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• Splicing signature analysis of RNU4-2, RNU5A-1 and RNU5B-1

  Pathogenic variants in the snRNA RNU4-2 were recently described as a frequent cause of neurodevelopmental disorders. In our study we further delineate the phenotype associated with RNU4-2 and we also identify pathogenic variants in RNU5A-A and RNU5B-1. Capture-based RNA-Seq were performed to compare splicing pattern between affected and control individuals. A strong signature based on alternative 5' splice site usage was found for RNU4-2 patients, and we suggest an either 5' or 3' signature depending on the variant's localiztion in U5 genes.

  Study EGAS50000000889

• RNA-seq of MPNSTs

  Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly aggressive soft-tissue sarcomas with a poor prognosis and a lack of therapeutic options. In this study, we analyse the whole-transcriptome MPNST and combine them with WGS data from a partially overlapping sample set. These analyses and the inclusion of another public dataset allow us to identify three genomic MPNST subgroups with distinct biological and clinicopathological features that can inform management and precision treatments. Published in "Identification of Malignant Peripheral Nerve Sheath Tumor (MPNST) subtypes with distinct genomic identities."

  Study EGAS50000001733

• Germline alterations of acute myeloid leukemia

  Germline variants may increase the risk of cancer. A systematic analysis was conducted of a consecutive series of primary and secondary adult acute myeloid leukemia (AML) patients. Exome sequencing was performed on leukemic blasts (somatic) and a skin biopsy (germline) followed by analysis on 35 acute myeloid leukemia or cancer predisposition candidate genes. Exome data were available from 68/80 (85%) patients, and full clinical history was available from all patients. The analysis revealed 34 rare single-nucleotide variants or short indels in 16 genes to be functionally adverse in silico.

  Study EGAS00001002760

• Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

  Gastric cancer (GC) is a major cause of global cancer mortality with high levels of heterogeneity, and intratumoral heterogeneity (ITH) represents a significant barrier to GC patient outcomes. In this study, we applied GeoMx DSP technology to identify ITH in GC. We found spatially colocalized RNA-based intratumor subgroups within samples, each correlated with distinct spatially oriented TME and immune profiles. The findings broadening our understanding of the spatial and molecular complexity of GC ITH and offering a valuable data resource for future exploration and discovery.

  Study EGAS50000000345

• Genome-wide NanoRCS of cfDNA from plasma of healthy individuals

  Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We adapted a new technique, NanoRCS, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to plasma of healthy controls.

  Study EGAS50000000695

• Placebo-only arm transcriptomic analysis of the phase 3 PROTECT clinical trial

  It is poorly understood how the tumor immune microenvironment influences disease recurrence in localized clear cell renal cell carcinoma (ccRCC). Here we perform whole-transcriptomic profiling of 236 tumors from patients assigned to the placebo-only arm of a randomized, adjuvant clinical trial for high-risk localized ccRCC. Unbiased pathway analysis identifies myeloid-derived interleukin-6 (IL-6) as a key mediator. Furthermore, a novel myeloid gene signature strongly correlates with disease recurrence and overall survival on uni- and multivariate analysis and is linked to TP53 inactivation across multiple datasets.

  Study EGAS00001006344

• Cystic fibrosis multi-omics study

  Cystic fibrosis (CF) is a genetic disorder affecting approximately 1 in 2,500 people in the UK. Here, we generated a number of high-throughput sequence data sets for monocytes and neutrophils from CF patients and matched healthy volunteers (HV); including ChIP-Seq (H3K27Ac), chromatin accessibility (ATAC-Seq), and transcript/gene expression (RNA-Seq) data. Analysis of gene expression and epigenetic profiles demonstrates a robust innate immune gene expression profile that distinguishes CF and HV during periods of disease exacerbation. Upregulation of pathways responsible for the production of proinflammatory cytokines is described.

  Study EGAS00001006421

• Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

  This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

  Study EGAS00001004942

• Single-cell RNA and ATAC sequencing data analysis of human postmenopausal fallopian tube and ovary

  In this study, we used a combination of technologies, including Drop-seq, 10X single-cell RNA-seq (scRNA-seq), and single-cell assay on transposase accessible chromatin (scATAC-seq) to generate  a high-quality cell atlas that consists of four tissue sites from the reproductive tract of postmenopausal women. This atlas, by far the most comprehensive map of the postmenopausal female reproductive system to date, will pave the way to a better understanding of the pathophysiology of many diseases affecting older women.

  Study EGAS00001006780

• Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023

  Synthetic - This submission contains a subset of a synthetic dataset derived from the project Heilsa Tryggvedottir - a Nordic collaboration on sharing sensitive human data. Heilsa Tryggvedottir is funded by the Nordic e-Infrastructure Collaboration (NeIC), the ELIXIR nodes of Finland, Norway, and Sweden, Computerome in Denmark, and the Estonian Scientific Computing Infrastructure (ETAIS). In the synthetic data creation process, it was attempted to strike a fine balance between the usability of the datasets (e.g. technical FEGA development, testing, user training, and basic bioinformatics) and compliance with GDPR. File names and file content (e.g. headers in fastq) are anonymized. Moreover, the X, Y, and mitochondrial sequences have been discarded from the original data since these data can be used for maternal, paternal, or ethnic origin tracing. The dataset does not follow natural haplotype distribution (inherent to imputation panels). The only inputs derived from real sequence data are variant distribution density per chromosome and learning sequencing error models. The synthetic dataset consists of two fastq files, a cram file, a vcf file, and two index files.

  Dataset EGAD50000000119