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• HGSOC genome-wide SNP (project ITH)

  SNP array genotyping of multi-site HGSOC samples

  Dataset EGAD00010002482

• Melanoma multi site metastases

  These are caveman, pindel, battenberg and brass calls for index patients' metastatic melanoma genomes within this study.

  Dataset EGAD00001005483

• PEVOsq

  The PEVOData PEVOsq basket trial is an open-label, multi-center, phase II trial investigating the combination of pembrolizumab (an immune checkpoint inhibitor) with vorinostat (a histone deacetylase inhibitor). This trial focuses on treating patients with recurrent or metastatic squamous carcinomas, including cancers of the cervix, head and neck, anus, vulva/vagina, penis, and lung. The aim is to evaluate the efficacy and safety of this combination, with pembrolizumab administered every 3 weeks and vorinostat daily. Outcomes include overall response rate and progression-free survival.

  Study EGAS50000000731

• cfDNAme allows early prediction of PE

  Preeclampsia (PE) is a leading cause for peripartal morbidity, especially if developing early in gestation. To enable prophylaxis to prevent PE, it is essential that pregnancies at risk of PE are identified early, in the first trimester. To identify patients at risk, we profiled methylomes of plasma-derived cell-free DNA (cfDNA) from pregnant women. We detected DNA methylation differences between control and PE pregnancies that enable risk stratification of patients, at PE diagnosis but also presymptomatically, around 12 weeks of gestation.

  Study EGAS00001007071

• Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

  Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no comprehensive and direct accuracy evaluations of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage), arbitrary sequencing read placement, and fetal DNA fraction on clinically validated NIPT samples.

  Study EGAS00001005323

• Molecular Analysis of Alliance A031201 Study

  This is the first study examining the relationship between clonal hematopoiesis and clinical outcomes in prostate cancer patients. We used a targeted gene sequencing panel to identify patients in the A031201 clinical trial with and without clonal hematopoiesis. We found that clonal hematopoiesis did not affect overall or progression free survival in A031201 but was associated more adverse cardiac events.

  Study phs003717

• Sequencing of cancer autopsies and ctDNA

  Tumor heterogeneity is a major obstacle for precision oncology strategies. To characterize inter-lesion heterogeneity in pre-treated cancers, we performed genetic and transcriptomic profiling of synchronous lesions from ten rapid autopsies comprising six cases of breast cancer, three of cholangiocarcinoma and one lung cancer case. For nine patients, we studied mutation representation in circulating cell-free DNA (cfDNA).

  Study EGAS00001005109

• The Genomic Map of Poland in Open Access

  The main goal is to prepare and share WGS/WES of Polish population In this project NGS (next generation sequencing) was performed using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner was used. Shared BAM and BAM.BAI files Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Study EGAS50000000091

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Background:Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. Methods:Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. Results:Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment were observed and led to a switch from a hot to a cold immune profile in three patients. Conclusions:This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support

  Study EGAS00001005328

• Center for Common Disease Genomics [CCDG] - Cardiovascular ATVB: Atherosclerosis Thrombosis and Vascular Biology

  Italian Atherosclerosis Thrombosis and Vascular Biology study is a prospective, nationwide, case-control study involving 125 coronary care units in Italy. The cases were patients who were hospitalised for a first MI before the age of 45 years and underwent coronary angiography. Acute MI was defined as resting chest pain lasting more than 30 minutes, accompanied by persistent electrocardiographic changes, and confirmed by an increase in total creatine kinase or in the MB fraction to more than twice the upper normal limits. The controls were healthy subjects without a history of thromboembolic disease who were unrelated to the patients, but individually matched with them by age, gender and geographical origin. They were enrolled from among the blood donors or staff of the same participating hospitals. Recruitment of cases and controls took place between 1994 and 2007. This site hosts data from ~60 whole exomes.

