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• Neutrophils infected with Leishmania donovani

  In the context of studying visceral leishmaniasis, neutrophils infected with Leishmania donovani have been compared to uninfected neutrophils. Compared time points are 0, 6 and 24 hours post infection. Neutrophils of three human donors have been used. Overall 6 samples for infected neutrophils at time point 6 hours and 6 samples for infected neutrophils at time point 24 hours exist, including three biological samples and two technical samples. Uninfected neutrophils represent 3 samples at time point 0 hours, 3 samples at time point 6 hours and 3 samples at time point 24 hours. Transcriptome of Leishmania donovani culture has been assessed in two replicates.

  Study EGAS00001004912

• Chracterising_cellur_pathways_underlying_CD3_CD28_activation_of_human_CD4__cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. 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/

  Study EGAS00001002438

• 'KOREAN' never-smoker female adenocarcinoma RNA-seq

  Multi-layered genomic studies such as the TCGA project have greatly advanced our understanding on molecular pathogenesis of lung cancer. For Asian nonsmoker patients, however, majority of studies have been limited to mutational analyses, emphasizing ethnic differences in driver mutations (e.g. more frequent EGFR mutations and ALK fusions). In essence, a comprehensive multi-layered characterization that could lead to molecular etiology and patient stratification scheme to be translated into clinical applications for this patient group is still missing. Here we report molecular profiling of tumor and matched normal tissues from 114 non-small-cell lung adenocarcinoma patients using whole exome sequencing, transcriptome sequencing, and array comparative genomic hybridization (CGH).

  Study EGAS00001003789

• Detection of Cancer Mutations by Urine Liquid Biopsy in Bladder Cancer Patients

  The management of bladder cancer faces multiple challenges concerning the diagnostics and fol-low-up approaches. The standard diagnostic test is invasive cystoscopy. Urine cytology and re-cently proposed urine-based biomarkers still could not replace cystoscopy, thus prompting calls for improvements. Here, we explore urine liquid biopsy to detect cancer mutations for therapeutic and prognostic assessment and subsequently evaluate the utility of urine as a suitable specimen in diagnosing bladder cancer. Our findings show that the analysis of pre-and post-operative urine enables the characterization of specific tumor mutations, which can be used to diagnose and evaluate a patient’s prognosis and therapy response.

  Study EGAS00001005758

• GWAS Results from Danjou et al, Nature Genetics 2015

  We report genome-wide association study results for the levels of A1, A2 and fetal hemoglobins, analyzed for the first time concurrently. Integrating high-density array genotyping and whole-genome sequencing in a large general population cohort from Sardinia, we detected 23 associations at 10 loci. Five signals are due to variants at previously undetected loci: MPHOSPH9, PLTP-PCIF1, ZFPM1 (FOG1), NFIX and CCND3. Among the signals at known loci, ten are new lead variants and four are new independent signals. Half of all variants also showed pleiotropic associations with different hemoglobins, which further corroborated some of the detected associations and identified features of coordinated hemoglobin species production.

  Study EGAS00001003645

• Single-cell transcriptomics identifies pathogenic T-helper 17.1 cells and pro-inflammatory monocytes in ICI-related pneumonitis

  ICI-pneumonitis is a frequent serious adverse event of cancer immunotherapy hinging on a cell-mediated immune response, though the exact pathophysiology is currently unknown. Using single-cell transcriptomics, an enrichment of pathogenic (TBX21, RORC, IFNG, IL17A, CSF2 expressing) T-helper 17.1 cells and pro-inflammatory (TNF, IL1B, IL6, IL23A expressing) monocytes was identified in ICI-pneumonitis bronchoalveolar lavage fluid, putatively engaging in a feedforward inflammatory loop. This finding yields several novel therapeutic targets for the treatment of ICI-pneumonitis. Most notably repurposing anti-IL-23 merits further research as a potential efficacious and safe treatment for ICI-pneumonitis.

  Study EGAS00001006762

• Methylation-based classification of human mesenchymal chondrosarcoma

  We applied methylome and copy number profiling to a set of 45 well characterized MCS cases to evaluate their potential diagnostic value. Notably, the findings were reproducible also when analysing the round cell and cartilaginous component separately. Furthermore, four outliers were identified by methylome profiling for which the diagnosis had to be revised. Methylome profiling represents a sensitive, specific and reliable tool to support the diagnosis of MCS, particularly if only the round cell component is obtained in a biopsy and the diagnosis is not suspected. It can furthermore aid in confirming the diagnosis in case RNA sequencing for the HEY1::NCOA2 fusion transcript is not available.

  Study EGAS00001007042

• Whole-genome sequencing of rare disease patients in a national healthcare system

  Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and mediating genes for more than half such disorders remain to be discovered. We implemented whole-genome sequencing (WGS) in a national healthcare system to streamline diagnosis and to discover unknown aetiological variants, in the coding and non-coding regions of the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rare alleles can explain the presence of some individuals in the tails of a quantitative red blood cell (RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.

  Dataset EGAD00001006065

• Spatially resolved antigen receptor and gene expression data from breast cancer patients

  The dataset includes spatially-resolved and single-cell antigen receptor, as well as gene expression, data from two different HER2+ breast cancer patients. The tumor piece obtained during surgery from each patient was divided into several regions and tissue sections were used for spatial transcriptomics (Visium, 10x genomics). As indicated, some tissue sections were analyzed by a new method (Spatial VDJ) to spatially resolve antigen receptor sequences (target capture), which was developed in our publication. In parallel, tissue pieces from the same tumor were dissociated for single-cell gene expression analysis (10x genomics GEX, VDJ, and feature barcoding/Hash Tag Oligonucleotide). The deposited data is in the form of fastq files. All processed data, metadata, micrographs of the tissue sections (of those used for spatial transcriptomics), and scripts used for the analysis are publicly available at Zenodo (DOI: 10.5281/zenodo.7961605). Final libraries were sequenced on NextSeq2000 (Illumina) or NovaSeq6000 (Illumina) and analyzed with Cell Ranger, Seurat, Space Ranger, and STutility pipelines.

  Dataset EGAD00001011061

• August 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001008101