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• Breast cancer PDTX sequencing data from Bruna et al, Cell 2016

  Breast cancer PDTX sequencing data from Bruna et al, Cell 2016 - Exome Sequencing - Shallow Whole Genome Sequencing - RRBS Methylation Sequencing

  Dataset EGAD00001002685

• Sequencing data for oesophageal and related samples - Ganguli et al (RNA)

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain

  These data are derived from iterative data collection and analysis partly reported in three primary publications (Gibbs et al., 2010, PMID: 20485568, Hernandez et al. 2011, PMID: 21216877, Hernandez et al. 2012, PMID: 22433082). This study includes an assessment of common genetic variability across the genome, chip based gene expression analysis and array based methylation analysis, across a series of 150 subjects from whom we had cerebellum, frontal cortex, pons, and temporal cortex tissue (600 tissue samples). In each tissue we assessed 27,578 DNA methylation sites and the expression level of 22,184 genes. This work was then expanded to include assessment of 232 additional subjects and two tissues (cerebellum and frontal cortex) for whom we collected genotype, RNA expression and DNA methylation data.

  Study phs000249

• Sequencing data for oesophageal samples - Killcoyne, Gregson et al (sWGS)

  Data supporting: "Genomic copy number predicts esophageal cancer years before transformation." Killcoyne, Gregson et al. sWGS data 1000 samples BAM files

  Dataset EGAD00001006033

• PFA ependymoma cancer study

  Sequencing data related the PFA ependymoma study (Michealraj et al., Cell 2020), a lethal glial malignancy of the hindbrain found in babies and toddlers.

  Study EGAS00001004312

• Linguistic utterance counts for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

  Dataset EGAD00001008978

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• Differential Transcription Start Site Usage in Brain-related Samples

  RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5' ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods - testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

  Study phs001463

• WES of der(1;7)(q10;p10)

  This dataset contains the BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10)(+) cases. The dataset was used to identify key driver genes in patients with der(1;7)(q10;p10). Already known drivers along with novel driver genes were identified through the use of this WES.

  Dataset EGAD50000000986

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• BLUEPRINT: RNA-seq of progenitor cells

  Data supporting the paper Transcriptional diversity during lineage commitment of human blood progenitors

  Dataset EGAD00001000745

• Cancerous Adaptive Dosing Melanoma WGS Dataset

  Illumina NovaSeq 6000 30x WGS of 26 samples, each with up to 5 matched timepoints. Timepoints A,B,C,D,and E correspond to Pretreatment, Week 3, Week 6, Week 9, and Week 12 after treatment, respectively. Additional sample metadata (sample recurrence, treatment course, age, sex, comorbidities, etc.) are present in sample description.

  Dataset EGAD00001010926

• Microbiome

  16S-sequencing: All stool samples were processed according to the standards of the Flemish Gut Flora Project (Falony et al., 2016). All samples were processed together and sequenced in as a single batch (dual index run DI23R22) which included positive controls (PC, identical stool sample), negative controls (PCR-mix) and ‘blanks’ or negative controls of the extraction (no sample). In addition, a Runella strain (RS) was included to check for potential cross-contamination, as this strain is not present in human samples. The V4 region of the 16S rRNA gene was amplified with the primer pair 515F and 806R (GTGYCAGCMGCCGCGGTAA and GGACTACNVGGGTWTCTAAT, resp.), modified to contain a barcode sequence between each primer and the Illumina adaptor sequences to produce dual- barcoded libraries (Tito et al., 2019). Sequencing was performed on the Illumina MiSeq. Sequences were processed using the LotuS (Hildebrand et al., 2014) and DADA2 pipeline (Callahan et al., 2016) using RDP 16 as the reference taxonomy.

  Dataset EGAD50000002027

• MeDALL epigenetics study

  MeDALL- (Mechanisms of the Development of ALLergy) is a collaborative project supported by the European Union under the Health Cooperation Work Programme of the 7th Framework programme (grant agreement number 261357).MeDALL epigenetics study includes illumina 450k methylation measurements from 4 cohorts: Infancia y Medio Ambiente (INMA), Etudes des Déterminants pré et postnatals précoces du développement et de la santé de l’ENfant (EDEN), Children’s Allergy Environment Stockholm Epidemiology study(BAMSE), and Prevention and Incidence of Asthma and Mite Allergy (PIAMA)

  Study EGAS00001002169

• Differential methylation positions

  This dataset includes an analyzed DMP file that provide the information about differential methylation positions based on Illumina Infinium MethylationEPIC BeadChip. All samples (5 lung cancer cases vs. 5 benign lung disease controls) were obtained from bronchial washings at the site of the lesion under bronchoscopy manipulation. Of the five lung cancer cases, 3 are adenocarcinoma and 2 are squamous carcinoma.

