination of pembrolizumab (an immune checkpoint inhibitor) with vorinostat (a histone deacetylase inhibitor). This trial focuses on treating patients with recurrent or metastatic squamous carcinomas, including cancers of the cervix, head and neck, anus, vulva/vagina, penis, and lung. The aim is to evaluate the efficacy and safety of this combination, with pembrolizumab administered every 3 weeks and vorinostat daily. Outcomes include overall response rate and progression-free survival.

Study EGAS50000000731

Metabolomic and transcriptomic analyses identify metabolic alterations and immune suppression in ovarian cancer

The objective of this study is to identify metabolic alterations and related phenotypes specific to ovarian cancer by performing metabolomic analysis of plasma and tissue samples. In addition, transcriptomic analysis is conducted to investigate the relationship between metabolic status and immune-related gene expression. By integrating metabolomic and transcriptomic data, this study aims to clarify how metabolic reprogramming contributes to tumor progression and immune suppression, particularly the reduction of natural killer (NK) cell activity, in ovarian cancer.

Study JGAS000831

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