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• CD36 defines CML cells less sensitive to imatinib

  Tyrosine kinase inhibitors (TKIs) are highly effective for treatment of chronic myeloid leukemia (CML), but very few patients are cured. Major drawbacks with TKIs are their low efficacy in eradicating the leukemic stem cells responsible for disease maintenance and relapse upon TKI cessation. Here, we performed RNA-sequencing of flow-sorted primitive (CD34+CD38low) and progenitor (CD34+CD38+) chronic phase CML cells and identified transcriptional upregulation of 32 cell surface molecules relative to corresponding normal bone marrow cells. Focusing on novel markers with increased expression on primitive CML cells, we confirmed upregulation of the scavenger receptor CD36 and the leptin receptor (LEPR) by flow cytometry. We also delineate a subpopulation of primitive CML cells expressing CD36 that is less sensitive to imatinib treatment. Using CD36 targeting antibodies, we show that the CD36 positive cells can be targeted and killed by antibody dependent cellular cytotoxicity (ADCC). In summary, CD36 defines a subpopulation of primitive CML cells with decreased imatinib sensitivity that can be effectively targeted by ADCC using an anti-CD36 antibody.

  Study EGAS00001002421

• Ovarian cancer organoid biobank

  Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Study EGAS00001003073

• Uveal melanoma patient with germline MBD4 nonsense mutation

  There is currently no effective treatment for metastasised uveal melanoma (UM). Recently, it was reported that a UM patient was responsive to checkpoint inhibitor (CI) treatment, due to a high tumour mutation burden correlated with a germline loss-of-function MBD4 mutation. Here, we report on another UM patient who carried an MBD4 germline nonsense variant (p.Leu563Ter) and her tumour showed a 5-fold higher than average mutation burden. We confirmed the association between germline loss-of-function variant in MBD4 and CI response. The patient experienced stable disease (10 months) and survived two years with metastatic disease, which is twice as long as median survival. Additionally, the frequency of MBD4 loss-of-function variants in reported UM cohorts was >20 times higher than in an aggregated population genome database (P < 5x10-5), implying a potential role as UM predisposition gene. These findings provide a strong basis for the inclusion of MBD4 in screening of potential UM-prone families as well as stratification of immunotherapy.

  Study EGAS00001003362

• RNA-seq study of a Princess Margaret Cancer Centre human acute myeloid leukemia patient cohort

  The PMCC AML RNAseq dataset consists of 81 AML patient samples (clinical data in Supplemental Table 11 of manuscript), processed in two batches. These patient samples are able to engraft in the NSG (NOD.Cg PrkdcscidIl2rgtm1Wjl /SzJ) mouse model. Five patients (90543, 598, 90240, 110484, 100500) were included in both batches. Viaably frozen material from the Leukemia Tissue Bank at Princess Margaret Cancer Centre/ University Health Network were thawed by dropwise addition of X-VIVO + 50% fetal calf serum supplemented with DNase (100μg/mL final concentration, Roche). RNA was extracted from bulk peripheral blood mononuclear cells (PBMC) using the RNeasy Micro Kit (Qiagen Inc.). A paired-end 76 base-pair flow-cell lane Illumina High seq 2000 yielded an average of 240 million sequence reads aligning to genome per sample at the Genome Sciences Centre, BC Cancer Agency for cohort 1. Cohort 2 was subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Centre for Applied Genomics, Sick Kids Hospital.

  Study EGAS00001004792

• Pilot_experiment_on_functional_genomics_in_osteoarthritis

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will generate genotype data on the HumanCoreExome array and will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of methylation (Illumina 450k array), transcription (RNASeq) and expression (quantitative proteomics). The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data. If successful, it is envisaged that we will proceed with expanding the work to 500 patients in the first year, with a target total sample size of 3,000 in the longer term. The key collaborators in this work are Mark Wilkinson (Sheffield) and Jyoti Choudhary

  Study EGAS00001001212

• FetalQuant-SD: Accurate quantification of fetal DNA fraction by shallow-depth sequencing of maternal plasma DNA

  Noninvasive prenatal testing using massively parallel sequencing of maternal plasma DNA has been rapidly adopted in clinical use worldwide. Fetal DNA fraction in a maternal plasma sample is an important parameter for accurate interpretations of these tests. However, there is a lack of methods involving low-sequencing depth and yet would allow a robust and accurate determination of fetal DNA fraction in maternal plasma for all pregnancies. In this study, we have developed a new method to accurately quantify the fetal DNA fraction by analysing the maternal genotypes and sequencing data of maternal plasma DNA. Fetal DNA fraction was calculated based on the proportion of non-maternal alleles at single-nucleotide polymorphisms where the mother is homozygous. This new approach achieves a median deviation of 0.6% between predicted fetal DNA fraction and the actual fetal DNA fraction using as low as 0.03-fold sequencing coverage of the human genome. We believe that this method will further enhance the clinical interpretations of noninvasive prenatal testing using genome-wide random sequencing.

