3994 results for "*geneti*"

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• Shedding light over COVID-19 susceptibility and severity

  “One of the most remarkable features of SARS-CoV-2 infection is the variation in consequence ranging from asymptomatic to life-threatening” state the authors of the majestic Nature paper released in accelerated pre-view on July 2021. This variation in consequences represent not only an issue of burning medical relevance, but also a scientific and intellectual challenge for scientists around the globe. Researchers are known to be easily triggered by a challenge, and they recently demonstrated to be even better at double their efforts to focus on an urgent societal need. In this work led and coordinated by the COVID-19 Host Genetics Initiative (COVID-19 HGI), researchers gathered data from 49,562 cases and two million controls from 46 studies performed worldwide. The majority of the data has been deposited at the EGA, where 29 datasets have been collected under the study number EGAS00001005304. Data gathered from diverse sources conferred a huge robustness to the results. Genetic data from different ancestry origin were included in the analyses, even though data from patients with European origin was highly predominant (approx. 75%). Separated analysis of the different ancestries gave rise to relevant differences in the results, highlighting how important it is to take this aspect in consideration for future studies. Data from the individual studies was compiled into three categories according to COVID-19 severity for a meta-analysis: (a) critically ill cases (b) moderate or severe cases (c) all cases. They were paired with non-COVID-19-reported controls. All three analysis resulted in a total of 13 genetic loci associated with COVID-19 severity. Out of those, 9 loci associated specifically with critical illness, while 6 (a few overlapped) associated with moderated illness. Some genomic position matched previous findings. Interestingly, working with such an enormous amount of data allowed the depth to discriminate association with disease susceptibility vs severity, an issue of large medical relevance. Several loci mapped into biological relevant genes, like TYK2, PPP1R15A and FOXP4, previously implicated in immune response and/or lung functions. Researchers participating in the COVID-19 Host Genetics Initiative have worked in an unprecedented time-tight collaboration, prioritizing data sharing and collective results to tackle the pandemic affecting the world. The scientific community won’t miss any of the lessons to learn from this, and the EGA is ready to keep working to enable safe data sharing and fruitful collaborations.

