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• Distribution of data using Live Distribution

  Live Distribution Welcome to the documentation for using the Live Distribution feature for distributing data files securely through the EGA platform. This guide will walk you through the process of downloading encrypted files and decrypting them using Crypt4GH. Please follow the steps below to ensure a smooth experience. Before Downloading Create an EGA user. Make sure that you have the permissions to download the dataset of interest. In case you don’t have access, request access to the dataset. Add your Crypt4GH-compatible public key to your EGA account. Please allow a few hours for your public key to be synced with your profile. Afterwards, you will be able to connect to your EGA outbox using the SFTP protocol. Download Graphical User Interface (GUI) You can use any GUI that supports SFTP connections, such as FileZilla, an open-source FTP client. For Filezilla as your GUI, follow these steps to download files: Open FileZilla and access Site Manager (File > Site Manager). Create a new connection with the following settings (Figure 1): Protocol: SFTP - SSH File Transfer Protocol Host: __EGA_OUTBOX_DOMAIN__ Logon Type: Key file User: your EGA username Key file: path/to/your/private_key Figure 1: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the EGA outbox, ensuring seamless data transfers. Click Connect to access your Outbox. This folder serves as your storage space within the EGA cloud, containing files accessible for download in a secure way. Browse the remote directory on the right side of the FileZilla screen. Select the files you wish to download, right-click, and choose Download (Figure 2). Figure 2: Step-by-step process of manually downñoad files from __EGA_OUTBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can downñoad data from the EGA outbox to their local storage by following the depicted steps SFTP command line You can also use the SFTP command line to securely download files from the EGA Outbox. Using SFTP command line client in Linux/Unix Open a terminal window Enter the following command to connect: sftp username@hostname Enter your EGA password To see a list of available sftp commands type help sftp> put – Upload file sftp> get – Download file sftp> cd path – Change remote directory to ‘path’ sftp> pwd – Display remote working directory sftp> lcd path – Change the local directory to ‘path’ sftp> lpwd – Display local working directory sftp> ls – Display the contents of the remote working directory sftp> lls – Display the contents of the local working directory Type get command to download files. For example: get encrypted_file.c4gh Use the bye command to close the connection (SFTP session). Convenient SSH settings Include the following settings in your SSH config file, located in ~/.ssh/config Host __EGA_OUTBOX_DOMAIN__ EGA-outbox hostname __EGA_OUTBOX_DOMAIN__ User username IdentityFile path/to/the/private/key Replace username and path/to/the/private/key with the appropriate settings, and you will be able to connect to the __EGA_OUTBOX_DOMAIN__ simply using sftp EGA-outbox. How to decrypt Files archived at the EGA are encrypted based on Crypt4GH. Hence, to decrypt the files you need to install Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git After installing Crypt4GH, decrypt files using the following command: crypt4gh decrypt --sk /path/private/key < encrypted_file.c4gh > decrypted_filename The command reads the encrypted file from stdin (with <) and output the decrypted version to stdout (with >). Replace encrypted_file.c4gh and decrypted_filename with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write. Frequently Asked Questions What username should I use to log in to my outbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username, not your email address. Therefore, if you registered a username different from your email address when creating your EGA account, you must use that username to log in. If you have forgotten your registered username, please, contact our Helpdesk team for assistance. I see that some files in my dataset have 'unavailable' as extension. What should I do? Within your Outbox, you'll find a list of all the datasets available for download. Occasionally, certain files may be marked as "unavailable". These unavailable files can be identified by the "unavailable" extension added to their filenames (e.g. filename.fastq.gz.unavailable.c4gh). If you encounter an unavailable file that you need, please reach out to our Helpdesk. We'll promptly work on making the file accessible for download as soon as possible. Specific to using keys Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

  Documentation access/download/files/live-outbox

• CosMX spatial transcriptomics

  This study consists of the spatial transcriptomics analyis data generated by : CosMxTM Human Universal Cell Characterization RNA Panel (1000-plex); NanoString, USA for n=4 SLD-HCC and n=4 non-SLD-HCC. The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Dataset EGAD50000001507

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (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). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• SG10K_Pilot Dataset: Whole genome sequencing data of 4810 individuals from Singapore

  Genomic data obtained from the joint processing and variant calling of 4,810 individuals from Singapore. VCF files are by Chromosome (chr. 1-22 plus X) for all 4,810 individuals. Self-reported ethnicity is found in the "Region" column of metadata file.

