11169 results for "fc points to coins calculator Visit Buyfc26coins.com Bardzo pod wrażeniem jakości usług..UK7B"

in 20.05 milliseconds.

• untargeted whole genome sequencing - Evaluation and correction of GC biases in cell-free DNA at the fragment level

  These are aligned paired-end reads from Illumina NovaSeq 6000 whole-genome sequencing of 4 cfDNA samples extracted from blood plasma (plasma-Seq). Three samples from patients with breast cancer, prostate cancer, or colorectal cancer and one sample from a healthy individual were aligned to GRCh38 (GCA_000001405.15_GRCh38_no_alt_plus_hs38d1_analysis_set). The observed GC bias is different in each of these cfDNA samples which leads to different average GC content per sample. This bias is corrected using the GCparagon commandline tool.

  Dataset EGAD00001010100

• Ither NB in Organoids WXS dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids WXS dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010281

• Ither NB in Organoids RNA-Seq dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids RNA-Seq dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010283

• Bulk RNA sequencing of SARC PDOs and UroCa PDOs.

  This dataset contains raw FASTQ files from bulk RNA sequencing of SarBC-01 organoids at different passages (Passage 6, Pssage 19, Passage 59), UroBC-01 organoids (Passage 70), UroBC-16 organoids (Passage 19) and UroBC-22 organoids (Passage 8). RNA was isolated using the Quick-DNA/RNA Miniprep kit (Zymo Research, Irvine, CA, USA, D7001) and subjected to bulk RNA sequencing. TruSeq Stranded mRNA kit (Illumina, 20020594) was used for the library preparation according to manufacturer’s guidelines. Sequencing was performed on Illumina NovaSeq 6000 using paired-end 100-bp reads.

  Dataset EGAD00001011156

• T-cell receptor targeting FLT3 D835Y mutation study

  We identified a T-cell receptor (TCR) reactive to the recurrent FLT3 D835Y mutation in the tyrosine-kinase domain. To validate the elimination efficacy of leukemia cells, we transplanted human acute myeloid leukemia (AML) cells with FLT3 D835Y mutations into NSG-SGM3 mice and treated either with TCR FLT3 D835Y redirected T cells, or control TCR (TCR 1G4). After treatment, we performed flow sorting of AML blasts (CD3-CD19-) and primary T cells (CD3+CD8+orCD4+CD19-CD33-) and performed whole-exome sequencing.

  Dataset EGAD00001011258

• Lung Cell Atlas: Paediatric RNA (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015722

• Lung Cell Atlas: Paediatric Spatial (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015723

• GBM-Space: Spatial Transcriptomic Profiling of Glioblastoma (10x Genomics - Visium)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours. Note: 2 new samples were added to the dataset on 2026-05-19.

  Dataset EGAD00001015527

• Amplicon-based sequencing of drug resistant lung cancer cell lines (2017-07-05)

  A EGFR mutant NSCLC cell line which is sensitive to AZD9291 inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a AZD9291. Single cell derived colonies were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors hypothesised from currently available literature. This dataset contains all the data available for this study on 2017-07-05.

  Dataset EGAD00001003425

• Finding structural variation from the patient-derived xenografts of pediatric T-cell leukemia at the single-cell level

  In this study, we aimed to identify somatic structural variation of T-cell acute lymphoblastic leukemias (T-ALLs_ from patient-derived xenografts (PDX) at the single-cell level. For this purpose, we performed strand-specific single-cell sequencing of PDX-derived T-ALL relapse samples from two juvenile patients (P1, P33). To validate structural variation detected via scTRIP, we profiled whole exome sequencing (WES) data from P33 (samples taken during initial disease, remission, relapse), and mate-pair sequencing data from P1 (relapse).

  Dataset EGAD00001004499

• Chondromyxoid fibroma

  Chondromxoid fibroma is a benign tumour of bone with unknown underlying pathogenesis. To determine pathognomic genomic event in chondromyxoid fibroma whole genome sequencing will be undertaken to reconstruct rearrangements and find underlying mutations.

  Dataset EGAD00001001063

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient (Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer)

  Genome and transcriptome sequence data from a colorectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study. These data are included in the manuscript entitled, "Response to Angiotensin Blockade with Irbesartan in a Patient with Metastatic Colorectal Cancer".

  Dataset EGAD00001001876

• Whole Genome Sequencing of Human Organoid Lines (2020-02-20)

  The study will use WGS to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there is any clonal differences introduced when culturing these lines in different conditions. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005995

• RNA sequencing data for Molecular Characterization of ETMRs

  The dataset contains two samples from one patient. As a representative FFPE tissue sample, ET174 was histologically iden- tified, targeted and microdissected with a puncher for nucleic acid extraction. RNA was extracted using the automated Maxwell system with the Maxwell 16 LEV RNA FFPE Kit (Promega), according to the manufacturer’s instructions. To evaluate FFPE RNA quality, we used the percentage of RNA fragments >200 nt fragment determination value (DV200). Only RNA samples with DV200 > 70% were included for sequencing on a NextSeq 500 (Illumina). Eight lanes have been sequenced resulting in 16 Fastq files (paired end).