  Study phs001592

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program - Neuroblastoma

  The goal of NCI's Pediatric In Vivo Testing Consortium (PIVOT) is to advance the development of effective treatments for pediatric cancers through preclinical in vivo testing of novel therapeutic agents. To design impactful experiments that can be rapidly translated to the clinic, PIVOT investigators require comprehensive genomic characterization of the patient-derived xenograft (PDX) models used across the consortium. This robust experimental design enhances collaboration with industry partners by providing proof-of-concept data for drugs in development. As part of this effort, neuroblastoma PDX models are being molecularly characterized to identify promising therapeutic candidates. The molecular profiling includes whole exome sequencing (WES), RNA-seq, MethylEPIC array, CytoSNP array, and DNA fingerprinting for quality control. Additionally, demographic and clinical data (e.g., diagnosis, disease site, disease status) are shared. These characterized PDX models, matched with patient tumors, guide model selection for preclinical drug testing.

  Study phs003163

• Genome-wide cell-free DNA biological patterns in patients with cancer

  The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

  Study EGAS00001007400

• Plasma mutation profile of precursor lesions and colorectal cancer using the Oncomine Colon cfDNA Assay

  Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection of precursor lesions or early-stage cancer could hamper cancer development or improve survival rates. Liquid biopsy, which detects tumor biomarkers, such as mutations, in blood, is a promising avenue for cancer screening. To assess the presence of genetic variants in plasma cell-free tumor DNA from patients with precursor lesions and colorectal cancer using the commercial Oncomine Colon cfDNA Assay. Cell-free DNA (cfDNA) samples from the blood plasma of 52 Brazilian patients were analyzed. Eight patients did not have any significant lesions (five normal colonoscopies and three hyperplastic polyps), 24 exhibited precursor lesions (13 nonadvanced adenomas, ten advanced adenomas, and one sessile serrated lesion), and 20 patients with cancer (CRC). The mutation profile of 14 CRC-associated genes were determined by next-generation sequencing (NGS) using the Oncomine Colon cfDNA Assay in the Ion Torrent PGM/S5 sequencer.

  Study EGAS50000000471

• 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

• Whole genome sequencing data of paediatric KMT2A-rearranged acute lymphoblastic leukemia

  Pediatric KMT2A-rearranged leukemia is an aggressive subtype of leukemia commonly seen in infants (less tha 1 year old) and young children. It involves rearrangements of the KMT2A gene (formerly MLL) on chromosome 11q23, resulting in fusion genes that drive uncontrolled cell growth. This subtype is most often found in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and is associated with a poor prognosis. In infants, the 5-year event-free and overall survival rates are around 35–40%. Despite intensive chemotherapy, outcomes remain challenging, prompting ongoing research into targeted therapies and novel treatment strategies.

  Study EGAS50000001079

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia

  Pediatric KMT2A-rearranged leukemia is an aggressive subtype of leukemia commonly seen in infants (less tha 1 year old) and young children. It involves rearrangements of the KMT2A gene (formerly MLL) on chromosome 11q23, resulting in fusion genes that drive uncontrolled cell growth. This subtype is most often found in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and is associated with a poor prognosis. In infants, the 5-year event-free and overall survival rates are around 35–40%. Despite intensive chemotherapy, outcomes remain challenging, prompting ongoing research into targeted therapies and novel treatment strategies.

  Study EGAS50000001799

• Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA

  This dataset contains a total of 10 families and 51 samples presented in 'Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA' study, in which 9 of them are cfDNA samples and the rest of samples are gDNA samples. All the samples are targeted sequencing data with a custom 45Mb capture library . Raw pair-end fastq files for each sample is available.

  Dataset EGAD00001004989

• Whole-exome sequencing of intravascular large B-Cell lymphoma

  Intravascular large B-cell lymphoma (IVLBCL) is a unique form of diffuse large B-cell lymphoma (DLBCL) characterized by extranodal cell growth especially in small vessels without systemic lymphadenopathy. The limitation in obtaining sufficient tumor materials hampers understanding the molecular pathogenesis of IVLBCL. We performed whole-exome sequencing of IVLBCL using plasma-derived cell-free DNA (cfDNA) and patient-derived xenograft (PDX) samples.

