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