  Blog covid-19-susceptibility-and-severity

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

• Providing access to COVID-19 data: one year later

  response efforts On 11 March 2020 the World Health Organization declared the novel coronavirus outbreak a global pandemic. Four months later, the European Genome-phenome Archive (EGA) released its first COVID-19 dataset. This dataset – single cell RNA and VDJ sequencing of B cells from 60 COVID-19 patients – showed that neutralizing antibodies could be identified by high-throughput sequencing in response to SARS-CoV-2 infection. That was one year ago. Today, the EGA provides access to fifteen COVID-19 datasets from researchers across seven countries in Asia, Europe, and North America. These studies represent almost 17,000 individuals and have resulted in at least sixteen publications and preprints. Researchers deposit controlled access COVID-19 data at EGA The global research community has come together rapidly to investigate the SARS-CoV-2 coronavirus and better understand the related disease, COVID-19. These research efforts generate valuable genetic and phenotypic data from patients and research participants that can be shared with approved researchers. The EGA enables sharing of this research data by providing a service for archiving and controlled distribution of sensitive data. Over the past year, the EGA has worked with researchers to archive and distribute COVID-19 data from high-throughput sequencing experiments, genotyping studies, and phenotypic information. These datasets investigate the immune system, blood, and cells and tissues of the lung, which are relevant for studying a contagious respiratory illness caused by a viral infection. *Study Spotlight. In January 2021, Ancestry.com demonstrated the utility of deep phenotyping based on self-reported outcomes from a large population of mild and asymptomatic COVID-19 cases. They identified genetic associations with eight COVID-19 phenotypes and showed distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. The supporting data is available at the EGA to approved researchers and includes both genotype and phenotype data for 15,000 individuals. EGA collaborates with global COVID-19 community Since the coronavirus outbreak, the EGA has collaborated with other life science resources to support discovery and access to COVID-19 datasets. COVID-19 Host Genetics Initiative. With the NHGRI’s Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) platform, the EGA enables sharing of individual-level genetic and phenotypic data from the COVID-19 Host Genetics Initiative (HGI). This initiative aims to generate, share, and analyze data from COVID-19 host genetics research projects to better understand the genetic determinants of COVID-19 susceptibility, severity, and outcomes. In response to COVID-19, the EGA actively supports COVID-19 data submissions and integration of data access and flow into the COVID-19-HGI analysis platform. *Study Spotlight. The COVID-19 HGI has combined individual-level data for 13,868 COVID-19 positive patients (N=7,167 hospitalized) from 17 cohorts in nine countries. The data were used to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. The genotype and phenotype data for 10 of these cohorts is available at the EGA to approved researchers under accession EGAS00001005304. Fig 1: EGA COVID-19 studies are searchable in the European COVID-19 Data Portal alongside other COVID-19 and SARS-CoV-2 public datasets. European COVID-19 Data Portal. EGA-archived COVID-19 data are discoverable via the European COVID-19 Data Portal (Fig. 1), which brings together public and controlled access data to accelerate coronavirus research for the international community. By indexing all COVID-19-related data in one place, researchers can more easily discover relevant datasets of interest, thus increasing the “FAIRness” (Findability, Accessibility, Interoperability, Reusability) of this valuable data. Fig 2: SARS-CoV-2 viral sequences are imported from ENA and analysed in Galaxy to detect variants. Results are accessible to researchers through the COVID-19 Viral Beacon. COVID-19 Viral Beacon. The COVID-19 Viral Beacon tool was developed in collaboration with the European Nucleotide Archive and Galaxy to enable near real-time browsing of SARS-CoV-2 variability at genomic, amino acid, and motif levels (Fig. 2). The COVID-19 Viral Beacon allows researchers to (i) perform detailed searches about genomic variants, (ii) filter queries and find unique cases, (iii) filter data based on strain-specific variants, and (iv) explore associated metadata. It uses the Global Alliance for Genomics and Health (GA4GH) Beacon standard including new Beacon v2 features. With this tool, researchers can study intra-host mutations on genomic regions of interest, or trace any variant frequency over time using raw read data. More than 200,000 SARS-CoV-2 analysed genomic data files are now available to researchers for further exploration. Ongoing COVID-19 efforts at EGA Addressing the COVID-19 pandemic is a global effort. Federated resources are necessary to support transnational deposition, access, and analysis of sensitive COVID-19 host genetics and other related data. At the same time, many countries now have emerging personalized medicine programmes which are generating data from national or regional healthcare initiatives. These data are subject to more stringent information governance than research data and often must comply with national data protection legislation. To address this need, the Federated EGA was established to serve as the primary global resource for discovery and access of sensitive human omics and associated data consented for secondary use. The Federated EGA will comprise a network of national human data repositories and will implement community standards and common interfaces. Launching Federated EGA promises to accelerate not only global research efforts to understand, diagnose, and treat COVID-19, but also to foster data reuse, enable reproducibility, and accelerate biomedical and disease research to ultimately improve human health.

  Blog providing-access-to-covid-19

• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

  Blog the-last-addition-to-the-list-of-clonal-evolution-studies-in-the-ega

• The Federated EGA network

  In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

  Blog the-federated-ega-network

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega

• 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

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• Solve-RD multi-omics data chud-faivre cohort

  The dataset includes short-read whole-genome sequencing (SR-WGS) data, SR-RNAseq data, OGM (Bionano) data, LR-WGS data, Epigenetics (RBSS) data and deep-WES data generated within the project Solve-RD from biosamples submitted by the group chud-faivre. The cohorts consists of 111 individuals recruited as part of Solve-RD cohorts 2-4 and aligns with ERN-ITHACA related disease entities (for a description of the Solve-RD cohorts see www.solve-rd.eu/fact-sheet-solve-rd-cohorts).

  Dataset EGAD00001015811

• Reduced platelet formation associated with serine metabolic dysregulation in integrin αIIbβ3-deficient megakaryocytes