  Study EGAS00001001611

• Field_effect_of_healthy_and_diseased_livers

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences).

  Study EGAS00001002382

• Genome-wide mutational consequences of nucleotide excision repair-deficiency through XPC deletion in a human adult stem cell culture

  Nucleotide excision repair (NER) is one of the main DNA repair pathways that protect cells against genomic damage. Deficiency in this pathway can contribute to the development of cancer and accelerate aging. NER-deficiency is an important determinant for cancer treatment outcome, as NER-deficient tumors are selectively sensitive to cisplatin treatment. While NER-deficiency has been linked to mutational Signature 5, not all NER-deficient tumors are characterized by a high Signature 5 contribution, illustrating the importance to further characterize the mutational consequences of NER-deficiency. Here, we analyzed the mutational profile of a human adult stem cell (organoid) culture that is deficient in NER through XPC deletion by CRISPR-Cas9 gene-editing, and subsequent whole-genome sequencing analysis of a clonally derived organoid. We found that XPC deletion results in an increase in base substitution load and specifically induces Signature 8 mutations, a mutational signature with previously unknown etiology. Presence of Signature 8 may, therefore, serve as a novel biomarker for NER-deficient tumors and could improve personalized treatment strategies.

  Study EGAS00001002681

• Using human induced pluripotent stem cells (iPSC) and iPSC-derived neurons to explore cellular phenotypes associated with schizophrenia.

  Schizophrenia and major mental illness are common devastating conditions. Whilst partially effective treatments are available, none are disease-modifying. Notwithstanding important insights provided by animal models there is a need for novel models of mental illness to develop more effective therapies. A study of sporadic schizophrenia-derived human induced pluripotent stem cells (hiPS) has demonstrated a neuronal phenotype representing a powerful proof of concept of in vitro disease modeling, even for diseases with complex causation such as schizophrenia. These techniques have been used here to examine the behaviour of neural stem cells and neurons derived from fibroblasts from subjects carrying NDE1 copy number variations (CNVs) associated with increased risk of major mental illness. Using hiPS from individuals with and without disease-associated CNVs we have investigated how disease risk is conferred at a cellular and molecular level through detailed comparative studies of neural progenitor proliferation, neuronal morphology, physiology, cytoskeletal organization, synaptic function, glutamate (NMDA) receptor expression and also RNA sequencing and proteomic studies of these patient-derived cells.

  Study EGAS00001002895

• Pheno-Seq, linking 3D phenotypes of clonal tumor spheroids to gene expression

  3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.

  Study EGAS00001002999

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Pilot_experiment_on_functional_genomics_in_osteoarthritis

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will generate genotype data on the HumanCoreExome array and will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of methylation (Illumina 450k array), transcription (RNASeq) and expression (quantitative proteomics). The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data. If successful, it is envisaged that we will proceed with expanding the work to 500 patients in the first year, with a target total sample size of 3,000 in the longer term. The key collaborators in this work are Mark Wilkinson (Sheffield) and Jyoti Choudhary

  Study EGAS00001001213

• Integrative genomic analysis identifies multiple subtypes and therapeutic targets in acute erythroid leukemia

  Acute erythroid leukemia (AEL) is a high risk leukemia of poorly understood genetic basis, and controversy regarding diagnosis in the spectrum of myelodysplasia and myeloid leukemia. We compared genomic and clinical features of 159 childhood and adult AEL cases to non-AEL myeloid disorders, and identified patterns of mutation that describe 5 age-related subgroups with distinct transcriptional profiles: adult, TP53-mutated; NPM1-mutated; KMT2A-mutated/rearranged; adult, DDX41-mutated; and pediatric, NUP98-rearranged. Mutational spectra were age-dependent and significantly associated with outcome, with NPM1 mutations and high HOXB9 expression being associated with favorable prognosis, and TP53, FLT3 and RB1 alterations associated with poor survival. Targetable signaling mutations were present in 45% of cases, and include recurrent mutations of ALK and NTRK1, the latter of which drive erythroid leukemogenesis sensitive to TRK inhibition. This genomic landscape of AEL provides the framework for accurate diagnosis and risk stratification of this disease, and the rationale for testing targeted therapies in this form of leukemia that has hitherto and dismal outcome.

