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• cfDNA in Hereditary And High-Risk Malignancies (CHARM)

  Our goal is to improve early cancer detection by developing a blood test to predict cancer development in carriers using circulating DNA. As carriers develop cancer, they may have pre-cancerous cells which release this DNA into the blood (cell-free DNA; cfDNA), which can be detected with novel genetic technologies. We propose to use three complementary cfDNA assays:shallow whole genome sequencing (sWGS), Liquid-Biopsy Sequencing (LB-Seq) and Cell-free Methylated DNA Immunoprecipitation and High-throughput Sequencing (cfMeDip-Seq) for early cancer detection.

  Study EGAS00001006539

• AfricanNeo aDNA Study

  With the largest genomic dataset to date of Bantu-speaking populations, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we shed fresh light on the expansion of peoples speaking Bantu languages that started ~4000 years ago in western Africa. We have generated whole-genome sequences from 12 Late Iron Age individuals. Our comprehensive genetic analysis of the expansion of people speaking Bantu languages reveals a complex history of serial founder events, variable levels of contact with local groups, and spread-over-spread events.

  Study EGAS00001007519

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual bloodderived stem cells (MenSCs) have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored. We conducted a clinical study (n=42; 19 endometriosis, 23 controls) to assess whether DNA methylation profiles of freshly isolated MenSCs can identify disease-specific biomarkers. Whole-genome methylation sequencing revealed differentially methylated regions (DMRs) enriched in genes linked to hallmarks of endometriosis (e.g., inflammation, tissue remodelling, development). These DMRs robustly distinguished cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these DMRs achieved high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset showed that the DMRs may modulate gene expression, further supporting their biological relevance. These findings position MenSC DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care.

  Dataset EGAD50000002353

• Estonian Microbiome Project second time point dataset

  Out of the 2,509 Estonian Microbiome Project participants, a sub-cohort of over 300 individuals provided an additional stool sample after a median follow-up period of 4.4 years. All participants of the EstMB cohort gave informed consent for the data and samples to be used for scientific purposes. In the second time point, the participants were instructed to send the samples by post immediately after taking the sample and time their sample collection to avoid shipping on the weekends. The median time between sampling and arrival at the freezer in the core facility for the second time point was 53 hours and 1 minute (mean: 59 hours and 22 minutes; minimum: 34 minutes; maximum: 168 hours and 7 minutes [note: additionally, one outlying measurement was 508 hours and 27 minutes. The shotgun metagenomics paired-end sequencing was performed by Novogene Bioinformatics Technology Co., Ltd., using Illumina NovaSeq6000 platform, resulting in 4.62 ± 0.44 Gb of data per sample (insert size 350 bp, read length 2 × 250 bp).

  Dataset EGAD50000001686

• Whole genome sequencing of neuroendocrine tumors of the small intestine

  This dataset contains whole genome sequences for 13 patients with neuroendocrine (unique/multiple) tumor(s) of the small intestine. There are in total 25 tumor and 12 matched normal genomes. Libraries were prepared using a Illumina DNA PCR Free kit following the manufacturer’s recommendations and sequencing was performed on Illumina Novaseq6000 machine with a 2x151bp paired-end fashion. It contains data for : - 1 patient with 4 tumors and 1 matched normal - 1 patient with 3 tumors and 1 matched normal - 1 patient with 2 tumors, 1 liver metastasis and 1 matched normal - 2 patients with 1 tumor, 1 mesenteric nodule and 1 matched normal - 7 patients with 1 tumor and 1 matched normal - 1 patient with 3 tumors and 1 mesenteric nodule

  Dataset EGAD50000000907

• Encompassing view of spatial and single-cell RNA-seq renews the role of the microvasculature in human atherosclerosis

  Atherosclerosis is a pervasive contributor to ischemic heart disease and stroke. Despite the advance of lipid lowering-therapies and antihypertensive agents, the residual risk of an atherosclerotic event remains high and developing therapeutic strategies has proven challenging. This is due to the complexity of atherosclerosis with a spatial interplay of multiple cell types within the vascular wall. Here we generate an integrative high-resolution map of human atherosclerotic plaques combining single-cell RNA-seq from multiple studies and spatial transcriptomics data from 12 human specimens, with different stages of atherosclerosis. We show cell-type and atherosclerosis-specific expression changes and spatially constrained alterations in cell-cell communication. We highlight the possible recruitment of lymphocytes via ACKR1 endothelial cells of the vasa vasorum, the migration of vascular smooth muscle cells towards the lumen by transforming into fibromyocytes, and cell-cell communication in the plaque region, indicating an intricate cellular interplay within the adventitia and the subendothelial space in human atherosclerosis.

