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• Polycystic Ovary Syndrome (PCOS) Genetics

  PCOS is a complex genetic disease reflecting the interplay of susceptibility genes and environmental factors. The cardinal reproductive feature of the syndrome, hyperandrogenemia, appears to play a direct role in the pathogenesis of the associated metabolic abnormalities. Male as well as female first-degree relatives have reproductive and metabolic phenotypes including increased prevalence rates of type 2 diabetes (T2D), metabolic syndrome (MBS) and other risk factors for cardiovascular disease (CVD). Northwestern University (NU) investigators lead a team that has extensive experience in phenotyping PCOS and in the genetic analysis of complex diseases including genome-wide association study (GWAS). Together with an expert group of collaborators from the Hershey Medical Center, and The University of Chicago, we have conducted a GWAS to identify PCOS susceptibility alleles using a large cohort of extensively and consistently phenotyped PCOS cases. Population controls for this study come from the NUgene project described below. NUgene project: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators.

  Study phs000368

• DNA sequening

  The dataset consist of DNA and RNA sequencing results and metadata of the samples. All sample numbers starting with 6716 are tumor samples which has been sequenced using WES (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata) and in some cases blood for germline mutation analysis. Sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000382

• 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

• A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer

  Background Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. Methods We combined immunohistochemistry (IHC) with RNA-sequencing and whole genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Further, we explored transcriptional features of immune archetypes, T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions, and assessed common adult biomarkers such as neoantigen load and TMB. Results A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. Conclusions Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

  Study EGAS00001007029

• Novel genes for Intellectual Disability identified using whole genome sequence and pathway analysis

  Intellectual Disability (ID) is one of the most common global disorders. However for ~30% of patients with ID no cause is identified, despite a clinical diagnostic odyssey that includes genome wide clinical microarray (CMA). We carefully selected 8 trios, each composed of a child with ID and brain structural defect, and both normal parents for whole genome sequencing (WGS). We conducted WGS on the trio and filtered out de novo single nucleotide variants (SNVs) and then used a pathway-based refinement to select candidates. We confirmed a de novo pathogenic SNV in ARID1B, and likely pathogenic SNVs in CACNB3, SPRY4, PHF6, SQSTM1 and UPF1 in 5 of the 8 children. All genes except ARID1B and PHF6 are previously unreported for ID. We analysed our WGS data using 4 independent algorthims for copy number and structural variation including using de novo whole genome assembly. We confirmed one likely contributory 165kb de novo CNV (missed by CMA). We conducted a validation study of over 2000 exomes for our novel candidate genes and also present a strategy to analyze the non-coding sequence space. This study provides an extensive analysis of WGS in the context of ID and yielded causative variants in >60% of cases.

  Study EGAS00001001386

• THE GENOMIC LANDSCAPE OF ACTINIC KERATOSIS

  Actinic keratoses (AK) are lesions of epidermal keratinocyte dysplasia and are precursors for invasive cutaneous squamous cell carcinoma (CSCC). Identifying the specific genomic alterations driving progression from normal skin-AK-invasive CSCC is challenging due to the massive ultraviolet radiation-induced mutational burden characteristic at all stages of this progression. Here, we report the largest AK whole exome sequencing study to date and perform mutational signature and candidate driver gene analysis on these lesions. We demonstrate in 37 AK, from both immunosuppressed and immunocompetent patients, that there are significant similarities to CSCC in terms of mutational burden, copy number alterations, mutational signatures and patterns of driver gene mutations. We identify 44 significantly mutated AK driver genes and confirm that these genes are similarly altered in CSCC. We identify the azathioprine mutational signature in all AK from patients exposed to the drug, providing further evidence for its role in keratinocyte carcinogenesis. CSCC differ from AK in having higher levels of intra-sample heterogeneity. Alterations in signaling pathways also differ, with immune-related signaling and TGF-β signaling significantly more mutated in CSCC. Integrating our findings with independent gene expression datasets confirms that dysregulated TGF-β signaling may represent an important event in AK-CSCC progression.

  Dataset EGAD00001006894

• Melanoma Genome Sequencing Project

  Melanoma is the most prevalent cause of skin cancer morbidity and mortality. In order to characterize the full range of somatic mutations that may drive the growth of melanoma, we are sequencing tumor and normal DNA from a set of roughly 150 melanomas. For the majority of samples (approximately 90% of the cases), mutations in protein coding genes will be assessed in the exonic DNA of tumor-normal pairs using hybrid capture and paired-end DNA sequencing. For a few of DNA samples (approximately 10% of the cases), the entire genomes will be analyzed to assess the possible contribution of complex structural rearrangements contributing to oncogenesis. The sequencing data are supplemented by copy number profiling on the same tumors using high-density SNP arrays. Integration of these approaches will enable the unbiased and comprehensive characterization of both known and novel recurrent DNA alterations that arise in melanoma.Versions 1-4 contain whole exome and bulk RNA sequencing data for patients with melanoma.Version 5 - We compared somatic genomic profiles from matched pre-treatment and post-resistance tumor biopsies in patients with metastatic melanoma who exhibited heterogeneous responses to immune checkpoint inhibitors (ICIs). This version includes whole exome sequencing (WES) data from 14 patients.

  Study phs000452

• Nanopore_and_Illumina_sequencing_of_human_glioblastomas

  Liquid biopsy analysis refers to methods designed to detect tumour-specific material (e.g., circulating tumour cells or tumour DNA) in body fluids, such as urine or blood samples. A widely-used liquid biopsy approach consists of genotyping the circulating tumour DNA (ctDNA) through sequencing of plasma/serum DNA. Although useful in the context of metastatic disease (where the concentration of ctDNA is high), current liquid biopsy technologies show limited sensitivity of detection for the early detection of cancer, and low specificity, as cancer-related mutations accumulate in healthy tissues as part of the ageing process, thus making it difficult to distinguish these from tumour mutations, and because sequencing errors and true mutations show overlapping profiles. Therefore, developing liquid biopsy protocols with increased sensitivity and specificity represents an urgent clinical need. Here we harness extrachromosomal circular DNA (eccDNA) elements, which are circular DNA structures physically separated from the chromosomes of up to several Mbp long pervasive in human cancers, for liquid biopsy analysis. In this pilot study we will focus on the analysis of glioblastomas, because there is strong evidence for the presence of eccDNA in these tumour types, and because developing liquid biopsy approaches for brain tumours to reduce the invasiveness of brain tumour biopsies remains an unmet clinical need.

  Study EGAS00001005812

• Genomic landscape and PD-1 blockade in Natural-killer/T cell lymphoma

  Natural killer/T-cell lymphoma (NKTL) is an aggressive malignancy with a predilection for Asian, Mexican and South American populations. With the exception of Japan, it is the most common mature T-cell lymphoma in Asia. NKTL presents as extranodal disease and mostly affects the upper aerodigestive tract. Neoplastic cells are invariably infected by the Epstein-Barr virus (EBV) and characterized by a cytotoxic phenotype. The genetic landscape of NKTL has been recently unraveled by discoveries describing recurring mutations altering the JAK-STAT pathway, epigenetic modifiers, the DDX3X gene and genetic predisposition in the HLA-DPB1 gene.The genomic landscape of NKTL has been interrogated by whole-exome sequencing, targeted sequencing and single nucleotide polymorphism arrays, but has yet been studied with whole-genome sequencing (WGS). In this study, we will use a combination of WGS, targeted-capture sequencing (TCS) and RNA sequencing data to explore the genetic landscape and its relevance to immunotherapy in NKTL

  Study EGAS00001003828

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605