  Study EGAS00001002537

• Genes associated with pancreas development and function maintain open chromatin in iPSCs generated from human pancreatic beta cells

  Current in-vitro islet differentiation protocols suffer from heterogeneity and low efficiency. Induced-pluripotent stem cells (iPSCs) derived from pancreatic beta-cells (BiPSCs) preferentially differentiate towards endocrine pancreas-like cells versus those from fibroblasts (FiPSCs). We interrogated genome-wide open chromatin in BiPSCs and FiPSCs via ATAC-seq, and identified ~8.3k significant, differential open chromatin sites (DOCS) between the two iPSC subtypes (FDR<0.05). DOCS where chromatin was more accessible in BiPSCs (Bi-DOCS) were significantly enriched for known regulators of endodermal development, including bivalent and weak enhancers, and FOXA2 binding sites (FDR<0.05). Bi-DOCS were associated with genes related to pancreas development and beta-cell function, including transcription factors mutated in monogenic diabetes (PDX1, NKX2-2, HNF1A; FDR<0.05). Moreover, Bi-DOCS correlated with enhanced gene expression in BiPSC-derived definitive endoderm and pancreatic progenitor cells. Bi-DOCS therefore highlight genes and pathways governing islet-lineage commitment, which can be exploited for differentiation protocol optimisation, diabetes disease modelling, and therapeutic purposes.

  Study EGAS00001002591

• Genomic and functional fidelity of small cell lung cancer patient-derived xenografts

  Small cell lung cancer (SCLC) patient-derived xenografts (PDXs) can be generated from biopsies or circulating tumor cells (CTCs), though scarcity of tissue and low efficiency of tumor growth have previously limited these approaches. Applying an established clinical-translational pipeline for tissue collection and an automated microfluidic platform for CTC-enrichment, we generated 17 biopsy-derived PDXs and 17 CTC-derived PDXs in a two-year timeframe, at efficiencies of 89% and 38%, respectively. Whole exome sequencing showed that somatic alterations are stably maintained between patient tumors and PDXs. Early-passage PDXs maintain the genomic and transcriptional profiles of the founder PDX. In vivo treatment with etoposide and cisplatin (EP) in 30 PDX models demonstrated greater sensitivity in PDXs from EP naïve patients, and resistance to EP corresponded to increased expression of a MYC gene signature. Finally, serial CTC-derived PDXs generated from an individual patient at multiple time points accurately recapitulated the evolving drug sensitivities of that patient’s disease. Collectively, this work highlights the translational potential of this strategy.

  Study EGAS00001002853

• Somatic_mutation_profiling_of_intestinal_crypts_from_IBD

  In this project we want to investigate the role that somatic mutations in intestinal stem cells play in IBD. We will use laser capture microdissection to ascertain epithelial cells from an individual crypts/vilus. We will extract DNA from these and use a new low-input material library prep methods to make accurate libraries for sequencing. In this pilot phase of the project we will perform 15X whole-genome sequencing of a small number of crypts biopsied from four patients. Biopsies have been taken from inflammed and noninflammed patches to compare mutation rates and mutational signatures. We will also test if crypts from inflammed patches of a single patient are clonal (either within a given inflammed patch or across inflammed patches). We will quantify the rate of cancer driver mutations in inflammed and non-inflammed crypts. 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 EGAS00001002896

• DERMATLAS__Hidradenoma_papilliferum_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are hidradenoma papilliferums.

  Study EGAS00001005715

• DERMATLAS__Porocarcinoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are porocarcinomas.

  Study EGAS00001005721

• DERMATLAS__Poroma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are poromas.

  Study EGAS00001005759

• Single-nuclei gene-expression analysis of pheochromocytoma and paraganglioma links tumor subtypes with tumor microenvironment

  Pheochromocytomas and paragangliomas (PCPG) are rare neuroendocrine tumors associated with autonomic nerves. We used single nuclei-RNA-seq (snRNA-seq) for analysis of 30 PCPG representing 13 known driver genes, plus two normal adrenal medullas to dissect cell composition, refine PCPG subtypes and compare PCPG and normal tissue expression. Incorporating bulk-tissue and snRNA-seq data we identified seven PCPG gene-expression subtypes with genotype and cell type associations. The tumor microenvironment reflected HIF pathway activation and neovascularization by detection of abundant tip-like endothelial cells and pericytes concordant with VEGFA expression in neoplastic cells with mutations in VHL, genes encoding SDH subunits and MAML3-fusions. Macrophages were abundant in PCPG with distinct tumor-associated features. Schwann-cell-like cells were also enriched in some subtypes. The transcriptional profile of neoplastic PCPG cells resembled normal chromaffin cells but early chromaffin and neuroblast cell markers were expressed in some subtypes including GPR139, a putative therapeutic target for a subset of pseudohypoxic PCPG.

