Search Results - EGA European Genome-phenome Archive

CLL Genome

The Chronic Lymphocytic Leukemia (CLL) Genome Project aims to identify genetic alterations involved in the development and progression of the CLL, which are still unknown, with the objective of generating a comprehensive catalogue of genetic alterations in 500 independent tumours. The CLL Genome Project, as a contributing member of the International Cancer Genome Consortium (ICGC), has the purposes of creating diagnostic tools, discovering therapeutic targets and developing new strategies that will allow a customized therapy for CLL in order to make it more precise and effective. This study consists of two datasets. EGAD00001000023 described in the Nature paper (2011), Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia, and the dataset EGA00001000044 & & EGAD00001000083 described in the Nature (2011) paper, Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia.Additional data generated within the ICGC-CLL genome project can be found in studies EGAS00001000374 and EGAS00001001306

Study EGAS00000000092

Clonal fitness inferred from timeseries modeling of single cell cancer genomes

Progress in defining genomic fitness landscapes in cancer by copy number alterations (CNA) has been impeded by lack of single cell and timeseries sampling. We generated 42,000 single cell whole genomes (scWGS) from breast epithelium and primary triple negative breast cancer (TNBC) patient-derived xenografts (PDX) collected during multi-year time series. Using a Wright-Fisher population genetics model, we inferred reproducible CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy, with accurate forecasting of experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDX resulted in cisplatin resistant clones that had shown low fitness in the untreated setting. By contrast high fitness clones from treatment naive controls were eradicated reflecting an inversion of the fitness landscape. Upon drug release selective pressure dynamics were reversed indicating a fitness cost of treatment resistance. Taken together, our findings reveal clonal fitness dynamics linked to CNA and therapeutic resistance in polyclonal tumours.

Study EGAS00001004448

Genetic landscape of pediatric Infant Acute Lymphoblastic leukemia

We performed whole genome sequencing of tumor and normal DNA samples obtained from 22 infant ALL cases with MLL rearrangements. In addition, we sequenced 2 paired diagnostic-relapse samples. Using complementary pipelines, somatically acquired genetic changes were analyzed, including single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes. In addition, exome sequencing was performed on paired diagnostic and normal DNA samples obtained from 20 cases of non-infant MLL rearranged leukemias and somatic mutations in the coding regions were identified.

Study EGAS00001000246

Submission 208 - study_title 1

Submission 208 - description 1

Study EGAS50000000321

Contribution of allelic imbalance to colorectal cancer

Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge, and unbiased CRISPR-Cas9 knockout and activation screens identified altogether 79 genes within AI peaks regulating cell growth. Genetic and functional data implicates loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

Study EGAS00001002966

The genomic landscape of lung adenocarcinoma in East Asians

We performed exome sequencing of 210 and transcriptome sequencing of 181 LUADs of Chinese patients. For more details, please see publication "Genomic landscape of lung adenocarcinoma in East Asians" by Chen J. et. al. in Nature Genetics 2020. https://www.nature.com/articles/s41588-019-0569-6.

Study EGAS00001002941

Leukemia stem cell containing fractions

Study EGAS00001004893

Acute Myeloid Leukemia peripheral blood samples

Study EGAS00001004896

Accessibility Over Transposable Elements Reveals Genetic Determinants of Stemness Properties in Normal and Leukemic Hematopoiesis

Study EGAS00001007191

Mapping_gene_environment_interactions_in_macrophages

Immune cells sense and respond to external stimuli such as pathogens and initiate an inflammatory response. Genetic variants altering the behaviour and responses of immune cells may inform the results of disease association studies and provide an insight into the regulation of immune response. Studies mapping quantitative trait loci (QTL) are usually performed in quiescent or naïve cells and therefore any variants with a condition-specific manner (e.g. those with an effect only detectable in a specific time-point after cell stimulation) are likely to remain undiscovered. So far, only a handful of studies have attempted to study QTL in multiple states and even on those studies the number of states has remained relatively low (<5). Only very recently Horst and colleagues published the largest study to date investigating the effect of host variable (e.g. age, sex, contraceptive use etc.) on protein levels in macrophages stimulated with 19 different conditions (Horst et al, 2016). This project aims to develop a high-throughput experimental platform to detect QTL in a large number of states using iPSC derived macrophages. 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 EGAS00001002268

