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• Best Practices for DACs

  Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

  Documentation access/data-access-committee/best-practices

• Extracellular RNA Profiling of Serum, Plasma, and Urine of Healthy Subjects

  This study was conducted to generate a reference dataset of extracellular RNA (exRNA) from standard human biofluids. Small RNA-seq data was obtained from plasma, serum, and urine of healthy subjects.

  Study phs003054

• PEDS-PLAN - Pediatric Precision Laboratory Advanced Neuroblastoma Therapy

  A multi-center clinical trial for newly diagnosed high-risk neuroblastoma patients. Molecular tumor boards selected one of six targeted agents based on tumor-normal whole exome sequencing and tumor RNA sequencing data.

  Study phs002303

• Comprehensive analyses of clinicopathological features and genomic mutations of combined hepatocellular-cholangiocarcinoma

  Combined hepatocellular and cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer. We performed whole exome sequencing to clarify the relationship between genetic mutations and clinicopathological features in cHCC-CCA.

  Study JGAS000599

• Genome-wide association scan in psoriasis

  To identify novel susceptibility loci for psoriasis, we undertook a genome-wide association scan of of 594,224 SNPs in 2,622 individuals with psoriasis and 5,667 controls.

  Study EGAS00000000108

• Targeted resequencing of ribosomal proteins in multiple myeloma patient samples.

  We studied 38 multiple myeloma samples to discover mutations in ribosomal proteins. To this end, we ran a specifically designed targeted resequencing study to resequence the coding regions of all ribosomal proteins.

  Study EGAS00001002405

• Detection of uniparental disomy from genome sequencing of family trio

  We created a bioinformatics pipeline to detect uniparental disomy from whole genome sequence data of family trios. We use inheritance patterns of single nucleotide polymorphisms to identify uniparental disomy events.

  Study EGAS00001006154

• Fibromyalgia versus small fiber neuropathy: Diverse keratinocyte transcriptome signature

  We provide a diverse keratinocyte transcriptome signature between SFN and FMS patients, which may hint towards distinct pathomechanisms of small fiber sensitization and lay the basis for advanced diagnostics in both entities

  Study EGAS00001005004

• Single-cell RNA sequencing of chemotherapy-resistant muscle-invasive urothelial bladder cancer

  All single-cell mRNA sequencing data were acquired from a single patient (BC159-T#3) and patient-derived xenografts (BC159-T#3-PDX-vehicle and BC159-T#3-PDX-tipifarnib).

  Study EGAS00001004233

• Methylation profiling of osteoblastomas and their mimics

  Here, we set out to comprehensively characterize a series of 77 osteoblastomas by immunohistochemistry, fluorescence in-situ hybridization as well as copy number and methylation profiling and compared our findings to histologic mimics.

  Study EGAS00001005932

• Chromatin landscape of medulloblastoma reveals context dependent driver

  In this study, we defined subgroup specific chromatin landscape (H3K27ac, H3K27me3, RNA-Seq, 27ac hichip, WGS) of medulloblastoma to identify pathogenic epigenetic alterations that regulate expression of a context dependent driver gene.

  Study EGAS00001006741

• Single cell RNA seq component of ATAC-RNA multiome analysis of a four weeks post conception embryo head

  Four single-cell RNA libraries were generated from an unbiased sample of cells of a human four weeks post conception embryo using the 10X Chromium Single-Cell Instrument and NextGEM Single Cell Multiome ATAC+Gene Expression kit (10X Genomics) according to the manufacturer’s protocol.

  Dataset EGAD50000001501

• Single cell ATAC seq component of ATAC-RNA multiome analysis of a four weeks post conception embryo head

  Four single-cell ATAC libraries were generated from an unbiased sample of cells of a human four weeks post conception embryo using the 10X Chromium Single-Cell Instrument and NextGEM Single Cell Multiome ATAC+Gene Expression kit (10X Genomics) according to the manufacturer’s protocol.

