15340 results for "Buy fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins All coins were delivered very promptly..EDvG"

in 28.08 milliseconds.

• DAC for HTS MRD study

  Dac EGAC00001000359

• DAC for Korean BC data

  Dac EGAC00001000740

• DAC for A Karadimitris Lab

  Dac EGAC00001001003

• Data Access Commitee for EGAS00001003258

  Dac EGAC00001001038

• Data access comittee for Institut Curie

  Dac EGAC00001001042

• DAC for the study EGAS00001003572

  Dac EGAC00001001174

• DAC for hepatitis B analysis

  Dac EGAC00001001228

• DAC for Wigler Group

  Dac EGAC00001001256

• DAC for panc_met data set

  Dac EGAC00001001480

• Center for Medical Genetics Ghent

  Dac EGAC00001001507

• DAC for mUC sequencing data

  Dac EGAC00001001710

• Data Access Commitee for ECA

  Dac EGAC00001001856

• DAC for Hypermutated Gliosarcoma project

  Dac EGAC00001001867

• Data Access Committee for EGAS00001005426

  Dac EGAC00001002194

• Data Access Committee for cfMeDIP

  Dac EGAC00001002250

• Center for Medical Genetics Ghent

  Dac EGAC00001002384

• DAC for intraphepatic cholangiocarcinoma

  Dac EGAC00001002521

• DAC for cfMethyl-Seq data

  Dac EGAC00001002534

• Data access committee for FL

  Dac EGAC00001002552

• Center for Medical Genetics Ghent

  Dac EGAC00001002909

• Center for Medical Genetics Ghent

  Dac EGAC00001003264

• EGAD00010000694

  HCC array for cnv

  Dataset EGAD00010000694

• Data Access Committee for EGAS00001007298

  Dac EGAC00001003422

• Data Access Committee for EGAS00001007299

  Dac EGAC00001003268

• DAC for noninvasive lung cancer subtyping

  Dac EGAC00001003474

• DAC for Molecular Oncology lab

  Dac EGAC50000000268

• DAC for EGAS00001007531

  Dac EGAC00001003437

• UCL Centre for Longitudinal Studies

  Dac EGAC00001003495

• DAC for v9 panel assay

  Dac EGAC00001003580

• Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients.

  Over the last decade, molecular stratification and associated therapies have greatly improved the treatment options and prognosis of patients diagnosed with breast cancer. However, metastatic disease remains incurable. Breast cancer cells mainly spread to the lung, liver, bone and brain and circulating tumor cells (CTCs) that migrate in the lymphatics or blood have been implicated as the cellular source of metastasis. Detailed molecular and functional characterization of patient CTCs remains poor due to their low number in patient’s bloodstream. In addition, CTCs are difficult to culture and expand ex vivo. Here we have established a novel method for culturing and unlimitedly expanding breast cancer patient-derived CTCs in CTC-derived organoids (CDOs). Our platform can serve as a foundation for serial longitudinal isolation and expansion of breast cancer cells from peripheral blood. This may enable the identification and functional validation of therapy resistance mechanisms during disease progression, which can be used for new approaches in precision medicine.

  Study EGAS00001007582

• Systematic kinase inhibitor profiling identifies CDK9 as a synthetic lethal target in NUT midline carcinoma

  Kinase inhibitors represent the backbone of targeted cancer therapy, yet only a limited number of oncogenic drivers are directly druggable. By interrogating the activity of 1,505 kinase inhibitors we found that BRD4-NUT-rearranged NUT midline carcinoma (NMC) cells are specifically killed by CDK9 inhibition (CDK9i) and exhibit a unique dependency on CDK9 and Cyclin-T1 expression. We show that CDK9i leads to robust induction of apoptosis and of markers of DNA damage response in NMC cells. While both CDK9i and bromodomain inhibition over time result in reduced Myc protein expression, only bromodomain inhibition induces cell differentiation and a p21-induced cell cycle arrest in these cells. Finally, RNA-Seq and ChIP-based analyses reveal a BRD4-NUT specific CDK9i-induced perturbation of transcriptional elongation. Thus, our data provide a mechanistic basis for the genotype-dependent vulnerability of NUT midline carcinoma cells to CDK9i that may be of relevance for the development of targeted therapies for NMC patients.

