6216 results for "mmoga fc coins Buyfc26coins.com is FC 26 coins official site..dH5e"

in 12.40 milliseconds.

• Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

  Early-generation TRK tyrosine kinase inhibitors (TKIs) approved for treating NTRK fusion–positive (NTRK+) solid tumors provide clinical benefit; however, resistance emerges. Repotrectinib is a next-generation ROS1/TRK TKI with a compact macrocyclic structure designed to improve durability of response. TRIDENT-1 is a registrational phase 1/2 trial assessing repotrectinib, a next-generation ROS1/TRK TKI, in adults with advanced solid tumors, including NTRK+ disease. The primary endpoint was confirmed objective response; secondary endpoints included duration of response (DOR), progression-free survival (PFS), overall survival and safety. Median follow-up ranged between 21.3 months and 25.7 months. In the TKI-naive cohort (n = 51; 95% confidence interval (CI)), the response rate was 59% (44–72); the median DOR was not estimable (NE); and the median PFS was 30.3 months (9.0–NE). In the TKI-pretreated cohort (n = 69; 95% CI), the response rate was 48% (36–60); the median DOR was 9.8 months (7.4–13.0); and the median PFS was 7.4 months (3.9–9.7). Of 30 TKI-pretreated patients with NTRK solvent front mutations, 16 had a response (53%; 95% CI: 34–72). Intracranial responses were observed in two of three TKI-naive patients and in four of six TKI-pretreated patients with measurable intracranial disease at baseline. Among all treated patients (n = 565), the most common any-grade treatment-related adverse event (TRAE) was dizziness (57%); most TRAEs were low grade; and 4% discontinued repotrectinib due to a TRAE. Overall, repotrectinib demonstrated durable systemic and intracranial responses with generally low-grade adverse events in patients with NTRK+ solid tumors, including those with previous TRK TKI treatment and solvent front mutations. These results support the use repotrectinib to treat patients with NTRK+ solid tumors. ClinicalTrials.gov identifier: NCT03093116 .

  Study EGAS50000001572

• Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

  Glioblastoma multiforme (GBM) is a lethal brain tumour in adults and children. However, DNA copy number and gene expression signatures indicate differences between adult and paediatric cases. To explore the genetic events underlying this distinction, we sequenced the exomes of 48 paediatric GBM samples. Somatic mutations in the H3.3-ATRX-DAXX chromatin remodelling pathway were identified in 44% of tumours (21/48). Recurrent mutations in H3F3A, which encodes the replication-independent histone 3 variant H3.3, were observed in 31% of tumours, and led to amino acid substitutions at two critical positions within the histone tail (K27M, G34R/G34V) involved in key regulatory post-translational modifications. Mutations in ATRX (alpha-thalassaemia/mental retardation syndrome X-linked) and DAXX (death-domain associated protein), encoding two subunits of a chromatin remodelling complex required for H3.3 incorporation at pericentric heterochromatin and telomeres, were identified in 31% of samples overall, and in 100% of tumours harbouring a G34R or G34V H3.3 mutation. Somatic TP53 mutations were identified in 54% of all cases, and in 86% of samples with H3F3A and/or ATRX mutations. Screening of a large cohort of gliomas of various grades and histologies (n=784) showed H3F3A mutations to be specific to GBM and highly prevalent in children and young adults. Furthermore, the presence of H3F3A/ATRX-DAXX/TP53 mutations was strongly associated with alternative lengthening of telomeres and specific gene expression profiles. This is, to our knowledge, the first report to highlight recurrent mutations in a regulatory histone in humans, and our data suggest that defects of the chromatin architecture underlie paediatric and young adult GBM pathogenesis.

  Study EGAS00001000226

• Out with the Java, in with the Python - new EGA data download client unveiled

  We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

  Blog new-ega-data-download-client

• New set of services for all users unveiled at the EGA

  The European Genome-phenome Archive (EGA) releases today a brand-new website as well as a set of improved services for users, comprising a revamped Submitter Portal with an improved API and data brokering functionality for submitters, as well as a new DAC Portal for Data Access Committee members to easily manage data access requests. The EGA team has been working hard over the past months on these improvements that will provide a better experience for the users. Discover them below! Visit our new EGA website and check the new functionalities and updated guides Our new website is live, with a fresh look and updated features to discover all the novelties. The homepage now includes three pathways to guide our users, depending on whether they want to deposit, download or manage data within the Archive. One of the most outstanding developments is the introduction of a streamlined process for requesting access to data: EGA Users can now directly request access to their preferred datasets through the website using their EGA accounts. Additionally, users can customise their profile, oversee active sessions, and manage the public keys, essential for our latest array of services, alongside a range of other features. Another major change is our new Help Desk contact method: a built-in website form tailored for user inquiries. This system, called "Need Help?", can be easily located on the top right-hand side of the website. It will encompass both EGA and Federated EGA node users' requests. We will detail its use soon, so stay tuned. Register your metadata to the EGA easily with our new Submitter Portal The new Submitter Portal makes the submission process quicker and more intuitive. The process is currently divided into sections that the user will know beforehand by taking the tour that the EGA team has created to guide users through the Portal before starting the first submission. Do not complete your data submissions alone! Our Submitter Portal now includes a collaboration mode so that every submission can be completed by authorised collaborators with an EGA Profile. There are a lot more features that we will be detailing from now on in incoming posts. A new platform for Data Access Committee Members The new DAC Portal brings novelties for individuals engaged in governance, legal, technical, operational roles, or those acting as data stewards. DAC members will be able to easily manage DACs, policies, and data access requests with the new Portal. Take the tour now to check them out! Help us improve the services completing the EGA Survey As part of our ongoing journey to improve your experience, we have created an EGA User Survey. This questionnaire covers a wide range of aspects such as user experience, support and data accessibility, among others. Participate now and take the opportunity to suggest your own improvements. Help us enhance your experience in this new era for the EGA. Subscribe to the EGA Mailing List and stay tuned In the next weeks we will share more information about the possibilities of the new services. You can easily join the EGA Mailing List to receive all the updates.

