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• Genomic Landscape of Colorectal Cancer in a Multi-Ancestry Cohort

  Elucidating the tumor mutational landscape of colorectal cancer (CRC) in admixed and ancestrally diverse populations is essential to enable precision medicine advancements that benefit individuals of all backgrounds. This study draws from the Latino Colorectal Cancer Consortium (LC3) and other prior initiatives to characterize and examine the somatic mutational patterns of colorectal tumors in Hispanic/Latino/Latina patients (henceforth referred to as Latino) as compared to other racial and ethnic populations. It includes paired tumor-normal whole-exome sequencing from 718 patients with primary CRC (128 Latino and 469 non-Latino individuals) to investigate the associations between somatic mutational features and both self-reported ethnicity and genetic ancestry. Somatic mutations and inherited variants were called, and global genetic ancestry proportions (African, Asian, European, Native American) were estimated from inherited variants using ADMIXTURE based on reference samples from the 1000 Genomes Project (1KGP) and the Population Architecture using Genomics and Epidemiology (PAGE) Study. Associations between genetic ancestry and gene-level mutational status, microsatellite instability status, and tumor mutational burden were estimated using logistic regression, after adjusting for age at diagnosis, sex, tumor location, and stage.

  Study phs003464

• National Human Genome Research Institute (NHGRI) Clinical Sequencing Exploratory Research (CSER) The MedSeq Project: Integration of Whole Genome Sequencing into Clinical Medicine (HG006500)

  Whole genome sequencing (WGS) and whole exome sequencing (WES) services are currently available to and being utilized by physicians and their patients in both research and clinical settings, and recently to anyone in the general public via direct-to-consumer companies. But the widespread availability and use of WGS and WES in the practice of clinical medicine is imminent. In the very near future, sequencing of individual genomes will be inexpensive and ubiquitous, and patients will be looking to the medical establishment for interpretations, insight and advice to improve their health. Developing standards and procedures for the use of WGS information in clinical medicine is an urgent need, but there are numerous obstacles related to integrity and storage of WGS data, interpretation and responsible clinical integration. The MedSeq Project is an exploratory trial of WGS in clinical medicine. At the conclusion of this study, we will have helped create innovative protocols and novel outcome measures that can be applied safely in future large-scale multi-site randomized clinical trials with larger numbers of physicians from broad specialties and with more economically and ethnically diverse patients. Together with our colleagues from across the nation through the U01 consortium formed as a result of this funding from the NIH, we will have invented a process of implementation and evaluation whereby the fruits of the Human Genome Project can be applied for the first time to the daily practice of medicine for the betterment of human health. The objectives of the MedSeq Project are to: Recruit, consent and enroll 2 study groups: 10 primary care physicians and 100 of their healthy middle-aged patients 10 cardiologists and 100 of their patients with cardiomyopathy. Randomize each study group to receive standard of care versus standard of care plus WGS. Monitor the entire protocol for subject safety. Only half the enrolled patients were selected for sequencing. Fifty subjects were selected from the primary care cohort and fifty were selected from the cardiomyopathy cohort. Whole genome sequencing was performed at 30x coverage in Illumina's CLIA-certified laboratory on these 100 individuals. Generate and optimize an algorithm for interpreting WGS data covering the spectrum of human genetic variation, in terms of both previously reported and novel variants likely to influence the health of patients. Create patient reports and provide an interface for communicating clinically relevant genomic information to practicing physicians. Describe physicians' and patients' attitudes toward, and preferences for, the disclosure of WGS results at the start of the study. Evaluate physicians' experiences with receiving and interpreting patients' genetic test results and how they communicate these results to their patients. Explore how patients respond to and use WGS results by administering validated scales of psychological impact, personal utility, and behavioral responses, as well as economic and health outcomes. Although we do not have a large enough sample size for statistical comparisons of outcomes, we will conduct exploratory comparisons: Exploratory Hypotheses: Patients who receive WGS results will show equivalent levels of distress compared to patients who receive family history only. Patients with higher genetic literacy and better understanding will report greater satisfaction and less decisional regret. Patients who receive WGS will (a) be more likely to change health behaviors and (b) utilize more health care resources than those who do not receive WGS.