  Dataset EGAD50000001502

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells

  The dataset contains bulk RNA sequencing data from 12 pediatric thymus samples collected during cardiac surgeries. These samples represent immunologically healthy donors with a mean age of 6 months. The sequencing was performed using Illumina HiSeq4000, and the processed files are available in standard formats such as FASTQ.

  Dataset EGAD50000001120

• GIST Whole Genome Sequencing

  Whole genome sequencing of tumour and normal samples from familial GIST. Multiple family members were affected with multifocal GIST who underwent whole genome sequencing of the germline and tumor. Affected individuals with GIST harbored a germline variant found within exon 13 of the KIT gene, (c.1965T>G; p.Asn655Lys, p.N655K) and a variant in the MSR1 gene (c.877C>T; p.Arg293*, pR293X).

  Dataset EGAD50000000549

• Total RNA sequencing of fibroblasts from unmethylated full mutation carrier 1

  Total RNA sequencing of fibroblasts from an individual with a fragile X syndrome related unmethylated full mutation (UFM1). Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000918

• T-ALL RNA-Seq raw data files

  The data set consists of unprocessed RNA-Seq data from 225 patients diagnosed with T cell acute lymphoblastic leukemia in fastq file format. Samples from bone marrow or peripheral blood were subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system yielding approximately 30 million reads per sample.

  Dataset EGAD50000000308

• EGAD00000000045

  Genomic sequencing and transcriptome shotgun sequencing of a metastatic tumour and its recurrence after drug therapy in a single patient

  Dataset EGAD00000000045

• Whole exome sequencing for HELIC

  The HELIC study has been whole genome sequencing individuals from 2 Greek isolatedpopulations at 1x depth. The genotype calling process crucially involves a VQSR stepfollowed by imputation-based refinement. We have been investigating optimal ways toincrease calling accuracy. To aid us in setting appropriate parameters for VQSR and otherQC steps, we have carried out whole exome sequencing of a small number ofHELIC samples.

  Dataset EGAD00001001638

• Congenital anosmia 2

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

  Dataset EGAD00001002228

• RNA sequencing and whole-genome mate-pair sequencing of osteosarcoma

  This data set includes 72 mate pair sequenced osteosarcomas (36 as part of a discovery cohort and 36 as part of a validation cohort). It also includes RNA-sequencing data on 67 osteosarcomas (mostly overlapping with the above mate pair sequenced cases) and 13 osteoblastomas used as controls for gene expression levels.

  Dataset EGAD00001005307

• HV31 - De novo assembly of eight immune system regions

  De novo assembly of eight immune system regions for individual HV31, generated using a multi-platform pipeline. A full description of the generation of these assemblies can be found at https://doi.org/10.1101/2021.02.03.429586.

  Dataset EGAD00001007050

• Single Cell DNA amplicon sequencing of 12 B-ALL patients (at diagnosis and during treatment)

  This dataset contains single cell DNA amplicon sequencing of 12 B-ALL patients. For all patients a diagnosis sample was processed, while 4 patients were also followed up during treatment, summing up to a total of 23 samples. Mutations were called in the predefined set of amplicons.

  Dataset EGAD00001006955

• RNAseq in ASD patients and controls

  RNA sequences of a total of 24 samples, including 13 unrelated ASD patients (13 males) and 11 adult individuals of Spanish origin as controls (4 males, 7 females). The RNAseq study was conducted on a HiSeq 4000 (Illumina) and paired-end sequences were obtained (fastq files).

  Dataset EGAD00001008160

• DNA methylation-based classification of sinonasal tumors [DNA sequencing]

  This dataset contains raw exome sequencing data from nine sinonasal undifferentiated carcinoma FFPE samples and matched normal tissue that were assigned to a shared epigenetic class using DNA methylation-based classification. They were analyzed using the Twist Human Core Exome Plus Kit (Twist Bioscience) on a NovaSeq 6000 sequencer.

  Dataset EGAD00001009668

• RNAseq data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - MUMC

  The dataset includes fastq files from 4 NEN tumors or metastases and matched PDTOs. The sequencing was done with either a Nextseq 2000 or a NovaSeq 6000 instrument.

