A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.
What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant. For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source. Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions. You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks. Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.
Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.
Rare individuals are highly resistant to infection with human immunodeficiency virus (HIV). Studies of candidate genes resulted in the discovery of a 32bp deletion in the CC-chemokine receptor 5 gene (CCR5Δ32), which rendered this critical co-receptor for primary HIV infection to be non-functional. Pharmacologic and vaccine-induced blockade of CCR5 is being pursued to treat and prevent HIV infection and other conditions. The allele frequency of CCR5Δ32 among persons of European ancestry is approximately 10%. CCR5Δ32/Δ32 homozygotes are almost totally resistant to HIV infection. People with severe hemophilia A require frequent replacement with clotting Factor VIII (FVIII) to control hemorrhage. Prior to the discovery of HIV in 1984 and licensure of recombinant FVIII in the late 1980s, people with severe hemophilia A were treated with plasma-derived FVIII and thus were intensively exposed to HIV. Only 5% of such patients were not infected with HIV. Of these, approximately 1/3 were CCR5Δ32/Δ32 homozygotes. The remaining 2/3 of these people who were highly resistant to HIV remain unexplained. This project seeks to discover genome variations among people who are highly resistant to HIV infection. Such variation is likely to serve as a target for reducing the morbidity and incidence of HIV.
Lipid lowering therapy using HMG-CoA reductase inhibitors (statins) is associated with an approximately 9-12% increase in the risk of new-onset type 2 diabetes (T2DM). The risk of diabetes could be increased by statins directly; however, genetic approaches have also implicated low LDL cholesterol (LDL-C) concentrations as a risk factor for T2DM. Mendelian randomization studies using functional variants in both HMGCR (GeneID:3156) and PCSK9 (GeneID:255738) genes found a higher risk of T2DM in individuals with variants associated with lower LDL-C concentrations. Since PCSK9 and HMGCR are involved in lipid metabolism through distinct molecular pathways, the altered glycemic effect associated with variants in both genes is likely to be the result of their common effect on LDL-C concentrations. Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations with increased risk of T2DM. Individuals who have very low LDL-C concentrations not due to lipid lowering therapy can provide insights into the relationship between low LDL-C concentrations and T2DM. Here, we used de-identified electronic health records (EHRs) to test the hypothesis that low LDL-C concentrations are associated with T2DM.
Developmental brain malformations are at the core of significant neurological diseases affecting many families in the United States and around the world. It is known that epilepsy, specific learning deficits and intellectual disability, cerebral palsy, and abnormalities of brain volume can be attributed in many cases to pathological malformations of the cerebral cortex. Although these consequences, such as epilepsy and intellectual disability, might appear broadly in the population as due to complex traits, this study's focus on those associated with cortical malformations highlights individual developmental pathways likely represented by innumerable and rare Mendelian alleles. Research has thus far uncovered dozens of genes responsible for these conditions and dissected the mechanisms underlying early cortical development in animals. However, this progress represents only the dawn of understanding the complex genetic network and neuronal architecture of the uniquely human cerebral cortex. The overall goal of this study is to define the genetic bases of human cerebral cortical development. This is accomplished through (1) the ascertainment of families with disorders of human brain development and malformation, (2) categorizing these using medical, physical and neuroimaging data, and (3) mapping and identifying the gene causing the disorder of cortical development, which can then be investigated for its normal expression and function, and role in human disease.
During rheumatoid arthritis (RA), TNF activates fibroblast-like synoviocytes (FLS) inducing in a temporal order a constellation of genes, which perpetuate synovial inflammation. Although the molecular mechanisms regulating TNF-induced transcription are well characterized, little is known about the impact of mRNA stability on gene expression and the impact of TNF on decay rates of mRNA transcripts in FLS. To address these issues we performed RNA sequencing and genome-wide analysis of the mRNA stabilome in RA FLS. We found that TNF induces a biphasic gene expression program: initially, the inducible transcriptome consists primarily of unstable transcripts but progressively switches and becomes dominated by very stable transcripts. This temporal switch is due to: a) TNF-induced prolonged stabilization of previously unstable transcripts that enables progressive transcript accumulation over days and b) sustained expression and late induction of very stable transcripts. TNF- induced mRNA stabilization in RA FLS occurs during the late phase of TNF response, is MAPK-dependent, and involves several genes with pathogenic potential such as IL6, CXCL1, CXCL3, CXCL8/IL8, CCL2, and PTGS2. These results provide the first insights into genome-wide regulation of mRNA stability in RA FLS and highlight the potential contribution of dynamic regulation of the mRNA stabilome by TNF to chronic synovitis.
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can have debilitating effects on multiple organ systems. In SLE, the pivotal immunologic disturbance is the formation of autoantibodies directed against nuclear and cellular antigens. These autoantibodies are associated with specific organ manifestations. Our previous work has shown that certain single nucleotide polymorphisms (SNPs) are associated with the production of SLE-related autoantibodies. However, these genetic associations do not completely explain autoantibody development in SLE. Therefore, we examined whether epigenetic factors such as DNA methylation may be associated with the development of SLE-related autoantibodies. In this study, we examined whether differential DNA methylation is associated with anti-dsDNA, anti-SSA/Ro, anti-Smith, and anti-RNP autoantibodies. Using the Illumina HumanMethylation450 Beadchip, over 450,000 DNA methylation sites were characterized in 325 female SLE cases of European descent. Using a multivariable regression analyses, the methylation status of 16 CpG sites in 11 genes was found to be associated with the SLE-related autoantibodies under study. This study shows that epigenetic factors are associated with autoimmune disease phenotypes, and epigenetic studies are a complementary method to genetic association studies for understanding the biologic mechanisms contributing to autoimmune disease.
Plasmacytoid dendritic cells (pDC) are a subset of dendritic cells with unique immunophenotypic properties and functions. While their role in antiviral immunity through production of type I interferons is well-established, their contributions to anti-tumor immunity are less clear. While some evidence demonstrates that pDC in the tumor microenvironment (TME) may drive CD4+ T cell to become Foxp3+ T regulatory cells, little is understood about the relationship of pDC with cytotoxic CD8+ T cell, the key player in antitumor immune responses. In this study, we perform comprehensive immunophenotyping and functional analysis of pDC from the TME and draining lymph nodes of patients with head and neck squamous cell carcinoma (HNSCC) and identify a novel pDC subset characterized by expression of the TNF receptor superfamily member CD134 (OX40). We show that OX40 expression is expressed on intratumoral pDC in both humans and mice in a tumor-model specific fashion and that this subset of pDC enhances tumor associated-antigen (TAA)-specific CD8+ T cell responses. Through transcriptomic profiling of OX40-expressing pDC from the TME, we further characterize gene signatures unique to this pDC subset that support its role as an important immunostimulatory immune population in the TME.
