17560 results for "fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins They are definitely a top seller..rG5l"

in 16.25 milliseconds.

• Arcagen – thoracic malignancies

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from rare thoracic malignancies (n=102)

  Dataset EGAD50000000168

• Host pathogen interaction long read transcriptome

  Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

  Study EGAS00001006779

• Allele-specific expression of GATA2 due to epigenetic dysregulation in double mutated CEBPA AML

  Transcriptional deregulation is a central event in the development of acute myeloid leukemia (AML). To identify potential disturbances in gene regulation, we conducted an unbiased screen of allele-specific expression (ASE) in 209 AML cases. The gene encoding GATA binding protein 2 (GATA2) displayed ASE more often than any other myeloid or cancer-related gene. GATA2 ASE was strongly associated with CEBPA double mutations (CEBPA DM), with 95% of cases presenting GATA2 ASE. In CEBPA DM AML with GATA2 mutations, the mutated allele was preferentially expressed. We found that GATA2 ASE is a somatic event lost in complete remission, supporting the notion that it plays a role in CEBPA DM AML. Acquisition of GATA2 ASE involved silencing of one allele via promoter methylation, compensated by overactivation of the other allele, thereby preserving expression levels. Notably, promoter methylation was also lost in remission together with GATA2 ASE. In summary, we propose that GATA2 ASE is acquired by epigenetic mechanisms and is a prerequisite for the development of AML with CEBPA DM. This finding constitutes a novel example of an epigenetic hit cooperating with a genetic hit in the pathogenesis of AML.

  Study EGAS00001004684

• Biological insights from the whole genome sequences of human embryonic stem cell lines

  Human embryonic stem cells (hESCs) are a powerful tool for the study of human development and can form the basis of cellular disease models or therapies. However, the genetic make-up and stability of hESCs has not been systematically studied at a genome-wide level with single nucleotide resolution. We therefore sequenced the whole genome and whole exomes of widely available hESC. This online resource will enable investigators to access raw sequencing data in order to interrogate cell lines for different disease- and trait-associated genetic variants.

  Study EGAS00001002400

• CNV detection in targeted NGS panel data

  The aim of this study was to compare copy-number-variation (CNV) detection methods for targeted NGS panel data in a clinical diagnostic setting. We present targeted NGS panel data from 170 samples that were processed using the TruSight(TM) Cancer (TSC) panel (Illumina, San Diego, CA, USA), which targets 94 genes and 284 SNPs associated with a predisposition towards cancer. The samples are enriched for CNVs in the genes of interest. All CNVs have previously been assessed with MLPA and can therefore be considered as confirmed.

  Study EGAS00001002481

• Genetic and transcriptional landscape of plasma cells in POEMS syndrome

  POEMS syndrome is a rare paraneoplastic disease, associated with monoclonal plasma cells whose pathogenic importance remains unclear. We performed comprehensive genetic analyses of plasma cells in 20 patients with POEMS syndrome. Whole exome sequencing and targeted sequencing identified 7 recurrently mutated genes: KLHL6, LTB, EHD1, EML4, HEPHL1, HIPK1, and PCDH10. None of the driver gene mutations frequently found in multiple myeloma (MM) such as NRAS, KRAS, BRAF, and TP53 was detected. Copy number analysis showed chromosomal abnormalities shared with monoclonal gammopathy of undetermined significance (MGUS). RNA sequencing revealed a transcription profile specific to POEMS syndrome, especially in terms of tumorigenesis. Unexpectedly, disease-specific VEGFA expression was not increased in POEMS syndrome. Our study illustrates that the genetic and transcriptional profiles of plasma cells in POEMS syndrome are distinct from MM and MGUS, indicating its unique pathogenesis.

  Study JGAS000150

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. The repository includes the raw mass spectrometry-based proteomics data

  Study EGAS00001006712

• DNA methylation-based classification of sinonasal tumors [DNA sequencing]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. This repository includes the results from DNA sequencing and mass spectrometry-based proteomics.

  Study EGAS00001006713

• Tracking the genomic evolution of esophageal adenocarcinoma through neoadjuvant chemotherapy

  Esophageal adenocarcinomas (EACs) are associated with dismal prognosis. Deciphering the evolutionary histories of this disease may shed light on therapeutically tractable targets and reveal changing mutational processes during the disease course and following neoadjuvant chemotherapy (NAC). We exome sequenced 40 tumor regions from 8 patients with operable EACs both before and after platinum-containing NAC. This revealed the evolutionary genomic landscape of EACs with the presence of heterogeneous driver mutations, parallel evolution, early genome doubling events and an association between high intratumor heterogeneity and poor response to NAC. Multi-region sequencing demonstrated a significant reduction in T>G mutations within a CTT context when comparing early and late mutational processes and the presence of a platinum signature with enrichment of C>A mutations within a CpC context following NAC. EACs are characterized by the presence of amplifications containing targetable oncogenes present before and after chemotherapy that may provide a rationale for future therapeutic approaches.

  Study EGAS00001001254

• Multiomics analyses of Parkinson's disease midbrains

  Understanding the key pathological mechanisms underlying Parkinson's Disease pathology is fundamental for the development of novel and more effective therapeutic strategies. In this study, post-mortem human midbrain tissue from a cohort of 13 PD patients and 10 controls was analyzed with a set of multi-omics technologies including small RNA sequencing, transcriptomics and proteomics profiling.

  Study EGAS00001004966