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• Somatic mutation and clonal evolution normal breast tissue TGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005787

• Molecular profiling of tissue autopsies and ctDNA

  The dataset contains high-throughput sequencing data derived from a cancer autopsy series of 10 patients. As part of this study, whole-exome sequencing and RNA-seq were performed for spatially distinct tissue biopsies from the patients. In addition, plasma samples from the patients were sequenced using a custom panelt to profile ctDNA. There are 106 files containing whole-exome sequencing data, 107 files containing RNA-seq data, and 9 files containing plasma sequencing data.

  Dataset EGAD00001007040

• Molecular characterization of NASH-HCC

  We collected 80 NASH-HCCs formalin fixed paraffin-embedded (FFPE) samples from 5 different institutions. NASH was diagnosed in FFPE samples by at least two expert pathologists following a described histological algorithm (Bedossa et al., Hepatology, 2012). All NASH patients included in the study were HBV- and HCV-negative. Patients reporting alcohol consumption ≥ 20 g/day for women and 30 g/day for men, as well as patients with a known liver disease superimposed to NASH were excluded. Tumour and paired non-tumour gDNA of NASH-HCC FFPE samples was submitted to Whole Exome Sequencing (WES). Exome capture and sequencing library preparation were performed using the SureSelect Human All Exon V5, no UTR hybridization capture kit from Agilent (Target Size 50 Mb). Libraries were sequenced on an Illumina HiSeq 4000 instrument with 100-bp paired-end reads.

  Dataset EGAD00001007524

• Development, maturation and maintenance of human prostate inferred from somatic mutations

  Stem cells within prostate epithelium frequently undergo malignant transformation, but there is limited information on their clonal dynamics and mutation burden in healthy human prostates. We sequenced whole genomes from 409 microdissections of prostate epithelium across 8 donors, using phylogenetic reconstruction with spatial mapping in a 59-year-old man’s prostate to provide high-resolution reconstruction of tissue dynamics across the lifespan. Somatic mutation burden increases linearly with age, at ~16 mutations/year/clone, and is higher in peripheral than peri-urethral regions. The 24-30 independent glandular subunits are established as rudimentary ductal structures during fetal development by 5-10 embryonic cells each. Puberty induces formation of further side branches and terminal acini by local stem cells disseminated through the rudimentary ducts during development. During adult tissue maintenance, clonal expansions are small, with limited geographic scope and minimal migration. Driver mutations are rare in normal ageing prostate epithelium, but the one canonical driver we did observe generated a sizable intraepithelial clonal expansion. By resolving unbiased, continuously occurring lineage-marking mutations, we define stem cell dynamics through embryogenesis, puberty and ageing, with relevance for prostate cancer.

  Dataset EGAD00001006591

• Single-cell transcriptome of T-ALL P1

  In this study, we profiled single-cell transcriptome (10X genomics) of Patient-derived xenografts (PDX) T-ALL replase samples from P1 patient. Primary human T-ALL cells were recovered from cryopreserved bone marrow aspirates of patients enrolled in the ALL-BFM 2009 study. Patient-derived xenografts (PDX) were generated as previously described by intrafemoral injection of 1 Million viable primary ALL cells in NSG mice110 PDX-derived (P1)28 cells were frozen until processing. For scRNA-seq library preparation, cryopreserved cells were thawed rapidly at 37 ℃ and resuspended in 10 ml warm Roswell Park Memorial Institute (RPMI) medium with 100 μg/ml Dnase I. Cells were centrifuged for 5 mins at 300 g, and resuspended in ice-cold phosphate buffered saline (PBS) with 2% foetal bovine serum (FBS) and 5mM EDTA. Cells were stained on ice with anti-murine-CD45-PE (mCD45)(clone 30-F11; BioLegend; 1:20) in the dark for 30 mins. 1:100 DAPI was added and incubated in the dark for 5 mins before sorting. Triple negative cells (DAPI-mCD45-GFP-) were sorted (Fig. S27) using a BD FACSAria™ Fusion Cell Sorter into ice cold 0.03% bovine serum albumin (BSA) in PBS. All isolated cells were immediately used for scRNA-seq libraries, which were generated as per the standard 10x Genomics Chromium 3′ (v.3.1 Chemistry) protocol. Completed libraries were sequenced on a NextSeq5000 sequencer (HIGH-mode, 75 bp paired-end).

  Dataset EGAD00001008325

• Using genetics to identify cell types and mechanisms underlying susceptibility to primary sclerosing cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001011815

• Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) tumor patient

  Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015291

• Genome and transcriptome sequence data from a diffuse aarge B-cell lymphoma (relapse) tumor patient

  Genome and transcriptome sequence data from a diffuse large B-cell lymphoma (relapse) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015308

• Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm tumor patient

  Genome and transcriptome sequence data from a relapsed blastic plasmacytoid dendritic cell neoplasm patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015312

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - TGS

  Targeted gene sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015468