Search Results - EGA European Genome-Phenome Archive

IDH-wildtype untreated human glioblastoma samples (GB-UK cohort), published in Noorani & Haughey et al 2025.

Extrachromosomal DNA (ecDNA) oncogene amplification is associated with treatment resistance and shorter survival in cancer. Currently, the spatial dynamics of ecDNA, and their evolutionary impact, are poorly understood. Here, we investigate the spatiotemporal evolution of ecDNA by integrating computational modeling with samples from 94 treatment-naive human IDH wild-type glioblastoma patients. Random ecDNA segregation combined with ecDNA-conferred fitness advantages induce distinct spatial ecDNA copy number patterns which depend on ecDNA oncogenic makeup. EGFR-ecDNAs often reach high copy numbers and confer strong fitness advantages. In contrast, PDGFRA-ecDNAs reach lower copy numbers and confer weaker fitness advantages. EGFR structural variants occur exclusively on ecDNA, arise from and are intermixed with wild-type EGFR-ecDNAs. Computational modeling suggests wild-type and variant EGFR-ecDNAs often accumulate before clonal expansion. Using a genetically engineered mouse model, we confirm that the accumulation of oncogenic ecDNA prior to clonal expansion under strong positive selection is observable both in vivo and in vitro in mouse neural stem cells. Intermixed wild-type and variant ecDNAs remain prevalent at diagnosis, as less fit wild-type ecDNAs hitchhike on strongly selected variant EGFR-ecDNAs. A dN/dS analysis in the Genomics England cohort further suggests positive selection of variants on EGFR-ecDNAs but not PDGFRA-ecDNAs in glioblastoma. Overall, our results suggest ecDNA oncogenic makeup determines unique evolutionary trajectories in glioblastoma. New concepts like ecDNA tumor clonality, ecDNA heteroplasmy and multi-species ecDNAs require a refined evolutionary interpretation of genomic data in a large subset of glioblastoma patients and likely other solid cancers.

Study EGAS00001008126

Paediatric Hepatic International Tumour Trial (JPLT2: PHITT)

Hepatoblastoma (HBL) is the most common primary liver tumor in children. Despite their diversity in histopathological phenotype and clinical outcome, the underlying molecular aberrations have not been fully understood. Here we describe a comprehensive landscape of genomic, epigenomic, and transcriptomic heterogeneity among the 163 cases of HBLs and transitional liver cell tumors (TLCTs) collected in the multicenter clinical trial JPLT-2. The total numbers of mutational events in HBLs are very few (0.52 SNVs/Mb on exonic regions) but show a positive correlation with the age of onset. While dysregulation of Wnt-pathway related genes was observed (somatic deletion or mutations of CTNNB1 and germline or somatic mutations of APC) in 83.6% of the HBL cases, TERT promoter mutations are mainly in the elderly HBLs (> 8 years old), meeting with the proposed criteria of TLCT. These TLCT cases are clustered in the hypermethylated epigenotype in promoter and enhancer regions. Copy number analyses also revealed recurrent 11p15.5 UPD/LOHs including the IGF2/H19 region (31.6%), focal deletions in 4q35 (15.8%) and focal amplifications in 2q24.3 (7.0%) predominantly in the child and infant HBLs. Motif enrichment analysis of the specific hypomethylated enhancers in these HBL subtypes suggests specific binding of ASCL2, the regulatory transcription factor for definitive endoderm and digestive systems. Transcriptome and histochemical analysis revealed that ASCL2 is upregulated not in HCC and TLCT but in child and infant HBL, suggesting their ?cell of origin? derived from the premature hepatoblast with high proliferative potential such as intestinal epithelial cells. Systematic molecular profiling of HBL will provide a fundamental understanding of hepatoblast carcinogenesis and clues for risk stratification.