  Glanzmann Thrombasthenia (GT) is characterized by absent platelet aggregation in response to all agonists except ristocetin and is caused by recessive inactivating variants in ITGA2B or ITGB3. While GT patients typically are described as having normal platelet counts, autosomal dominant activating variants in ITGA2B or ITGB3 cause macrothrombocytopenia. Interestingly, in our cohort of 16 GT patients, eight consistently exhibited platelet counts at the lower end of the normal range. We studied the role of integrin αIIbβ3 in platelet formation using megakaryocytes (MKs) derived from genetically modified immortalized megakaryocyte cell lines (imMKCLs), focusing on two modifications of ITGB3: ITGB3-/- (inactivating) and ITGB3WT/D673_E713del (activating). In static differentiation cultures, ITGB3-/- and ITGB3WT/D673_E713del imMKCLs exhibited normal MK differentiation but reduced proplatelet formation. Platelet production was also impaired in a 3D silk-based bone marrow system and in shaking cultures, confirming a quantitative role for ITGB3 in platelet production, independent of the type of variant. While TRAP-activated in vitro-generated platelets lacking αIIbβ3 failed to bind the activation-dependent PAC-1 antibody, ITGB3WT/D673_E713del platelets bound PAC-1 prior to activation mimicking the patient’s phenotype. Transcriptome profiling and metabolomic analyses ofintegrin αIIbβ3 deficient MKs revealed impaired serine metabolism and downregulation of SLC3A2 (CD98hc), an amino acid transporter chaperon known to interact with the β3 subunit. Flow cytometry confirmed decreased CD98hc in mutant MKs, while re-expression of wild-type ITGB3 in ITGB3-/- MKs restored αIIbβ3 and CD98hc expression, normalized proplatelet formation, and enhanced serine uptake. These results uncover a previously unrecognized role of integrin αIIbβ3 in coupling serine metabolism to platelet biogenesis.

  Study EGAS50000001711

• RNA sequencing of genetically modifed immortalized megakaryocytes

  The dataset contains bulk RNAseq samples from 7 ITGB3 mutants (3 with ITGB3 knock-out and 4 with an ITGB3 splice variant) compared to 4 wildtypes. The ITGB3 mutants and WT_1 and WT_2 are from the same batch; WT_3 and WT_4 are from another sequencing batch. The library was performed using the TruSeq Stranded Total RNA with Ribo-Zero H/M/R_Gold kit and the read length is 100 bp.

  Dataset EGAD50000002462

• VLAIO DenMark Project Data Access Committee

  The VLAIO DenMark Project Data Access Committee is responsible for reviewing and approving controlled-access requests for human genetic, immunological, omics, and associated phenotype data generated within the VLAIO O&O project HBC.2022.0988, titled “Use of multimodel omics technologies to study Dengue host response markers”. The project is a collaboration between Janssen Pharmaceutica NV, Universiteit Gent, and the Institute of Tropical Medicine Antwerp, covering dengue host-response data generated from human challenge, natural infection, and related biomarker studies. The DAC evaluates whether proposed data use is consistent with participant consent, applicable ethics approvals, data protection requirements, institutional policies, and the data access policy linked to the relevant EGA dataset. Access decisions should be made by the project representatives from Janssen, ITG, and UGent, including Ole Lagatie, Kevin Ariën, and Filip Van Nieuwerburgh. EGA will distribute controlled-access data only upon approval granted by this DAC.

  Dac EGAC50000001078

• Germline variants in patients with five cutaneous melanoma

  Skin melanoma arises from a complex interplay between UV radiation exposure and inherited genetic susceptibility. A subset of invidiuals experience multiple independent tumours, suggestingh a stronger underlying genetic component. In this study, we investigate the germline contribution to melanoma development in individuals diagnosed with five or more primary melanomas.

  Study EGAS50000001361

• RASA2 deletion rescues immune synapse dysfunction, enhancing CAR T cell efficacy against DMGs

  Methods: We compared the efficacy of B7-H3 CAR T-cells between SJ-DIPGX7c (DMG) and U87-MG (adult glioblastoma) patient-derived cell lines and showed impaired efficacy both in vitro and in vivo. We performed live-cell imaging and single-cell RNA sequencing to investigate deficiencies in immune synapse (IS) formation between CAR T-cells and DMGs. Lastly, we genetically deleted RASA2, a negative regulator of T cell activation, and evaluated the resulting impact on IS formation and quality, as well as in vitro and in vivo functionality. Sample preparation and sequencing For single cell RNA sequencing, two sets of co-culture arrays were prepared: (1) 2.5×106 Ctrl T cells were co-cultured with 2.5×106 tumor cells (SJ-DIPGX7c, SJ-DIPGX9c, SJ-DIPGX37c, D425, ST1, and U87-MG) and (2) 1×106 CAR T-cells were co-cultured with 4×106 tumor cells (SJ-DIPGX7c, SJ-DIPGX9c, SJ-DIPGX37c, D425, ST1, and U87-MG). Both co-culture arrays were incubated at 37°C 5% CO2 for 16 hours. Co-cultures were enzymatically digested with Accutase (Thermofisher; A1110501) for 10 min at room temperature, and cells were filtered by using Miltenyi dead cell removal kit (Miltenyi; 130-090-101). Highly viable cells were recovered and prepared using the Fixation Kit (PARSE Bioscience) according to manufacturer ‘s protocol. After fixation, the cell count was determined by using a Neubauer hemocytometer. A total of 1.14×105 cells from 12 coculture conditions were used, resulting in approximately 9.5×104 cells per condition. These cells were subjected to the Single Cell Whole Transcriptomic kit v2 (PARSE Bioscience) for library construction. Libraries were subsequently sequenced using the Illumina NovaSeq 6000 platform, generating paired-end 200 bp reads.