  Study EGAS00001003970

• Ischemic Stroke Genetics Study (ISGS)

  The third leading cause of death in the United States, stroke is an acute neurological event leading to death of neural tissues. Although the majority of strokes are ischemic strokes, meaning there is oxygen deprivation to the brain, almost 20% of strokes are hemorrhagic, resulting from bleeding into the brain. Stroke is a complex disorder and likely multigenic in nature, resulting from a combination of genetic and environmental factors. These well characterized risk factors that contribute to the incidence of stroke include hypertension, cardiac disease, sickle cell disease, hyperhomocysteinemia, family history of stroke and smoking. ISGS aim is to perform a prospective genetic association study of ischemic stroke focusing on the hemostatic system. ISGS is a 5-center case-control study of first-ever ischemic stroke cases and concurrent controls individually matched for age, sex and recruitment site. This data includes that from subjects both banked in the NINDS repository with biologicals publicly available, and those whose samples are not banked/not available. Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ --> This study utilized the NINDS Repository Cerebrovascular/Stroke Study, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis.

  Study phs000102

• Childhood Cancer Model Atlas

  we establish a single-site collection of 243 cell lines, including 207 paediatric cancer cell lines representing 14 distinct extracranial and brain childhood tumour types. We subjected 164 paediatric cancer cell lines to multi-omic analyses across three dimensions (DNA-sequencing, RNA-sequencing, DNA methylation) to classify them based on clinically relevant molecular subtypes.

  Study EGAS00001006320

• Inhibiton of the GABPB1L-containing GABP tetramer is sufficient to reverse replicative immortality in TERT promoter mutant glioblastoma cells.

  Over 50 types of cancer acquire TERT promoter mutations. These single point mutations reactivate telomerase, allowing for indefinite maintenance of telomere length and enabling cellular immortalization. The transcription factor binding site created by the point mutations specifically recruit the ETS factor GABP, a multimeric transcription factor composed of the GABPα and GABPβ subunits. GABP can form two functionally independent transcription factor species – a dimer or a tetramer – depending on which of the structurally distinct GABPβ isoforms is incorporated into the complex. In this study, we show that genetic disruption of GABPβ1L, a tetramer forming isoform of GABPβ that is dispensable in normal development, results in TERT silencing in a TERT promoter mutation dependent manner. Failure to activate TERT expression by GABPβ1L culminates in telomere dysfunction, DNA damage, and mitotic cell death exclusively in TERT promoter mutant cells. Furthermore, exogenous expression of TERT is sufficient to prevent telomere degradation and loss of cell viability in GABPβ1L-reduced lines bearing the mutant TERT promoter. Orthotopic injection of tetramer-deficient mutant TERT promoter GBM cells rendered lower tumor burden and prolonged the overall survival of the tumor-bearing mice. These results highlight the potentially widespread role of GABPB1L in enabling replicative immortality of TERT promoter cancers.

  Study EGAS00001002582

• Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

  Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

  Dataset EGAD00001004208

• Cookies

  Cookies https://ega-archive.org does not identify users on this site. It does use cookies, though. What is a cookie? Cookies are text files containing small amounts of information which are downloaded to your device when you visit a website. They allow a website to remember your preferences and are therefore useful to improve your online experience. Find out more information about cookies. Types of cookies we use Functional These cookies record the columns you wish to display or hide in the results page.Performance These cookies are used to analyse trends, administer the website, track visitor movements and gather broad demographic information for aggregate use. We use the information to compile reports and to help us improve our websites. These cookies are not linked to personally identifiable information. Session cookie A session cookie for a website only exists whilst the user is reading or navigating the website. When the user closes their web browser these cookies are usually removed.

  Documentation cookies

• Genome-wide NanoRCS of cfDNA from plasma of healthy individuals

  Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We adapted a new technique, NanoRCS, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to plasma of healthy controls.

  Study EGAS50000000695

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010914