  Dataset EGAD00001006209

• A rare CTSC mutation in Papillon-Lefèvre Syndrome

  Papillon-Lefèvre Syndrome (PLS) is an autosomal recessive monogenic disease caused by loss-of-function mutations in the CTSC gene. In this study we performed whole genome sequencing on two siblings, with the PLS-typical symptoms. After sequencing the CTSC gene was analyzed to confirm the PLS diagnosis genetically.

  Study EGAS00001005040

• Raw microarray gene expression data from NPC samples_Cohort 1

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006273

• Raw microarray gene expression data from NPC samples_Cohort 2

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006272

• Processed microarray gene expression data from NPC samples_Cohort 2

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006274

• Processed microarray gene expression data from NPC samples_Cohort 1

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006275

• The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation

  In this study, we will apply a multi-staged approach to reveal genes harboring rare variants that are associated with aggressive PCa. Whole-exome sequencing (Aim 1a) of 2,774 aggressive cases and 2,776 non-aggressive cases of European ancestry will be conducted followed by rare variant analysis of single sites and gene burden testing to identify novel susceptibility loci/genes for aggressive disease. We will validate the most significantly associated genes (~500) through targeted sequencing in an additional 6,415 aggressive and 5,586 non-aggressive cases and 1,890 controls (Aim 1b). Next, we will investigate the clinical predictive utility of the genes/variants identified in 2,291 cases in the STHM3 trial who are undergoing biopsy based on PSA and genetic risk score stratification (Aim 2). Through this tiered approach we expect to significantly advance knowledge of aggressive PCa etiology and health disparities as well as guide the development of early detection and prognostic strategies for the subset of men who are most susceptible to this fatal form of disease. In this case-case study of aggressive vs non aggressive prostate cancer, aggressive cases are defined as prostate cancer as cause of death, (T4 disease or T3 disease) and Gleason 8+. Non-aggressive cases are men with T1/2 disease and Gleason ACKNOWLEDGMENTS and CONTRIBUTING SITES CAPS, PROCAP, STHM1, STHM2: Swedish Cancer Society (CAN 2016/818), Swedish Research Council (2014/2269).STHM3: Stockholm County Council (Stockholms Läns Landsting).MEC: Funding provided by the National Cancer Institute: Understanding Ethnic Differences in Cancer, 2U01CA164973 and The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation, 5R01CA196931-02.ATBC: The ATBC Study is supported by the Intramural Research Program of the U.S. National Cancer Institute, National Institutes of Health, and by U.S. Public Health Service contract HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services.COSM: The Swedish Research Council/National Research Infrastructure Grant (VR 2014/6397; VR 2015/5997) The Swedish Cancer Foundation (CAN 2013/456; CAN 2016/727)CPSII: The authors express sincere appreciation to all Cancer Prevention Study II participants and to each member of the study and biospecimen management group. The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort.MCCS/APCS/PCFS: The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria and further supported by Australian National Health and Medical Research Council (NHMRC) grants 209057 and 396414. The Aggressive Prostate Cancer Case-Control Study (APCS) was funded by NHMRC grant 623204. The Prostate Cancer Family Study (PCFS) was fully funded by Cancer Council Victoria. Cancer Council Victoria funds the continuing maintenance and updating of the MCCS, APCS and PCFS. Cases and their vital status are ascertained and followed up through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.PLCO: The Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO) was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, US National Institutes of Health, Department of Health and Human Services. EPIC: The coordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition Potsdam- Rehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology - ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A19170 and C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford). (United Kingdom). DFCI: Linda and Arthur Gelb and Rebecca and Nathan Milikowsky. HPFS and PHS: The Health Professionals Follow-up Study was supported by U01 167552 and P01 CA228696 from the National Cancer Institute, and with support from the Prostate Cancer Foundation. The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490 and HL34595.Northwestern: P50CA180995 (Catalona) 08/01/15 – 07/31/20 NIH/NCI SPORE in Prostate Cancer; The Urological Research FoundationPROMPT: MRC UK - Project reference G0500966, Cambridge BRC infrastructure funding, Cambridge Biomedical Research Campus (BRC-1215-20014), CRUK Cambridge Cancer Centre infrastructure funding (they are requesting this statement is written in blue for publications).ICR: This work was supported by the NIH R01 grant 5R01CA196931-02. The samples from the UK were from UKGPCS and PrompT. The UKGPCS study was supported by Cancer Research UK (grant numbers C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. We also acknowledge The Institute of Cancer Research, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK for their ongoing support. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.Funding:CIDR grant X01HG008336

