21157 results for "fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins The service is affordable and quick..6Xgd"

in 30.63 milliseconds.

• Detection of Cancer Mutations by Urine Liquid Biopsy in Bladder Cancer Patients

  The management of bladder cancer faces multiple challenges concerning the diagnostics and fol-low-up approaches. The standard diagnostic test is invasive cystoscopy. Urine cytology and re-cently proposed urine-based biomarkers still could not replace cystoscopy, thus prompting calls for improvements. Here, we explore urine liquid biopsy to detect cancer mutations for therapeutic and prognostic assessment and subsequently evaluate the utility of urine as a suitable specimen in diagnosing bladder cancer. Our findings show that the analysis of pre-and post-operative urine enables the characterization of specific tumor mutations, which can be used to diagnose and evaluate a patient’s prognosis and therapy response.

  Study EGAS00001005758

• 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

• glioblastoma single cell RNAseq

  Understanding the cellular origin and differentiation status of glioblastoma is critical to resolve the etiology of the disease. we profile 18 patient glioblastomas by single cell RNA sequencing (scRNAseq). From this, we uncovered two principal cell-of-origin relations. Each lineage displays unique directional differentiation trajectories and transcriptional cores from the naïve cell populations. Thus, glioblastoma is defined by robust cell lineage features which may provide insights into the cell origin of the diseases.

  Study EGAS00001006236

• Location and Function of NSun2-Mediated Cytosine-5 Methylation in RNA and its Effect on Translation

  Mutations in the cytosine-5 RNA methyltransferase NSun2 can cause neurodevelopmental disorders and symptoms commonly found in patients with Dubowitz-like syndrome. Some tRNAs are known to be methylated NSun2, however the occurrence of cytosine-5 methylation (m5C) in other RNA biotypes is still under debate. Location in RNA and function of m5C has not been studied yet. This study is aimed at identifying new m5C methylated RNA biotypes, as well as the location at specific structures or sequences and the ultimate biological function. The impact of the loss of NSun2-mediated methylation is also determined by comparing gene expression data with the global cytosine-5 RNA methylome in Dubowitz-like syndrome patients. We also use ribosomal profiling to assess the impact of the loss and rescue of Nsun2-mediated cytosine-5 RNA methylation on translation rates and ribosome occupancy.

  Study phs000645

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Human liver cholangiocyte organoids capture the heterogeneity of in vivo human liver ductal epithelium

  Human liver ductal epithelium is morphologically, functionally and transcriptionally heterogeneous. However, understanding the dynamics within human biliary/ductal epithelium has been hampered by the absence of an in vitro system that fully mimics its complex cellular heterogeneity. Here, we found that the human liver cholangiocyte (ductal-cell) organoids we previously published (Huch et al., 2015) are fairly homogenous and do not retain the cellular heterogeneity of the in vivo human biliary/ductal epithelium. Inspired by the knowledge of the in vivo niche, we refined our previous organoid culture medium to fully capture the cellular heterogeneity of the human ductal epithelium. We employed this refined system to analyse the interactions and relationships between the different human biliary epithelial cell states and discovered that acquiring a bipotent ductal cell state is necessary for differentiating the human ductal epithelium into functional hepatocyte-like cells. Our improved cholangiocyte organoid model represents a new platform to investigate cell plasticity and duct-to-hepatocyte differentiation in human liver.

  Study EGAS50000001000

• Data access committee for "Detection of brain cancer using genome-wide cell-free DNA fragmentomes"

  The data access committee for “ Detection of brain cancer using genome-wide cell-free DNA fragmentomes”. The DAC is comprised of Drs. Dimitrios Mathios, Jillian Phallen, Victor Velculescu, Robert Scharpf, Noushin Niknafs, and Shashikant Koul, and can be contacted at skoul3@jh.edu.

  Dac EGAC50000000605

• Development and first-in-human CAR T therapy targeting the pathognomonic MiT-fusion driven protein GPNMB

  Summary: CAR T therapy for solid tumors is constrained by the scarcity of safe, uniformly expressed cell-surface targets. Here we identify GPNMB, a MiT fusion-driven protein, as highly, homogeneously, and stably expressed in primary and relapsed translocation-positive alveolar soft part sarcoma (ASPS) and renal cell carcinoma (tRCC). We develop a GPNMB-directed CAR T cell product, GCAR1, which demonstrates potent activity against patient-matched cells, organoids and xenograft models. In a first-in-human treatment of two patients with relapsed/refractory, metastatic ASPS, GCAR1 is well tolerated and induces stable disease for up to 6 months, accompanied by resolution of many non-target lesions. GCAR1 T cells expand in peripheral blood as a polyclonal population and remain detectable for up to 6 months. Spatial transcriptomics identify multiple immunosuppressive niches adjacent to T cells infiltrating treatment-resistant lesions; biological PDL1 blockade or PD1 and TIGIT double knockout overcomes this resistance and shows synergistic activity with GCAR1 in xenograft models. Taken together, these data provide clinical proof-of-concept for treating solid tumors with CAR T cells targeting a surface antigen driven by an oncogenic gene fusion.

  Study EGAS50000001696

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• TCELL_PILOT_ATAC_SEQ

  This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000758