10679 results for "fc coins olx Navštivte Buyfc26coins.com Podpora pro profesionální hráče a týmy..zSiZ"

in 15.72 milliseconds.

• The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas

  Tuberous sclerosis complex (TSC) is an autosomal dominantly inherited neurocutaneous disorder caused by inactivating mutations in TSC1 or TSC2, key regulators of the mechanistic target of rapamycin complex 1 (mTORC1) pathway. In the central nervous system TSC is characterized by cortical tubers, subependymal nodules and subependymal giant cell astrocytomas (SEGAs). SEGAs may lead to the impaired circulation of cerebrospinal fluid resulting in hydrocephalus and raised intracranial pressure in patients with TSC. Currently, surgical resection and mTORC1 inhibitors are the recommended treatment options for patients with SEGA. Here, we performed RNA-Seq and small RNA-Seq on SEGAs (n=19) and periventricular controls (n=8) to gain a better understanding of the underlying molecular basis of SEGAs, so that novel treatment targets could be identified.

  Study EGAS00001003787

• Integrative Profiling of T790M Negative EGFR Mutated NSCLC Reveals Pervasive Lineage Transition and Therapeutic Opportunities

  We performed whole exome and transcriptome analysis of 59 first- and second-generation EGFR TKI resistant metastatic EGFR mutated patients to characterize and compare molecular alterations mediating resistance in T790M positive and negative disease. Transcriptomic analysis revealed ubiquitous loss of adenocarcinoma lineage gene expression in T790M negative tumors, orthogonally validated using multiplex immunohistochemistry. There was enrichment of genomic features such as TP53 alterations, 3q chromosomal amplifications, whole genome doubling and non-aging mutational signatures in T790M negative tumors. Almost half of resistant tumors were further classified as Immunehot, with clinical outcomes conditional on immune cell infiltration state and T790M status. Finally, using a Bayesian statistical approach, we explored how T790M negative and positive disease might be predicted using comprehensive genomic and transcriptomic profiles of treatment-naïve patients.

  Study EGAS00001005389

• Microbiota 16S sequencing study in NSCLC patients eligible for surgery without neoadjuvant treatment

  18 non-small cell lung cancer patients eligible for surgery without neaodjuvant treatment were included in the study at Centre Jean Perrin (France). Patients did not take any antibiotics, food supplements or immunostimulants 2 months prior to inclusion. During surgery, patients underwent partial or complete lobectomy where samples of non-malignant lung tissue, peritumoural tissue and tumour were resected from the removed lobe. This was preceeded by the washing of the removed lobe and obtaining the broncho-alveolar lavage fluid. These four sample types were analysed by 16S sequencing in 17 from 18 patients. The study is a part of the project "Characterization of Microbiota (Intestinal, From Lungs, and Upper Airways) in Patients With Non-small Cell Lung Carcinoma: Exploratory Study " which is registered under ref. NCT03068663 (clinicaltrials.gov).

  Study EGAS00001004728

• Single cell whole genome sequencing of high hyperdiploid acute lymphoblastic leukemia

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15). The dataset has been used for copy number aberrations analysis.

  Study EGAS00001006347

• Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

  Here, we performed genome-wide 5-mC profiling in plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis and therapy monitoring. Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples were available from previous studies.

  Study EGAS00001006573

• Profiling of childhood neuroblastoma and the immune microenvironment by single-cell sequencing of RNA and TCR

  Neuroblastoma tumor cells and their tumor microenvironment are studied by single-cell RNA sequencing of primary neuroblastoma tumors and neuroblastoma-infiltrated tissues/metastases. Both diagnostic samples, taken pre-treatment and samples taken after induction chemotherapy at surgical resection and biopsies from relapse samples are included.  For a number of patients single-cell RNA sequencing of blood samples (controls) are included and additionally we performed single-cell T cell receptor sequencing (TCR) on the tumor and blood samples. With this study, we will focus on identifying differences in tumor cells and their (immune) microenvironment 1) before and after treatment or at relapse and 2) between primary tumors and infiltrated tissues/metastases. Moreover, with TCR sequencing we aim to unveil immune cell dynamics in patients with neuroblastoma.

  Study EGAS00001006823

• Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

  In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.

  Study EGAS00001007078

• Ex vivo RNA-seq in moderate COVID-19 monocytes

  This dataset was used to compare gene expression profiles of ex vivo isolated classical CD14+ monocytes from patients with moderate COVID-19 to those of healthy individuals. Blood samples were taken from patients with moderate COVID-19 admitted to hospitals in London (Hammersmith Hospital, Charing Cross Hospital, Saint Mary’s Hospital) 3-14 days after disease onset and 0-2 days after hospitalization and positive PCR, and before study treatment initiation. Moderate patients displayed mild or moderate COVID-19 pneumonia, defined as grade 3 or 4 WHO severity. Samples were collected from March 2020 to February 2021. Healthy donors were Imperial College staff with no prior diagnosis of or recent symptoms consistent with COVID-19, and where possible, were matched in age and sex distribution with COVID-19 patients. None of the participants of this study were COVID-19 vaccinated. Peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll Hypaque (GE Healthcare) gradient centrifugation <4 hours after blood collection. CD14+ monocytes were isolated using a positive selection magnetic sorting kit (StemCell Technologies, UK) from total PBMC and stimulated with vehicle, UV-inactivated SARS-CoV-2 (CoV-2). RNA was isolated using the RNeasy Micro Plus Kit (QIAGEN) following the manufacturer’s guidelines. RNA-sequencing was performed by the Oxford Genomics Centre. PolyA-enriched strand- specific libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kits (Illumina). All samples were pooled together and 150bp PE reads were sequenced on a Novaseq 6000 system.

  Dataset EGAD00001009800

• Genomics Define Malignant Transformation in Myeloma Precursor Conditions

  Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

  Dataset EGAD00001015768

• Genome-wide associations of human gut microbiota variation and implications for causal inference analyses

  Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

  Study EGAS00001004420