  Dataset EGAD50000000936

• Long read mRNA sequencing of human neural retinal samples - Usher syndrome transcript landscape

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Three PacBio libraries were prepared according the 'standard workflow' optimized for sequencing transcripts centered around 2kb. Additionally one Library (input HNR_S2) was prepared according an optimized 'long workflow' to enrich for larger transcripts up to >10kb. To further enhance the capture of full-length transcripts for USH2A and ADGRV1 (USH2C) genes, we also employed a targeted enrichment approach using the Samplix Xdrop System, followed by PacBio long-read sequencing. USH2A and ADGRV1 enrichment was performed by targeting '5- mid and 3' targets of the respective genes. Finally, we also added ONT (Oxford Nanopore technology) long-read mRNA sequencing of three independent neural retina samples. These data were used for the validation of events observed from the Iso-Seq and Samplix data. The ONT datasets contain sequencing data of the Usher-associated genes. Files are raw BAM, and CRAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000720

• Precise reconstruction of the tumor microenvironment using bulk RNA-seq and a unique machine learning-based algorithm trained on artificial transcriptomes

  Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. Here, we present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of > 9,400 tissue and blood sorted cell RNA profiles to accurately reconstruct the tumor microenvironment (TME). Bioinformatic correction for technical and biological variability, aberrant cancer cell expression inclusion, and the accurate quantification and normalization of transcript expression increased the stability and robustness of Kassandra. Performance was validated on over 4,000 H&E tissue slides and more than 1,000 normal and tumor tissues by comparison with cytometric, immunohistochemical or single-cell RNA-seq measurements. Kassandra accurately deconvolved stromal and immune elements of blood and tumors, revealing the role of the TME in tumor pathogenesis. Digital TME reconstruction revealed that the presence of PD1-positive CD8+ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

  Dataset EGAD00001008776

• WGS and RNA-Seq data from a GBM patient PT-SJ5453

  WGS and RNA-Seq data from a GBM patient PT-SJ5453

  Dataset EGAD00001008529

• WGS and RNA-Seq data from a GBM patient PT-PV2594

  WGS and RNA-Seq data from a GBM patient PT-PV2594

  Dataset EGAD00001008526

• WGS and RNA-Seq data from a GBM patient PT-SS3647

  WGS and RNA-Seq data from a GBM patient PT-SS3647

  Dataset EGAD00001008530

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• RNA-sequencing of ex vivo exhausted human antigen-specific T cells

  Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

  Dataset EGAD00001009754

• WGS of tumor and blood control samples of neuroblastoma

  high coverage whole genome sequencing of 38 samples was done on a patterned flowcell v.2.5 (150 bp paired end, HiSeq X Ten) with coverage of about 60x for the tumor and whole blood control samples. All tumors had a tumor cell content of ≥60%. Sequencing libraries were prepared using the Truseq DNA Nano kit (Illumina) according to the manufacturers’ instructions and size selected using SPRI beads (Beckman Coulter Genomics).

  Dataset EGAD00001009624

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Dataset EGAD00001011048

• Familial breast cancer targeted sequencing with ONT

  A large cohort of 600 cases with familial breast cancer as classified by the Spanish Society of Medical Oncology (SEOM) Clinical Guidelines Update that were recruited during 6 years at Hospital Universitario Morales Meseguer (Murcia, Spain) were retrospectively evaluated to select 16 cases with no positive finding in NGS analysis of 20 genes implicated in this disease. These 16 cases were selected for further investigation using nanopore sequencing. This method involved the use of adaptive sampling enrichment, targeting a panel of 18 human genome regions, which contained the 20 genes (PTEN, ATM, BRCA2, PALB2, CDH1, TP53, NF1, RAD51D, BRCA1, RAD51C ,BRIP1, STK11, CHEK2, EPCAM, MSH2, MSH6, BARD1, MLH1, PMS2, NBN). In 5 samples (P1, P2, P4, P15 and P16) no selection of long reads was performed. Additionally, in 3 samples (P7, P9 and P10), both procedures were performed in two independent runs, and for the second run of P7, the DNA was previously fragmented using g-TUBE Covaris® (ref 520079) according to the protocol for 6 kb fragments.

