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• Development of Novel Histiocytic Sarcoma Organoid Model for Drug Discovery

  Histiocytic sarcoma is an extremely rare and aggressive hematopoietic malignancy. Its pathogenesis remains poorly understood and effective treatments are lacking. We treated a patient with histiocytic sarcoma of soft tissue in Osaka International Cancer Institute and established an organoid culture from a resected tumor specimen using a modified air���liquid interface method. After serial passaging, the organoid was successfully xenografted into NOD-scid IL2Rgnull (NSG) mice. The established organoid retained key histological features and genetic characteristics of the original tumor. This organoid model offers a novel and reliable platform for studying the biology of histiocytic sarcoma and may contribute to the development of future therapeutic strategies.

  Study JGAS000807

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• BrainCloud: Data from human postmortem brain procurement for the neuropathology section

  This study explores the temporal dynamics and genetic control of transcription and DNA methylation in the human dorsolateral prefrontal cortex in postmortem tissue. This study examines 269 subjects for gene expression (version 1) and 108 subjects for DNA methylation (version 2). The subjects are normal controls without neuropathological and neuropsychiatric diagnosis and range in age from fetal weeks 14-20 through old age (>80). We discover fast changes in gene expression occurring during early brain development. Later in life, the changes are considerably slower. Many genes reverse pattern of expression between fetal and early postnatal development. We identify thousands of strong associations of SNPs with gene expression. We examine DNA methylation in ~14,500 genes at ~27,000 CpG loci focused on 5' promoter regions. The fastest changes in DNA methylation also occur during the prenatal period, slow down markedly after birth and continue to slow further with aging. DNA methylation is strongly associated with genotypic variants and correlates with expression of a subset of genes. DNA for genotyping was obtained from the cerebella and applied to either Illumina 650K or 1 million BeadArrays - only genotypes common to both platforms are analyzed here. Genotypes were called using BeadExpress software. Doi: 10.1038/nature10524 Nature, 478:519-524, 2011; doi:10.1016/j.ajhg.2011.12.020, AJHG 90, 1-13, Feb 10, 2012. The methylation data can be downloaded at: BrainCloud.

  Study phs000417

• A_systems_biology_approach_to_understand_immunity_and_pathogenesis_of_malaria_in_children_exposed_to_endemic_Plasmodium_falciparum_transmission

  From long-term studies of children in Kenya, we know that some children have numerous malaria episodes through to older age, while other children become immune more rapidly. Our hypothesis is that these children with frequent malaria episodes are caught in a vicious circle, whereby malaria episodes lead to impaired immunity to malaria, which in turn leads to further episodes of malaria. We will therefore investigate immune responses in children with different life histories of malaria episodes. We will also include a group of children living in similar environmental conditions but who are completely unexposed to malaria. Aims: Using RNAseq we will characterise the transcriptome of a group of children with frequent and febrile malaria or infrequent/asymptomatic. These data will be combined with cytokine profiling data (NIMR) and used to build predictive models (Exeter). The predictions will be validated against a similar second group. A single snap shot of immune responses may represent only the endpoint of many immune processes and may not reflect those that are causally related to differences in malaria outcome. Therefore, we will collect and store samples from a larger group of children who will then be followed up for over 3-4 years. This extended follow up will allow us to identify the same groups as described above, and then examine samples taken before the development of those outcomes. 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 EGAS00001002978

• The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas

  Tuberous sclerosis complex (TSC) is an autosomal dominantly inherited neurocutaneous disorder caused by inactivating mutations in TSC1 or TSC2, key regulators of the mechanistic target of rapamycin complex 1 (mTORC1) pathway. In the central nervous system TSC is characterized by cortical tubers, subependymal nodules and subependymal giant cell astrocytomas (SEGAs). SEGAs may lead to the impaired circulation of cerebrospinal fluid resulting in hydrocephalus and raised intracranial pressure in patients with TSC. Currently, surgical resection and mTORC1 inhibitors are the recommended treatment options for patients with SEGA. Here, we performed RNA-Seq and small RNA-Seq on SEGAs (n=19) and periventricular controls (n=8) to gain a better understanding of the underlying molecular basis of SEGAs, so that novel treatment targets could be identified.