  Study EGAS00001005861

• DLBCL NGS Genomic Datasets of non-China cohort from Phoenix Clinical Trial

  Study biopsies (n=773; 189 cases as China cohort and 584 cases as non-China cohort) underwent whole exome sequencing or targeted gene panel DNA sequencing and RNA sequencing, allowing the identification of somatic mutations. Tumors were assigned to DLBCL genetic subtypes as the MCD (n=110), BN2 (n=47) or N1 (n=28) using the LymphGen algorithm based on their somatically mutated genes. In younger patients (age≤60), ibrutinib plus R-CHOP was associated with a 100% event free survival (EFS) at 3-years in the MCD and N1 groups, whereas R-CHOP alone was associated with a 3-year EFS of 42.9% (p=0.01) and 50% (p=0.016) in the MCD and N1 groups, respectively. This analysis showed a benefit of ibrutinib with R-CHOP chemotherapy in particular genetic subtypes, providing mechanistic support for its survival benefit in younger patients with non-GCB DLBCL. The EGA collects RNA-Seq and NuGene targeted sequencing datasets of 584 cases for non-China cohort.

  Study EGAS00001005554

• Serum proteomics of aortic diseases

  Aortic diseases are a rare but potentially life-threatening condition. We present a serum proteomic study for a spectrum of aortic diseases including thoracic aortic aneurysms (n = 11), chronic dissections (n = 9), acute aortic dissections (n = 11), and surgically treated dissections (n = 19) as well as healthy controls (n = 10) and patients of coronary heart disease (n = 10) to represent non-aortic cardiovascular disease. In total, we identified and quantified 425 proteins across all 70 samples. The different aortic diseases represented distinguishable proteome profiles. We identified protein clusters that positively or negatively correlate with disease severity, including increase of cytosolic tissue leakage proteins and decrease of components of the coagulation and complement system. Further, we identified a serum proteome fingerprint of acute aortic dissections, consisting, among others, of enriched inflammatory markers such as C-reactive protein and members of the S100 protein family. The study underlines the applicability of serum proteomics for the investigation of aortic diseases and highlights the possibility to establish disease-specific prognostic markers.

  Study EGAS00001006201

• Salivary Gland Cancer TSO500 dataset

  Salivary gland cancer (SGC) is a rare cancer for which systemic treatment options are limited. Therefore, it is important to characterize its genetic landscape in search for actionable aberrations. This research aimed to identify these actionable aberrations by NGS-based analysis of DNA (single and multiple nucleotide variants, copy number variants, microsatellite instability and tumor mutational burden) in a large cohort of SGC patients. DNA was extracted from archival tissue of 119 patients with various SGC subtypes and sequenced using a targeted NGS panel encompassing 523 cancer related genes (TruSight Oncology 500, TSO500). The 119 patients included 46 AdCC patients, 43 SDC patients, 15 MEC patients, 9 AciCC patients and 6 patients with other subtypes (1 secretory carcinoma, 1 polymorphic adenocarcinoma (PAC), 1 adenocarcinoma NOS, 1 myoepithelial carcinoma, 1 epithelial/myoepithelial carcinoma and 1 mixed PAC/myoepithelial carcinoma). Median exon coverage ranged from 80-904 (median 308) unique reads and the median percentage of exon coverage with at least 100 unique reads was median 96.6% in these 119 samples.

  Study EGAS00001006232

• Genetic and epigenetic variation at regulatory regions contribute to cancer evolution under endocrine treatment

  Comprehensive profiling of hormone-dependent breast cancer (HDBC) has identified hundreds of protein-coding alterations contributing to cancer initiation, but only a handful have been linked to endocrine therapy resistance, potentially contributing to 40% of relapses. If other mechanisms underlie the evolution of HDBC under adjuvant therapy is currently unknown. In this work, we employ integrative functional genomics to dissect the contribution of cis-regulatory elements (CREs) to cancer evolution by focusing on 12 megabases of non-coding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Massive parallel perturbation in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance9. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies non-coding changes involved in therapy resistance. Overall, our data uncover actionable transient transcriptional programs critical for dormant persister cells and unveil new regulatory nodes driving evolutionary trajectories towards disease progression.

  Study EGAS00001006340

• DERMATLAS__Tubular_adenoma

  IVirtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are tubular adenomas.

