999 results for "1993+article+mouse+line+professor"

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• A comprehensive DNA methylation landscape of human and mouse cell lines derived from hematological malignancies

  The dataset from Infinium Human MethylationEPIC v1.0 (IDAT files) includes 91 primary samples from patients with B-cell acute lymphoblastic leukemia (B-ALL) (n=34) and T-cell acute lymphoblastic leukemia (T-ALL) (n=57). This dataset was used in the article "A Comprehensive DNA Methylation Landscape of Human and Mouse Cell Lines Derived from Hematological Malignancies" to validate differentially methylated CpG sites, which were utilized to classify hematologic malignancies.

  Dataset EGAD50000000888

• Transcriptomic profiling of granulosa cells from IVF patients at different ages

  Two major factors contributing to reduced fertility is use of exogenous hormones and old age. Here, we sequenced RNA from granulosa cell samples from human patients undergoing in vitro fertilization to test how hormonally stimulated cells' transcriptional profiles change with age. All patients were normal responders referred for male infertility and were grouped into two age groups. The gene expression differences in aging were compared to mouse data (previous experiments, see ArrayExpress E-MTAB-13479) and the results are published in the article "Granulosa cell transcription is similarly impacted by superovulation and aging and predicts early embryonic trajectories". Corresponding count tables are available in ArrayExpress (E-MTAB-13496).

  Study EGAS50000000824

• Exome_sequencing_of_short_SGA_children_with_IGF_I_and_insulin_resistance

  Exome sequencing of short SGA children with IGF-I and insulin resistance. Collaboration with Professor David Dunger, University of Cambridge. Funded by NIHR.

  Study EGAS00001001086

• Professor

  Dac EGAC00001002780

• Associate Professor

  Dac EGAC00001001255

• Associate Professor

  Dac EGAC00001001279

• Professor

  Dac EGAC00001002386

• HCI-PDX Trial Center for Breast Cancer Therapy

  The HCI-PDX Trial Center for Breast Cancer Therapy study is a collection of patient-tumor samples that are serially established as patient-derived tumor xenografts (human tumor in mouse) and matching organoids. For this study, we describe valuable methods and resources to generate organoids and use them as cost-effective models for precision drug screens. This study leveraged whole-exome sequencing, RNAseq, and SNP-array data to illustrate how the heterogeneity of tumors is preserved in xenograft and organoid models. Sequencing files are provided for whole-exome and RNAseq data. Processed copy number variant calls from the SNP arrays are also available. A full description of the study can be found in the article entitled, "A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology," written by Guillen et al., 2022 in Nature Cancer (PMID: 35221336).

  Study phs002479

• DAC Endoresist

  Data access committee for the Endoresist project of panel sequencing: Professor Johan Hartman

  Dac EGAC50000000174

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models: validation cohort

  While cell-free DNA (cfDNA) in liquid biopsies is widely being used and investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve therapy response monitoring and cancer detection due to its dynamic nature. A fundamental open question hampering the initiation of large-scale liquid biopsy collections for tumour exRNA analysis is that it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We set out to develop a host-xenograft deconvolution framework, exRNAxeno, with cDNA mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, that can be applied to exRNA sequencing data from liquid biopsies of human xenograft mouse models, enabling to distinguish (human) tumoural RNA from (murine) host RNA, and as such to specifically analyse tumour-derived exRNA. Subsequently, the preferred exRNAxeno combination pipeline was applied to total exRNA sequencing data from blood platelets and three plasma fractions from a breast cancer patient-derived and neuroblastoma cell line-derived xenograft mouse model. We show that tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA levels and gene content across individual mice is observed. In general, the tumoural gene detectability in plasma is correlated with the RNA expression levels in the tumour tissue or cancer cell line. Our results unravel new aspects of tumour-derived exRNA biology in xenograft mouse models.

  Study EGAS00001006582

• Dataset for scRNA glioblastoma samples

  This dataset contains 5 scRNA samples of human glioblastoma samples, human cortical spheroid derived from hiPSC line 028-4 and 3 samples of mouse xenografts. Sequencing has been performed on Illumina NovaSeq 6000. Sequencing has always been paired.

  Dataset EGAD50000001117

• Exome sequencing of short SGA children with IGF-I and insulin resistance

  Exome sequencing of short SGA children with IGF-I and insulin resistance. Collaboration with Professor David Dunger, University of Cambridge. Funded by NIHR.

