12405 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

in 27.28 milliseconds.

• Childhood Cancer Survivor Study (CCSS)

  Background and Rationale for the Childhood Cancer Survivor Study (CCSS) Over the last several decades, advances in treatments for childhood and adolescent cancer have substantially improved survival following diagnosis. These improvements gave rise to the responsibility for investigating long-term treatment-associated morbidity and mortality. Early efforts to describe late effects were largely conducted through single-institution and limited consortia studies. However, by the mid-1980s, it became increasingly clear that these approaches had inherent limitations, including small sample size, convenience sampling, incompletely characterized populations, and limited length of follow-up. To overcome these limitations, the CCSS was proposed and funded by the National Cancer Institute (NCI) as a U01 grant in 1994. Subsequently, the strengths of the CCSS, including an efficient and extensive infrastructure, plus expanding database and biorepository, were recognized and appreciated. Thus, in consultation with the NCI, the CCSS was converted to a U24 (resource grant) funding mechanism to serve the scientific community in 2000. The overarching goal of the CCSS resource is to increase the conduct of innovative and high impact research related to pediatric cancer survivorship. CCSS has been used extensively by researchers from a wide range of disciplines to address a broad spectrum of topics. Strengths of the resource include its large size, comprehensive annotation of treatment exposures, ongoing longitudinal follow-up with characterization of a wide array of participant characteristics and outcomes, and an established biorepository. Design of the Childhood Cancer Survivor Study The Childhood Cancer Survivor Study (CCSS) is a multi-institutional, multi-disciplinary collaborative research resource comprised of a retrospective hospital-based cohort of survivors of childhood cancer and a comparison sibling cohort. Eligible survivors from 31 participating institutions were diagnosed between 1970 and 1999, prior to age 21 years, with selected common pediatric cancers (leukemia, central nervous system tumors, Hodgkin lymphoma, non-Hodgkin lymphoma, kidney tumors, neuroblastoma, soft tissue sarcoma, or bone tumors). All patients who survived five years from the date of diagnosis were eligible, regardless of disease or treatment status. The baseline questionnaire was completed by 24,368 survivors and 5,039 siblings recruited to serve as a comparison group. To date, participants have completed three general follow-up surveys, as well as a number of specialized surveys on specific topics (e.g. health care, insurance, screening practices, men's and women's health issues, adolescent health, sleep and fatigue). In addition, biological samples (buccal cells, saliva and/or blood) have been collected for over 11,000 participants. Full descriptions of the design and characteristics of the CCSS have been previously published (Robison et al; Leisenring et al.), and available data and samples are described at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html. Treatment Data in the Childhood Cancer Survivor Study A key feature of CCSS is the availability of detailed treatment data, which were collected by abstraction of medical records for each individual member of the cohort. Detailed abstraction included dates of therapy, protocol information, and specific details regarding surgery, chemotherapy and radiation. Quantitative dose details were collected for 22 specific chemotherapeutic agents, including alkylating agents, anthracyclines, platinum compounds and epipodophyllotoxins. In addition to individual agent doses, algorithms have been created to calculate cumulative doses of all drugs in a specific class, such as anthracyclines (doxorubicin, daunomycin and idarubicin) or platinum agents (cisplatinum and carboplatinum). Data abstracted for surgeries included dates and both the names and corresponding International Classification of Diseases (9th revision) code. For radiation treatment data, all relevant records were sent to the Radiation Physics Center at M.D. Anderson Cancer Center for detailed abstraction and dosimetry. Initial body region dosimetry was performed for all participants, followed by more detailed dosimetry as needed for specific studies. Genomics Data in the Childhood Cancer Survivor StudyThe NCI's Division of Cancer Epidemiology and Genetics and CCSS investigators collaborated to conduct genomics studies (SNP array genotyping and whole exome sequencing) using samples from the CCSS Biorepository. Studies included all cohort participants with available DNA regardless of sex or ancestry when the genomics studies were initiated. Phenotype Data in the Childhood Cancer Survivor Study Vital status and cause of death for both participants and non-participants is determined via linkage with the National Death Index (NDI). Identification of subsequent neoplasms is based on self-report, followed by validation using medical records, or via NDI. A wide array of additional health outcomes have been ascertained via a comprehensive set of questions on the CCSS questionnaires, covering potential adverse events across a range of organ systems (hearing/vision/speech, urinary, hormonal, heart and circulatory, respiratory, digestive, brain and nervous systems). In addition to health outcomes, longitudinal data have been collected on demographics, health behaviors, family history, screening practices, insurance status, and a range of psychosocial and neurocognitive factors. A full listing of available variables and copies of the CCSS questionnaires are available at http://ccss.stjude.org. Research Areas in the Childhood Cancer Survivor Study Extensive use by the research community has resulted in over 265 published manuscripts on a wide range of topics, including associations between treatment factors and mortality, subsequent neoplasms, chronic health conditions, cardiac events, neurocognitive sequelae, psychosocial factors, fertility, and health status. Additional topics have included health behaviors, screening practices, health care access and utilization, statistical and exposure assessment methodology, and development of risk prediction models. A full listing of published manuscripts using CCSS data is available on the CCSS website at https://ccss.stjude.org/published-research/publications.html. The Childhood Cancer Survivor Study as a Resource for Investigators The CCSS is an NCI-funded resource (U24 CA55727) to promote and facilitate research among long-term survivors of cancer diagnosed during childhood and adolescence. Interested investigators are encouraged to develop research ideas and propose projects within CCSS, whether or not they are from a participating CCSS institution. The CCSS is now accepting proposals to collaborate with CCSS and NCI investigators in the use of genomics data and corresponding outcomes-related data to address innovative research questions relating to potential genetic contributions to risk for treatment-related outcomes. Any researcher, or group of researchers, qualified to conduct genetic research can submit a proposal. There are no restrictions relative to country, institution, or prior involvement in CCSS. A full description of the process for developing a proposal for genetic research in CCSS can be found at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html, along with listings of approved proposals.