  Dataset EGAD00001005337

• Transcriptomic analysis of Acute Myeloid Leukemia stem cells

  Acute Myeloid Leukemia (AML) is characterized by the accumulation of clonal myeloid blast cells unable to differentiate into mature leukocytes. Chemotherapy induces remission in the majority of patients, but relapse rates are high and lead to poor clinical outcomes. Since this is primarily caused by chemotherapy-resistant leukemic stem cells (LSCs), it is essential to eradicate LSCs to improve patient survival. LSCs have predominantly been studied at the transcript level, thus lacking information about post-transcriptionally regulated genes and associated networks. Here we extend our previous report on LSC proteomes to healthy age-matched hematopoietic stem and progenitor cells (HSPCs) and correlate the proteomes to the corresponding transcriptomes. By comparing LSCs to leukemic blasts and healthy HSPCs, we validate candidate LSC markers and highlight novel and potentially targetable proteins that are absent or only lowly expressed in HSPCs. In addition, our data provides strong evidence that LSCs harbor a characteristic energy metabolism, adhesion molecule composition, as well as RNA processing properties. Furthermore, correlating proteome and transcript data of the same individual samples highlights the strength of proteome analyses, which are particularly potent in detecting alterations in metabolic pathways. In summary, our study provides a comprehensive proteomic and transcriptomic characterization of functionally validated LSCs, blasts and healthy HSPCs, representing a valuable resource helping to design LSC-directed therapies.

  Study EGAS00001004402

• Mesothelioma_Whole_Genomes

  Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project.

  Study EGAS00001000830

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

  Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R.

  Study phs002908

• AYA glioma NGS

  Gliomas are a major cause of cancer-related death in adolescents and young adults (AYA, ages 15-39 years). Different molecular alterations drive gliomas in children and adults leading to distinct biology and clinical consequences. At the convergence of these age groups - the AYA population – little is known about the implications of pediatric vs adult-type alterations. To address this, we analyzed a population-based cohort of 1456 clinically and molecularly characterized gliomas aged 0-39 years. Potentially targetable pediatric-type alterations were found in 31% of AYA gliomas and conferred superior outcomes compared to adult-type alterations. This submission includes the generated NGS data for children, adolescent, and young adults with gliomas. Data includes targeted panel of glioma genes and low-pass WGS (1x coverage).

  Study EGAS50000000383

• mutational landscape of normal human breast

  The accumulation of somatic mutations in the healthy breast throughout life and pregnancy is poorly understood. Here we describe whole genome sequencing analysis of epithelial and stromal compartments from the normal breast. We aimed to study how pregnancy and age affect both the mutational burden and the clonality of the healthy breast, and the subsequent implications on breast cancer risk.

  Study EGAS00001004672

• Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer

  This dataset contains all available targeted exon sequencing bam files from our study, "Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which serial sample is referenced (1st, 2nd, 3rd, etc.), and whether the sample represents cell-free DNA ("cfdna") or paired white-blood cell control ("WBC"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006122

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064

• Circulating cell-free DNA methylation profiles as noninvasive multiple sclerosis biomarkers: A proof-of-concept study

  In chronic neurodegenerative diseases such as multiple sclerosis (MS), there is a critical unmet need for cost-effective non-invasive blood biomarkers to concurrently classify disease subtypes, monitor disability severity, and predict long-term progression. In this proof-of-concept study, we performed low-coverage whole-genome bisulfite sequencing (WGBS) on 75 plasma cell-free DNA (cfDNA) samples collected from a well-characterized real-world prospective clinic cohort with longitudinal disability outcome measurements. We assessed the clinical utility of cfDNA methylation profile for differentiating MS patients from non-MS controls, classifying MS subtypes, estimating disability severity, and predicting disease trajectories.

