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• Data access commitee to DAISY study

  Dac EGAC00001003031

• Method to Assess Lung Water Accumulation During Exercise

  The goal of this non-significant risk medical device study is to test the initial technical feasibility of a 0.55T MRI in healthy volunteers by technical optimization of scanner protocols, and to test accuracy of standard MR measurements in adult patients with known stable disease. Exercise-induced lung water is a key feature in heart failure. Dynamic quantitative lung water imaging during exercise stress is therefore of interest to unmask latent heart failure. We developed a novel magnetic resonance imaging (MRI) method using a proton density weighted ultrashort echo time MRI sequence along with a time-resolved and respiratory motion compensated image reconstruction for exercise lung water imaging. We validated our method in a porcine model of dynamic lung water accumulation (n=5), and tested its feasibility for use in humans using 12 healthy subjects, 1 patient with heart failure with preserved ejection fraction, and 1 patient with heart failure with reduced ejection fraction. Data suggest the novel imaging method is capable of dynamically imaging lung water accumulation during exercise stress. Reference 1 (PMID: 37288601) contains the main results for this study.

  Study phs003346

• Harnessing Epigenetic Regulators to improve HSC-based lentiviral gene therapy

  Curative benefits of autologous and allogeneic transplantation of hematopoietic stem cells (HSCs) have been proven for various diseases. However, the low number of true HSCs that can be collected from patients and subsequently in vitro maintenance and expansion of true HSCs for genetic correction remain challenging. Addressing this issue, we here focused on optimizing culture conditions to improve the ex vivo expansion of true HSCs for gene therapy purposes. In particular, we explore the use of epigenetic regulators to enhance the effectiveness of HSC-based lentiviral (LV) gene therapy. The HDAC inhibitor Quisinostat and the bromodomain inhibitor CPI203 each promote ex vivo expansion of functional HSCs, as validated by xenotransplantation assays and single cell RNA-sequencing analysis. We confirmed the stealth effect of LV transduction on the loss of HSC numbers in commonly used culture protocols, while addition of Quisinostat or CPI203 improved expansion of HSCs in transduction protocols. Of note, we demonstrated that addition of Quisinostat improved LV transduction efficiency of HSCs and early progenitors. Our suggested culture conditions highlight the potential therapeutic effect of epigenetic regulators in hematopoietic stem cell biology and their clinical applications to advance HSC-based gene correction.

  Study EGAS50000000175

• Synovial Fibroblast Gene Expression in Response to Fibronectin Fragment

  Osteoarthritis (OA) is a prevalent joint disease characterized by the progressive degradation of articular cartilage, hypertrophy of neighboring bone, and varying degrees of synovial inflammation. Recent research has highlighted the potential role of synovial fibroblasts in the pathogenesis of OA, particularly their inflammatory properties that disrupt cartilage homeostasis. Notably, degraded cartilage matrix components, such as fibronectin fragments (FN-f), have been identified in the synovial fluid of OA patients, suggesting that FN-f signaling influences the synovium where synovial fibroblasts reside. Despite affecting over 500 million individuals globally, our limited understanding of the underlying mechanisms of OA has significantly impeded the development of effective treatment strategies. To investigate this, we obtained deidentified surgical waste material from individuals undergoing knee replacement for OA. Synovial tissue was used to isolate synovial fibroblasts for cell culture studies. We generated bulk RNA-seq data from primary synovial fibroblasts (N=5 individuals) treated at passage 3 with either Phosphate-Buffered Saline (PBS) as control or FN-f for 18h to model the OA synovial fibroblast phenotype. We identified differentially expressed genes at an adjusted p-value of

  Study phs003999

• Phosphoproteomics adds value to treatment recommendations in molecular tumor boards

  Precision oncology approaches employing genomics-guided targeted therapies for individual patients have provided significant survival benefits in several cancer types. However, low response rates in most solid malignancies, many patients without actionable genomic lesions, and increasing evidence that non-genomic mechanisms may play an important role in tumors indicate that genomics alone is often insufficient to inform and guide the clinical care of patients. Here, we show for the first time that comprehensive (phospho)proteome profiling is feasible and informative in a real-world prospective precision oncology setting. We developed a novel tumor pathway activity (TUPAC) scoring methodology that provides a holistic perspective on dysregulated receptor tyrosine kinase (RTK) signaling in individual patients. Based on 919 tumor tissue profiles of patients enrolled in the national NCT/DKTK MASTER study and the INFORM registry trial, we illustrate how TUPAC scoring can be used to uncover individual tumor biology in rare cancers and demonstrate that TUPAC methodology identifies EGFR-driven sarcomas despite the absence of genetic EGFR alterations. Overall, our work demonstrates the utility of the additional phosphoproteome data layer to enhance therapeutic recommendations in molecular tumor boards.

  Study EGAS00001007891

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• Exome sequencing of patients with Ewings sarcoma

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing,s sarcoma tumours.

  Dataset EGAD00001000333

• SNP_array

  33 ETMR samples were genotyped using Illumina HumanOmni2.5M array. Hybridization and scanning was done according to the manufacturer's instructions (Illumina). Copy number (Log R) and B allele frequency estimates were obtained sing the Genotyping module (v1.9.4) in GenomeStudio v2011.1 (Illumina). Normalized and log2-transformed copy number measurements were imported from genomestudio and analysed using R package CopyNumber to identify segments with similar copy number.

  Dataset EGAD00010001667

• NHLBI TOPMed: Boston-Brazil Sickle Cell Disease (SCD) Cohort

  This study involves sequencing of patients with a diagnosis of sickle cell disease from Brazil. No exclusionary criteria were employed and any eligible patients that consented to this study were recruited.

  Study phs001599