17128 results for "free coins in fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..xwWa"

in 15.29 milliseconds.

• Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo

  Despite improvement in the treatment of medulloblastoma (MB) over the last years, numerous patients with MYC- and MYCN-driven tumors still fail the current therapeutic regimen. The retinoblastoma (RB) pathway is often compromised in MB with RB remaining intact suggesting that CDK4/6 inhibition might represent a therapeutic strategy for which drug combination remains understudied. Using tumor lines grown in stem cell conditions referred as tumorspheres as well as tumor cells freshly dissociated from the brain of mice harboring intracranial patient-derived xenografts (PDX) of Group3 (G3) and Sonic Hedgehog (SHH) MB, we conducted high throughput drug combination screens using the CDK4/6 inhibitor (CDK4/6i) ribociclib as an anchor and 87 oncology drugs approved by FDA or currently in clinical trials. Bromodomain and extra terminal (BET) and PI3K/mTOR inhibitors potentiated ribociclib’s inhibition of proliferation in G3 and SHH MB. A reverse combination screen using BET inhibitor JQ1 as the anchor, revealed the three FDA approved CDK4/6i as the most potentiating drugs. Those synergistic combinations were tested in vivo in mice intracranially implanted with G3 and SHH MB tumor cells. Ribociclib showed single agent activity in several in vivo MB models. However, despite in vitro synergy, combinations of ribociclib with JQ1 and ribociclib with the PI3K/mTOR inhibitor paxalisib failed to improve the survival of MB bearing mice compared to ribociclib alone. Our data illustrates the difficulty in translating in vitro findings to in vivo for brain tumors partly due to insufficient free brain concentration and altered signaling pathways activation in vitro compared to in vivo.

  Study EGAS00001006286

• FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

  The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

  Blog fega-faqs-elixir-ahm-2024

• Atezolizumab Plus Chemotherapy With or Without Bevacizumab in Advanced Biliary Tract Cancer: Clinical and Biomarker Data From the Randomized Phase II IMbrave151 Trial

  PURPOSE Biliary tract cancers (BTCs) harbor an immunosuppressed tumor microenvironment (TME) and respond poorly to PD-1/PD-L1 inhibitors. Bevacizumab (anti-VEGF) plus chemotherapy can promote anticancer immunity, augmenting response to PD-L1 inhibition. PATIENTS AND METHODS This randomized, double-blind, proof-of-concept Phase II study enrolled patients (n=162) with previously untreated advanced BTC (IMbrave151; NCT04677504). Patients were randomized 1:1 to receive 3-weekly cycles of atezolizumab (1200 mg) plus bevacizumab (15 mg/kg) or atezolizumab plus placebo until disease progression or unacceptable toxicity. All patients received cisplatin (25 mg/m2) plus gemcitabine (1000 mg/m2; CisGem) on Days 1 and 8 every 3 weeks for up to 8 cycles. Stratification of patients was by disease status, geographic region, and primary tumor location. The primary endpoint was progression-free survival (PFS). No formal hypothesis testing was performed. Exploratory correlative biomarker analysis was undertaken using transcriptome analysis (n=95) and mutation profiling (n=102) on baseline tumor samples. RESULTS Between February and September 2021, 162 patients were enrolled. Median PFS was 8.3 months in the bevacizumab arm and 7.9 months in the placebo

  Study EGAS50000000387

• Circulating cell-free DNA analysis in Small Cell Lung Cancer

  Small cell lung cancer (SCLC) accounts for ~250,000 deaths worldwide each year. Acquisition of adequate tumour biopsies is challenging and liquid biopsies present the best option for patient stratification and response monitoring. We present genome-wide and targeted plasma DNA sequencing data that identifies tumour related changes in 91% of limited (LS-SCLC) and 100% of extensive stage (ES-SCLC) patients. Parallel analysis of circulating tumour cells (CTCs, by CellSearch) based on ≥ 1 CTC/7.5ml blood increased tumour detection frequencies to 98% patients (95% for LS-SCLC) where CTC count and plasma DNA readouts correlated with disease stage and overall survival (OS). Targeted plasma DNA sequencing identified potential therapeutic targets in >50% of patients. This approach will support trials of targeted therapies where improved patients outcomes are urgently required.

  Study EGAS00001003110

• Detection of low-frequency DNA variants by targeted sequencing of the Watson and Crick strands

  Identification and quantification of low-frequency mutations remain challenging despite improvements in the baseline error rate of next-generation sequencing technologies. Here, we describe a method, termed SaferSeqS, that addresses this challenge by (1) efficiently introducing identical molecular barcodes in the Watson and Crick strands of template molecules and (2) enriching target sequences with strand-specific PCR. The method achieves high sensitivity and specificity and detects variants at frequencies below 1 in 100,000 DNA template molecules with a background mutation rate of <5 × 10-7 mutants per base pair (bp). We demonstrate that it can evaluate mutations in a single amplicon or simultaneously in multiple amplicons, assess limited quantities of cell-free DNA with high recovery of both strands and reduce the error rate of existing PCR-based molecular barcoding approaches by >100-fold.