  Dataset EGAD00001010147

• Mid-pass Whole-genome Sequencing in a Malagasy Cohort Uncovers Body Composition Associations

  The majority of human genomic research studies have been conducted in European-ancestry cohorts, reducing the likelihood of detecting potentially novel and globally impactful findings. Here, we present mid-pass whole-genome sequencing data and a genome-wide association study in a cohort of 264 self-reported Malagasy individuals from three locations on the island of Madagascar. We describe genetic variation in this Malagasy cohort, providing insight into the shared and unique patterns of genetic variation across the island. We observe phenotypic variation by location, and find high rates of hypertension particularly in the Southern Highlands sampling site as well as elevated self-reported malaria prevalence in the West Coast site relative to other sites. After filtering to a subset of 214 minimally-related individuals, we find a number of genetic associations with body composition traits, including many variants that are only observed in African populations or populations with admixed African ancestry from the 1000 Genomes Project. This study highlights the importance of including diverse populations in genomic research for the potential to gain novel insights, even with small cohort sizes. This project was conducted in partnership and consultation with local stakeholders in Madagascar and serves as an example of genomic research that prioritizes community engagement and that has potential impacts on our understanding of human health and disease.

  Study EGAS50000000496

• NHLBI Family Heart Study (FamHS-Visit1 and FamHS-Visit2)

  The Family Heart Study (FamHS) was funded by the National Heart, Lung, and Blood Institute (NHLBI). It was begun in 1992 with the ascertainment of 1,200 families, half randomly sampled, and half selected because of an excess of coronary heart disease (CHD) or risk factor abnormalities as compared with age- and sex-specific population rates (Higgins et al. 1996). The families, with approximately 6,000 individuals, were sampled on the basis of information on probands from four population-based parent studies: the Framingham Heart Study, the Utah Family Tree Study, and two Atherosclerosis Risk in Communities (ARIC) centers (Minneapolis, and Forsyth County, NC). A broad range of phenotypes were assessed at a clinic examination in broad domains of CHD, atherosclerosis, cardiac and vascular function, inflammation and hemostasis, lipids and lipoproteins, blood pressure, diabetes and insulin resistance, pulmonary function, and anthropometry (FamHS Visit 1). Approximately 8 years later, study participants belonging to the largest pedigrees were invited for a second clinical exam (FamHS Visit 2). A total of 2,756 Caucasian subjects in 508 extended families were examined. A two-phase design was adopted for the genome wide association (GWA) study. In phase-1, 1007 subjects were chosen, equally distributed between the upper and lower quartile of age- and sex-adjusted values for coronary artery calcification, assessed by CT scan in Visit 2. These subjects were chosen to be largely unrelated; 34% of the subjects were from unique families, while 200 other subjects had 1 or more siblings selected into the sample, yielding a sample of 465 unrelated subjects. The remaining family members (N=1749) were genotyped in the phase-2 for replication of the top hits from the phase-1. The results presented here represent those for the analysis of the phase-1 case-control sample for variables assessed in FamHS Visit 1 (from 1992 to 1995) and for the variables assessed in FamHS Visit 2 (from 2002 to 2003). All subjects were typed on the Illumina HumMap 550 chip (Phase 1 genotype). Of these, 33 (3.3%) were excluded due to technical errors, call rates below 98%, and discrepancies between reported sex and sex-diagnostic markers. The final sample of 974 subjects have Visit 2 phenotypes, approximately 100 of these do not have Visit 1 phenotypes. There was no significant plate-to-plate variation in allele frequencies. The covariate adjustments were performed separately by sex using cubic polynomial age and clinical centers, and retaining the terms in the stepwise regression analysis that were significant at the 5% level. Extreme outliers (>4 SD from the mean) were set aside, temporarily, for the adjustments. The final phenotypes were computed for all individuals using the best mean regression models and standardizing to 0 mean and unit variance. The FamHS has contributed GWA results in many phenotype domains (antropometric and adiposity, atherosclerosis and coronary heart disease, lipid profile, diabetes and glicemic traits, metabolic syndrome etc) to meta-analyses and various consortia, including Heard-Costa et al. 2009, Köttgen et al. 2010, Teslovich et al. 2010, Nettleton et al. 2010, Lango et al. 2010, Heid et al. 2010, Speliotes et al. 2010, Dupuis et al. 2010, Kraja et al. 2011.