Rna-Seq Leiomyosarcoma subtypes

Leiomyosarcomas (LMS) are genetically heterogeneous tumors differentiating along smooth muscle lines. Currently, LMS treatment is not informed by molecular subtyping and is associated with highly variable survival. While disease site continues to dictate clinical management, the contribution of genetic factors to LMS subtype, origins, and timing are unknown. Here we analyzed 70 genomes and 130 transcriptomes of LMS, including multiple tumor regions and paired metastases. Molecular profiling highlighted the extremely early origins of LMS. Three specific subtypes of LMS develop from distinct lineages of smooth muscle cells. Of these, dedifferentiated LMS with high immune infiltration and tumors primarily of gynaecological origin acquired the highest burden of genomic mutation and are associated with worse survival. Homologous recombination defects lead to genome-wide mutational signatures, and a corresponding sensitivity to PARP and other DNA damage response inhibitors, suggesting a novel therapeutic strategy for LMS. Finally, by phylogenetic reconstruction, we present evidence that clones seeding lethal metastases arise decades prior to LMS diagnosis.

Study EGAS00001004783

The Genetic History of Greenlandic-European contact

The Inuit ancestors of the Greenlandic people arrived in Greenland close to 1000 years ago. Since then, Europeans from many different countries have been present in Greenland. Consequently, the present-day Greenlandic population has ~25% of its genetic ancestry from Europe. In this study, we investigated to what extent different European countries have contributed to this genetic ancestry.

Study EGAS00001004933

Genetic regulation of gene expression in human brain cell types

We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

Study EGAS00001006345

Prostate cancer ancestral genomic disparity

Prostate cancer is characterised by significant global disparity; mortality rates in SubSaharan Africa are double to quadruple those in Eurasia. Hypothesising unknown interplay between genetic and non-genetic factors, tumour genome profiling envisages contributing mutational processes. Through whole-genome sequencing of treatment-naïve prostate cancer from 183 ethnically/globally distinct patients (African versus European), we generate the largest cancer genomics resource for Sub-Saharan Africa. Identifying ~2 million somatic variants, Africans carried the greatest burden. We describe a new molecular taxonomy using all mutational types and ethno39 geographic identifiers, including Asian. Defined as Global Mutational Subtypes (GMS) A–D, although Africans presented within all subtypes, we found GMS-B to be ‘African-specific’ and GMS-D ‘African-predominant’, including Admixed and European Africans. Conversely, Europeans from Australia, Africa and Brazil predominated within ‘mutationally-quiet’ and ethnically/globally ‘universal’ GMS-A, while European Australians shared a higher mutational burden with Africans in GMS45 C. GMS predicts clinical outcomes; reconstructing cancer timelines suggests four evolutionary trajectories with different mutation rates (GMS-A, low 0.968/year versus D, highest 1.315/year). Our data suggest both common genetic factors across extant populations and regional environmental factors contributing to carcinogenesis, analogous to gene-environment interaction defined here as a different effect of an environmental surrounding in persons with different ancestries or vice versa. We anticipate GMS acting as a proxy to intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

Study EGAS00001006425

DNA methylation atlas of normal human cell types

DNA methylation is a fundamental epigenetic mark that governs chromatin organization, cell identity, and gene expression. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell-type are >99.5% identical, demonstrating robustness of cell identity programs to genetic variation and environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny, and identifies methylation patterns retained since gastrulation. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hyper-methylated loci are rare and are enriched for CpG islands, polycomb targets, and CTCF binding sites, suggesting a novel role in shaping cell type-specific chromatin looping. The atlas provides an essential resource for interpretation of disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

Study EGAS00001006791

Epigenetic reprogramming shapes monocytes and heterologous T cell derived cytokine responses in BCG vaccination

Study EGAS00001007498

UCSF Pediatric Bithalamic Glioma Genome Project

Brain tumors are the most common solid tumors of childhood, and the genetic drivers and optimal therapeutic strategies for many of the different subtypes remain unknown. We performed targeted next-generation sequencing of approximately 500 cancer-associated genes on a cohort of 13 pediatric bithalamic diffuse gliomas, a lethal brain tumor of childhood for which the genetic basis is largely unknown. We identified that bithalamic diffuse gliomas harbor frequent mutations in the EGFR oncogene in the absence of accompanying gene amplification and only rare histone H3 mutation. These EGFR mutations were either small in-frame insertions within exon 20 (intracellular tyrosine kinase domain) or missense mutations within exon 7 (extracellular ligand-binding domain). Accompanying alterations included frequent TP53 mutation, CDK6 amplification or CDKN2C mutation, and BCOR and BCORL1 mutation or deletion.