Study JGAS000236

Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

Early-generation TRK tyrosine kinase inhibitors (TKIs) approved for treating NTRK fusion–positive (NTRK+) solid tumors provide clinical benefit; however, resistance emerges. Repotrectinib is a next-generation ROS1/TRK TKI with a compact macrocyclic structure designed to improve durability of response. TRIDENT-1 is a registrational phase 1/2 trial assessing repotrectinib, a next-generation ROS1/TRK TKI, in adults with advanced solid tumors, including NTRK+ disease. The primary endpoint was confirmed objective response; secondary endpoints included duration of response (DOR), progression-free survival (PFS), overall survival and safety. Median follow-up ranged between 21.3 months and 25.7 months. In the TKI-naive cohort (n = 51; 95% confidence interval (CI)), the response rate was 59% (44–72); the median DOR was not estimable (NE); and the median PFS was 30.3 months (9.0–NE). In the TKI-pretreated cohort (n = 69; 95% CI), the response rate was 48% (36–60); the median DOR was 9.8 months (7.4–13.0); and the median PFS was 7.4 months (3.9–9.7). Of 30 TKI-pretreated patients with NTRK solvent front mutations, 16 had a response (53%; 95% CI: 34–72). Intracranial responses were observed in two of three TKI-naive patients and in four of six TKI-pretreated patients with measurable intracranial disease at baseline. Among all treated patients (n = 565), the most common any-grade treatment-related adverse event (TRAE) was dizziness (57%); most TRAEs were low grade; and 4% discontinued repotrectinib due to a TRAE. Overall, repotrectinib demonstrated durable systemic and intracranial responses with generally low-grade adverse events in patients with NTRK+ solid tumors, including those with previous TRK TKI treatment and solvent front mutations. These results support the use repotrectinib to treat patients with NTRK+ solid tumors. ClinicalTrials.gov identifier: NCT03093116 .

Study EGAS50000001572

How to use the EGA search box

Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

Documentation discovery/metadata/search-box

EGA account management

How to manage your EGA account Welcome to the documentation page for creating an EGA user. The European Genome-Phenome Archive (EGA) is a platform for archiving, managing, and sharing human genomic and phenotypic data. To submit, access, and manage requests for the data hosted on the EGA platform, users are required to register for an account. This documentation page provides step-by-step instructions for creating an EGA user account, as well as information on the different types of EGA user accounts and their associated privileges. You can check the EGA data flow for a better understanding. Manage EGA account step-by-step guide Contact Information Public Keys Password Authenticator Federated Identity Sessions Request an EGA account step-by-step guide Fill in this form.You cannot use a generic email account (e.g., Gmail). Make sure you use your institutional email account.Your email is by default your username.The criteria for a strong password is: It should contain between 8 and 32 charactersIt should contain at least one uppercase letterIt should contain at least one numberIt should contain at least one special characterYou will need to wait for the Helpdesk team to check your identity. Please allow two business days for this step.After the Helpdesk validation step, you will receive an email with a link to validate your institutional email.Click the link to verify your email. It will redirect you to the EGA website.As soon as your account has been validated, you will be able to start adding more information to your EGA profile. For that, you first need to log in using your credentials from step 1. Manage EGA account step-by-step guide As a logged-in user, go to your profile by clicking on Welcome > My Profile. To modify it, click the Edit button.You will see the following options: Contact Information In this section, you can modify the personal information of your EGA account. Public Keys Adding a public key is necessary for downloading data via Live Outbox distribution. If you don’t know how to generate your key, you can follow the instructions available on How do I create a key? Password In the Password tab, you can change your password anytime to ensure the security of your account. However, if you receive an email notifying you that your password was modified and you did not initiate the change, it could be a sign that your account has been compromised. In this case, you should immediately contact our Helpdesk team to report the issue and receive assistance in restoring your account security. Authenticator You can set your two-factor authentication (2FA) system for your EGA account as an identity and access management security method that requires two forms of identification to access resources and data. To obtain your code, please follow the instructions below, also available in the Authenticator tab in your profile. Sessions The Sessions tab displays a list of all devices where you are currently logged in as an EGA user. This includes any open sessions you have on your computer, phone, or other devices. By reviewing the list of active sessions, you can monitor the devices that have access to your account and ensure that there are no unauthorised logins. If you notice any suspicious activity, you can close the sessions from this page to immediately terminate access to your account from the unauthorised device.