  Study phs000221

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• sn-RNAseq profiling of the impact of a cytokine storm model in human cardiac organoids

  We developed conditions to model conditions of diastolic dysfunction caused by inflammatory factors in human cardiac organoids. Our organoid model is based on conditions promoting maturation (Mills et al., PNAS, 2017 and Voges et al., In Revision) and incorporating human pluripotent stem cell derived cardiomyocytes, epicardial cells, fibroblasts, endothelial cells and pericytes. Following 15 days of differentiation (Voges et al., Development, 2017) we formed human cardiac organoids incorporating both our multicellular differentiation (Mills et al., PNAS, 2017) and additional endothelial cells (Voges et al., In Revision). After another 12 days of maturation in 5 days maturation medium and 5 days weaning medium (Voges et al., In Revision) human cardiac organoids were either treated with weaning medium or “cardiac cytokine storm” comprised of 100 ng/ml IFNg, 10 ng/ml IL-1 β and 10 µg/ml poly(I:C). After 48 hours human cardiac organoids were harvested and snap frozen in -80C before nuclei isolation and single nuclei RNA sequencing.Pooled hCO (~40) were homogenized in 4 mL lysis buffer (300 mM sucrose, 10 mM Tris-HCl (pH = 8), 5 mM CaCl2, 5 mM magnesium acetate, 2 mM EDTA, 0.5 mM EGTA, 1 mM DTT)(all Sigma-Aldrich) with 30 strokes of a dounce tissue grinder (Wheaton). Large pieces of hCO were allowed to settle and homogenate was passed through pre-wetted 40 µm cell strainers (Becton Dickinson). Remaining hCO material in the douncer was resuspended in 4 mL and the douncing and filtering steps were repeated twice. All steps of the homogenization were performed on ice. The filtered homogenate was centrifuged at 1500 x g for 5 min at 4oC. Nuclei pellets were then re-suspended in PBS. A fraction of resuspended nuclei were then stained with hoechst nuclear stain (1:500 dilution) and counted on a haemocytometer under fluorescent microscope.The nuclei were then re-centrifuged (1500 x g for 5 min at 4°C) and resuspended at a density to load ~5,000 nuclei per sample. Cell were loaded into the Chromium Controller (10X Genomics) for gel bead emulsion (GEM) formation. Library preparation was conducted according to the manufacturer’s recommended protocol using the Chromium Next GEM Single Cell 3’ GEM, Library & Gel Bead Kit v3.1. Libraries were sequenced on the NextSeq 500/550 v2 (Illumina) with 150 bp reads.In the snRNA-seq we note the lower than expected percentage of non-myocytes and the loss of endothelial cells (Mills et al., PNAS, 2017 and Voges et al., In Revision), indicating the protocol requires further optimization for hCO samples.

  Study EGAS00001005174

• Oncogene activated human breast luminal progenitors contribute basally located myoepithelial cells

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions.

  Study EGAS50000000505

• Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

  In this study, we demonstrate that aberrant expression of SLAMF6 on acute myeloid leukemia (AML) cells serves as a novel immune escape mechanism that can be inhibited by antibodies against the SLAMF6 dimerization site. This constitutes a novel mechanism of checkpoint inhibition, which paves the way for immunotherapy in AML and other SLAMF6-expressing cancers. This study utilizes single cell sequencing data from the AML cell line HNT-34 co-cultured with normal T cells, with and without antibody targeting SLAMF6, as well as single cell data of 38 primary AML samples.

  Study EGAS50000001085

• Competitive selection of somatic mutant clones in normal human skin varies with body site

  The risk of getting non-melanoma skin cancer varies over 40-fold across the body. Here we map mutations in normal skin in high and low risk sites in normal donors and those with an increased risk of skin cancer. The density of mutations varied widely, with evidence of positive and negative genetic selection.  Regional differences in mutational signatures in high and low cancer risk sites and preferential selection of mutants of TP53 in high risk skin and FAT1 in lower risk skin were observed. 10% of clones had copy number changes in cancer associated genes and the largest had multiple driver mutations with loss of heterozygosity. In hair follicles, a proposed site of origin of skin cancers, mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. We conclude cancer risk reflects the efficiency of transformation of oncogenic mutants rather than the density of mutant clones.

  Dataset EGAD00001006194

• Spatial and temporal intra-tumoural heterogeneity in advanced High-Grade Serous Ovarian Cancer: implications for surgical and clinical outcomes

  Limited evidence exists on the extent and impact of spatial and temporal heterogeneity of high grade serous ovarian cancer (HGSOC) on tumour evolution and patients surgical and clinical outcome. We investigated this through systematic mapping of multi-site tumours at initial presentation and matched relapse from 49 chemo-naïve HGSOC patients with high tumour load, operated upfront. Our data provides a unique insight into the tumour evolution and metastatic pathways of HGSOC across time and space, how this complexity relates to surgical and clinical outcome and its consequences on clinical decision-making.

  Study EGAS00001007164

• GWAS membranous nephropathy Stanescu et al., 2011 UK cohort, chr2 region of interest, imputed

  334 biopsy-confirmed membranous nephropathy (MN) cases and 349 ethnically matched healthy controls: the British cohort of the Stanescu et al., 2011 GWAS. Genotyped and imputed region of interest on chromosome 2 (hg19 chr2:160500000-161500000), as used to determine Neanderthal introgression near the PLA2R1 MN risk locus (lead SNP: rs4664308).

  Study EGAS00001007700