Study EGAS00001004033

Whole exome and transcriptome sequencing of biliary tract cancer

To uncover the full repertoire of genetic and transcriptomic landscape of biliary tract cancer (BTC), we molecularly characterized BTC based on genetic and transcriptomic alteration profiles.

Study EGAS00001000950

Genome-wide Ancestry and Demographic History of African-Descendant Maroon Communities from French Guiana and Surname.

The transatlantic slave trade (TAST) was the largest forced migration in world history. However, the origins of the enslaved Africans and their admixture dynamics remain unclear. To investigate the demographic history of African-descendant Marron populations, we generated genome-wide SNP data (4.3 million markers) from 107 individuals from three African-descendant populations in South America, as well as 124 individuals from six west African populations to complement underrepresented African data sets. Our study sheds additional light on the demographic consequences of the TAST and illustrates how genetic data can complement historical sources.

Study EGAS00001002535

Genomic landscape of oral cancers (Illumina RNA-Seq)

Human papillomavirus (HPV) is a necessary but insufficient cause of a subset of oral squamous cell carcinomas (OSCC) that is increasing markedly in frequency. To identify contributory, secondary genetic alterations in these cancers, we used comprehensive genomics methods to compare 149 HPV-positive and 335 HPV-negative OSCC tumor/normal pairs. Different behavioral risk factors underlying the two OSCC types were reflected in distinctive genomic mutational signatures. In HPV-positive OSCC, the signatures of APOBEC cytosine deaminase editing, associated with anti-viral immunity, were strongly linked to overall mutational burden. By contrast, in HPV-negative OSCC, T>C substitutions in the sequence context 5’-ATN-3’ correlated with tobacco exposure. Universal expression of HPV E6*1 and E7 oncogenes was a sine qua non of HPV-positive OSCC. Significant enrichment of somatic mutations was confirmed or newly identified in PIK3CA, KMT2D, FGFR3, FBXW7, DDX3X, PTEN, TRAF3, RB1, CYLD, RIPK4, ZNF750, EP300, CASZ1, TAF5, RBL1, IFNGR1 and NFKBIA. Of these, many affect host pathways already targeted by HPV oncoproteins, including the p53 and pRB pathways, or disrupt host defenses against viral infections, including interferon and nuclear factor-B signaling. Frequent copy number changes were associated with concordant changes in gene expression. Chr. 11q (including CCND1) and 14q (including DICER1 and AKT1) were recurrently lost in HPV-positive OSCC, in contrast to their gains in HPV-negative OSCC. High-ranking variant allele fractions implicated ZNF750, PIK3CA and EP300 mutations as candidate driver events in HPV-positive cancers. We conclude that virus-host interactions cooperatively shape the unique genetic features of these cancers, distinguishing them from their HPV-negative counterparts.

Study EGAS00001003237

Malignant mesothelioma EWAS on European prospective study

Study EGAS00001006432

After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

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The EGA at the International Congress of Human Genetics