Documentation how-to-manage-your-account

Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

Glioblastoma multiforme (GBM) is a lethal brain tumour in adults and children. However, DNA copy number and gene expression signatures indicate differences between adult and paediatric cases. To explore the genetic events underlying this distinction, we sequenced the exomes of 48 paediatric GBM samples. Somatic mutations in the H3.3-ATRX-DAXX chromatin remodelling pathway were identified in 44% of tumours (21/48). Recurrent mutations in H3F3A, which encodes the replication-independent histone 3 variant H3.3, were observed in 31% of tumours, and led to amino acid substitutions at two critical positions within the histone tail (K27M, G34R/G34V) involved in key regulatory post-translational modifications. Mutations in ATRX (alpha-thalassaemia/mental retardation syndrome X-linked) and DAXX (death-domain associated protein), encoding two subunits of a chromatin remodelling complex required for H3.3 incorporation at pericentric heterochromatin and telomeres, were identified in 31% of samples overall, and in 100% of tumours harbouring a G34R or G34V H3.3 mutation. Somatic TP53 mutations were identified in 54% of all cases, and in 86% of samples with H3F3A and/or ATRX mutations. Screening of a large cohort of gliomas of various grades and histologies (n=784) showed H3F3A mutations to be specific to GBM and highly prevalent in children and young adults. Furthermore, the presence of H3F3A/ATRX-DAXX/TP53 mutations was strongly associated with alternative lengthening of telomeres and specific gene expression profiles. This is, to our knowledge, the first report to highlight recurrent mutations in a regulatory histone in humans, and our data suggest that defects of the chromatin architecture underlie paediatric and young adult GBM pathogenesis.

Study EGAS00001000226

Out with the Java, in with the Python - new EGA data download client unveiled

We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

Blog new-ega-data-download-client

New set of services for all users unveiled at the EGA

The European Genome-phenome Archive (EGA) releases today a brand-new website as well as a set of improved services for users, comprising a revamped Submitter Portal with an improved API and data brokering functionality for submitters, as well as a new DAC Portal for Data Access Committee members to easily manage data access requests. The EGA team has been working hard over the past months on these improvements that will provide a better experience for the users. Discover them below! Visit our new EGA website and check the new functionalities and updated guides Our new website is live, with a fresh look and updated features to discover all the novelties. The homepage now includes three pathways to guide our users, depending on whether they want to deposit, download or manage data within the Archive. One of the most outstanding developments is the introduction of a streamlined process for requesting access to data: EGA Users can now directly request access to their preferred datasets through the website using their EGA accounts. Additionally, users can customise their profile, oversee active sessions, and manage the public keys, essential for our latest array of services, alongside a range of other features. Another major change is our new Help Desk contact method: a built-in website form tailored for user inquiries. This system, called "Need Help?", can be easily located on the top right-hand side of the website. It will encompass both EGA and Federated EGA node users' requests. We will detail its use soon, so stay tuned. Register your metadata to the EGA easily with our new Submitter Portal The new Submitter Portal makes the submission process quicker and more intuitive. The process is currently divided into sections that the user will know beforehand by taking the tour that the EGA team has created to guide users through the Portal before starting the first submission. Do not complete your data submissions alone! Our Submitter Portal now includes a collaboration mode so that every submission can be completed by authorised collaborators with an EGA Profile. There are a lot more features that we will be detailing from now on in incoming posts. A new platform for Data Access Committee Members The new DAC Portal brings novelties for individuals engaged in governance, legal, technical, operational roles, or those acting as data stewards. DAC members will be able to easily manage DACs, policies, and data access requests with the new Portal. Take the tour now to check them out! Help us improve the services completing the EGA Survey As part of our ongoing journey to improve your experience, we have created an EGA User Survey. This questionnaire covers a wide range of aspects such as user experience, support and data accessibility, among others. Participate now and take the opportunity to suggest your own improvements. Help us enhance your experience in this new era for the EGA. Subscribe to the EGA Mailing List and stay tuned In the next weeks we will share more information about the possibilities of the new services. You can easily join the EGA Mailing List to receive all the updates.