  Study EGAS00001002588

• WGS of MAPKi acquired resistant samples from patients and PDX models

  Blocking cancer genomic instability, which generates diverse variants that enable rapid adaptations, may prevent tumor escape from therapies. We show that, after MAPK inhibitor (MAPKi) therapy in patients and patient-derived xenografts, acquired-resistant genomes of metastatic cutaneous melanoma accumulate amplicons of resistance-driver, non-homologous end-joining (NHEJ), and homologous recombination repair (HRR) genes within complex genomic rearrangements (CGRs) and extrachromosomal circular DNAs (ecDNAs). Also, chromothriptic genomic regions enrich for mutations and may engender ecDNAs and CGRs. Overall, somatic mutations within ecDNA- and CGR-amplicons enrich for HRR signatures, and, in acquired resistance, ecDNA (versus CGR) mutations enrich for APOBEC3 signatures. Breakpoint-sequence analysis suggests NHEJ as critical to double-stranded DNA break repair underlying CGR and ecDNA formation. In vivo, NHEJ-targeting by a DNA-PKCS inhibitor prevented acquired MAPKi-resistance by reducing the size of ecDNAs and CGRs early on combination treatment. Thus, targeting the cause(s), as opposed to the consequences, of genomic instability prevents acquired resistance.

  Study EGAS00001006874

• RNAseq of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007300

• WES of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007301

• DAC for the study EGAS00001001738

  Dac EGAC00001000450

• DAC for sputum fungal microbiome data

  Dac EGAC00001003006

• DAC for Oncogenomics QIMR Berghofer

  Dac EGAC00001001088

• Data Access Committee for WES RCC

  Dac EGAC00001003161

• DAC for study Vel Exome Sequencing

  Dac EGAC00001000012

• DAC for Sardinia FACS pilot project

  Dac EGAC00001000132

• DAC for study POT1 splice

  Dac EGAC00001000184

• DAC for SNP phenotyping Kiel

  Dac EGAC00001000316

• DAC for Mesothelioma Genomics Study

  Dac EGAC00001000615

• DAC for Human Stem Sell Sequencing

  Dac EGAC00001000642

• DAC for studying early onset IBD

  Dac EGAC00001000840

• DAC for Familial Breast Cancer study EGAS00001003305

  Dac EGAC00001001087

• DAC for genentech GBC study

  Dac EGAC00001001155

• Department for BioMedical Research, University of Bern

  Dac EGAC00001001457

• DAC for Gastric Adenocarcinoma Heterogeneity study

  Dac EGAC00001001649

• Data Access Committee for IMBA

  Dac EGAC00001001690

• Data Access Committee for data from EGAS00001005174

  Dac EGAC00001002059

• Data Access Committee for data from EGAS00001005395

  Dac EGAC00001002183

• Data Access Committee for PPIL4 Paper

  Dac EGAC00001002301

• Data Access Committee for Massim study

  Dac EGAC00001002522

• Data Access Committee for Institut Curie

  Dac EGAC00001002711

• Data Access Committee for Pediatric Medulloblastoma

  Dac EGAC00001002896

• Institute for Surgical Pathology

  Dac EGAC00001002949

• Data Access Commitee for MNP2

  Dac EGAC00001003033

• DAC for Karolinska Institute REM Lab

  Dac EGAC00001003142

• EGAD00010000608

  SNP6 data for seminoma samples

  Dataset EGAD00010000608

• DAC for Kotsch/Lukassen/Conrad labs

  Dac EGAC00001003464

• Data Access Committee for data from EGAS00001002864

  Dac EGAC00001003487

• Data Access Committee for data from EGAS00001007832

  Dac EGAC00001003500

• Data Access Committee for data from EGAS00001007819

  Dac EGAC00001003501

• Data Access Committee for data from EGAS00001007904

  Dac EGAC00001003512

• Data Access Committee for data from EGAS00001008107

  Dac EGAC00001003568

• UCL Centre for Longitudinal Studies

  Dac EGAC00001001041

• BAP1 Project

  For our BAP1 manuscript

  Dac EGAC50000000006

• A Microwell Platform for High-Throughput Longitudinal Phenotyping and Selective Retrieval of Organoids