  Study phs001327

• How to upload Crypt4GH files

  Uploading files Users who hold an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files, please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention, such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. To manage the available resources, we enforce a limit of 10TB per submission account at any one time. If you exceed this limit, a “permission denied” message will be displayed. This will prevent you from uploading more files, but connecting to your inbox.For submissions larger than 10TB, please perform uploads in 10TB batches: register all the metadata and then finalise the submission. Upload the next batch of files and repeat the same metadata registration and finalisation process until you have completed the file upload. Further information can be found in the SP documentation. INBOX FTP The INBOX is only compatible with files encrypted using the Crypt4gh tool Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated, you will be able to request a submitter role. [Optional] Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g., ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. To upload files to your account, you can use the graphical user interface (GUI) or the command line. Graphical User Interface (GUI)We recommend using FileZilla, a free, open-source FTP client. However, you can use any other GUI that allows connecting over the SFTP protocol. For FileZilla as your GUI, follow these steps to upload files: Create a new connection in Site Manager (File > Site Manager) and select the following options (Figure 1): Protocol: SFTP - SSH File Transfer ProtocolHost: __EGA_INBOX_DOMAIN__Logon Type: Key fileUser: your EGA usernameKey file: Path/to/your/private_keyFigure 1: Process of establishing a new connection to __EGA_INBOX_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 inbox, ensuring seamless data transfers.Click Connect, and you will log in remotely to your home directory. You can think of this folder as a storage "in the EGA cloud" in which you will add your files for the EGA. The uploading area has three folders:To-encrypt: Files uploaded in this folder will be encrypted automatically on the fly.Encrypted: Files uploaded in this folder must already be encrypted with Crypt4gh. Upload your files here if your connection is unstable or you have problems completing the upload into-encrypt.Etc: This folder contains two files that allow the server to show you your username and group instead of some internal numbers. Please do not upload files here; otherwise, you will obtain a permission denied error. Find the files you want to upload by browsing your local storage (left side of your screen in FileZilla). Select all the files you want to upload, then right-click on them and select Upload (Figure 2). Figure 2: Step-by-step process of manually uploading files to __EGA_INBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can transfer data from their local storage to the "EGA cloud" by following the depicted steps Please note that regardless of which folder you upload your files in, both folders (to-encrypt, encrypted) will point to the same path (/) (Figure 3). Therefore, you will see your files in both folders. Figure 3: Both folders, to-encrypt and encrypted, point to the same path (/)" If your connection is unstable, please encrypt your files first using Crypt4gh. Then upload them to the ‘encrypted’ folder. The example above shows how to connect to __EGA_INBOX_DOMAIN__ using the private key. However, if you prefer to log in using your credentials, you can do so. Please go to the Frequently Asked Questions (FAQs)  for more information. SFTP command line To upload files securely to your private area of the EGA, you can use SFTP(Secure File Transfer Protocol) with your favorite FTP client. Here's what you need to know to get started: Connect to the target host __EGA_INBOX_DOMAIN__. This is the new hostname for the EGA SFTP service. Log in with your EGA username and key files (or password). Upload files to your private EGA inbox to ensure that only you can access the files. By following these steps, you can securely upload your files to the EGA for safe storage