Blog new-set-of-services-at-EGA

Molecular evolution of metastatic clear cell renal cell carcinoma progressing under tyrosine kinase inhibitor therapy (HIPO-045)

Background:Acquired resistance to targeted drugs is largely due to intra-tumor molecular heterogeneity and clonal selection. Objective:The objective of this study was to determine molecular alterations and mediating resistant mechanisms and to suggest additional treatment options.Design, Setting, and Participants:Four patients were enrolled into the MORE (Molecular Renal Cancer Evolution) trial. We investigated the mutational spectra of metastatic clear cell renal cell carcinoma (ccRCC) at baseline and compared them to those upon clonal evolution at progression on systemic therapy with tyrosine kinase inhibitors.Outcome Measurements:DNA was isolated from tumor tissues after surgery, metastasis biopsies after progression on sunitinib or axitinib, and subjected to whole-exome sequencing (WES). In addition, the exomes of circulating tumor DNA (ctDNA) from two patients were sequenced at baseline and at progression.Results and Limitations:Our data provide evidence for clonal evolution and various acquired resistance mechanisms of ccRCC with subclonal mutations in FLT4, MTOR, ITGA3/5, SETD2, and VHL on metastatic progression. The limited number of shared mutations in tissue and plasma biopsies indicates that both sources provide complementary information, possibly due to mutations present in metastatic lesions which were not amenable to tissue sampling but are represented in the ctDNA. Conclusion:Acquired resistance to targeted therapies in metastatic ccRCC is due to intra-tumor heterogeneity and clonal evolution. Larger patient cohorts have to be studied to estimate the benefit of WES from biopsies and ctDNA for therapy decision in metastatic ccRCC.Patient Summary:We analyzed the molecular profiles of ccRCC patients in primary tissues and metastatic tissues upon progression on tyrosine kinase inhibitor therapy. Clinically relevant mutations upon progression were detected in the metastatic sites of all of four patients, suggesting that it might be possible to derive therapies based on sequencing the metastases.?HIPO-045

Study EGAS00001001861

Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. Standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the power of short reads. Starting from only 1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as 'Linked-Reads'. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes. In this manuscript, we show the utility of reference based analysis using a single Linked-Read library for full spectrum genome analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

Study EGAS00001003121

Indonesian Genome Diversity Project

Indonesia, the world’s fourth largest country by population, comprises an archipelago of about 900 permanently inhabited islands in tropical Asia, and hosts an astonishing array of human diversity that remains largely underrepresented in modern biological surveys. The region is unique for its key role in both the early and recent evolution of Homo outside of Africa. It has one of the first traces of anatomically modern humans in Eurasia, and was the focus of extensive interaction between archaic hominins and humans – both in the likely co-existence of H. floresiensis with modern humans, and in the introgression of Denisovans into the ancestors of its present inhabitants. More recently, Indonesia was a center of the spread of Neolithic culture by Austronesian speakers. Advancing maritime technologies allowed farming populations to treat this region as a springboard to reach oceanic islands as remote as Madagascar, Hawaii, Easter Island and New Zealand. Here we present complete human genomes from healthy individuals from multiple key islands in Indonesia and Papua. The genomes were sequenced to high depth (30x). The purpose of this dataset is to address different questions of human evolution in Island Southeast Asia and beyond, including early settlement of the area by anatomically modern humans, population structure, genetic admixture and adaptation, and contacts with archaic hominins. We employed a sampling strategy to capture a broad range of diversity across the region incorporating an average of 12 samples from each of 14 islands spanning Indonesia and Papua, from Sumatra in the west to New Britain in the east. Genomes from this dataset form part of an ongoing project to describe and understand human evolutionary history in Island Southeast Asia and Eurasia in general.