  Study EGAS00001003787

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

• EGA synthetic data

  Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. Access to synthetic data studies is managed by the EGA Helpdesk Data Access Committee. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

  Documentation synthetic-data

• Integrative genomic profiling of hepatocellular adenomas reveals recurrent FRK activating mutations and mutational processes of malignant transformation

  Hepatocellular adenomas (HCA) are benign liver tumors predominantly developed in women using oral contraception. Here, exome sequencing identified novel recurrent somatic FRK mutations that induce constitutive kinase activity, STAT3 activation and cell proliferation sensitive to Src inhibitors. We also found new recurrent mutations activating JAK1, gp130 or ß-catenin. Chromosome copy-number and methylation profiling revealed patterns that correlated with specific gene mutations and tumor phenotypes. Finally, integrative analysis of HCA transformed to hepatocellular carcinoma revealed ß-catenin mutation as an early alteration and TERT promoter mutations as associated with the last step of the adenoma-carcinoma transition. In conclusion, we identified the genomic diversity in benign hepatocyte proliferation, new therapeutic targets and the key genomic determinants of the adenoma-carcinoma transformation sequence. Significance: Malignant transformation of benign adenoma into malignant carcinoma is frequently observed in several epithelial tumor types. Adenoma-carcinoma transition is crucial for the patient prognosis, however, little is known on the molecular mechanisms involved. Here, we performed an integrated genomic analysis of hepatocellular adenomas (HCA). Among several novel gene mutations, we identified recurrent somatic mutation activating FRK, a Src-like kinase. FRK activating mutations induce STAT3 activation and cell proliferation that can be targeted by Src inhibitors. Focusing on malignant transformation of HCA in hepatocellular carcinoma, we identified CTNNB1 and TERT promoter mutation as early and late genomic events involved in adenoma-carcinoma transition. In conclusion, we propose new therapeutic targets and an identification of adenomas with the highest risk of malignant transformation. Highlights: - FRK is activated by somatic recurrent mutations. - FRK mutants promote cell proliferation sensitive to src inhibitors. - CTNNB1 activation is an early event in HCA transformation. - TERT promoter mutations are associated with adenoma-carcinoma transition.

  Study EGAS00001000679

• Hereditary Cancer Diagnostics with I2HCP gene panel

  Germline blood DNA sequencing data generated in routine diagnostics of hereditary cancer using the I2HCP gene panel (~135 genes). There are 130 samples sequenced in a MiSeq machine and 108 sequenced in a HiSeq machine. There is a partial overlap between those two sets, meaning that some samples were sequenced in both machines. There is a strong enrichment in samples with copy-number variants (CNV), both single- and multi-exon, since this dataset was compiled for a benchmarking effort of CNV calling tools for genetic diagnostics.

  Dataset EGAD00001006171

• TONIC-Trial-cfDNA-Project

  Cell-free DNA (cfDNA) is an emerging technology to predict and monitor response to cancer treatment, including immune checkpoint blockade (ICB). However, data on cfDNA dynamics during ICB in metastatic triple negative breast cancer (mTNBC) are limited. While most applications of cfDNA involve assays that focus on mutation detection, mTNBC and multiple other cancer types are driven by copy number alterations (CNAs). We evaluate cfDNA-based copy number profile abnormality (CPA) score as a potential biomarker for monitoring ICB response in mTNBC, analyzing data from 87 patients enrolled in stage 1 and stage 2 of the TONIC-trial. We find significant concordance between cfDNA-based and tissue-based CNA profiles. Additionally, responders show a decrease in CPA scores upon ICB at week 6 (3 cycles of nivolumab). These findings underscore the potential of cfDNA-based CNA dynamics as a non-invasive biomarker for ICB early response assessment in patients with mTNBC.

  Study EGAS50000001308