  In traditional bulk culture, organoids tend to overlap, hindering the analysis of individual organoid characteristics in a high-throughput manner. Additionally, variations in the local spatial properties of the bulk matrix make it challenging to distinguish whether phenotypic differences between organoids stem from inherent cellular disparities or disparities in the microenvironment. To address these challenges, we have developed a microwell-based technique that facilitates the quantification of image-based parameters for organoids grown from single cells. Furthermore, these organoids can be easily retrieved from their respective microwells for molecular profiling. By employing a deep-learning image processing pipeline, we conducted a comprehensive assessment of various phenotypic traits in two CRISPR-engineered human gastric organoid models. This analysis encompassed growth rates, cellular movement, and apical-basal polarity. Through our investigation, we successfully identified genomic alterations associated with increased growth rate, as well as changes in accessibility and expression patterns correlated with apical-basal polarity. This novel methodology offers a valuable tool for studying organoid behavior at a single-cell level, enabling researchers to gain deeper insights into organoid biology and associated genetic modifications.

  Study phs003315

• A Pilot Study Using Next Generation Sequencing in Advanced Cancers: Feasibility and Challenges

  In this study, we used NGS to identify somatic events in advanced stage cancer patients to demonstrate the feasibility for using this approach to improve patient treatment.

  Study phs000657

• Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype"

  Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype" with Name: Menghong Yin Email address: menghong.yin@dkfz-heidelberg.de Associated affiliation: Translational Skin Cancer Research Lab (DKFZ)

  Dac EGAC50000000168

• SALTO: chromosomal copy number alterations to predict response to bevacizumab

  Study of the correlation between vessel formation and or CMS subtypes in relation to a predictive copy number marker for bevacizumab. Shallow Whole Genome Sequencing of 92 mCRC samples.

  Study EGAS50000000711

• CRITICS trial Whole Exome Sequencing (WES)

  Chemotherapy versus chemoradiotherapy after surgery and preoperative chemotherapy for resectable gastric cancer (CRITICS): an international, open-label, randomised phase 3 trial. Molecular characterisation of N=36 resectable gastric adenocarcinomas from CRITICS trial, describing mutations obtained by matched (Tumor-Normal) whole exome sequencing (WES). Samples are annotated for TCGA’s molecular classification (MSI, GS and CIN).

  Dataset EGAD50000001145

• DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy"

  DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy" with Florian Janke (f.janke@dkfz-heidelberg.de) and Holger Sültmann (h.sueltmann@dkfz-heidelberg.de)

  Dac EGAC50000000308

• Dataset for "HPV integration induces gene fusions" (RNA)

  RNA-seq data for "HPV integration induces gene fusions" We performed RNA-seq analysis of five HPV+ head and neck cancer samples using Illumina short reads. Sequenced are submitted in bam format. We also sequenced one samples with pacBio long reads, and the reads are submitted in fastq format.

  Dataset EGAD50000001303

• The dataset for Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  The dataset for “Detection of brain cancer using genome-wide cell-free DNA fragmentomes” includes 310 bam files from whole genome next-generation sequencing on the Illumina Novaseq 6000. The dataset analyzed include plasma cfDNA samples from patients with cancer, patients with neurological conditions, and healthy individuals.

  Dataset EGAD50000001445

• singel cell RNAseq dataset for the study "Longitudinal Multi-Omics Study Reveals Molecular Drivers and Tumor Microenvironment in Extramedullary Multiple Myeloma"

  This dataset contains 16 fastq files of raw single-cell RNAsequencing data from 6 patients with Extramedullary multiple myeloma used for the study "Longitudinal Multi-Omics Study Reveals Molecular Drivers and Tumor Microenvironment in Extramedullary Multiple Myeloma"

  Dataset EGAD50000000053

• Whole Genome Sequencing Analysis of Adult T-cell Leukemia/Lymphoma

  In this study, we have performed the whole genome sequencing (WGS) for primary tumors from adult T-cell leukemia/lymphoma (ATL) to identify recurrent genetic mutations and structural variants.

  Study JGAS000320

• Total NF1 sequence in the patients with neurofaibromatosis type1

  We analyzed whole NF1 gene region at DNA (including whole exon and intron sequences) and RNA (full length cDNA of leukocyte) level for 20 patients with neurofibromatosis type 1.

  Study JGAS000288

• OCCAMS_Oesophageal_Cancer_Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Study EGAS00001001382

• Targeted_NanoSeq_Buccal

  Targeted NanoSeq in buccal epithelium obtained longitudinally from a number of donors. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).