Study EGAS00001003054

Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive NSCLC patients

Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but efficacy varies between patients and is believed to depend in part on the amount and properties of tumor infiltrating lymphocytes (TILs). To comprehensively depict and dissect the baseline landscape of the composition, lineage and functional states of TILs in lung cancer, here we generated deep single-cell RNA sequencing data for 12,346 T cells from the primary tumour, adjacent normal tissues and peripheral blood of 14 treatment-naive NSCLC patients. Combined expression and TCR-based lineage tracking revealed a significant proportion of effector T cells with common origins and similar functional states across peripheral blood and tumours pointing towards a highly migratory nature of these T cells. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of pre-exhausted to exhausted T cells is associated with better prognosis of lung adenocarcinoma (LUAD). In addition, we observed further heterogeneity within the tumour regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of this group of activated tumour Tregs, which included IL1R2, correlated with poor prognosis in LUAD. The T cell clusters revealed by our single cell analyses provide a new approach for patient stratification, and the accompanying compendium of data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

Study EGAS00001002430

UK10K NEURO FSZ

In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. These Finnish schizophrenia samples have been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder, each family having at least two affected siblings. 170 families originate from an internal isolate (Kuusamo) with a three-fold lifetime risk for the trait. The genealogy of the internal isolate is well documented and the individuals form a “megapedigree” reaching to the 17th Century. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data. For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

Study EGAS00001000118

'Targeted High Throughput Sequencing in Clinical Cancer Settings: Formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity'

"Background: Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings. Methods: Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.Results: We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance. Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations, but is of minor importance for the detection of somatic variations.Conclusions: The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies taken, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - on a long-range - result in a more reliable prediction of individual cancer therapies."

Study EGAS00001000136

Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution

Human cancers, including breast cancers, are comprised of clones differing in mutation content that evolve dynamically in space and time following principles of Darwinian evolution, underpinning important emergent features such as drug resistance and metastasis. Human breast cancer xenoengraftment is used as a means of capturing and studying tumour biology, and breast tumour xenografts are generally assumed to be reasonable models of the originating tumours. However the consequences and reproducibility of engraftment and propagation on the genomic clonal architecture of tumours has not been systematically examined at single cell resolution. Here we show by both deep genome and single cell sequencing methods, the clonal dynamics of initial engraftment and subsequent serial propagation of primary and metastatic human breast cancers in immunodeficient mice. In all cases examined, clonal selection on engraftment was observed in both primary and metastatic breast tumours, varying in degree from extreme selective engraftment of minor (<5% of starting population) clones to moderate, polyclonal engraftment. Furthermore, ongoing clonal dynamics during serial passaging is a feature of tumours experiencing modest initial selection. Through single cell sequencing, we show that major mutation clusters estimated from tumour population sequencing relate predictably to the most abundant clonal genotypes, even in clonally complex and rapidly evolving cases. Finally, we show that similar clonal expansion patterns can emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. Our results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies utilizing patient-derived breast cancer xenoengraftment.

Study EGAS00001000952

1 Intratumoral genetic heterogeneity and clonal evolution following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal tumors.

Purpose: Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment forpatients with locally advanced rectal cancer. However, little is known about the effect of nCRT in the mutational landscape and intratumoral genetic heterogeneity (ITGH) of rectal tumors. Moreover, response to nCRT vary substantially among patients and the genetic determinants of treatment response are not fully understood. Here, we sought to determine the impact of nCRT in the mutational landscape and ITGH of rectal tumors and to identify putative drivers of therapeutic resistance. Patients and Methods: We analyzed whole-exome sequencing (WES) and clinical data from 79 primary non-treated rectal cancers obtained from The Cancer Genome Atlas (TCGA). We also compared the mutational landscape of a matched set of peripheral blood cells, irradiated tumor-adjacent colonic mucosa and pre and post-treatment tumor samples to determine the iatrogenic effects of nCRT and its impact in tissue genetic heterogeneity. Finally, we performed WES of 7 matched pre and post-treatment tumor samples to examine how nCRT affects the clonal architecture of rectal tumors. Results: We show that rectal tumors exhibit remarkable ITGH, which increases with disease progression. We also show that nCRT, per se, does not introduce novel somatic mutations, nor alters the clonal architecture of the irradiated colonic mucosa. Instead, we show that it acts as a potent selective pressure, favoring the expansion of tumor cell subpopulations more prone to resist therapy and increasing ITGH in the residual tumor. Conclusion: Our results reveal the highly heterogeneous and dynamic clonal architecture of rectal tumors undergoing nCRT. Our results also uncover putative genetic determinants of response to nCRT and a possible role for ITGH in predicting treatment outcome.