  Dataset EGAD50000002785

• Single-cell RNA sequencing of liver metastasis-derived colorectal cancer organoids profiling cellular heterogeneity and lineage dynamics across time

  The objective of this analysis was to identify, at single-cell resolution, trasncriptionally distinct subpopulations in untreated metastatic colorectal cancer organoids with diverse genetic backgrounds and to investigate their temporal dynamics.

  Study EGAS50000001927

• Exome sequencing of advanced hepatocellular carcinoma

  The aim of our project is to decipher the genomic of advanced hepatocellular carcinoma using whole exome sequencing. To this purpose, we aim to compare genetic landscape of advanced hepatocellular carcinoma with early tumor in order to understand the mechanisms of tumor progression. This work will also help to identify new therapeutic targets potentially useful to treat patients at advanced stage. This study contain whole exome sequencing aligned reads for 41 tumor with matched normal samples

  Study EGAS00001003130

• 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 EGAS00001003136

• Whole exome sequencing of small cell neuroendocrine cancer of the cervix

  In order to improve treatment selection for high grade neuroendocrine carcinomas of the cervix (NECC), we performed a comparative genomic analysis between this rare tumor type and other cervical cancer types, as well as extra-cervical neuroendocrine small cell carcinomas of the lung and bladder. We performed whole exome sequencing on fresh-frozen tissue from 15 NECCs and matched normal tissue. We then identified mutations and copy number variants using standard analysis pipelines. Published mutation tables from cervical cancers and extra-cervical small cell carcinomas were used for comparative analysis. Descriptive statistical methods were used and a two-sided threshold of P < .05 was used for significance. In the NECC cohort, we detected a median of 1.7 somatic mutations per megabase (range 1.0-20.9). PIK3CA p.E545K mutations were the most frequency observed oncogenic mutation (4/15 tumors, 27%). Activating MAPK pathway mutations in KRAS (p.G12D) and GNAS (p.R201C) co-occurred in two tumors (13%). In total we identified PI3-kinase or MAPK pathway activating mutations in 67% of NECC. When compared to NECC, lung and bladder small cell carcinomas exhibited a statistically significant higher rate of coding mutations (P < .001 for lung; P = .001 for bladder). Mutation of TP53 was uncommon in NECC (13%) and was more frequent in both lung (103 of 110 tumors [94%], P < .001) and bladder (18 of 19 tumors [95%], P < .001) small cell carcinoma. These comparative genomics data suggest that NECC may be genetically more similar to common cervical cancer subtypes than to extra-cervical small cell neuroendocrine carcinomas of the lung and bladder. These results may have implications for the selection of cytotoxic and targeted therapy regimens for this rare disease.

  Study EGAS00001003142

• Molecular profiling of EBV associated diffuse large B-cell lymphoma

  We describe distinct molecular mechanisms leading to recurrent activation of JAK-STAT signaling, perturbation of epigenetic regulators as well as other direct targetable alterations such as PD-L1 amplification and overexpression contributing to immune evasion of lymphoma cells. Using the LymphGen 2.0 classifier, we combine data of recurrent mutations, somatic copy number alterations, and structural variants in an integrative analysis . For the first time, we reveal that less than 20% of primary EBV+ DLBCLs can be attributed to established molecular clusters of DLBCL NOS emphasizing the unique molecular character of this disease.

