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• Defining and Overcoming Intrinsic T Cell Dysfunction to Enable Pediatric Immunotherapy

  T-cells from 71 children and young adults with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy were analyzed. These T-cells represent the pre-manufacture T-cells that were subsequently used for CAR T manufacture. Bulk RNA-Seq was performed on sorted T-cell subsets for all patients, in addition to CITE-Seq and single-cell ATAC-Seq on a subset of 6 patients. The primary clinical outcome was duration of B-cell aplasia, a surrogate measure of functional CAR T-cell persistence. From these data, molecular signatures associated with long and short-term CAR T-cell persistence were identified. This data submission includes bulk RNA-Seq, CITE-Seq, and single-cell ATAC-Seq data from this study.

  Study phs002323

• Accelerating Medicines Partnership-Rheumatoid Arthritis (AMP-RA/SLE)

  This project is analyzing tissue and blood samples from people with RA and lupus to pinpoint genes, proteins, chemical pathways, and networks involved at a single cell level. This type of modular, molecular analysis will allow comparisons across the diseases and will provide insights into key aspects of the disease process. The project will identify differences between those RA patients who respond to therapies and those who do not, as well as provide a better systems level understanding of disease mechanisms in both RA and lupus. This knowledge is essential for the development of targeted therapies and for the application of existing and future therapies to appropriate patient populations. Additional datasets can be accessed through ImmPort (http://www.immport.org/immport-open/public/home/studySearch), accession: SDY998, SDY999.

  Study phs001457

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Study

  The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits. The initial effort involved linkage analysis of affected-sibling-pair (ASP) families based on over 5,000 individuals living in Finland, and association fine mapping based on these family members and additional T2D cases and controls. Recently we completed a genome-wide association scan on 1161 T2D cases and 1174 normal glucose tolerant (NGT) controls. Individual-level data is available here for the 919 T2D cases and 787 NGT controls who reconsented to the use of their data or are deceased. Version 3 adds individual-level data for additional phenotypic variables.

  Study phs000100

• Patient-derived organoids as a novel tool to study cervical cancer

  Cervical cancer is the most prevalent gynecological malignancy worldwide, often caused by infection with a high-risk human papillomavirus. Currently, there are only limited number of human-derived culture systems available that enable to study the viral infection for short-term. Here, we report on establishment of long-term human-derived organoid cultures from both healthy ecto- and endocervical epithelia that closely recapitulate the tissues of origin by maintaining the authentic histological and tissue-specific gene expression profiles. Additionally, using material from patients’ Pap-brush material, a successful panel of long-term patient-derived cancer organoids was established that maintain the causative viral infection in vitro and show differential response to common chemotherapy regimens. This study provides a promising platform for cervical cancer research and studying direct virus-host interactions.

  Study EGAS00001004439

• Single cell whole genome sequencing of high hyperdiploid acute lymphoblastic leukemia

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15). The dataset has been used for copy number aberrations analysis.

  Study EGAS00001006347

• ATAC-Seq of inflamed and non-inflamed biopsies

  Inflamed and non-inflamed biopsies were digested for 45 minutes at 37ºC with collagenase from Clostridium histolyticum (Sigma). Suspension cells were then stained with an antibody cocktail to sort live CD8-CD4+ T cells. After isolating crude nuclei of two thousand live CD4+ T cells, they were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007344

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001000825

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Dataset EGAD00001007978

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Dataset EGAD00001004554

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090