  Dataset EGAD00001009991

• Genome and transcriptome sequence data from a infantile fibrosarcoma tumor patient

  Genome and transcriptome sequence data from a infantile fibrosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015263

• Genome and transcriptome sequence data from a CNS sarcoma tumor patient

  Genome and transcriptome sequence data from a CNS sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015268

• Genome and transcriptome sequence data from a ocular melanoma tumor patient

  Genome and transcriptome sequence data from a ocular Melanoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015269

• Genome and transcriptome sequence data from a fibrovascular brain tumor tumor patient

  Genome and transcriptome sequence data from a fibrovascular brain tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015271

• Segmental Cherry Angioma case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Dataset EGAD00001015641

• TCR and BCR sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the TCR and BCR sequencing data

  Study EGAS50000001743

• Microvascular Permeability, Inflammation, and Lesion Physiology in Endometriosis: A Microphysiological Systems Approach

  The goal of the study is to identify novel molecular pathways involved in the etiology of endometriosis and to develop in vitro model systems to enable the study of the mechanisms regulating reproductive function. Using a physiomimetic modeling approach, primary tissue samples of the human endometrium derived from patients diagnosed with and without endometriosis and/or endometriotic diseases (e.g. adenomyosis) were used for secondary analysis using multi-omic systems biology analysis and to build tissue engineered models. We performed single cell RNA sequencing (scRNA-Seq, N=6)) to study the cellular and transcriptomic composition of the endometrial tissue microenvironment and proteomics (LC-MS/MS) to study protein-level signaling pathways and the matrisome of the native endometrium. Systems biology analysis of these datasets helped identified a putative dysregulated inflammatory signaling pathway in endometriosis patients compared to controls. Moreover, subsets from these scRNA-Seq and proteomic datasets were used to aid the design of a synthetic extracellular matrix hydrogel as an in vitro platform for the culture of endometrial cells. Tissue-engineered synthetic PEG hydrogel enables the simultaneous co-culture of endometrial epithelial organoids and stromal fibroblasts in a fully defined, 3D, and tunable environment. We demonstrated that the in vitro co-culture model recapitulates key phenotypic processes observed across the human menstrual cycle in response to sex hormone stimulation through both biochemical and transcriptomic (bulk RNA-sequencing) analysis. This model will enable future mechanistic studies that examine origins of endometriotic disease phenotypes. The transcriptomic data generated for this study including the scRNA-Seq data from primary human endometrial tissues and the bulk RNA-Seq datasets from the experimental co-culture models is available through dbGAP.

  Study phs003326

• Correlative Studies for Protocol #14-C-0059: T Cells Expressing an Anti-GD2 Chimeric Antigen Receptor in Patients with GD2+ Solid Tumors, a Collaboration with CIMAC-CIDC

  This study is a retrospective correlative analysis of immune cell phenotypes in samples from a Phase I clinical trial (NCT02107963) of GD2 CAR-T cells (GD2-CAR.OX40.28.z.iC9) in children and young adults with osteosarcoma and neuroblastoma. The study was a 3+3 dose-escalation study with four dose levels (1 x 10(5) transduced T cells/kg; 1 x 106 transduced T cells/kg; 3 x 106 transduced T cells/kg; and 1 x 107 transduced T cells/kg). Apheresis and final manufactured GD2 CAR-T product samples were analyzed by bulk RNA sequencing and ATAC sequencing. The patients were stratified into good CAR-T expanders (peak CAR-T expansion >1000 GD2 CAR copies/100ng DNA) and poor CAR-T expansion (peak CAR-T expansion Increased naïve T cell subsets in baseline apheresis are associated with patients who experienced good CAR T cell expansion A T cell exhaustion signature was observed in the manufactured GD2 CAR-T product and may have contributed to lack of efficacy observed in this trial Increased myeloid-derived suppressor cell (MDSC) signatures were observed in patients with poor CAR-T expansion CAR-T product in good expanders displayed increased AP-1 factor transcription factor motifs, such as BATF, JUN, and FOS Data provided in dbGaP for this study include: Bulk RNA-Seq data for 11 pre-treatment peripheral blood and 11 GD2 CAR-T product from 14 patients. ATAC sequencing of 22 peripheral blood samples and 5 GD2 CAR-T products from 14 patients.