  Study phs000958

• Submission FAQ

  Submission FAQ Before Submission Is the EGA the right archive for my data? The most suitable archive for your data is dependent on the type of data you are wishing to submit and whether the data require public or controlled access. Public access is defined as complete and open access to all submitted data. On the contrary, controlled access, exerted by the EGA, requires formal applications to be made to access the submitted data files and metadata. EGA only accepts human-derived data subject to controlled access. If your submission contains other types of data, please choose the appropriate repository for it (see image below): ENA, EVA, ArrayExpress, BioSD and GWAS catalog.  Should your submission be subjected to controlled access? Data access conditions are normally defined in the original informed consent agreements signed by the participants involved in your study. All data submitted to the EGA is subject to controlled access. These consents prevent the derived data files, potentially identifiable, from being dispersed by open and public access. Controlled access data often refers to human data derived from medical research and consortium projects. If in doubt, consult the informed consent agreements that apply to your study The EGA enables you to hold a submission before publication. What data types can be submitted to the EGA? Data types accepted by the EGA can be split into three categories: Sequences: both in generic and platform-specific formats. Array-based: from raw signal files to processed matrices. Phenotypes: all possible phenotype formats are accepted. All manufacturer-specific raw data formats derived from major next generation sequencing platforms are accepted. Also generic sequence formats: flat reads in a FASTQ file, aligned sequences (BAM or CRAM files) as well as sequence variation files in VCF format. All array-based technologies are accepted, including raw data, intensity and analysis files, without any restriction on data formats accepted. We also accept and distribute phenotype data (associated to the samples) in almost any format: from an image to a README file. How long does a submission take? Submissions to EGA come in a variety of formats and sizes, thus it is difficult for us to exactly predict how long a submission will take. We, therefore, advise all of our submitters to allow as much time as possible to make a submission. Based on previous records, we anticipate that the submission process may take at least one month. The submitter’s familiarity with the procedures, possible technical issues that may arise during submission and the amount of data that is being submitted are the main factors that will affect the length of the submission process. However, each step of a regular submission should be considered when estimating the time it would take: Encryption of the files Upload of the files Metadata submission Archival of the files Release of the study and datasets to EGA webpage For example, the upload of the files depends on the submission size, while metadata submission mainly relies on each submitter’s expertise. Further, some steps (e.g. answering to inquiries) depend on the EGA Helpdesk team, which may take some days to be processed during busy times Is data deposited in the EGA secure? The EGA set-up consists of a secure computing facility for data processing, a shared EBI set-up for data submissions and distribution of data via data requests made through the EGA website. Data is also copied in the Barcelona Supercomputing Center (BSC) infrastructure, where all stored and distributed data is encrypted Data is encrypted along the submission process and stored securely, granting its access to authorised users exclusively. During the download process, through our Python Client or Aspera, all requested data is downloaded over secure https connections. All data at the EGA is encrypted, and only accessible (for log-in and download) through secure protocols. For further information please, visit our security overview. What documentation do I need to provide? All submissions require policy’s documentation: 'Data Access Agreement (DAA)', 'Data Processing Agreement (DPA)' and 'Authorized Submitters Formulary'. The data processors (EGA) and the data owners will also sign the DPA. Will all metadata be public? Among the submitted metadata we need to make the distinction between identifiable and unidentifiable metadata: (1) the former may allow the identification of the human the sample derived from (e.g. detailed geographical providence, personal name, family ancestry…); (2) while the latter can be used to interpret the data without compromising the anonymity of the patients. The majority of the metadata submitted to the EGA corresponds to the unidentifiable category (e.g. sequencer's model). This type of metadata is publicly available on the EGA website and other EBI resources/partners’ websites. On the other hand, some parts samples’ metadata are subject to being identifiable, and thus only accessible by authorized data requesters, with the exception of: 5 submitter-defined attributes of the sample: alias, title, subject_id, gender and phenotype. It is the submitter’s responsibility not to submit sensitive metadata in these public fields. 