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• Lactate metabolism in cancer stem cell fate regulation

  Tumors arise as a result of uncontrolled cell proliferation driven by mutations in the signaling pathways that regulate the balance between cell division and differentiation. Despite of that, in the tumor, cancer stem cells seem to retain their capability to differentiate, which can lead to differential chemotherapy response. We previously showed that intestinal stem cells and differentiated cells display specific metabolic features and that they interact through metabolites. Moreover, we found that altering mitochondrial metabolism is sufficient to lead and define stem cell differentiation. In cancer, cellular metabolism is highly derailed. However, how metabolic changes in the cancer cell contribute to cell fate decisions remains unknown. Recently, the crosstalk between metabolism and epigenetics has emerged as one of the players in tumor development. Here we aim to address the impact of the altered metabolism of cancer cells on their epigenome as a regulatory axis of cell identity and fate. We use human-derived tumor organoids where we introduce genetic encoded fluorescent-based reporters to visualize cell identity and metabolism at single cell level. We combine 4D live imaging with a recently developed machine learning method to re-construct cell-lineages, trace stem cell state and metabolic changes during tumor organoid development. We find that, mimicking the tumor metabolic microenvironment (Warburg effect-driven low-glucose high-lactate) leads to changes cellular metabolism and histone acetylation. Strikingly, these alterations provoke profound changes in tumor development by increasing the population of cancer stem cells and their proliferation and differentiation dynamics.

  Study EGAS50000000063

• Study on the consequences of prenatal famine exposure on DNA methylation.

  The potential of the epigenome to undergo environmentally-induced changes during early development is central to its postulated role in human disease. Here, we report a genome-scale view of DNA methylation differences after early gestational malnutrition that was caused by the Dutch Hunger Winter, a severe famine at the end of World War II. We adopted an annotation guided analysis of reduced-representation bisulfite sequencing data generated in 24 middle-aged individuals who had been exposed to famine in utero and 24 unexposed sibling controls. We observed differential DNA methylation primarily at genomic regions with regulatory potential, including enhancers active during early development. In-depth annotation of 181 prenatally-induced differentially methylated regions (P-DMRs) showed that they were predominantly located in gene bodies and co-occurred with histone marks denoting an active state. In line with the early gestational timing of the exposure, the P-DMRs mapped to genes that were enriched for differential expression patterns during blastocyst development and early organogenesis. Validation and further explorative analyses of 6 P-DMRs mapping to SMAD7, CDH23, INSR, RFTN1, CPT1A and KLF13 highlighted the critical role of gestational timing, indicated that differential methylation extended along pathways involved in growth, development and metabolism, and suggested associations with birth weight and serum LDL cholesterol in adulthood and confirmed an enhancer function for the INSR and CPT1A P-DMRs. Our results point toward a link between prenatal malnutrition and epigenetic modulation of growth and lipid metabolism that may underlie the adverse metabolic phenotype of exposed individuals in later life.

  Study EGAS00001000668

• Associations between APOE status and cognitive ability across the lifecourse

  The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population, hence meta-analyses have been based on many small, heterogeneous studies. Here we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18,337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18-94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.

  Study EGAS00001001235

• Next-Generation Sequencing of AV Nodal Reentry Tachycardia patients

  Atrioventricular nodal reentry tachycardia (AVNRT) is the most common form of regular paroxysmal supraventricular tachycardia. This arrhythmia affects women twice as frequently as men, and is often diagnosed in patients below 40 years of age. Familial clustering, early onset of symptoms, and lack of structural anomaly indicate involvement of genetic factors in AVNRT pathophysiology. We hypothesized that AVNRT patients have a high prevalence of variants in genes that are highly expressed in the atrioventricular conduction axis of the heart and potentially involved in arrhythmic diseases. Next-generation sequencing of 67 genes was applied to the DNA profile of 298 AVNRT patients and 10 AVNRT family members using HaloPlex Target Enrichment System.In total, we identified 229 variants in 60 genes; 215 missenses, four frame shifts, four codon deletions, three missense and splice sites, two stop-gain variants, and one start-lost variant. Sixty-five of these were not present in the Exome Aggregation Consortium (ExAC) database. Furthermore, we report two AVNRT families with co-segregating variants. Seventy-five of 284 AVNRT patients (26.4%) and three family members to different AVNRT probands had one or more variants in genes affecting the sodium handling. Fifty-four out of 284 AVNRT patients (19.0%) had variants in genes affecting the calcium handling of the heart. We furthermore find a large proportion of variants in the HCN1-4 genes. We did not detect a significant enrichment of rare variants in the tested genes.This could be an indication that AVNRT might be an electrical arrhythmic disease with abnormal sodium and calcium handling.