  Study phs003455

• Mutational Landscape and Tumor Burden Assessed by Cell-Free DNA in Diffuse Large B-Cell Lymphoma: a Population-based Study

  Purpose: We analyzed the utility of cfDNA in a prospective population-based cohort to determine the mutational profile, assess tumor burden, and estimate its impact in response rate and outcome in patients with DLBCL. Experimental Design: One-hundred patients were diagnosed with DLBCL during the study period. Mutational status of 112 genes was studied in cfDNA by targeted next-generation sequencing. Paired formalin-fixed paraffin-embedded samples and volumetric PET/CT were assessed when available. Results: Appropriate cfDNA to perform the analyses was obtained in 79/100 cases. At least one mutation could be detected in 69/79 cases (87%). The sensitivity of cfDNA to detect the mutations was 68% (95% CI: 56.2-78.7). The mutational landscape found in cfDNA samples was highly consistent with that shown in the tissue and allowed genetic classification in 43% of the cases. A higher amount of ctDNA significantly correlated with clinical parameters related to tumor burden (elevated LDH and β2-microglobulin serum levels, advanced stage, and high-risk IPI) and total metabolic tumor volume assessed by PET/CT. In patients treated with curative intent, high ctDNA levels (>2.5 log hGE/mL) were associated with lower complete response (65% vs. 96%, P<0.004), shorter progression-free survival (65% vs. 85%, P=0.038) and overall survival (73% vs. 100%, P=0.007) at 2 years, although it did not maintain prognostic value in multivariate analyses. Conclusions: In a population-based prospective DLBCL series, cfDNA resulted an alternative source to estimate tumor burden and to determine the tumor mutational profile and genetic classification, which have prognostic implications and may contribute to a future tailored

  Study EGAS00001004733

• Molecular and clinical diversity in primary central nervous system lymphoma: a LOC Network study

  Primary central nervous system lymphoma (PCNSL) is a distinct extranodal lymphoma presenting with limited stage disease but variable response rates to treatment despite homogenous pathological presentation. The likely underlying molecular heterogeneity and its clinical impact is poorly understood. We performed a comprehensive genome-wide analysis of 147 PCNSL from fresh-frozen tumor tissue from immunocompetent, treatment naïve PCNSL patients, employing whole-exome sequencing, assessment of somatic copy number alterations and DNA methylation, and RNA expression. These data were integrated and correlated with the clinico-radiological characteristics and outcomes of the patients. We validated our results in an independent series of 93 PCNSL formalin-fixed, paraffin-embedded (FFPE) samples. Consensus clustering of multi-omics data identified four robust, non-overlapping, prognostically significant clusters (CS) within PCNSL. The CS1 group, characterized by high proliferation and Polycomb Repressive Complex 2 (PRC2) complex activity had an intermediate outcome between CS2/CS3 and CS4. Patients who had PCNSL with an “immune-hot” (CS4) profile had the most favorable clinical outcome. In contrast, patients with the immune-cold hypermethylated CS2 and the heterogenous-immune CS3 groups had a poor prognosis. Nearly all PCNSL patients with meningeal infiltration harbored HIST1H1E mutations, enriched in the CS3 group. The integrated analysis suggests that the CS4 group may be more susceptible to immunotherapy. The integration of genome-wide data from multi-omics data revealed four molecular patterns in PCNSL with a distinctive prognostic impact that significantly improved the current clinical stratification. This molecular classification using FFPE samples facilitates routine use in clinical practice and provides potential precision-medicine strategies in PCNSL.

  Study EGAS00001006191

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• Tubulointerstitial fibrosis is the histological hallmark of chronic kidney disease (CKD). Hypoxia and inflammation (i.e., interleukin (IL)-1β signalling) are independent mediators of tubulointerstitial fibrosis. However, the physiological response of human kidney tubular cells to IL-1β/IL-1RI signalling under the hypoxic conditions of CKD is poorly understood and remains a clinical imperative for therapeutic targeting. This study reports that hypoxia and IL-1β act in synergy to trigger cell cycle arrest/cellular senescence of ex vivo patient-derived primary proximal tubular epithelial cells (PTECs).