Study EGAS00001003250

THAP11 mutations in a patient with a cblX-like phenotype implicates THAP11 in the regulation of cobalamin metabolism and early vertebrate development

Mutations in HCFC1 are associated with cblX (MIM309541), an X-linked recessive disorder, characterized by defects in cobalamin metabolism and other developmental defects. HCFC1 is a transcriptional co-regulator, which interacts with transcription factors to regulate the expression of a myriad of genes. Notably, HCFC1 regulates cobalamin metabolism via the regulation of MMACHC expression through its interaction with THAP11, a THAP domain-containing transcription factor. In addition, the HCFC1/THAP11 complex potentially regulates genes involved in diverse cellular functions including cell cycle, proliferation, and transcription. Thus, it is likely that mutations in THAP11 may also result in biochemical and other phenotypes similar to those observed in patients with cblX. We report a patient who presented with phenotypic features that overlap cblX, but did not have any mutations in either MMACHC or HCFC1. We sequenced THAP11 by Sanger sequencing and discovered a potentially pathogenic, homozygous variant in THAP11, c.240C>G (p.Phe80Leu). Functional analysis in the developing zebrafish embryo, demonstrate that both THAP11 and HCFC1 regulate the proliferation and differentiation of neural precursors, suggesting important roles in normal brain development. Further, the loss of THAP11 in zebrafish embryos, results in craniofacial abnormalities including the complete loss of Meckel’s cartilage, the ceratohyal, and all of the ceratobranchial cartilages. These data are consistent with our previous work which demonstrated a role for HCFC1 in vertebrate craniofacial development. Furthermore, our high throughput RNA-sequencing analysis reveals several overlapping gene targets of HCFC1 and THAP11 that likely contribute to the phenotypes associated with cblX and related disorders. Thus, both HCFC1 and THAP11 play important roles in the regulation of cobalamin metabolism as well as other pathways involved in early vertebrate development.

Study EGAS00001002201

The Genomic Landscape of Response to EGFR Blockade in Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer world-wide with 1.2 million patients diagnosed yearly. In late stage CRC, the most commonly used targeted therapies are monoclonal antibodies cetuximab and panitumumab, which inactivate EGFR. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in CRC and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in CRC on response to anti-EGFR antibody therapy, we performed complete exome sequence and copy number analyses of 129 patient-derived tumorgrafts and targeted genomic analyses of 55 patient tumors, all of which were KRAS wild-type. We analyzed the response of tumors to anti-EGFR antibody blockade in tumorgraft models or in clinical settings. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumors with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumorgraft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluate response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and provide new avenues for intervention in the management of CRC.

Study EGAS00001001305

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

Targeting the DNA Repair Pathway in Ewing Sarcoma

Ewing’s Sarcoma is a bone and soft tissue tumor that primarily affects adolescents and young adults. With current therapies, 70% of patients with localized disease survive but survival for metastatic and recurrent disease is poor. Whole genome sequencing of 19 Ewing’s Sarcoma tumors showed that STAG2 was mutated in 10% (2/19) of the tumors and STAG2 protein was absent in 14% (13/106) tumors by immunohistochemical staining. Previous studies have shown that glioblastoma cells lacking STAG2 are more sensitive to poly-ADP ribose polymerase (PARP) inhibitors. We found that Ewing’s Sarcoma cell lines are sensitive to PARP inhibitors irrespective of STAG2 protein expression. Ewing Sarcoma cell lines are defective in double strand DNA break repair. PARP inhibitor cytotoxicity in Ewing’s Sarcoma cells was potentiated 10-1,000 fold by DNA damaging agents (irinotecan and temozolomide). To extend these studies in vivo, we developed an orthotopic Ewing’s Sarcoma mouse model and performed pharmacokinetic and pharmacodynamic studies with three different PARP inhibitors (BMN-673, olaparib and veliparib) in clinical development for pediatric cancer. Those data were used to design preclinical phase I studies to identify tolerable drug combinations for pilot efficacy testing (preclinical phase II). Based on the results of the preclinical phase I/II data, we performed a double blind, randomized, placebo controlled preclinical phase III trial with 274 mice in 15 treatment groups. Irinotecan administered in a low-dose protracted schedule optimized for pediatric patients was an effective DNA damaging agent to combine with olaparib and BMN-673 and was better tolerated than combinations with temozolomide. Combining olaparib or BMN-673 with irinotecan and temozolomide gave complete and durable responses in over 80% of the mice.