Today is the start of the International Congress of Human Genetics (ICHG). This event, hosted by the African Society of Human Genetics (AfSHG) and the Southern African Society for Human Genetics (SASHG), will reunite international experts to highlight how genomic technologies are being managed to address challenges generated by the current status of Human Health and Genomics. The European Genome-phenome Archive (EGA) will be at the Congress participating in workshops, meetings and talks where topics such as data access and discovery as well as the Federated EGA will be present. Data access and discovery In the context of the “Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. Data access and discovery In the context of the “ Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. During the last four years, CINECA has been identifying gaps in data sharing between Africa, Canada and Europe in order to build a federated solution for data access. Thomas Keane will present the project within the sessions happening the 24ᵗʰ. The Federated EGA at the ICHG A Federated EGA poster will be shown during the Poster Session 1 that will take place the 23ʳᵈ. The objective is to bring awareness of the European Genome-phenome Archive as a resource for permanent archive and secure data sharing. In this context, the network generated by the Federated EGA is key for cases where research data cannot be shared outside local jurisdictions. The Federated EGA was officially launched on 2022 with research institutes from five countries becoming the first nodes of this network. Nowadays, with more than 20 nodes preparing to join, it aims to become the largest human omics data sharing initiative towards understanding human health and disease. The H3Africa Initiative and the African research represented in the EGA 1.1% of the EGA studies include samples from African populations. Countries such as South Africa, Kenya, Uganda or Egypt, among others, are present in the 72.577 samples from African individuals archived at the EGA. 23 EGA datasets are managed by the Human Heredity and Health in Africa Initiative (H3Africa). This Initiative will celebrate its Consortium Meeting the 27ᵗʰ and 28ᵗʰ, back-to-back with the ICHG. H3ABioNet, the Pan African Bioinformatics Network for the H3Africa consortium, will also take this context to celebrate its 10-Year Symposium during the Congress. Members of the EGA team will attend both of them, as the H3ABioNet works in conjunction with H3Africa projects, to submit data to the European Genome-Phenome Archive.

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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.

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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.

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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.

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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!

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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.

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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

Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___single_cell_RNA_sequencing

This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

Study EGAS00001003519

ATAC-seq/ChIP part

Epigenetics: ATAC-seq and ChIP-seq data

Study EGAS00001006520

Molecular heterogeneity and commonalities in pancreatic cancer precursors with gastric and intestinal phenotype

Due to the limited number of modifiable risk factors, secondary prevention strategies based on early diagnosis represent the preferred route to improve the prognosis of pancreatic ductal adenocarcinoma (PDAC). Here, we provide a comparative morphogenetic analysis of PDAC precursors aiming at dissecting the process of carcinogenesis and tackling the heterogeneity of preinvasive lesions.

Study EGAS00001006793

Transcriptomic and epigentic analysis of human peripheral blood NK cell subsets revealing role of Bcl11b in differentiation

Transcriptomic analysis of seven human peripheral blood NK cell subsets and three T cell subsets purified from healthy cytomeglovirus seropositive donors. Epigenetic analysis including identification of open chromatin and active enhancer elements confirms key regulatory factors defining an NK cell differentiation axis. Chromatin-immunoprecipitation sequencing reveals contribution of key transcription factors associated with NK cell differentiation including Bcl11b.

Study EGAS00001005025

BLUEPRINT Hematopoietic Stem/Progenitor Cell Methylomes

Study EGAS00001002070

RNA-seq of Liver Cancer

The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

Study EGAS00001002879

Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

Study EGAS00001003063

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

Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

Study EGAS00001004289

Genetic and evolutionary patterns of treatment resistance in relapsed B-cell lymphoma

Study EGAS00001004469

Targeting AXL Kinase Uniquely Sensitizes Therapy-Insensitive Leukemic Stem and Progenitor Cells to Venetoclax Treatment in Acute Myeloid Leukemia

The abundance of genetic abnormalities and phenotypic heterogeneities in AML pose significant challenges to developing improved treatments. Here we demonstrated that a key GAS6/AXL axis is highly activated in AML patient cells, particularly in leukemic stem cells. We developed a potent, selective AXL inhibitor that has excellent pharmaceutical properties and efficacy against preclinical patient-derived xenotransplantation models of AML. Importantly, inhibition of AXL sensitized AML stem/progenitor cells to venetoclax treatment, with strong synergistic effects in vitro and in vivo. Mechanistically, single-cell RNA-sequencing and functional validation studies uncovered that AXL inhibition or in combination with venetoclax potentially targets intrinsic metabolic vulnerabilities of AML stem/progenitor cells, which shows a distinct transcriptomic profile and inhibits mitochondrial oxidative phosphorylation. These findings have direct translational impact on the treatment of AML and other cancers with high AXL activity.

Study EGAS00001004663

BLUEPRINT ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

Study EGAS00001000326

Whole Genome Sequencing of HCC

The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

Study EGAS00001002888

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

Genomic analyses promise to improve tumor characterization in order to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors revealed mutational signatures associated with specific risk factors, mainly combined alcohol/tobacco consumption, aflatoxin B1 and HBV infection. We identified 161 putative driver genes associated with 11 recurrent pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (HBV) and AXIN1. Analyses according to tumor stage progression revealed TERT promoter mutation as an early event whereas FGF/CCND1 amplification, TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 24% of the tumors, we identified genetic alterations potentially targetable by FDA-approved drugs. In conclusion, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.