  Hypoxia and interleukin (IL)-1β are independent mediators of tubulointerstitial fibrosis, the histological hallmark of chronic kidney disease (CKD). Here, we examine how hypoxia and IL-1β act in synergy to augment maladaptive proximal tubular epithelial cell (PTEC) repair in human CKD. Ex vivo patient-derived PTECs were cultured under normoxic (21% O2) or hypoxic (1% O2) conditions in the absence or presence of IL-1β and examined for maladaptive repair signatures. Hypoxic PTECs incubated with IL-1β displayed a discrete transcriptomic profile distinct from PTECs cultured under hypoxia alone, IL-1β alone or under normoxia. Hypoxia+IL-1β-treated PTECs had 692 ‘unique’ differentially expressed genes (DEGs) compared to normoxic PTECs, with ‘cell cycle’ the most significantly enriched KEGG pathway based on ‘unique’ down-regulated DEGs (including CCNA2, CCNB1 and CCNB2). Hypoxia+IL-1β-treated PTECs displayed signatures of cellular senescence, with reduced proliferation, G2/M cell cycle arrest, elevated senescence-associated β-galactosidase (SA-β-gal) activity and increased production of pro-inflammatory/fibrotic senescence-associated secretory phenotype (SASP) factors compared to normoxic conditions. Treatment of Hypoxia+IL-1β-treated PTECs with either a senolytic drug combination, quercetin+dasatinib, or a type I IL-1 receptor (IL-1RI) neutralizing antibody attenuated senescent cell burden. Our data identify a mechanism whereby hypoxia in combination with IL-1β/IL-1RI signalling trigger PTEC senescence, providing novel therapeutic and diagnostic check-points for restoring tubular regeneration in human CKD.

  Study EGAS00001007904

• Cell-Free, Methylated DNA in Blood Samples Reveals Tissue-Specific, Cellular Damage from Radiation Treatment

  Radiation therapy is an effective cancer treatment, although damage to surrounding healthy tissues can also occur. Cell-type specific DNA methylation patterns can be used to decode the cellular origins of cell-free DNA fragments, allowing for minimally-invasive monitoring of tissue damage. To evaluate whether changes in cell-free DNA methylation can indicate damages to tissues in patients treated with radiation, we collected serum samples from 15 breast cancer patients at three timepoints during their standard-of-care radiation therapy after surgery. A baseline sample was taken for each patient before onset of radiation therapy and a second End-Of-Treatment (EOT) sample was taken 30 minutes after the last treatment fraction. Finally, a recovery sample was taken one month after completion of radiation therapy. From serum samples, cell-free DNA was isolated and bisulfite capture-sequencing DNA methylation data were generated. Bisulfite capture-sequencing DNA methylation data were also generated from buffy coat and tissue-specific endothelial gDNA samples as well as from serum/plasma samples of healthy controls. The analysis of serum samples from breast cancer patients undergoing radiation treatment revealed distinct tissue-specific epithelial and endothelial responses to radiation across multiple organs. In conclusion, as a proof of concept we show that cell-type specific methylation signatures can be applied to detect cellular injury from radiation treatment using minimally invasive cell-free DNA in blood samples.

  Study phs003290

• Clinical Sequencing Exploratory Research (CSER): Clinical sequencing in cancer: Clinical, ethical, and technological studies