  Dataset EGAD00001011106

• Genomic Advances in Sepsis (GAinS) genotyping

  This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 35 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected over the first five days of ICU admission to investigate how host genetics affects the individual repsonse to sepsis. DNA was extracted from buffy coat or whole blood samples using the Qiagen DNA extraction protocol, the automated Maxwell Blood purification kit (Promega), or the QIAamp Blood Midi kit protocol (Qiagen). Genotyping data were generated using the Illumina HumanOmniExpress BeadChip (295 patients), the Infinium CoreExome BeadChip (655 patients), and the Infinium Global Screening Array BeadChip (307 patients). Genotyping QC and imputation into the Haplotype Reference Consortium was perfomed within each batch. The datasets were combined and following post-imputation filtering data were available on 1168 samples.

  Dataset EGAD00001015369

• RNA-seq dataset: Single-cell spatial analysis of pediatric high-grade glioma reveals a novel population of immunosuppressive and tumor-promoting SPP1+/GPNMB+ myeloid cells

  Our study utilizes two novel techniques, cyclical immunofluorescence imaging and single-cell spatial transcriptomics, to spatially map the tumor microenvironment of a large sample set of pediatric high-grade gliomas (pHGG). Using these methods, we have identified an abundant immunosuppressive myeloid cell population that has not been described in the context of pediatric high-grade gliomas. We validate our findings using an in vitro assay, spatial analysis on additional pHGG biopsies, independent spatial transcriptomic data, bulk RNA sequencing data of an expanded cohort of in-house patients, and publicly available bulk RNA sequencing data of an even larger cohort of pHGG patients.

  Dataset EGAD00001015450

• Gene expression QTL mapping in stimulated iPSC-derived macrophages

  Immune cells sense and respond to external stimuli, initiating an inflammatory response, with genetic variants potentially altering these responses. Traditional QTL mapping often uses naïve cells, missing condition-specific variants detectable post-stimulation. Our study uses a high-throughput platform to map eQTLs across 24 conditions using iPSC-derived macrophages, identifying that 76% of eQTLs in stimulated conditions were also present in naïve cells. We found response eQTLs (reQTLs) vary widely across conditions, with rare single-condition reQTLs being overrepresented among disease-colocalizing eQTLs. This study nominates 21.7% more disease effector genes at GWAS loci through reQTL colocalization, with 38.6% not found in the GTEx catalogue, highlighting the importance of condition-specific regulatory variation in understanding disease risk alleles. Our findings underscore the value of condition-specific studies in elucidating the genetic mechanisms underlying complex diseases. 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 EGAD00001015380

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Adult RNA (2025-10-14)

  Animal studies have demonstrated that resident memory T (Trm) cells provide enhanced protective responses to a broad array of tissue-tropic pathogens, thus making Trm cells promising targets for novel vaccination strategies. However, the biological pathways that enable the long-term survival of Trm cells are poorly understood in humans. Here, we will employ a unique human intestinal transplantation setting that allows us to study the retention of persistent T cells in the grafts and the temporal development of resident T-cell populations from recruited recipient T cells. We will integrate high resolution transcriptomics, epigenetics, proteomics and immune repertoire single-cell data from purified intestinal T cells. These single-cell multiomics approaches will uncover the diversity and differentiation of the T cell populations in the human intestine, allowing us to temporally resolve the generation and maintenance of gut resident T cells. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015739

• Neuroblastoma and adrenal gland single-cell study

  Neuroblastoma is a pediatric tumor of the developing sympathetic nervous system. However, the cellular origin of neuroblastoma remains to be defined. Here, we study single-cell transcriptomes of neuroblastomas and normal human developing adrenal glands at various stages of embryonic and fetal development. We define normal differentiation trajectories during adrenal medullary development and identify the cellular origin of neuroblastoma. Importantly, adrenergic and mesenchymal neuroblastomas with varying clinical phenotypes match different temporal states along normal differentiation trajectories, with the degree of differentiation corresponding to clinical prognosis.

  Study EGAS00001004388

• Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002974

• Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002975

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002977

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002978