3 anonymised fields that pinpoint the sample record in archivals: sample’s EGA stable ID (EGAN…), BioSample ID (SAMEA…) and submitter’s center name. During Submission Are there any sample specific requirements for EGA? All samples submitted to the EGA must include the attributes of biological sex, subject ID (anonymised individual identifier) and phenotype information. These are critical for data findability and its analysis, and we highly recommend using controlled ontology terms where applicable. For example: defining tumour and non-tumour samples and/or defining disease state. The EGA recommends using the Experimental Factor Ontology Database to find ontologized terms that describe your sample phenotypes. How do I get an accession number to use in my publication? You will receive your study accession number (EGAS…) upon complete your submission, either: Programmatically. As soon as the metadata is submitted and validated your study will be assigned an accession number that will be given in the submission’s response. Manually registering your study and relevant metadata using the online metadata submission tool: the EGA submitter Portal. How are files uploaded to the EGA? Data files are uploaded into private submission drop boxes (i.e. environments to which you are granted access and where you can transfer your files) using INBOX or FTP. These spaces are provided as part of the submission procedure. Before uploading any file, you must encrypt your files, . Only encrypted files shall be uploaded to the drop boxes. Why does data need to to encrypted for my submitted files? It is one of the security steps the EGA has implemented. In case of a security breach, people without the proper encryption key will not be able to read or use the information that could have been leaked. This measure is essential when working with sensitive data, such as controlled access human data. All submitters must use crypt4gh to create EGA compliant files prior to uploading them. This encryption is GPG-based, using EGA’s public key. Why are my files not available if I see them in the INBOX? There exists a time window between the data upload and the availability of such files via the Submitter Portal. For this reason, some metadata (run and analysis objects) cannot be registered until at least 24 hours after the files have been uploaded to your box. Why are MD5 sum values generated for my submitted files? We require pre- and post- encryption MD5 (message-digest) checksum values to be provided for all submitted files. These 128-bit values are computed using the content of each file, creating unique sequences that allow us to ensure that file integrity has been maintained during the transfer process. In other words, if the MD5 checksums we generate and those you generated match, we infer that the content of the transferred files is correct (i.e. files are not corrupted or truncated). MD5 checksums are computed automatically using the crypt4gh tool provided. Your submission will not be accepted and may be significantly delayed if you do not provide MD5 checksum values for all data files in the required format. How can I check if my files are correctly uploaded to the inbox? It is important to check the status pf your file so you know whether your files are in the inbox, being processed, or if there is any issue with one of them. In order to check this, you should: Look for the file locally. Drag and drop it to the file table. Then bars will appear on the table, which means that we are processing it. Green: The files checksum are correct and your file will move to “ingested files”. No further actions are needed from your end.. Red: The files checksum does not match and your file needs to be re-uploaded. Please re-upload relevant files to your inbox using the same path. After Submission How do I use my accession number in my publication? We suggest the use of the below template, using your study accession ID (EGAS…) : Data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX. Further information about EGA can be found at https://ega-archive.org and "The European Genome-phenome Archive of human data consented for biomedical research" Your study ID will be the one that groups your whole submission, and thus its usage is recommended as such. Nevertheless, all metadata submitted to EGA hold a unique and persistent identifier (starting with EGA…) that can be used to identify specific records. For example, you could reference a specific dataset (EGAD…) or sample (EGAN…) in your publications (see full list of identifiers). How do I make my data searchable? Once you have finalized your submission, you can schedule the data release. Please take into account that the release process needs time for the files to be archived in our system, and for the Helpdesk team to validate your submission. Can I withdraw (meta)data from the EGA? We have methods in place for the secure removal of deposited (meta)data. Contact EGA-helpdesk for further details. EGA complies with FAIRness of (meta)data, and thus, even when the data is removed we keep an entry for their identifiers in our system. In other words, we execute a soft delete on canceled objects (e.g. a study): metadata is still stored in our systems, but it loses all links, cannot be queried and data files cannot be retrieved anymore. The reason behind this behaviour is so that queries using withdrawn data properly respond back (see example of a canceled study). What happens to the data once it has been submitted to the EGA? When the data is submitted, the submitter can choose either keep their data private or schedule the release of their data.

