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• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003520

• Single-Cell DNA Methylation Profiling with sciMETv2

  In this study we developed a high-throughput single-cell DNA methylation analysis technology, sciMETv2. This technique is rapid, cost-effective, and robust, enabling large-scale single-cell methylome dataset generation. We demonstrate this technology on human middle frontal gyrus, where we identified major cell types. We additionally performed target enrichment using sciMET-cap to enable a reduction in sequencing costs per cell while achieving comparable cell type identification.

  Study phs003091

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002278

• Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

  IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

  Study phs002686

• Whole Genome Sequencing of Liver Cancers

  Genomic alterations driving tumorigenesis result from the interaction of environmental exposures and endogeneous cellular processes. With a diversity of risk factors including viral infection, carcinogenic exposures and metabolic diseases, liver cancer is an ideal model to study these interactions. Whole genome sequencing of liver tumors identified 10 mutational signatures showing distinct relationships with environmental exposures, replication and transcription. Transcription-coupled damage was specifically associated with the liver-specific signature 16 and alcohol intake. Flood of indels were identified in very highly expressed hepato-specific genes, likely resulting from replication-transcription collisions. Reconstruction of sub-clonal architecture revealed mutational signature evolution during tumor development exemplified by the vanishing of aflatoxin-B1 signature in African migrants. These findings shed new light on the natural history of liver cancers.

  Dataset EGAD00001003281

• Comprehensive Genomic Profiling of a National Cohort of Pediatric Papillary Thyroid Carcinoma in Hungary

  Pediatric papillary thyroid carcinoma (PTC) is a rare childhood malignancy with increasing incidence and distinct clinicopathological features, including high rate of locoregional metastases and different molecular background compared to adult cases. Traditional treatments (surgery, radioactive iodine) are effective but pose long-term risks, prompting the exploration of targeted therapies. We performed comprehensive genomic profiling on 21 pediatric PTC patients applying Illumina TruSight Oncology 500 platform and detected mutations, gene fusions, copy number variations and revealed tumor mutational burden.

  Dataset EGAD50000002659

• Functional single-cell characterization of immune aplastic anemia shows convergence of NK and NK-like CD8+ T cells with disease-associated TCR signature

  Immune aplastic anemia (AA) is a life-threatening bone marrow (BM) failure disorder driven by an autoimmune T cell attack against the hematopoietic stem and progenitor cells (HSPCs). However, the autoantigen targets and the role of other immune cells are unknown. Here, by analyzing an international cohort of 156 AA patients with scRNA+TCRαβ-seq, TCRβ-seq, flow cytometry, and plasma cytokine profiling with comparisons to healthy controls and patients with other hematological disorders, we identify NK cells and CD8+ TEMRA cells expressing NK receptors with AA-associated TCRβ-seq motifs as the most dysregulated immune cell populations in AA BM. Functional co-culture experiments with scRNA-TCRαβ-seq readout utilizing primary HSPCs and immune cells provide evidence that NK cellscannot kill HSPCs alone, but sensitize them to CD8+ T cell-mediated killing. Furthermore, HSPCs induce strong activation of T cell clones with CD8+ TEMRA NK-like phenotype and AA-associated TCR motifs. Our results reveal the convergent evolution of innate and adaptive immune cells in AA, where NK cells support CD8+ T cell-mediated autoimmunity.

  Study EGAS00001007604

• Functional single-cell characterization of immune aplastic anemia shows convergence of NK and NK-like CD8+ T cells with disease-associated TCR signature

  Immune aplastic anemia (AA) is a life-threatening bone marrow (BM) failure disorder driven by an autoimmune T cell attack against the hematopoietic stem and progenitor cells (HSPCs). However, the autoantigen targets and the role of other immune cells are unknown. Here, by analyzing an international cohort of 156 AA patients with scRNA+TCRαβ-seq, TCRβ-seq, flow cytometry, and plasma cytokine profiling with comparisons to healthy controls and patients with other hematological disorders, we identify NK cells and CD8+ TEMRA cells expressing NK receptors with AA-associated TCRβ-seq motifs as the most dysregulated immune cell populations in AA BM. Functional co-culture experiments with scRNA-TCRαβ-seq readout utilizing primary HSPCs and immune cells provide evidence that NK cellscannot kill HSPCs alone, but sensitize them to CD8+ T cell-mediated killing. Furthermore, HSPCs induce strong activation of T cell clones with CD8+ TEMRA NK-like phenotype and AA-associated TCR motifs. Our results reveal the convergent evolution of innate and adaptive immune cells in AA, where NK cells support CD8+ T cell-mediated autoimmunity.

  Study EGAS00001007602

• Tumor Profiler Project - OV scRNA data additional samples

  The dataset contains 10x Chromium single-cell transcriptomics data from 6 samples from 4 different patients with ovarian cancer. 3 samples were collected from the tumor, 3 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. This dataset contains additional samples from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001293

• microRNA-seq of human serum from a longitudinal study of 66 women with no history of cancer

  This dataset includes microRNA sequencing data from 198 human serum samples, representing a subset of 66 women with no history of cancer who participated in the UKCTOCS study and with serum samples collected at three timepoints over a period of up to 5 years. Small RNA libraries prepared from the serum samples were sequenced with 50-bp single end reads on an Illumina HiSeq 2000 instrument. Data is provided as FASTQ files.

  Dataset EGAD00001004348