  Study EGAS00001002745

• Transcriptional profiling of ovarian tumours and cell lines

  Purpose: Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC. Experimental Design: ERV expression was assessed using EOC transcriptional data from TCGA and from an independent cohort (HH), as well as from untreated or DNMTi-treated EOC cell lines. LASSO logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells. Results: ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+ T cells (r=0.46, p=0.0001). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of ERV expression by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells. Conclusions: These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence tumor immune infiltration and affect anti-tumor immunity.

  Study EGAS00001004814

• The Dutch Microbiome Project: Defining the (un)healthy gut microbiome

  The Dutch Microbiome Project (DMP) data includes raw data generated by shotgun metagenomic sequencing of faecal samples of 8,208 Dutch individuals, processed microbiome data analysed using Biobakery2 tools (including taxonomy, pathway, virulence factors and antibiotic resistance gene profiles), and basic phenotypes (age and sex, BMI). Data is made available in two randomly assigned batches to facilitate the data access and maintenance. Access to this dataset requires a minimal access procedure (data access form at https://forms.gle/eHeBdXJMXbVvCJRc8 or email request to the data access committee (DAC) of this study, listed at DAC EGAC00001001996, https://ega-archive.org/dacs/EGAC00001001996). This access procedure is to ensure that the data is being requested for research/scientific purposes only and thus complies with the informed consent signed by Lifelines participants, which specifies that the collected data will not be used for commercial purposes. Submitted data access forms will be evaluated by the DAC and Lifelines, and a response to requests will be given within two weeks. For requests from verified academic parties, access will be given without further delay. For requests from commercial parties, Lifelines will perform a pre-DPIA (Data Privacy Impact Assessment) to assess the risks of the proposed processing of personal data (e.g. purpose, storage, access, archiving, etc.) with respect to the GDPR (EU privacy laws) subject rights. Based on the outcome of the pre-DPIA, Lifelines will decide whether sharing data with the commercial entity is allowed and/or whether additional measures have to be taken.

  Study EGAS00001005027

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 EGAS00001003137

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 EGAS00001003139

• Healthy_ageing_thymus

  Single cell RNA sequencing of immune and non-immune cells from healthy ageing thymus Thymus is a primary lymphoid organ that creates an environment for the T lymphocyte precursors differentiation into the naive T cells, which involves TCR gene rearrangement, negative and positive selection. Despite thymus critical function for the recognition of the pathogens it starts to atrophy very early in life. Thymic Epithelial Space (TES), where thymocyte education occurs, starts to decline rapidly just after birth, while with the onset of puberty thymus is also progressively replaced with adipose tissue. This leads to a reduced naive T cell output,which decreases an organism's ability to recognize pathogens. In our lab, we have already collected and characterized cell type composition and gene regulatory networks of the fetal tand adult human thymus (Park et al, Science 2020). In the current project we plan to expand the number of paediatric and adult samples in the study with the aim to understand how the process of thymic involution happens. We will use single-cell transcriptomics to zoom on changes that occur in immune and non-immune cell types in different phases of thymic involution with the hope to understand which gene expression changes are causal for the thymic involution process and how naïve T cell production can be increased in elderly. 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 EGAS00001004311

• Colorectal cancer study

  Matrix metalloproteinase-11 (MMP11) is an enzyme with proteolytic activity against matrix and non-matrix proteins. Although most MMPs are secreted as inactive proenzymes and they are later activated extracellularly, MMP11 is activated intracellularly by furin within the constitutive secretory pathway. It is a key factor in physiological tissue remodeling and its alteration may play an important role in the progression of epithelial malignancies and other diseases. TCGA colon and colorectal adenocarcinoma data showed that upregulation of MMP11 expression correlates with tumorigenesis and malignancy. Here, we provide evidence that a germline variant in the MMP11 gene (NM_005940: c.232C>T; p.(Pro78Ser)), identified by whole exome sequencing, can increase the tumorigenic properties of colorectal cancer (CRC) cells. P78S is located in the prodomain region, which is responsible for blocking MMP11’s protease activity. This variant was detected in the proband and all the cancer-affected family members analyzed, while it was not detected in healthy relatives. In silico analyses predict that P78S could have an impact on the activation of the enzyme. Furthermore, our in vitro analyses show that the expression of P78S in HCT116 cells increases tumor cell invasion and proliferation. In summary, our results show that this variant could modify the structure of the MMP11 prodomain, producing a premature or uncontrolled activation of the enzyme that may contribute to an early CRC onset in these patients. The study of this gene in other CRC cases will provide further information about its role in CRC development, which might improve patient treatment in the future.