  Study EGAS00001006686

• The miR-185/PAK6 Axis Predicts Therapy Response and Regulates Survival of Drug-Resistant Leukemic Stem Cells in Chronic Myeloid Leukemia

  Overcoming drug resistance and targeting cancer stem cells remain challenges for curative cancer treatment. To investigate the role of miRNAs in regulating drug resistance and leukemic stem cell (LSCs) fate, we performed global transcriptome profiling in treatment-naïve chronic myeloid leukemia (CML) stem/progenitor cells and identified that miR-185 levels anticipate their response to ABL tyrosine kinase inhibitors (TKIs). miR-185 functions as a tumor suppressor; its restored expression impaired survival of drug-resistant cells, sensitized them to TKIs in vitro, and markedly eliminated long-term repopulating LSCs and infiltrating blast cells, conferring a survival advantage in pre-clinical xenotransplantation models. Integrative analysis with mRNA profiles uncovered PAK6 as a crucial target of miR-185 and pharmacological inhibition of PAK6 perturbed the RAS/MAPK pathway and mitochondrial activity, sensitizing therapy-resistant cells to TKIs. Thus, miR-185 presents as a potential predictive biomarker, and dual targeting of miR-185-mediated PAK6 activity and BCR-ABL may provide a valuable strategy for overcoming drug resistance in patients.

  Study EGAS00001004153

• DERMATLAS__Tubular_adenoma_RNAseq

  IVirtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are tubular adenomas.

  Study EGAS00001006685

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• Introducing Federated EGA Affiliates: a newly defined tier in the Federated EGA Network

  We're happy to announce that we are now accepting Affiliates in the Federated EGA Network! Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Currently, Federated EGA consists of Central EGA (CEGA), which serves the global community, and nine national Nodes that serve respective jurisdictions. Did you know that the Federated EGA (FEGA) has always envisioned a third tier within the network? This brings us to FEGA Affiliates, recently defined in the newly approved "Federated EGA Structure and Organisation" document. This new tier broadens the range of institutions or organisations that can become part of FEGA. Thus begins a new era for the network. What is a FEGA Affiliate? A FEGA Affiliate archives and serves controlled-access data within its own governance scope, while still participating in federated discovery through the EGA catalogue. Affiliates can be individual organisations or institutions, healthcare genomics initiatives, consortia of institutions, as well as project-specific consortia (national or international). In practical terms, a FEGA Affiliate: Hosts and safeguards the data it archives. Submits non-personal metadata to CEGA so studies are discoverable and can receive EGA accessions. Manages permissions and data access workflows for its datasets. Provides data access and/or distribution, along with support, to authorised users. Key takeaways about FEGA Affiliates FEGA is now organised into three tiers: CEGA, FEGA Nodes, and FEGA Affiliates. Affiliates archive data from their own organisation and/or selected partner institutions (for example, an international consortium). Affiliates make studies discoverable through the EGA catalogue by submitting non-personal metadata for accessioning. Access decisions and conditions are managed locally by the Affiliate (e.g. distribution or access in a trusted research environment). Are you considering whether your institution or project might be a good fit as a FEGA Affiliate? Would you like to learn more about this tier? We have published a blog post that addresses potential common questions, providing answers on this topic. You can read it here.

  Blog fega-affiliates

• Genome Diversity in Africa Project: Uganda (2021-02-17)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics . This dataset contains all the data available for this study on 2021-02-17.

  Dataset EGAD00001006976

• DERMATLAS__Leiomyosarcoma_WES

  irtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyosarcomas.

  Study EGAS00001007628

• DERMATLAS__Poroma_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are poromas.

  Study EGAS00001007705

• DERMATLAS__SG_basal_cell_adenoma_and_adenocarcinoma_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are SG basal cell adenomas and adenocarcinomas.

  Study EGAS00001007745

• DERMATLAS__SG_basal_cell_adenoma_and_adenocarcinoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are SG basal cell adenomas and adenocarcinomas.

  Study EGAS00001007746

• RNA sequencing data of 257 samples from 106 patients with HR+/HER2- breast cancer treated with AC plus paclitaxel or letrozole plus ribociclib (SOLTI-1402 CORALLEEN trial)

  Early-stage Luminal B breast cancer is frequent and is a major cause of breast cancer death due to its poor prognosis. Our proposal aims to study the biology behind the sensitivity and resistance of Luminal B breast cancer to chemotherapy (CHT) or a non-CHT regimen composed of hormone therapy in combination with ribociclib, a CDK4/6 inhibitor. To accomplish this, we first completed the SOLTI-1402 CORALLEEN phase II trial, a study where 106 patients with early-stage Luminal B breast cancer were randomized to standard neoadjuvant CHT for 6 months, or neoadjuvant letrozole and ribociclib for 6 months. After treatment, patients underwent surgery. The primary results of the study, which showed that the response rate to letrozole+ribociclib was similar to CHT, was reported (Prat et al; Lancet Oncol). Tumor biopsies were available at baseline, week 3 and surgery. A total of 257 samples were analyzed using the Illumina TruSeq Stranded Total RNA w/Ribo Zero Gold with MiSeq in TGL (Sequencer NovaSeq S4/PE/100x).