  Study EGAS00001005925

• A95732B

  Whole genome sequencing for single cells for library A95732B 655 samples; filetype=bam

  Dataset EGAD00001008231

• A95633B

  Whole genome sequencing for single cells for library A95633B 2259 cells; filetype=bam

  Dataset EGAD00001007104

• RNAseq of jejunum (small intestine) harvested from CDAHFD mice treated for 8 weeks with either the MGAT2 inhibitor compound BMS-963272 or vehicle

  This experiment consists of RNAseq of jejunum (small intestine) harvested from CDAHFD mice treated for 8 weeks with either the MGAT2 inhibitor compound BMS-963272 (N = 14) or with vehicle (N = 14).

  Dataset EGAD00001009390

• BLUEPRINT release August 2016, ChIP-Seq for macrophage - T=6days LPS, on genome GRCh38

  ChIP-Seq data for 2 macrophage - T=6days LPS sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002498

• BLUEPRINT September 2016, ATAC-seq for venous blood, on Genome GRCh38

  ATAC-seq data for 136 sample(s) from venous blood, on Genome GRCh38. 141 run(s), 139 experiment(s), 139 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002709

• Whole-exome and whole-genome sequencing data

  Multi-omic data for lung neuroendocrine neoplasms, including the first multi-omic sequencing data for the understudied lung atypical carcinoids. The data includes Whole-exomes, whole-genomes, RNA-seq, and EPIC 850K methylation array data.

  Dataset EGAD00001005087

• Single-cell RNA-seq and spatial transcriptomics data of patients with sarcoidosis

  Single-cell RNA-seq and spatial transcriptomics data for 12 patients with sarcoidosis. From each patient, we analyzed skin biopsies of both lesional and non-lesional skin and we performed spatial transcriptomics for lesional skin samples. The data are provided as aligned BAM files.

  Dataset EGAD00001010020

• Common clonal origin of chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia in a patient with a germline CHEK2 variant

  Whole exome sequencing data obtained from sorted leukemic clones and a buccal swab as germline reference. The dataset contains raw sequencing data (paired-end reads) for 3 samples (2 leukemic, 1 buccal swab), for a total of 6 fastq files.

  Dataset EGAD00001007644

• BLUEPRINT release August 2016, ChIP-Seq for macrophage - T=6days untreated, on genome GRCh38

  ChIP-Seq data for 2 macrophage - T=6days untreated sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002458

• BLUEPRINT release August 2016, DNase-Hypersensitivity for inflammatory macrophage, on genome GRCh38

  DNase-Hypersensitivity data for 3 inflammatory macrophage sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002374

• BLUEPRINT release August 2016, DNase-Hypersensitivity for macrophage, on genome GRCh38

  DNase-Hypersensitivity data for 4 macrophage sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002382

• EGA dataset for High Grade Serous Ovarian Carcinomas Originate in the Fallopian Tube

  The dataset for High Grade Serous Ovarian Carcinomas Originate in the Fallopian Tube includes 46 bam files from next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include multiple lesions from nine patients, five with high grade serous ovarian carcinoma and four who are BRCA-carriers.

  Dataset EGAD00001003792

• BLUEPRINT release August 2016, DNase-Hypersensitivity for macrophage - T=6days B-glucan, on genome GRCh38

  DNase-Hypersensitivity data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002425

• BLUEPRINT release August 2016, RNA-Seq for monocyte - T=0days, on genome GRCh38

  RNA-Seq data for 4 monocyte - T=0days sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002360

• BLUEPRINT release August 2015, DNase-Hypersensitivity for inflammatory macrophage, on genome GRCh38

  DNase-Hypersensitivity data for 3 inflammatory macrophage sample(s). 3 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001573

• BLUEPRINT release August 2015, RNA-Seq for plasma cell, on genome GRCh38

  RNA-Seq data for 4 plasma cell sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001523

• BLUEPRINT release August 2015, RNA-Seq for monocyte - None, on genome GRCh38

  RNA-Seq data for 4 monocyte - None sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001532

• SPECTA: NGS Screening Program for Efficient Clinical Trial Access

  SPECTA comprises a network of participating European clinical sites and NGS screening platforms that can screen individual patients for multiple molecular targets and potentially allow the design of trials that will match the specific biology of the diseases affecting specific patients with cancer.

  Dataset EGAD00001000894

• Dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA

  The dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA includes 602 bam files from next-generation sequencing on the Illumina HiSeq2500 or MiSeq. The samples analyzed include cancer cell lines as well as plasma and tissue specimens from healthy individuals and patients with cancer.

  Dataset EGAD00001003601