and sharing. Using the SFTP command line client in Linux/Unix Open a terminal and type sftp username@hostnameEnter your EGA passwordTo see a list of available SFTP commands, type helpsftp> put – Upload filesftp> get – Download filesftp> cd path – Change remote directory to ‘path’sftp> pwd – Display remote working directorysftp> lcd path – Change the local directory to ‘path’sftp> lpwd – Display local working directorysftp> ls – Display the contents of the remote working directorysftp> lls – Display the contents of the local working directoryType the "put" command to upload files. For example: put *.bamUse the bye command to close the connection (SFTP session). After uploading- Once you have uploaded files to the inbox, please bear in mind that the checksum needs to be calculated, which can take up to two days. You will only be able to link your files to a run/analysis once the encrypted checksum has been calculated.- When linking your files to the 'Run' or 'Analysis', ensure that the file name matches the file path '/name' in the INBOX folder.- Please delete the files from your SFTP INBOX after all the runs/analyses have been registered and files are ingested (SP > Files > Files ingested). This will clear your inbox space an allow you to upload more files. This will also prevent the files from reappearing in your Submitter Portal inbox. Frequently Asked Questions Specific to the inbox What username should I use to log in to my inbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username.  If you have forgotten your registered username, please contact our Helpdesk team for assistance. How are checksums calculated in your inbox? If you encrypt the file beforehand and upload it to the "encrypted" folder, the unencrypted checksum will not be calculated until the file is ingested (i.e., until it is used in a run/analysis). If the file is uploaded to the "to-encrypt" folder, then both checksums are calculated.Please bear in mind that after files have been uploaded to the inbox, the checksum must be calculated, which can take from a few hours to two days.  Specific to using keys to authenticate 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_INBOX_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 submission/data/uploading-files/inbox

• Control sets genotyped with Dynal RELI SSO and Roche Molecular Systems platfroms

  HLA typing on subjects in WTCCC and T1DGC GWA studies using Dynal RELI SSO assays (Invitrogen, Paisley, UK), sequence-specific oligonucleotide probe-based method and line strips from Roche Molecular Systems (Alameda, CA, USA)

  Study EGAS00000000032

• Familial Melanoma Sequencing

  In this experiment we have sequenced the exome of 15 individuals from eight families who have familial melanoma. By sequencing the exome we hope to be able to identify new genes that are associated with this disease.

  Study EGAS00001000017

• Blastic plasmacytoid dendritic cell neoplasm (BPDCN)_cases

  Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy that is most similar in expression profiles to plasmacytoid dendritic cells. However, patients often exhibit features of AML and can progress to AML. In this project, we will determine the differentially and commonly expressed genes between BPDCN and AML specimens. Available BPDCN and TET2-mutated AML specimens were taken for transcriptome microarray analysis.

  Dataset EGAD00010001727

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• Exome sequencing of samples for Corvin_Dublin_BipEx

  This research project was a collaboration between Trinity College Dublin, Ireland and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 191 Bipolar case/control samples from collaborators in Ireland. Genomic DNA from each sample was sequenced to a mean depth of 20x. The project used Illumina WXS sequencing of DNA and the file type is cram.

  Dataset EGAD50000000392

• Investigation of Human DNA Replication Timing Variation by Whole Genome Sequencing

  To study inter-individual variation in human DNA replication timing, we performed whole-genome sequencing of human pluripotent stem cell lines. This data was used to infer replication timing and link them to genetic polymorphisms.