  Study EGAS00001006489

• Treatment stratification and biomarker validation using patient-derived head and neck cancer organoids

  Background Organoids are three-dimensional structures that can be grown from patient-derived material including carcinomas. These in vitro models can be cryopreserved to generate “living” biobanks that reflect patient heterogeneity. Head and neck cancer (HNC) is a collective term used for tumors arising in the head and neck area, including squamous cell carcinomas (HNSCC) and adenocarcinoma of the salivary gland. Methods to culture patient-derived HNC organoids have previously been described. Methods Organoids were derived from resection or biopsy material of patients included between 2016 and 2022. Organoids were characterised with immunohistochemistry and whole exome sequencing (WES) and exposed to chemo-, radio- and targeted-therapies. CRISPR/Cas9-based gene editing was applied to validate proposed biomarkers. Results We have extended our previously published organoid biobank to a total of 110 organoid models, some of which were characterised by histology and WES. Organoids recapitulated both single nucleotide variants and copy number alterations as found in patient HNSCC samples. Organoid and patient response to radiotherapy (RT; primary (n=6) and adjuvant (n=15)) could be compared in 21 HNC cases. In the adjuvant RT group, organoids derived from patients that relapsed were more resistant to RT in vitro, showing potential for guiding treatment options in this subset of patients. Conclusion Taken together, these results indicate illustrate the potential of organoids as a diagnostic tool in personalised medicine for HNC and indicate the potential of this technology for biomarker discovery and validation within the context of relevant patient heterogeneity.

  Study EGAS00001007076

• Efficacy of nivolumab in pediatric cancers with high mutation burden and mismatch-repair deficiency

  Purpose: Checkpoint-inhibitors have limited efficacy for children with unselected solid and brain tumors. We report the first prospective pediatric trial (NCT02992964) using nivolumab exclusively for refractory non-hematological cancers harboring tumor mutation burden (TMB) ≥5 mutations/megabase (mut/Mb) and/or mismatch-repair deficiency (MMRD). Patients and methods: Twenty patients were screened, and ten ultimately included in the response cohort of whom nine had TMB >10mut/Mb (three initially eligible based on MMRD) and one patient had TMB between 5-10 mut/Mb. Results: Delayed immune responses contributed to best overall response of 50%, improving on initial objective responses (20%) and leading to 2-year overall survival (OS) of 50% (95% CI; 27, 93). Four children, including three with refractory malignant gliomas are in complete remission at a median follow-up of 37-months (range: 32.4-60), culminating in 2-year OS of 43% (95% CI; 18.2, 100). Biomarker analyses confirmed benefit in children with germline MMRD, microsatellite instability, higher activated and lower regulatory circulating T-cells. Stochastic mutation accumulation driven by underlying germline MMRD impacted the tumor microenvironment, contributing to delayed responses. No benefit was observed in the single patient with a MMR-proficient tumour and TMB 7.4 mut/Mb. Conclusions: Nivolumab resulted in durable responses and prolonged survival for the first time in a pediatric trial of refractory hypermutated cancers including malignant gliomas. Novel biomarkers identified here need to be translated rapidly to clinical care to identify children who can benefit from checkpoint-inhibitors, including for upfront management of their cancers.

