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• MYOSEQ

  The MYOSEQ project focuses on the application of next generation sequencing, in particular whole exome sequencing (WES), in a large cohort of patients with unexplained limb‐girdle weakness (LGW). Focusing on undiagnosed patients with a clearly defined clinical phenotype enables increased diagnostic rates for known genes (in particular Pompe disease, GNE related pathologies and other known LGMD subtypes) in this cohort, while the use of WES provides scope both for new gene discovery and for additional research into disease modifiers and genotype‐phenotype correlation with substantial cost effectiveness. The LGW patient cohort was collated by Newcastle University in collaboration with clinical centers across Europe. The sequencing was performed at the Broad Institute and jointly analyzed with Newcastle University.

  Dataset EGAD00001006158

• NCI CCSG CCDI Supplement Additional Genomic Submission

  The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. This supplement data from the Beat AML program provides Adolescent and Young Adult (AYA) and pediatric tumor specimens not previously released. These data include exome and RNA level characterization as well as analyses of ex vivo drug sensitivity. Collectively, this data can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of leukemia in pediatric and AYA populations.

  Study phs002599

• Molecular Features of Hepatocellular Carcinoma Associated with 18F-Fluorocholine PET/CT Imaging Phenotype

  Molecular imaging with 18F-fluorocholine PET/CT reveals two distinct imaging phenotypes for hepatocellular carcinoma (HCC) as a potential source of non-invasive insight into its molecular heterogeneity. Using gene set enrichment analyses, we found 18F-fluorocholine-avid tumors to be significantly enriched by genes comprising a subset of previously published HCC-related gene signatures. Significant gene sets included those from existing molecular classification systems for HCC as well as gene signatures predictive of clinical outcomes after tumor resection. PET/CT imaging using 18F-fluorocholine might therefore provide surrogate information about tumor molecular characteristics and prognosis in HCC.

  Study phs001784

• Determinants of Venetoclax Resistance

  The study aimed to identify genetic determinants of resistance to Venetoclax, a recently approved BCL-2 inhibitor for patients with chronic lymphocytic leukemia (CLL). Whole exome sequencing of tumor samples from 6 CLL patients relapsing on Venetoclax revealed clonal evolution when comparing pre- and post-Venetoclax samples. Genetic screens for genes involved in sensitivity to Venetoclax and investigations of resistant cell lines (including OCI-Ly1) revealed MCL-1 and regulators of cellular energy metabolism (AMPK pathway) to drive resistance to Venetoclax. Further explorations of patient samples confirmed MCL-1 expression and AMPK activation to be increased at relapse on Venetoclax.

  Study phs001875

• Bulk RNA-seq of monocytes and in vitro cultured monocyte-derived macrophages of ANCA-associated vasculitis patients with active and stable disease and healthy controls

  To study monocyte and macrophage activation in ANCA-associtated vasculitis (AAV), we performed bulk RNA sequencing of bead-selected monocytes and in vitro cultured monocyte-derived macrophages from AAV patients and healthy controls. Overview patients included for sequencing monocytes: - AAV active disease, n=4, MPO-AAV=4 - AAV remission, n=10, PR3-AAV=5, MPO-AAV=5 - Healthy controls, n=6 Overview patients included for sequencing monocyte-derived macrophages: - AAV active, n=1, PR3-AAV=1 - AAV remission, n=3, PR3-AAV=3 - Healthy controls, n=3

  Study EGAS50000000311

• A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk

  Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

  Dataset EGAD50000000518

• human CMV-specific CD8+ T cells

  In this study we established a comprehensive workflow to collect multi-omics single-cell data using a commercially available micro-well based platform. This included whole transcriptome, cell surface markers (targeted sequencing-based cell surface proteomics), T cell specificities, adaptive immune receptor repertoire (AIRR) profiles and sample multiplexing. With this technique we identified novel paired T cell receptor sequences for three prominent human CMV epitopes. In addition, we review the ability of dCODE dextramers to detect antigenspecific T cells at low frequencies by estimating sensitivities and specificities when used as reagents for single-cell multi-omics.

  Study EGAS50000000633

• Neuroblastoma Smart-Seq2 Single Nuclei Sequencing Data

  Heterogeneity of tumors, including the presence of resistant clones, represents a great challenge for high-risk neuroblastoma (NB). Currently, there are no treatments that address cancer heterogeneity. Classification of bulk tumors and corresponding predictions are poor and too general. Understanding heterogeneity will provide critical insight for the development of targeted therapeutic strategies. In this study, we collected 10 human neuroblastoma tumor samples and performed whole-transcriptome profiling at single-nucleus resolution using SMART-Seq2 technology. This approach enables comprehensive characterization of transcriptional diversity within individual tumors, allowing us to identify distinct cellular subpopulations.

  Study EGAS50000001103

• Pancreatic cancer organoids recapitulate disease and allow personalized drug screening

  We report derivation of 30 Patient-Derived Organoid lines (PDOs) from tumors arising in the pancreas and distal bile duct. PDOs recapitulate tumor histology and contain genetic alterations typical for pancreatic cancer. In vitro testing of a panel of 76 therapeutic agents revealed sensitivities currently not exploited in the clinic. The PRMT5 inhibitor EZP015556, shown to target MTAP negative tumors, was validated as such, but also appeared to constitute an effective therapy for a subset of MTAP+ tumors. Taken together, the work presented here provides a platform to identify novel therapeutics to target pancreatic tumor cells using PDOs.

  Study EGAS00001003369

• Transcriptomic analysis of the Phase 3 COMPARZ clinical trial

  Metastasis remains the main reason for renal cell carcinoma (RCC)-associated mortality. Tyrosine kinase inhibitors (TKI) impart clinical benefit for most RCC patients but the determinants of response are poorly understood. We report an integrated genomic and transcriptomic analysis of metastatic clear cell RCC (ccRCC) patients treated with TKI therapy and identify predictors of response. Patients in the COMPARZ phase III trial received first-line sunitinib or pazopanib with comparable efficacy. Microarray-based transcriptomic analyses with results from Next-gen genomic analyses of targeted genes revealed distinct molecular subgroups associated with response and survival.

  Study EGAS00001004534