  Blog new-set-of-services-at-EGA

• Molecular evolution of metastatic clear cell renal cell carcinoma progressing under tyrosine kinase inhibitor therapy (HIPO-045)

  Background:Acquired resistance to targeted drugs is largely due to intra-tumor molecular heterogeneity and clonal selection. Objective:The objective of this study was to determine molecular alterations and mediating resistant mechanisms and to suggest additional treatment options.Design, Setting, and Participants:Four patients were enrolled into the MORE (Molecular Renal Cancer Evolution) trial. We investigated the mutational spectra of metastatic clear cell renal cell carcinoma (ccRCC) at baseline and compared them to those upon clonal evolution at progression on systemic therapy with tyrosine kinase inhibitors.Outcome Measurements:DNA was isolated from tumor tissues after surgery, metastasis biopsies after progression on sunitinib or axitinib, and subjected to whole-exome sequencing (WES). In addition, the exomes of circulating tumor DNA (ctDNA) from two patients were sequenced at baseline and at progression.Results and Limitations:Our data provide evidence for clonal evolution and various acquired resistance mechanisms of ccRCC with subclonal mutations in FLT4, MTOR, ITGA3/5, SETD2, and VHL on metastatic progression. The limited number of shared mutations in tissue and plasma biopsies indicates that both sources provide complementary information, possibly due to mutations present in metastatic lesions which were not amenable to tissue sampling but are represented in the ctDNA. Conclusion:Acquired resistance to targeted therapies in metastatic ccRCC is due to intra-tumor heterogeneity and clonal evolution. Larger patient cohorts have to be studied to estimate the benefit of WES from biopsies and ctDNA for therapy decision in metastatic ccRCC.Patient Summary:We analyzed the molecular profiles of ccRCC patients in primary tissues and metastatic tissues upon progression on tyrosine kinase inhibitor therapy. Clinically relevant mutations upon progression were detected in the metastatic sites of all of four patients, suggesting that it might be possible to derive therapies based on sequencing the metastases.?HIPO-045

  Study EGAS00001001861

• Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

  Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. Standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the power of short reads. Starting from only 1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as 'Linked-Reads'. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes. In this manuscript, we show the utility of reference based analysis using a single Linked-Read library for full spectrum genome analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

  Study EGAS00001003121

• Indonesian Genome Diversity Project

  Indonesia, the world’s fourth largest country by population, comprises an archipelago of about 900 permanently inhabited islands in tropical Asia, and hosts an astonishing array of human diversity that remains largely underrepresented in modern biological surveys. The region is unique for its key role in both the early and recent evolution of Homo outside of Africa. It has one of the first traces of anatomically modern humans in Eurasia, and was the focus of extensive interaction between archaic hominins and humans – both in the likely co-existence of H. floresiensis with modern humans, and in the introgression of Denisovans into the ancestors of its present inhabitants. More recently, Indonesia was a center of the spread of Neolithic culture by Austronesian speakers. Advancing maritime technologies allowed farming populations to treat this region as a springboard to reach oceanic islands as remote as Madagascar, Hawaii, Easter Island and New Zealand. Here we present complete human genomes from healthy individuals from multiple key islands in Indonesia and Papua. The genomes were sequenced to high depth (30x). The purpose of this dataset is to address different questions of human evolution in Island Southeast Asia and beyond, including early settlement of the area by anatomically modern humans, population structure, genetic admixture and adaptation, and contacts with archaic hominins. We employed a sampling strategy to capture a broad range of diversity across the region incorporating an average of 12 samples from each of 14 islands spanning Indonesia and Papua, from Sumatra in the west to New Britain in the east. Genomes from this dataset form part of an ongoing project to describe and understand human evolutionary history in Island Southeast Asia and Eurasia in general.

  Study EGAS00001003054

• Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive NSCLC patients

  Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but efficacy varies between patients and is believed to depend in part on the amount and properties of tumor infiltrating lymphocytes (TILs). To comprehensively depict and dissect the baseline landscape of the composition, lineage and functional states of TILs in lung cancer, here we generated deep single-cell RNA sequencing data for 12,346 T cells from the primary tumour, adjacent normal tissues and peripheral blood of 14 treatment-naive NSCLC patients. Combined expression and TCR-based lineage tracking revealed a significant proportion of effector T cells with common origins and similar functional states across peripheral blood and tumours pointing towards a highly migratory nature of these T cells. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of pre-exhausted to exhausted T cells is associated with better prognosis of lung adenocarcinoma (LUAD). In addition, we observed further heterogeneity within the tumour regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of this group of activated tumour Tregs, which included IL1R2, correlated with poor prognosis in LUAD. The T cell clusters revealed by our single cell analyses provide a new approach for patient stratification, and the accompanying compendium of data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

  Study EGAS00001002430

• UK10K NEURO FSZ

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. These Finnish schizophrenia samples have been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder, each family having at least two affected siblings. 170 families originate from an internal isolate (Kuusamo) with a three-fold lifetime risk for the trait. The genealogy of the internal isolate is well documented and the individuals form a “megapedigree” reaching to the 17th Century. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data. For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

  Study EGAS00001000118

• 'Targeted High Throughput Sequencing in Clinical Cancer Settings: Formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity'

  "Background: Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings. Methods: Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.Results: We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance. Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations, but is of minor importance for the detection of somatic variations.Conclusions: The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies taken, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - on a long-range - result in a more reliable prediction of individual cancer therapies."

  Study EGAS00001000136