  Study EGAS00001007393

• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Rectal cancer poses challenges in preoperative treatment response, with up to 30% achieving a complete response (CR). Personalized treatment relies on accurate identification of responders at diagnosis. This study aimed to unravel CR determinants, overall survival (OS), and time to recurrence (TTR) using clinical and targeted sequencing data. Analyzing 402 patients undergoing preoperative treatment, tumor stage, size, and treatment emerged as robust response predictors. CR rates were higher in smaller, early-stage, and intensively treated tumors. Targeted sequencing analyzed 216 cases, while 120 patients provided hotspot mutation data. KRAS mutation dramatically reduced CR odds by over 50% (odds ratio [OR]=0.3 in the targeted sequencing and OR=0.4 hotspot cohorts, respectively). In contrast, SMAD4 and SYNE1 mutations were associated with higher CR rates (OR=6.0 and 6.8, respectively). Favorable OS was linked to younger age, CR, and low baseline carcinoembryonic antigen levels. Notably, CR and an APC mutation increased TTR, while a BRAF mutation negatively affected TTR. Beyond tumor burden, SMAD4 and SYNE1 mutations significantly influenced CR. KRAS mutations independently correlated with radiotherapy resistance, and BRAF mutations heightened recurrence risk. Intriguingly, nonresponding tumors with initially small sizes carried a higher risk of recurrence. These findings offer insights into rectal cancer treatment response, guiding personalized therapeutic strategies. By uncovering factors impacting CR, OS, and TTR, this study underscores the importance of tailored approaches for rectal cancer patients. These findings, based on extensive analysis and mutation data, pave the way for personalized interventions, optimizing outcomes in the challenges of rectal cancer preoperative treatment.

  Study EGAS00001007501

• Peripheral blood DNA methylome in adalimumab-treated patients with rheumatoid arthritis

  Background and aims Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade such as anti-TNFα therapy. Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood Methods DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of adalimumab (ADA) was determined using Illumina HumanMethylationEPIC BeadChip Array. After 6 months, treatment response was assessed according to the Alliance of Associations for Rheumatology (EULAR) criteria for disease response. Patients were classified as responders (DAS28<3.2 or decrease of 1.2 points) or as non-responders (DAS28>5.1 or decrease of less than 0.6 points). Machine learning models were built with gradient boosting and stability selection models to predict response prior to ADA treatment with predictor DNA methylation markers. Results We demonstrated a 27-feature panel of DNA methylation markers or CpG classifiers that predict response in RA patients treated with ADA. Forty-nine patients were assigned as responder and 43 patients assigned as non-responders. We differentiate responders from non-responders with a high sensitivity (AUC 0.76). The predictor CpGs annotated to genes involved in immunological- and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology and angiogenesis. Conclusion Our findings indicate that DNA methylation signatures discriminate responders and non-responders to ADA treatment and can serve as a tool for therapy prediction.

  Study EGAS00001007578

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• tRCC UTSW 2024 Cohort

  This submission contains the WES and RNA-Seq raw data for the study titled 'Comparative Genomics of a Translocation Renal Cell Carcinoma Mouse Model Reveals Molecular Mechanisms of Tumorigenesis.

  Dac EGAC50000000105

• RCRF release 2

  RNA sequencing of a Chromophobe renal cell carcinoma, Non-clear cell chromophobe renal cell carcinoma, Neuroendocrine PDAC and clear cell sarcoma

  Dataset EGAD50000000872

• RNA-seq and WGS data of MB-0152

  Identification of fusion transcripts by RNA-sequencing and Whole genome sequencing of a breast cancer patient sample (METABRIC ID MB-0152)

  Dataset EGAD00001003342

• ICGC Prostate Cancer Whole Genome Sequencing

  A small subsample of EGAD00001000689. Please do not use.

  Dataset EGAD00001000263

• Reference epigenome IPS02_N_NPC_mRNA-Seq data generated from KEP study

  A IPS02_N_NPC_mRNA-Seq paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003489

• Reference epigenome IPS03_N_ENeuron_mRNA-Seq data generated from KEP study

  A IPS03_N_ENeuron_mRNA-Seq paired end data for Early neuron cells(Tuj1)

  Dataset EGAD00001003490

• Reference epigenome IPS05_X_NPC_mRNA-Seq data generated from KEP study

  A IPS05_X_NPC_mRNA-Seq paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003492

• Reference epigenome IPS06_X_ENeuron_mRNA-Seq data generated from KEP study

  A IPS06_X_ENeuron_mRNA-Seq paired end data for Early neuron cells(Tuj1)

  Dataset EGAD00001003493

• Reference epigenome IPS02_N_NPC_smRNA-Seq data generated from KEP study

  A IPS02_N_NPC_smRNA-Seq single end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003502