  Study EGAS50000001277

• RNA-sequencing of adult T-cell leukemia/lymphoma samples

  Adult T-cell leukemia/lymphoma (ATL) is a highly aggressive hematological malignancy derived from mature CD4+ T-lymphocytes. In this study, we performed RNA-sequencing (RNA-seq) analysis for ATL samples including 9 primary tumors and 1 ATL cell line to clarify gene expression profiles in this disease.

  Study EGAS00001003575

• Persistent Mutation Burden Drives Sustained Anti-Tumor Immune Responses

  Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss and discovered that clonal mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) that is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

  Study EGAS00001006660

• Macrophage response in preterm infants compared to term infants

  Preterm infants are highly susceptible to sustained lung inflammation, which may be triggered by exposure to multiple environmental cues such as supplemental oxygen (O2) and infections. The underlying mechanisms are still poorly understood. The hypothesis of this study is that dysregulated macrophage activation is a key feature leading to inflammation-mediated development of bronchopulmonary dysplasia (BPD) in preterm infants. Cord blood samples of preterm infants (n=14) and term infants (n=19) as well as peripheral blood from healthy adults (n=17) were collected. Age-dependent differences in immune responses of monocyte-derived MФ from preterm infants were characterized and compared to term infants and adults after lipopolysaccharide (LPS) exposure.

  Study EGAS00001004974

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Purpose: DNA originating from degenerate tumour cells can be detected in the circulation in many tumour types, where it can be used as a marker of disease burden as well as to monitor treatment response. Although circulating tumour DNA (ctDNA) measurement has prognostic/predictive value in metastatic prostate cancer, its utility in localised disease is unknown. Patients and Methods: We performed whole genome sequencing of tumour-normal pairs in eight patients with clinically localised disease undergoing prostatectomy, identifying high confidence genomic aberrations. A bespoke DNA capture and amplification panel against the highest prevalence, highest confidence aberrations for each individual was designed and used to interrogate ctDNA isolated from plasma prospectively obtained pre- and post- (24 hours and 6 weeks) surgery. In a separate cohort (n=189) we identified the presence of ctDNA TP53 mutations in pre-operative plasma in a retrospective cohort, and determined its association with biochemical- and metastasis-free survival. Results: Tumour variants in ctDNA were positively identified pre-treatment in two of eight patients, which in both cases remained detectable postoperatively. Patients with tumour variants in ctDNA had extremely rapid disease recurrence and progression compared to those where variants could not be detected. In terms of aberrations targeted, single nucleotide and structural variants outperformed indels and copy number aberrations. Detection of ctDNA TP53 mutations was associated with a significantly shorter metastasis-free survival (6.2 vs. 9.5 years (HR 2.4; 95% CIs 1.2-4.8, p = 0.014)). Conclusions: CtDNA is uncommonly detected in localised prostate cancer but its presence portends more rapidly progressive disease.

  Study EGAS00001004636

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• A genomic approach towards an understanding of clonal evolution and disease progression in multiple myeloma