Study EGAS00001000839

Exome sequencing in bipolar disorder families

Bipolar disorder (BD) is a major psychiatric disorder affecting around 1% of the global population. BD is characterized by recurrent manic and depressive episodes, and has an estimated heritability of around 70% Research has identified the first BD susceptibility genes. However, the underlying pathways and regulatory networks remain largely unknown. Since research has shown that the cumulative impact of common alleles with small effect appears to explain only around 25-38% of the phenotypic variance for BD, rare variants of high penetrance may also contribute to BD risk. The present study investigated the role of rare, nonsynonymous, and potentially functional variants via whole exome sequencing in 15 BD cases from two large, multiply affected families from Cuba. The high prevalence of BD in these pedigrees renders them promising in terms of the identification of genetic risk variants with large effect sizes. In addition, SNP array data were used to calculate polygenic risk scores for affected and unaffected family members. After correction for multiple testing, polygenic risk scores for common, BD-associated genetic variants were not significantly higher in BD cases than in healthy relatives. Exome sequencing identified a total of 17 rare and potentially damaging variants in 17 genes. The identified variants were shared by all investigated BD cases in the respective pedigree. The most promising variant was located in the gene SERPING1 (p.L349F), which has been reported as a genome-wide significant risk gene for schizophrenia. A further promising variant was located in CAPN2, which has been implicated in synaptic plasticity. The present data suggest novel candidate genes for BD susceptibility, and may facilitate the discovery of disease-relevant pathways and regulatory networks.

Study EGAS00001003085

Genomic landscape of oral cancers (Complete Genomics WGS)

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 EGAS00001002393

Genome wide association study on coronary heart disease in patients with familial hypercholesterolemia

Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17 000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap 550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (p<1×10-4). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an ‘extreme genetics’ approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may therefore not lead to significant gains in statistical power. (NB submitten and conditionally accepted at European Journal of Human Genetics-please use abstract only for internal review until submission complete)

Study EGAS00001000734

Ischemic stroke in a Swedish case-control study.

Background. Genetic risk scores (GRS), summing up the total effect of several single nucleotide polymorphisms (SNPs) in genes associated with either coronary risk or cardiovascular risk factors, have been tested for association with ischemic stroke with conflicting results. Recently an association was found between a GRS, based on 29 SNPs discovered by genome-wide association studies (GWAS) and hypertension. The aim of our study was to investigate the possible association of the same GRS with ischemic stroke on top of other “traditional risk factors”, also testing its potential improvement in indices of discrimination and reclassification, in a Swedish case-control study. Methods and results. Twenty-nine SNPs were genotyped in 3,677 stroke cases and 2,415 controls included in the Lund Stroke Register (LSR), the Malmö Diet and Cancer (MDC) study and the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). The analysis was conducted in the entire material, and separately for the three samples. After adjustment for hypertension, diabetes mellitus and smoking habits, the GRS was associated with ischemic stroke in the entire material [OR (95% CI) 1.086 (1.029-1.147) per SD increase in the GRS p=0.003] with similar trends in all three samples; LSR [1.050 (0.967-1.140)]; p=0.25], MDC [1.168 (1.060-1.288); p=0.002] and SAHLSIS [1.124 (0.997-1.267); P=0.055]. Measures of discrimination and reclassification improved marginally using the GRS. Conclusions. A blood pressure GRS is independently associated with ischemic stroke risk in three Swedish case-control studies, however, the effect size is low and adds marginally to prediction of stroke on top of traditional risk factors including hypertension.

Study EGAS00001000936

A reference map of potential determinants for the human serum metabolome

The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

Study EGAS00001004512

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