  The Clinical Sequencing Exploratory Research (CSER) program supports multi-disciplinary projects that bring together clinicians, bioinformaticians, and ethicists to research the challenges of utilizing genomic sequence data in the clinic in the routine practice of medicine. The challenges are many and not disease-specific. Important aims of the research include: development of technical specifications and standards for sequencing in a clinical setting, investigation of methods to transmit genome-scale data to physicians in a fashion and timescale that fits the normal clinical workflow, exploration of regulatory requirements for applying genomic sequence data to patient care, study of physician and patient preferences regarding presentation of genomic information, and study of the ethical implications of returning unanticipated findings. More information about CSER and the investigators and institutions who comprise the CSER consortium can be found at http://www.genome.gov/27546194. The NEXT (New Exome Technology) Medicine Study utilizes a randomized controlled trial (RCT) structure to compare usual care (UC) practice in Medical Genetics Clinics with the introduction of a powerful research tool of whole exome sequencing plus UC practices for Colorectal Cancer and Polyposis (CRCP) in adults. In doing so, the study aims to explore the practical, economic, and ethical implications of identifying and returning incidental findings ("extra" whole exome genetic risk results not associated with CRCP that includes pharmacogenetic variants) to patients. The study will also attempt to identify novel causal genes for CRCP by studying relatives of selected research subjects.

  Study phs000999

• Genome and Transcriptome Assembly Reveals SVA-Mediated Aberrant Splicing in X-Linked Dystonia Parkinsonism

  X-linked Dystonia-Parkinsonism (XDP, DYT3) is a long-standing quandary in human disease genetics. XDP is predominantly observed on Panay island in the Philippines. This study is one of the first of its kind to interrogate an unsolved Mendelian disorder by integrating genome and transcriptome assembly methods using Illumina, 10X Genomics, Pacific Biosciences, and Agilent genome targeting technologies. These data provide strong evidence for a pathogenic link between a noncoding SVA retrotransposon and XDP. We demonstrate that this Mendelian disorder is associated with a sine-VNTR-Alu (SVA) retrotransposon that inserted into the TAF1 gene and is shared by all XDP probands, yet never observed in controls from worldwide populations. Transcriptome assembly in iPSC-derived neural stem cells (NSCs) and neurons revealed that this SVA caused aberrant splicing and significant intron retention, which was negatively correlated with TAF1 expression. Remarkably, CRISPR/Cas9 excision of the SVA rescued the aberrant transcriptional signature and normalized expression of TAF1 in patient-derived NSCs. We have also interrogated iPSC-derived microglia to investigate the contribution of glial components to the cellular and molecular deficit, effect of TNF treatment on XDP transcriptional signatures. To further understand what XDP may have in common with other hereditary dystonias (such as DYT6), we are further comparing these signatures to ones associated with dystonia-specific variants in proteins that, like TAF1, are also involved in regulating transcription, i.e. THAP1. 

  Study phs001525

• MAITS in HCC

  Hepatocellular Carcinoma (HCC) is a leading cause of cancer-related death and can be considered a prototype of inflammation-derived cancer arising from chronic liver injury. The cell composition of the HCC tumor immune microenvironment (TiME) has a major impact on cancer biology as the TiME can have divergent capacities on tumor initiation, progress, and response to therapy. Recent development of multi-omics and single-cell technologies help us to comprehensively quantify the cellular heterogeneity and spatial organization of the TiME and to further our understanding of antitumor immunity. We investigated the cellular composition of liver cancer patient samples (n=8) using single-cell RNA-seq. For this purpose, mononuclear cells were isolated from human liver cancer samples. Three locations within the tumor-bearing liver were used: adjacent liver, rim and tumor core. Then, cells were FACS sorted (either CD45+ cells or MAIT cells) and subjected to 10X Chromium-based scRNA-seq. We investigated immune cell changes and the cellular heterogeneity of the HCC TiME with a focus on MAIT cells. Annotated H5 files are provided. Clinical metadata including TMN stage, sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Further details on the study can be obtained in our paper once it’s published.A complementary dataset derived from ultrahighplex CO-Detection by indEXing (CODEX) from paired patient samples can be accessed through The Cancer Imaging Archives (TCIA) under DOI: https://doi.org/10.7937/bh0r-y074.