Study EGAS00001001002

De novo assembly of 150 Danish genomes reveals rich structural complexity

Most known genetic variation in human genomes has been called from comparison of short reads to the reference genome, an approach biased against finding complex variation. We sequenced 150 individuals from 50 parent-offspring trios with multiple insert-size libraries to very high coverage. We show that each genome could be independently de novo assembled into a small number of high-quality scaffolds (median N50 > 21 Mb), each of quality comparable to long read assemblies while being very cost-effective. We show that our variant call set from comparing de novo assemblies is far more complete in terms of complex variation than previous studies. Importantly, even the complex 4-5 Mb extended MHC region was assembled and resolved into haplotypes, revealing >700kb novel sequence in this important region of the genome, and major parts of the Y chromosome including some palindromes were assembled with high accuracy. Finally, we show that our variant call-set allows for the genotyping of many more complex variants when used as a reference-panel for imputation into SNP-chip data or into previously resequenced genomes.

Study EGAS00001002108

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma

Diffuse large B cell lymphoma (DLBCL) is the most common hematologic malignancy and is characterized by a striking degree of heterogeneity. We enrolled a total of 1001 DLBCL patients and comprehensively defined the landscape of genetic mutations, copy number alterations and expression through whole-exome and transcriptome sequencing. We identified 150 genetic drivers of DLBCL including many novel, clinically relevant genes (e.g. SPEN, SETD1B and KLHL14). Genetic drivers were highly enriched among essential genes identified by CRISPR screening in DLBCL cell lines including those of immediate potential therapeutic relevance such as MTOR, SYK, SF3B1 and XPO1. RHOA emerged as a critical driver gene from our genetic analysis and CRISPR screen; we further delineated its functional role in vitro and in vivo models to define its role as an essential oncogene in DLBCL. Our work thus identifies the functional landscape of genetic drivers and their clinical and therapeutic relevance in DLBCL patients.

Study EGAS00001002606

Summary statistics from genome-wide association study in glioma of 12,488 cases and 18,169 controls.

Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,488 cases and 18,169 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10-9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10-10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10-11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10-10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10-9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10-10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10-10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10-9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10-10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10-11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10-9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.

Study EGAS00001003372

Targeted sequencing of follicular lymphoma tumour samples from the UK's Haematological Malignancy Research Network

Follicular lymphoma displays morphological and clinical heterogeneity, underpinned by shared molecular pathogenesis. Mutations in epigenetic regulators alongside t(14;18) have been identified as disease initiating events. Additional mutational diversity suggests disease heterogeneity. Whether this resolves into mechanistically distinct subsets remains an open question. Targeted sequencing was applied to an unselected population-based FL cohort (n=548) diagnosed in a catchment population of ~4 million (14 centers), with full clinical follow-up (n=538) that included 96 DLBCL transformations. We investigated whether molecular subclusters of FL can be identified, and whether mutational data provide predictive information relating to transformation.

Study EGAS00001005238

Multimodal single-cell and bulk glioma analyses

Glioma intratumoral heterogeneity enables adaptation to challenging microenvironments and contributes to therapeutic resistance. We integrated 914 single-cell DNA methylomes, 55,284 single-cell transcriptomes, and bulk multi-omic profiles across 11 adult IDH-mutant or IDH-wild-type gliomas to delineate sources of intratumoral heterogeneity. We show that local DNA methylation disorder associates with cell-to-cell DNA methylation differences, is elevated in more aggressive tumors, links with transcriptional disruption, and is altered in environmental stress response. Glioma cells under in vitro hypoxic and irradiation stress increased local DNA methylation disorder and shifted cell states. We identified a positive association between genetic and epigenetic instability that was supported in bulk longitudinally collected DNA methylation data. Increased DNA methylation disorder associated with accelerated disease progression, and recurrently selected DNA methylation changes were enriched for environmental stress response pathways. Our work identifies an epigenetically facilitated adaptive stress response process and highlights the importance of epigenetic heterogeneity in shaping therapeutic outcomes.

Study EGAS00001005300

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