  Study EGAS00001007060

• Sequential Antigen-loss and Branching Evolution in Lymphoma after Anti-CD19 and Anti-CD20 Targeted T Cell Engaging Immunotherapy

  CD19 CAR T cells and CD20 targeting T cell engaging bispecific antibodies have been approved in B-cell Non-Hodgkin lymphoma lately, heralding a new clinical setting where patients are treated with both approaches, sequentially. The aim of our study was to investigate the selective pressure of CD19 and CD20 directed therapy on the clonal architecture in lymphoma. Using a broad analytical pipeline, we identified truncating mutations in the gene encoding CD20 conferring antigen loss in 80% of patients relapsing from CD20 bispecs. Pronounced T cell exhaustion was identified in cases with progressive disease and retained CD20 expression. We also confirmed CD19 loss after CAR T cell therapy and report the case of sequential CD19 and CD20 loss. We observed branching evolution with re-emergence of CD20 positive subclones at later time points and spatial heterogeneity for CD20 expression in response to targeted therapy. Our results highlight immunotherapy as an evolutionary bottleneck selecting for antigen-loss variants but also complex evolutionary pathways underlying disease progression from these novel therapies.

  Study EGAS00001007561

• DERMATLAS__Leiomyoma_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyomas.

  Study EGAS00001007629

• DERMATLAS__Leiomyoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyomas.

  Study EGAS00001007630

• DERMATLAS__Leiomyosarcoma_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previoulsy, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles. The cases in this cohort are leiomyosarcomas.

  Study EGAS00001007631

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001000416 study data is whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Study EGAS00001000416

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001000417 study data is whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Study EGAS00001000417

• Pan Prostate Cancer Group data

  The Pan Prostate Cancer Group intends to provide breakthrough advances from the analysis of a very large series of Whole Genome DNA data, contributed by many of the leading scientists and clinicians working in prostate cancer genomics generating Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The accumulated data, collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals, are presented in this series. This project will provide a global framework for the future analysis of even larger series of genomes as costs of DNA sequencing, storage, and sequence analysis decrease. In addition to these WGS data from different clinical categories, ethnicities, levels of aggressiveness, and disease managed by different treatments with information linked to long-term clinical follow up, we intend to add additional layers of data, including transcriptome and methylation data. The current data series focuses primarily on the analysis of WGS data. For further information, please refer to https://panprostate.org/, and The Pan Prostate Cancer Group Data Sharing Policy, EGAP50000000784.

  Study EGAS00001002876

• Sequencing data (BAM files) from - A mutation in VPS15 (PIK3R4) causes a ciliopathy and affects IFT20 release from the cis-Golgi. The Data Access Committee (DAC) is responsible for sequencing data release to external requestors based on consent and/or National Research Ethics terms.

  Dac EGAC00001000552

• EGAD00010000744

  Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only.

  Dataset EGAD00010000744

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• OncoScan SNP data set for localized follicular lymphoma (lFL)

  149 unpaired initial tumor samples (133/149 FFPE and 16/149 fresh frozen samples) of lFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002593

• SECRETO Oral metagenome

  The dataset comprises data for n=329 participants who underwent saliva sampling. Shotgun metagenomic paired-end sequencing was conducted using the Illumina NovaSeq 6000 platform, and the resulting files are in FASTQ format.

  Dataset EGAD50000000283

• Multi time/space shallow whole genome sequencing of esophageal adenocarcinoma's

  Shallow whole genome sequencing of 170 samples from 24 esophageal adenocarcinoma's. DNA was obtained from FFPE stored material. Illumna Hiseq 400 was used for sequencing.

  Dataset EGAD50000000318

• Multimodal epigenetic sequencing analysis for colon cancer

  Targeted methylation sequencing (enzymatic conversion) data of plasma samples collected from colon cancer patients and non-cancer subjects.