  Documentation submission/metadata/submission/FAQ

• Digitalis Investigation Group (DIG-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To determine the effect of increasing age on mortality, hospitalizations, and digoxin side effects in patients with heart failure (HF), and to determine whether the effect of digoxin on clinical outcomes varies as a function of age. Background The incidence and prevalence of HF increase with advancing age, but there are limited data on the clinical course and response to specific interventions in elderly patients with HF. Participants A total of 302 centers in the United States and Canada enrolled 7,788 patients between February 1991 and September 1993. Design The Digitalis Investigation Group (DIG) study was a prospective, randomized clinical trial involving 7,788 patients with HF randomized to digoxin or placebo and followed for an average of 37 months. Interactions between age and the following clinical outcomes were examined: total mortality, all-cause hospitalizations, HF hospitalizations, the composite of HF death or HF hospitalizations, hospitalization for suspected digoxin toxicity and withdrawal from therapy because of side effects. Conclusions Increasing age is associated with progressively worse clinical outcomes in patients with HF. However, the beneficial effects of digoxin in reducing all-cause admissions, HF admissions, and HF death or hospitalization are independent of age. Thus, digoxin remains a useful agent to the adjunctive treatment of HF due to impaired left ventricular systolic function in patients of all ages.

  Study phs003872

• Defective Homologous Recombination DNA Repair as Therapeutic Target in Advanced-Stage Chordoma (HIPO_021)

  HIPO project: HIPO_021 Importance: Chordomas are rare tumors of the axial skeleton and skull base with few therapeutic options and no clinically validated molecular drug targets. The value of comprehensive genomic analyses for guiding medical therapy of patients with advanced-stage chordoma is unknown.Objective: To identify therapeutically tractable genetic lesions in a cohort of chordoma patients within a genomics-guided precision oncology program and to document the outcome of individualized, molecularly targeted chordoma therapy.Design, Setting, and Participants: We performed whole-exome sequencing of tumor and matched germline control samples from seven patients with locally advanced or metastatic chordoma who were enrolled in a cross-institutional molecular stratification registry trial for younger adults with advanced-stage cancer across all histologies and patients with rare tumors. All patients were heavily pretreated and had progressive disease prior to molecular analysis.Interventions: Individualized medical therapy was administered according to the patients’ molecular profiles.Main Outcomes and Measures: Candidate therapeutic targets identified by whole-exome sequencing and response to genotype-directed therapy.Results: All patients harbored alterations of two or more genes known to be involved in DNA repair via homologous recombination (HR), including heterozygous deletions of ERCC6, FANC family members, RAD51L (n = 6), BRCA2 (n = 5), ATR, CHEK2, RAD18, RAD51B, and XRCC3 (n = 4); inactivating PTEN mutations coupled with loss of heterozygosity (n = 2); and pathogenic germline variants in BRCA2 (n = 1), NBN (n = 1), and CHEK2 (n = 1) that were accompanied by somatic deletion of the corresponding wild-type alleles. Consistently, a mutational signature associated with defective HR was enriched in all samples and co-occurred with extensive genomic instability, as evidenced by HR deficiency scores and high numbers of large-scale state transitions. These results prompted off-label treatment with the poly(ADP-ribose) polymerase (PARP) inhibitor olaparib in a patient whose tumor was refractory to irradiation and systemic treatment with imatinib, which led to a prolonged response and substantial clinical improvement.Conclusions and Relevance: Advanced-stage chordomas are frequently characterized by genomic imprints of defective HR DNA repair. HR deficiency represents a new therapeutic opportunity in this intractable disease through repositioning of PARP inhibitors that warrants further exploration in clinical trials.

  Study EGAS00001002720

• Non-invasive prenatal diagnosis by genome-wide haplotyping of maternal cell-free plasma DNA

  Whereas non-invasive prenatal testing for aneuploidies (NIPT-A) is widely implemented, non-invasive prenatal testing for monogenic diseases (NIPT-M) is lagging. By capturing and targeted sequencing of 250000 polymorphic SNP loci from maternal plasma circulating cell-free DNA (cfDNA) and DNA from relatives, the fetal haplotype and chromosomal copy numbers are deduced. In all families tested, the cfDNA derived haplotypes are on average 97% concordant with the neonatal and embryo haplotype. This generic non-invasive prenatal diagnostic approach allows cost efficient scrutinizing the fetal genome for the presence of any inherited monogenic disease or trait.

  Study EGAS00001003634

• Identification and targeting of extremely high-risk gamma delta T-ALL in children

  Acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) is an uncommon, poorly understood disease. We studied 200 pediatric γδ T-ALL enrolled on clinical trials to understand the clinical and genetic features of this disease, which showed variation in outcome according to age and genetic driver. γδ T-ALL diagnosed in children under three years of age was extremely high-risk and enriched for genetic alterations leading to both LMO2 activation and STAG2 inactivation. Using patient samples and isogenic cell lines, we show that inactivation of STAG2 profoundly perturbs chromatin organization by altering enhancer-promoter looping and results in deregulation of gene expression related to T-cell differentiation. High throughput drug screening identified a vulnerability in DNA repair pathways arising from STAG2 inactivation, which was efficaciously targeted by PARP inhibition. These data provide a diagnostic and therapeutic framework for classification and risk stratification of pediatric γδ T-ALL.

  Study EGAS50000000018

• Rapid Acceleration of Diagnostics - Digital Health Technologies' (RADx-DHT) Collection of General Research Use Datasets

  This individual-level collection of datasets contains all the RADx Digital Health Technologies (RADx-DHT) studies in dbGaP for General Research Use (GRU). Access to studies in this collection is on the RAPIDS platform. To request access to this study collection, select phs003666 in the dbGaP when submitting a data access request.

  Study phs003666

• Type I Interferon and Cycling Lymphocytes in Macrophage Activation Syndrome

  We performed immune profiling of peripheral blood mononuclear cells from patients with Still's disease and macrophage activation syndrome (MAS) using bulk RNA sequencing and single-cell RNA sequencing. Three groups were included in the study: healthy controls, patients with Still's disease without macrophage activation syndrome, and patients with Still's disease and macrophage activation syndrome. We found that macrophage activation syndrome is associated with transcriptomic signatures of interferon upregulation and cell cycling. We identified cycling lymphocytes within T cell and NK cell populations that are correlated with MAS disease activity. All sequencing data are available through dbGaP.

  Study phs003310

• Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

  Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data, we applied non-negative matrix factorization, which identified four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed signature (SCLC-A, N, P and I, respectively). The presence of these subtypes were then validated in tumor gene expression data from the IMpower133 clinical trial.

  Study EGAS00001004888