  Study EGAS00001006400

• Cystic fibrosis multi-omics study

  Cystic fibrosis (CF) is a genetic disorder affecting approximately 1 in 2,500 people in the UK. Here, we generated a number of high-throughput sequence data sets for monocytes and neutrophils from CF patients and matched healthy volunteers (HV); including ChIP-Seq (H3K27Ac), chromatin accessibility (ATAC-Seq), and transcript/gene expression (RNA-Seq) data. Analysis of gene expression and epigenetic profiles demonstrates a robust innate immune gene expression profile that distinguishes CF and HV during periods of disease exacerbation. Upregulation of pathways responsible for the production of proinflammatory cytokines is described.

  Study EGAS00001006421

• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - WXS

  B-PLL is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003275

• Germline biallelic mutation affecting the transcription factor Helios causes pleiotropic defects of immunity

  We studied a patient with recurrent respiratory infections and hypogammaglobulinemia and identified a germline homozygous missense mutation in IKZF2 encoding Helios (p.Ile325Val). We show that HeliosI325V retains DNA-binding and dimerization properties, but loses interaction with several partners, including epigenetic remodelers HDAC1, HDAC3 and the ATAC complex. Single-cell RNA-sequencing of peripheral blood mononuclear cells revealed gene expression signatures indicative of a shift towards pro-inflammatory, effector-like status in the patient’s T cells. We observed an upregulation of the anti-inflammatory gene, TSC22D3, encoding the glucocorticoid-induced leucine zipper (GILZ), whose expression was reported to increase upon IL-2 deprivation. We validated this finding in primary T cells, where we observed a pronounced reduction in IL-2 production upon their stimulation, together with a defect in their ability to proliferate, rendering them more anergic. Collectively, we identify a novel germline-encoded inborn error of immunity and define a role for Helios in conventional T cells, whereby interactions with specific binding partners is necessary to mediate the transcriptional programs that enable T-cell homeostasis in health and disease.

  Study EGAS00001005675

• Multimodal Epigenetic Sequencing Analysis (MESA) of Cell-free DNA for Non-invasive Cancer Detection

  Multimodal characterization of cell-free DNA (cfDNA) in the blood can enable the sensitive and non-invasive detection of human cancers but remains technically challenging and costly. Here, we developed Multimodal Epigenetic Sequencing Analysis (MESA), a flexible and sensitive method of capturing and integrating multimodal epigenetic information of cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq (EM-seq) and TET-assisted pyridine borane sequencing (TAPS). MESA can simultaneously infer cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and fragmentation profile for regions surrounding the promoters and polyadenylation sites (PASs). MESA’s integrated analysis of multimodal epigenetic features significantly improved the performance of cancer detection models compared to the usage of any single modality alone. MESA captures additional and highly complementary epigenetic information from cfDNA without additional experimental assays, highlighting the importance and clinical prospect of using multimodal epigenetic features for non-invasive cancer detection

  Study EGAS00001006462

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• Multi-organ landscape of therapy-resistant melanoma

  Metastasis and failure of present-day therapies represent the most common causes of mortality in patients with cutaneous melanoma. To identify the underlying genetic and transcriptomic landscapes, here we analyzed multi-organ metastases and tumor-adjacent tissues from eleven rapid autopsies after treatment with MAPK inhibitor (MAPKi) and/or immune checkpoint blockade (ICB) and death due to acquired resistance. Either treatment elicits shared genetic alterations that suggest immune-evasive, cross-therapy resistance mechanisms. Large, non-clustered deletions, inversions, and inter-chromosomal translocations dominate rearrangements. Using 345 therapy-naïve TCGA melanoma and 131 patient-matched melanoma pre-and-post acquired resistance to only either treatment, we performed cross-cohort analyses to identify MAPKi and ICB as respective contributors to gene amplifications and deletions enriched in autopsy versus therapy-naïve tumors. Private/late mutations and structural variants display shifted mutational and rearrangement signatures, with MAPKi specifically selecting for signatures of defective homologous-recombination, mismatch, and base-excision repair. Transcriptomic signatures and cross-talks with tumor-adjacent macroenvironments nominate organ-specific adaptive pathways. An immune-desert, CD8+-macrophage-biased archetype, T-cell exhaustion, and type-2 immunity characterize the immune contexture. This multi-organ analysis of lethal, therapy-resistant melanoma presents preliminary insights with potential to improve therapeutic strategies.

  Study EGAS00001006644