  Study EGAS50000000052

• AmsterdamUMC Data Access Committee for the EPIC-CD study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the EPIC-CD project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000097

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024

• L1-Architect Project DAC

  This Data Access Committee and policies are for controlling the correct use of the omics datasets generated within the L1-Architect Project, to investigate the impact of L1 transposable elements in tumours with high and ultrahigh rates of somatic retrotransposition

  Dac EGAC50000000289

• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• Clinical data and mapping file

  Patient demographic characteristics, treatment, and survival data for IMbrave151 (N = 162), with one patient per line. Mapping file to map anonymized subject IDs to RNAseq IDs

  Dataset EGAD50000000569

• WGS FASTQ files studied in A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  This data set contains 2 paired fastq files (WGS).

  Dataset EGAD50000000947

• UMI-4C in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  UMI-4C sequencing data generated for MLH1 promoter to assess allele-specific interactions in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  Dataset EGAD50000000713

• RNAseq TPM

  RNAseq TPM matrix (transcriptome profiling by high-thoughput sequencing) Matrix (30,727 features by 2,803 samples) of log2-transformed TPM counts from RNAseq data for the four IMvigor trials.

  Dataset EGAD50000001100

• WGBS dataset for lymphnode metastasis samples from prostate cancer

  This dataset contains WGBS sequencing data of lymphnode metastasis samples from prostate cancer. Sequencing was performed on Illumina HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000001183

• Dac for "Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)" with PD Dr. med. Tobias Kessler, t.kessler@dkfz.de/ Prof. Dr. med. Wolfgang Wick, wolfgang.wick@med.uni-heidelberg.de

  Dac EGAC00001003521

• ST lobular manuscript dataset

  Spatial transcriptomics analysis for 43 breast cancer lobular samples. Note that there are 2 runs per sample Images and read counts will be made availalble on Zenodo upon publication.

  Dataset EGAD50000001467

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• Dataset for RNA sequencing glioblastoma data

  This dataset contains RNA sequencing data of 36 glioblastoma samples. Sequencing was performed on Illumina NovaSeq 6000 using TruSeq Stranded RNA Kit. The sequencing was always paired.

  Dataset EGAD50000000688

• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• Dynamic human admixture histories over the past ~1,300 years at the northern Himalayan frontier

  Data access for present-day whole-genome dataset (fastq and bam files) from the study titled "Dynamic human admixture histories over the last ~1,300 years at the northern Himalayan frontier"

  Dac EGAC50000000760

• Hypoxia and plasma treatment of glioblastoma organoids

  RNA sequencing of organoids derived from human glioblastoma subject to hypoxia, plasma, or a combination of both for 72h, sampled at 0, 24, 72, and 144h.

  Dataset EGAD50000002081

• DNA methylation array study for 7 pairs of primary NSCLCs and distant metastases

  This study is to compare DNA methylation profiles between primary NSCLCs and paired distant metastases.

  Study EGAS00001004079

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Study EGAS00001006609

• H3Africa H3AChipDesign NEEDI

  50 samples from Mali generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004334

• Dataset for glioblastoma panel sequencing

  This dataset contains panel sequencing data of 228 samples from patients with glioblastoma. Sequencing has been performed on Illumina NovaSeq 6000 and NextSeq 500. The sequencing was always paired.

  Dataset EGAD00001015505

• Normal brain controls for ICGC PedBrain DNA methylation sequencing

  DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4)

  Dataset EGAD00001000952

• Paired-end sequenced plasma DNA samples

  Merged file of low-coverage WGS from 179 plasma DNA samples from non-cancer controls and cancer patients for assessment of size distribution of plasma nuclear DNA fragments.

  Dataset EGAD00001002217

• Whole exome sequencing of Belvarafenib resistant IPC-298 clones

  Whole Exome Sequencing of Belvarafenib resistant IPC-298 clones after treatment for 3-4 weeks with 10uM belvarafenib

  Dataset EGAD00001007062

• New Caledonia low-coverage whole-genome sequencing data

  Mapped sequence reads in BAM format for 64 individuals reporting Kanak ancestry recruited in New Caledonia sequenced at four times target coverage using the Illumina HiSeq 4000 platform.

  Dataset EGAD00001002665

• MiSeq-Low Coverage

  Fourteen files of patients 1, 2, 4, 6, 7, 8, 9, 12, 14, 16, 17, 18, 19 and 27 with WGS done on Illumina MiSeq with low coverage. For research purpose and authorised user only.

  Dataset EGAD00001003437

• H3Africa H3AChipDesign CAfGEN

  48 samples from Botswana generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004533

• Patient TSO500 RNA

  Original patient tumours from which PDX models were derived. TruSight Oncology RNA panel for 2 samples, sequenced over 4 lanes each, gave 8 pairs of fastq files

  Dataset EGAD00001009659

• Whole genome sequencing of osteosarcoma and blood

  We profiled 2 patient osteosarcoma tumor samples as well as the blood of the same patients by whole genome sequencing, for a total of 4 samples. The raw fastqs are provided.