  Dataset EGAD00001002208

• Combination_therapies_for_personalized_cancer_medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Study EGAS00001000655

• Pathogenesis and Immunity in Endemic Burkitt Lymphoma

  This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

  Study phs001282

• Sequence data to study genomic CNVs that drive apoptotic resistance and relapses on immune checkpoint inhibitors

  The dataset consists of bulk whole exome sequencing (WES) and whole genome sequencing (WGS) data from baseline and disease-progressed tumors after immune checkpoint inhibitor (ICI) treatment, derived from patients, human cell lines, and mouse models. Whole exome sequencing includes 17 clinical cases and one human cell line model with parental and acquired resistant cell lines (n = 5). Whole genome sequencing encompasses the YUMMER mouse model, including vehicle-treated controls (n = 2) and acquired resistant tumors (n = 3). The sequence reads have been aligned to hg19 and mm9 reference genomes, with mapped files (BAM) made available for analysis.

  Dataset EGAD50000001537

• RNA seq of MPNST tumour samples

  RNA sequencing of 10 MPNST tumour samples as part of a larger study of MPNST. Article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Study EGAS00001004528

• COVID_19_UK_CIC_Spatial

  Understanding the immune response to SARS-CoV-2 is critical to our ability to control the coronavirus pandemic. Spatial transcriptomics will be performed on COVID-19 post-mortem tissues in collaboration with the UK - Coronavirus Immunology Consortium (UK-CIC). UK-CIC encompasses a concerted effort by the UK's world-leading immunology community to deliver a co-ordinated and agile national research programme to increase our understanding of how the immune system interacts with SARS-CoV-2. UK-CIC is led by Professor Paul Moss (University of Birmingham) and brings together 20 UK immunology centres of excellence, with support from the British Society for Immunology.

  Study EGAS00001005817

• Combination therapies for personalized cancer medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Dataset EGAD00001000869

• Dataset belonging to the article "Genotyping from targeted NGS data based on a small set of SNPs correctly matches patient samples"

  This dataset consists of raw sequencing data from targeted next generation sequencing of samples from patients with chronic lymphocytic leukaemia. These samples were used to validate an approach for detection of sample mislabelling and swapping in clinical cohorts using single nucleotide polymorphisms (SNPs), as described in the associated article. The data are divided into two parts - data from the initial validation experiment (discovery cohort) and data from an additional independent cohort.

  Dataset EGAD50000000757

• RODAM

  The RODAM study assesses the health and wellbeing of Ghanaian residents in Ghana and Europe and follows them up over time. With this unique approach the RODAM study attempts to unravel the causes of cardiovascular disease and its risk factors among African migrants in Europe and non-migrants sub-Saharan Africa. Data are available upon reasonable request. These requests can be made to de RODAM-Pros cohort coordinator (rodamcoordinator@amsterdamumc.nl) or principal investigator, Professor Charles Agyemang (c.o.agyemang@amsterdamumc.nl).

  Dac EGAC50000000474

• Whole Exome Sequencing of cohorts of Mutant Braf mouse model melanoma DNA and germline DNA.

  Whole Exome Sequencing of cohorts of Mutant Braf mouse model melanoma DNA and germline DNA. The cohorts are (1) Mutant Braf mouse model melanomas, (2) Mutant Braf mouse model melanomas from UVR exposed mice and (3) Mutant Braf mouse model melanomas from UVR exposed, sunscreen protected mice.

  Study EGAS00001000729

• DCLRE1B/Apollo germline mutations associated with renal cell carcinoma

  Highlights of Bories et al. article submitted to BBA - Molecular Basis of Disease: We identified 2 germline mutations in the DCLRE1B gene encoding the Apollo protein by Whole Exome Sequencing (WES) in two families with inherited clear-cell Renal Cell Carcinoma. Our study suggests a putative link between DNA repair, telomere protection and renal oncogenesis.

  Study EGAS50000000216

• DAC "Genotyping based on SNPs covered by targeted NGS"

  DAC for the dataset from the article "Genotyping from targeted NGS data based on a small set of SNPs correctly matches patient samples"

  Dac EGAC50000000358

• Plasma DNA end analysis (mouse)

  Plasma DNA end analysis (mouse)

  Study EGAS00001006700

• Jagged ends of plasma DNA (mouse)

  Jagged ends of plasma DNA (mouse)

  Study EGAS00001005563