  Multiple Myeloma (MM) is a largely incurable haematological malignancy defined by the clonal proliferation of malignant plasma cells within the bone marrow. Clonal heterogeneity has recently been established as a feature in MM, however, the subclonal evolution associated with disease progression has not been described. We used whole exome sequencing to analyse 10 paired patient samples, providing new insights into the progression from Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smouldering MM (SMM), to symptomatic MM. We confirm that clonal heterogeneity is a common feature at diagnosis and that the driving events involved in disease progression are more complex than previously reported. While we observe some previously identified known “drivers” of MM, we find that the driving events involved in progression are complex and not limited to the known SNVs or CNVs. The RAS/MAPK pathway was found to be the most frequently deregulated pathway, with recurrent mutations in KRAS and NRAS observed in patients at both MGUS/SMM and MM stages. We reveal that MM evolution is mainly characterised by the phenomenon of clonal stability, where the subclonal plasma cell populations identified at MM progression are already present in the asymptomatic MGUS/SMM stages. These subclonal populations could be amenable to therapeutic intervention to arrest transformation to MM.

  Study EGAS00001002850

• Samples from the Greek island of Crete, MANOLIS cohort

  Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on isolated populations from Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

  Study EGAS00001000067

• Gene_Characterization_in_Carbohydrate_metabolic_alterations__neonatel_diabetes___congenital_hyperinsulinemic__in_early_childhood

  Whole Exome Sequencing of trios (proband + parents) or probands only with Neonatal Diabetes Mellitus (NDM) or Congenital Hyperinsulinism of Infancy (CHI) of unknown genetic origin. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002074

• DAC for "Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy"

  This is the DAC for "Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy" with Florian Janke f.janke@dkfz-heidelberg.de German Cancer Research Center, Division of Cancer Genome Research Holger Sültmann h.sueltmann@dkfz-heidelberg.de German Cancer Research Center, Division of Cancer Genome Research Magdalena Görtz magdalena.goertz@dkfz-heidelberg.de German Cancer Research Center, Multiparametric Methods for Early Detection of Prostate Cancer

  Dac EGAC50000000114

• Hypermutation of the inactive X chromosome is a frequent event in cancer

  Mutation is a fundamental process in tumorigenesis. However the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. As part of the ICGC PedBrain and Malignant Lymphoma (MMML-Seq) consortium we performed a cross-cancer comparison of whole genomes comprising a diverse set of childhood and adult tumors including both solid and hematopoietic malignancies. In addition we performed whole genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals to compare somatic mutation rates.

  Study EGAS00001000565

• Identification of hypermutation and defective mismatch repair in ctDNA from metastatic prostate cancer

  DNA mismatch repair defects (MMRd) and tumor hypermutation are rare and under-characterized in metastatic prostate cancer. Furthermore, since hypermutated MMRd prostate cancers can respond to immune checkpoint inhibitors, there is an urgent need for practical detection tools. We analyzed cell-free DNA targeted sequencing data from 434 metastatic prostate cancer patients with circulating tumor DNA (ctDNA) purity above 2%. Samples with somatic hypermutation were subjected to 150x whole exome sequencing. These data allowed us to interrogate the salient genomic properties of this rare prostate cancer subtype and correlate findings with patient clinical outcomes.

  Study EGAS00001003899

• Single-Nuclei Paired Multiomic Analysis of Young, Aged, and Parkinson's Disease Human Midbrain Reveals Age-Associated Glial Changes and Their Contribution to Parkinson's Disease

  Age is the primary risk factor for Parkinson's disease (PD), but how aging to change the expression and regulatory landscape of the brain remains unclear. Here, we present a single-nuclei multiomic study profiling shared gene expression and chromatin accessibility of young, aged and PD post-mortem midbrain samples. Combined multiomic analysis of midbrain nuclei along a pseudo-pathogenesis trajectory reveals that all glial cell types are affected by age, but microglia and oligodendrocytes are further altered in PD. We present evidence for a novel disease-associated oligodendrocyte subtype and identify genes lost over the aging and disease process, including CARNS1, that may predispose healthy cells to develop a disease-associated phenotype. Peak-gene association analysis from paired data identifies 89 PD-associated SNP loci, including five in MAPT, that only correlate with gene expression in disease-associated oligodendrocytes. Our study suggests a previously undescribed role for oligodendrocytes in aging and PD pathogenesis.

  Study phs002819