  Dataset EGAD00001011372

• Raw count matrix for 44 baseline + 44 progression samples

  Count matrix from 44 pre-treatment (Ven-Obi or Clb-Obi) and 44 paired, post-treatment relapsed CD19+ B cells.

  Dataset EGAD00001009500

• RNAseq of 25 sarcoma samples

  100 bp paired-end fastq RNAseq files for 25 sarcoma samples. RNAseq data from exon capture library prep.

  Dataset EGAD00001010839

• liCHi-C Samples of blood cell types

  Libraries of liCHi-C for 9 blood cell types (HSC, CMP, CLP, Ery, Mon, MK, nB, nCD4 and nCD8) with 2 biological replicates each. Fastq file format.

  Dataset EGAD00001008828

• GIS-LUNGTCR1-2016_WES-BAM

  This dataset contains BAM file for multi-region exome-sequencing of EGFR-mutant lung adenocarcinomas from Asian patient. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors.

  Dataset EGAD00001001979

• RNA-sequencing of adult T-cell leukemia/lymphoma sample

  This dataset includes 10 RNA-sequencing (RNA-seq) data for 9 primary tumors and 1 cell line from adult T-cell leukemia/lymphoma (ATL).

  Dataset EGAD00001004937

• CCMA

  This dataset has the processed WGS data for the cancer models in CCMA.

  Dataset EGAD00001009633

• in silico drug target prediction for melanoma

  31 samples transcriptomics to simulate the knock-out of all targets of a drug on an objective function such as growth or energy balance.

  Dataset EGAD00001009089

• Germline loss-of-function P2RY8 variants in SLE

  Set of 8 bam files from patients affected with Lupus. BAM alignments for exonic variants present in P2RY8 gene. VCF file describing the variants.

  Dataset EGAD00001008330

• ctDNA data

  ctDNA data for IMpower150, including individual mutation calls (one mutation per sample per line), sample list including ctDNA status (one sample per line), and patient-level ctDNA summaries called ctDNA features (one patient per line).

  Dataset EGAD00001009725

• Illumina RNA sequencing data

  RNA sequence data for HKCI-2, HKCI-C1, HKCI-C2, HKCI-C3 and MIHA. RNA-seq data of all the 5 samples were stored in compressed fastq format.

  Dataset EGAD00001004476

• Dataset for HCPlus_WES

  WES/WGS sequencing data of 234 chromothriptic tumor and control runs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001009272

• H3Africa H3AChipDesign ELSI

  24 samples from Cameroon generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004316

• 14 scDNAseq samples

  14 samples were processed for single cell DNA sequencing

  Dataset EGAD00001007521

• H3Africa H3AChipDesign ACCME

  49 samples from Nigeria generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004505

• H3Africa H3AChipDesign TrypanoGEN2

  41 samples from Zambia generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004220

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0079_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0079_002 for Triple negative breast cancer patient-derived xenograft SA1035X6XB03211

  Dataset EGAD00001011242

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult DNA (2025-10-16)

  Human Cell Atlas - WGS Adult Heart . This dataset contains all the data available for this study on 2025-10-16.

  Dataset EGAD00001015751

• Glioblastoma stem cell lines RNA-seq data

  RNA-seq data for 54 Glioblastoma stem cell (GSC) lines. Fastq files of the strand-specific paired-end RNA-seq data are available.

  Dataset EGAD00001006195

• WGS data for medulloblastoma samples (MDT-AP)

  WGS data of medulloblastoma tumor/control pairs.

  Dataset EGAD00001003125

• Transcriptome - MBD4-deficient AML

  Transcriptome sequencing for WEHI-AML-1 and WEHI-AML-2. RNA libraries were generated using the Illumina TruSeq RNA Sample Preparation Kit v2 and sequenced on an Illumina HiSeq2500.

  Dataset EGAD00001003569

• FFPE_normals_v2_gbm_wtsi_panel (2018-06-06)

  Targeted pulldown of approx 60 ffpe normal samples to use as normal controls . This dataset contains all the data available for this study on 2018-06-06.

  Dataset EGAD00001004152

• ICGC PACA-CA Release 18

  Supporting data for ICGC PACA-CA Release 18

  Dataset EGAD00001001095

• G&T-seq: Parallel sequencing of single-cell genomes and transcriptomes

  Development of a method for separation and parallel sequencing of the genomes and transcriptomes of single cells.

  Dataset EGAD00001001332