  Study phs003279

• Rapid Whole Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units

  Monogenic diseases are frequent causes of neonatal morbidity and mortality, and disease presentations are often undifferentiated at birth. More than 3,500 monogenic diseases have been characterized, but clinical testing is available for only some of them and many feature clinical and genetic heterogeneity. As such, an immense unmet need exists for improved molecular diagnosis in infants. Because disease progression is extremely rapid, albeit heterogeneous, in newborns, molecular diagnoses must occur quickly to be relevant for clinical decision-making. We describe 50-hour differential diagnosis of genetic disorders by whole-genome sequencing (WGS) that features automated bioinformatic analysis and is intended to be a prototype for use in neonatal intensive care units. Retrospective 50-hour WGS identified known molecular diagnoses in two children. Prospective WGS disclosed potential molecular diagnosis of a severe GJB2-related skin disease in one neonate; BRAT1-related lethal neonatal rigidity and multifocal seizure syndrome in another infant, identified BCL9L as a novel, recessive visceral heterotaxy gene (HTX6) in a pedigree, and ruled out known candidate genes in one infants. Sequencing of parents or affected siblings expedited the identification of disease gene in prospective cases. Thus, rapid WGS can potentially broaden and foreshorten differential diagnosis, resulting in fewer empirical treatments and faster progression to genetic and prognostic counseling. Reprinted from Saunders et. al, Rapid Whole-Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units. Sci. Transl. Med. 4, 154ra135 (2012; PMID: 23035047) with permission from AAAS.

  Study phs000564

• Rare Cancer Tumors Project

  A large proportion of common cancers affecting patients around the world have been selected for comprehensive cancer genome studies. Further efforts will be needed to tackle the remaining tumor types, including the rare forms of cancers. Although rare, these cancers tend to be more aggressive and fast growing with an early recurrence following initial chemotherapy and poor prognosis. Besides, patients diagnosed with rare cancers may have difficulty finding a physician knowledgeable in treating their type of cancer. While sample collection is a major challenge, the integrated genomic analyses would identify novel causative genes in these rare cancers, shed new light on the biology of the rare cancers, as well as guide novel targeted cancer therapies. Through efficient collaboration, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine (BCM) has collected/is expected to collect 20 different types of rare cancers, 15-30 cases each. Whole-exome sequencing and high-resolution SNP array analysis were/will be performed for all cases and whole-genome sequencing was designed for a selected subset of the cases. The Rare Cancer Tumors Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" section of this top-level study page phs000725 Rare Cancer Tumors Cohort. phs000754 Intracranial Germ Cell Tumors phs000861 Craniopharyngioma Tumors phs000859 Sezary Syndrome Genomic Analysis

  Study phs000725

• Genomic Analysis of Pediatric Low Grade Gliomas

  Pediatric low-grade gliomas (PLGGs) are among the most common solid tumors in children but, apart from mutations or duplications in the BRAF kinase in specific subclasses, few genetic driver events are known. Diffuse PLGGs compose a set of uncommon subtypes that exhibit invasive growth and are therefore especially challenging clinically. These tumors are particularly poorly understood. We performed high-resolution copy-number analysis of 44 diffuse PLGGs to identify recurrent alterations. Diffuse PLGGs exhibited fewer such alterations than adult low-grade gliomas, but we identified several significantly recurrent events. The most significant event, 8q13.1 gains, was observed in 28% of diffuse astrocytoma WHO grade II (DA2) and resulted in partial duplication of the transcription factor MYBL1 with truncation of its C-terminal negative-regulatory domain. A similar recurrent deletion-truncation breakpoint was identified in two angiocentric gliomas in the related gene MYB on 6q23.3. Whole genome sequencing of a MYBL1-rearranged diffuse astrocytoma grade II demonstrated MYBL1 tandem duplication and few other events. Two truncated MYBL1 transcripts identified in this tumor induced anchorage-independent growth when expressed in 3T3 cells and tumor formation in nude mice. Truncated transcripts were also expressed in two additional tumors with MYBL1 partial duplication. Our results define clinically relevant molecular subclasses of diffuse PLGGs and highlight a potential role for the MYB family in the biology of low-grade gliomas. "Reprinted from www.pnas.org/cgi/doi/10.1073/pnas.1300252110 with permission from PNAS."