  Study EGAS00001005048

• STAMPEED: Northern Finland Birth Cohort 1966 (NFBC1966)

  The Northern Finland Birth Cohorts program (NFBC) was initiated in the 1960s in the two northernmost provinces of Finland to study risk factors involved in pre-term birth and intrauterine growth retardation, and the consequences of these early adverse events on subsequent morbidity and mortality. The uniqueness of NBFCs is that the data of the cohorts were obtained from early fetal life (including maternal health during pregnancy) to adulthood. The NFBC1966 includes 12,058 live births to mothers in the two northern-most provinces of Finland. Two decades later, a second cohort of 9432 births was obtained (NFBC1986). In NFBC1966 pregnancies were followed prospectively from the first antenatal contact (10-16th week). After birth, the offspring were examined and then again underwent clinical evaluation at ages 1y, 7y, 14-16y and 31y. At each visit, a wide range of phenotypic, lifestyle and demographic data were gathered by questionnaires and clinical examinations. For the most part, NFBC1986 has undergone similar evaluations to NFBC1966. Linkage to national registries includes hospitalization, deaths, education, medication, pensions, and provides up-to-date demographic and clinical information for members of both cohorts. DNA samples were obtained from 5,923 subjects from NFBC1966 and 6688 subjects from NFBC1986. Data coverage, 96% of all births in 1966 and 99% in 1986, is highly representative for the whole population. The NFBC program comprises more than 20 different projects coordinated by the Center of Lifecourse Disease studies in Northern Finland (COLD) at Oulu University. The prospective data collected from the NFBCs form a unique resource, allowing the study of disease emergence, and of the importance of genetic, biological, social and behavioral risk factors. The genome-wide association (GWA) study sponsored through the STAMPEED program of NHLBI employed genomic DNA samples previously collected by the NFBC1966 study and stored in the DNA repository of the National Institute for Health and Welfare, Finland. This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to metabolic and cardiovascular diseases (CVD). In addition to de-identified genome wide genotypic data, a selected list of phenotypic data related to CVD including weight, height, BMI, HDL, LDL, total cholesterol, triglyceride, glucose, insulin and fasting status, are also available in dbGaP. A summary of the GWAS for the NFBC1966 cardiovascular risk traits can be found in Sabatti et al., Nature Genetics 41: 35-46, 2009, PMID: 19060910. The version 2 release of this study contains sequence data from seventeen loci associated with levels of triglyceride, HDL-C, LDL-C, total cholesterol, fasting plasma glucose, and fasting plasma insulin (Kathiresan et al. 2008, Willer et al. 2008, Sabatti et al. 2009, Dupuis et al. 2010, Teslovich et al. 2010). At each locus, protein-coding regions and 5' and 3' untranslated regions of genes nearest to single nucleotide polymorphisms showing genome-wide significant association with metabolic syndrome-related traits, were sequenced. Targeted Illumina sequencing of 78 genes (~270kb) using 150bp probes was performed on 4943 subjects of the Northern Finland Birth Cohort 1966 (NFBC1966). Whole exome sequencing on the Illumina platform was carried out on 586 of those participants. The sequencing study is part of a larger project that is funded by the National Human Genome Research Institute's Allelic Spectrum in Common Disease Initiative, and comprises sequence data from more than 7000 individuals in two Finnish cohorts: NFBC1966 and the Finland-United States Investigation of NIDDM Genetics (FUSION) study.

  Study phs000276

• Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer

  This dataset contains all available targeted exon sequencing bam files from our study, "Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which serial sample is referenced (1st, 2nd, 3rd, etc.), and whether the sample represents cell-free DNA ("cfdna") or paired white-blood cell control ("WBC"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006122

• Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

  Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

  Study EGAS00001006490

• TruSight Oncology 500 ctDNA targeted sequencing data from endometrial cancer patients

  This dataset contains targeted sequencing data generated using the TruSight Oncology 500 ctDNA v2 assay from plasma-derived cell-free DNA of dMMR endometrial cancer patients, at baseline and C3D1 of immunotherapy. Sequencing was performed on Illumina NovaSeq600. Dataset includes aligned sequencing files in BAM format generated using the DRAGEN TruSight Oncology 500 ctDNA v2.6.0 analysis pipeline.

  Dataset EGAD50000002262

• lymphoma plasma cfRNA

  Dataset contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma (DLBCL) and 13 primary mediastinal large B-cell lymphoma (PMBCL) patients, and 22 cancer-free controls. Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Dataset EGAD00001010259