  Study phs001524

• Center for Common Disease Genomics [CCDG] - Cardiovascular ATVB: Atherosclerosis Thrombosis and Vascular Biology

  Italian Atherosclerosis Thrombosis and Vascular Biology study is a prospective, nationwide, case-control study involving 125 coronary care units in Italy. The cases were patients who were hospitalised for a first MI before the age of 45 years and underwent coronary angiography. Acute MI was defined as resting chest pain lasting more than 30 minutes, accompanied by persistent electrocardiographic changes, and confirmed by an increase in total creatine kinase or in the MB fraction to more than twice the upper normal limits. The controls were healthy subjects without a history of thromboembolic disease who were unrelated to the patients, but individually matched with them by age, gender and geographical origin. They were enrolled from among the blood donors or staff of the same participating hospitals. Recruitment of cases and controls took place between 1994 and 2007. This site hosts data from ~60 whole exomes.

  Study phs001592

• HuBMAP: KULMAP - Human Kidney, Urinary Tract, and Lung Mapping Center

  The major goal of the Human Kidney, Urinary Tract, and Lung Mapping Center (KULMAP) is to generate multi-omic and spatially resolved molecular anatomical maps of the human bladder, ureter and kidneys (BUKMAP) and the lung airways and parenchyma (LAPMAP) at a single cell resolution. This entails sequencing of the transcriptomes and epigenomes of dissociated single cells in a massively parallel manner. These profiles will then inform on highly multiplexed RNA in situ imaging for spatial mapping of hundreds of molecular targets in the tissue sections, at a subcellular resolution. These spatial molecular maps will serve as scaffolds for computational registration of cell types and the associated transcriptome/chromatin maps to the tissue space. The combination of sequencing single dissociated cells and multiplexed in situ mapping will allow the construction of detailed spatial maps for these large organs.

  Study phs002249

• SU2C-MARK Lung Cancer Consortium - Checkpoint Blockade Response Project

  Immune checkpoint inhibitors have become a critical part of the armamentarium against advanced Non-Small Cell Lung Cancer (NSCLC). While early studies have identified Tumor Mutation Burden (TMB) and PD-L1 staining as important biomarkers of response, they remain imperfect predictors. Here we describe a multi-institutional effort as part of the SU2C-MARK Lung Cancer Consortium in which Whole Exome Sequencing (WES) - and in select cases, RNA sequencing – was performed on a large collection of NSCLC samples prior to immune checkpoint blockade therapy, along with matched clinical response data following therapy. (Profiling of a small number of on- or post-treatment samples was also performed.) We anticipate this dataset to be of high value for the development of a deep understanding of the molecular determinants of immune checkpoint blockade response as well as the discovery of novel biomarkers.

  Study phs002822

• Notch Signaling and Efficacy PD-1/PD-L1 Blockade in Relapsed Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer that accounts for approximately 15% of all lung cancer, with an annual incidence of more than 34,000 in the United States alone. SCLC is characterized by loss of function of p53 and RB and high tumor mutational burden, which suggests that these tumors could be immunogenic and respond to immune checkpoint blockade (ICB). However, the benefit from ICB in an unselected SCLC population is modest. In this study, we evaluated the genomic features associated with clinical outcomes in relapsed SCLC to gain insight into the underlying mechanisms of ICB response. Exome, RNA and TCR sequencing data from a prospective clinical trial of relapsed SCLC treated with durvalumab and olaparib and RNA-sequencing data for second cohort of relapsed SCLC cohort treated with nivolumab are included.   

  Study phs002176

• A Pilot Study of Neoadjuvant Nivolumab, Ipilimumab and Intralesional Oncolytic Virotherapy for HER2-Negative Breast Cancer

  This study was a single arm phase 1 trial that assessed the regimen safety and feasibility as well as tumor response in patients with localized HER2-negative breast cancer treated with talimogene laherparepvec (T-VEC) in combination with nivolumab and ipilimumab. The primary objective was to evaluate the safety and adverse event profile of this treatment combination. Six patients were enrolled, four having relapses after prior neoadjuvant chemotherapy, and two who were previously untreated. One patient had a pathological complete response, three patients had pathological partial responses, one showed no significant response, and one had disease progression. Biopsies demonstrated increased immune cell infiltration in samples from patients who responded to therapy. In this study, the checkpoint blockade immunotherapy combined with T-VEC provided responses in patients with advanced or relapsed HER2-negative breast cancer at the expense of long-term toxicities.

  Study phs003316