  Study phs000614

• The Library of Integrated Network-Based Cellular Signatures (LINCS) - NeuroLINCS

  The NeuroLINCS Center is part of the NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of human cells, tissues and the entire organism respond to perturbations by drugs and other molecular factors. As Part of the LINCS program, the NeuroLINCS study concentrates on human brain cells, which are far less understood than other cells in the body. Our initial focus is to produce diseased motor neurons from patients by utilizing high-quality induced pluripotent stem cell (iPSC) lines from Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA) patients in addition to unaffected normal healthy controls. Using state-of-the-art OMICS methods (genomics, epigenomics, transcriptomics, and proteomics), we intend to create a wealth of cellular data that is patient-specific in the context of their baseline genetic perturbations and in the presence of other genetic and environmental perturbagens (e.g. endoplasmic reticulum stress). The primary data will be used to build cell signatures that convey the key features that distinguish the state of a cell and determine its behavior. Ultimately, the analysis of these datasets will lead to the identification of a network of unique signatures relevant to each of these motor neuron diseases. The datasets represented in this study are generated from assays interrogating RNA expression (RNA-seq), chromatin accessibility (ATAC-seq) and whole genome sequencing.

  Study phs001231

• Detection and Targeting of Splicing Deregulation in Pediatric Acute Myeloid Leukemia Stem Cells

  This study evaluates the gene expression and splicing changes between pediatric patients with and without Acute Myeloid Leukemia (AML) and pediatric and adult patients with AML. We obtained bone marrow or peripheral blood from patients and isolated CD34+ stem and/or progenitor cells from pediatric patients with AML (10) or without AML (6) and adult patients with AML (5). In parallel, a targeted analysis for known, deleterious, genetic mutations in the KRAS, NRAS, and KMT2C genes identified 2, 5, and 6 AML patients with alterations, respectively. Additionally, Tapestri analysis further identified a mutation in the intronic region of the SF3B1 gene in multiple pediatric AML patients. RNA-Seq was performed on the purified cell populations at The Scripps Research Institute Next Generation Core on an Illumina NextSeq 500 sequencer with 150bp paired-end reads.These datasets revealed that, similar to adult AML, pediatric AML samples were enriched for Leukemia Stem Cells (LSC) markers. A deeper analysis showed widespread dysregulation of splicing in pediatric AML samples compared to age-matched non-leukemic samples. In addition, the splicing regulator RBFOX2 was downregulated with an accompanying increase in specific CD47 splice isoforms in the pediatric AML samples. Thus, the increased presence of LSCs in pediatric AML is possibly driven by global splicing deregulation, and the treatment with splicing modulators like Rebecsinib has a potential therapeutic value for eradicating LSCs in these patients.

  Study phs003196

• The Genetics of Type 2 Diabetes Consortium (GoT2D): Low-Pass Sequencing and High-Density SNP Genotyping for Type 2 Diabetes

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (EGA), by virtue of the project specific funding requirements.

  Study phs000840

• A Phase I Study with a Personalized Neoantigen Cancer Vaccine in Melanoma

  Effective anti-tumor immunity in humans has been associated with presence of T cells targeting neoantigens that arise from non-silent tumor-specific mutations. Here we conducted whole-exome sequencing of tumor and normal cells from individual patients to identify mutations. We assessed the expression of mutated alleles by RNA-sequencing of tumor. We demonstrated the feasibility, safety and immunogenicity of a vaccine that targets up to 20 personal neoantigens predicted to be presented by the autologous patient tumor.Antigen-specific CD8+ T cells that can recognize and eliminate cancer cells play a crucial role in anti-tumor immune responses. Here we conducted single-cell sequencing of cells infiltrating melanoma specimens originating from 4 patients and determine the TCR clonality of the CD8+ tumor infiltrating cells. We investigated the relationship between T cell clonality and phenotypic cell states coupling single-cell transcriptome to single-cell TCR seq. The surface expression of a panel of protein was detected in parallel using CITE-Seq antibodies. Sorted tumor and peripheral blood specimens were processed in parallel.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out matched ribosome profiling (Ribo-seq), RNA-sequencing, and whole genome sequencing on one of the patients, as well as Ribo-seq on an additional patient. We used it to discover novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001451

• The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

  In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

  Study phs003417