  Study phs001957

• Comparison of the single-cell and single-nucleus hepatic myeloid landscape within decompensated cirrhosis patients

  In-patient comparison of single-cell RNA-sequencing (scRNA-seq) and single-nucleus (snRNA-seq) technologies and accompanying tissue processing protocols on transjugular liver biopsy from decompensated cirrhosis patients (n = 3).

  Study EGAS50000000073

• Swedish Bipolar Disorder exome sequencing (SWEBIC)

  This research project was a collaboration between the Karolinska Institute and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 5340 SWEBIC Bipolar case samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001123

• Bulk RNA-sequencing data from five lines of human iPSC-derived (hiPSC-derived) astrocytes, both alone and in co-culture with neurons, to define the molecular response of astrocytes to misfolded alpha-synuclein.

  Samples were derived from five lines of human iPSC-derived (hiPSC-derived) astrocytes, both alone and in co-culture with neurons +/- alpha-synuclein oligomer treatment. Paired-end FASTQ files for each of the samples are provided.

  Dataset EGAD50000001109

• Tumor Profiler Project - OV scRNA data additional samples

  The dataset contains 10x Chromium single-cell transcriptomics data from 6 samples from 4 different patients with ovarian cancer. 3 samples were collected from the tumor, 3 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. This dataset contains additional samples from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001293

• Tumor Profiler Project - OV scDNA data additional samples

  The dataset contains 10x Chromium single-cell DNA sequencing data from 6 samples from 5 different patients with ovarian cancer. 4 samples were collected from the tumor, and 2 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. This dataset contains additional samples from patients not classified as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001294

• Tumor Profiler Project - OV bulk transcriptomics data additional samples

  The dataset contains bulk transcriptomics data from 4 samples from 3 different patients with ovarian cancer. 3 samples were collected from the tumor, 1 sample from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. These samples are from patients not classified as as having high-grade serous adenocarcinoma.

  Dataset EGAD50000001411

• MEMORI WES bams

  This project stores bam files from deep whole exome sequencing from oesophageal adenocarcinoma at different timepoints during neoadjuvant treatment (prior, during, post treatment), which were used to analyse evolutionary and phenotype dynamics in oesophageal adenocarcinoma during neoadjuvant treatment.

  Study EGAS50000000240

• RODAM

  The RODAM study assesses the health and wellbeing of Ghanaian residents in Ghana and Europe and follows them up over time. With this unique approach the RODAM study attempts to unravel the causes of cardiovascular disease and its risk factors among African migrants in Europe and non-migrants sub-Saharan Africa. Data are available upon reasonable request. These requests can be made to de RODAM-Pros cohort coordinator (rodamcoordinator@amsterdamumc.nl) or principal investigator, Professor Charles Agyemang (c.o.agyemang@amsterdamumc.nl).

  Dac EGAC50000000474

• Transcriptome of periadrenal and subcutaneous fat in patients with hyperaldosteronism in comparison to patients with non-functional adenomas

  This study analyzed subcutaneous fat (SCF) and periadrenal fat (PAF) from patients with aldosterone-producing adenomas (APAs) and, as controls, non-functional adrenal adenomas (NFA) (SCF, n = 7; PAF, n = 5).

  Study EGAS50000001095

• Transcriptome data of periadrenal and subcutaneous fat in patients with hyperaldosteronism in comparison to patients with non-functional adenomas

  We analyzed subcutaneous adipose tissue (scAT) and periadrenal adipose tissue (paAT) from patients with Aldosterone-Producing Adenomas (APA) and, as controls, non-functional adrenal adenomas (NFA). RNA sequencing and immunohistochemistry of AT was performed (IHC, only on scAT). IHC markers included adipokines (leptin, adiponectin) and transcription factors (eg, c-jun, CaMKII)

  Dataset EGAD50000001590

• Whole transcriptome sequencing of pediatric T-cell acute lymphoblastic leukemia

  Pediatric T-cell acute lymphoblastic leukemia (T-ALL) is rare and its pathogenesis is poorly understood. To investigate molecular basis of pediatric T-ALL, we performed whole transcriptome sequencing in 123 cases of pediatric T-ALL.

  Study JGAS000090

• Whole-exome sequencing of pediatric solid tumors

  Pediatric solid tumors are rare, whose pathogenesis is poorly understood. To investigate the genetic basis of pediatric solid tumors, we performed whole exome sequencing in 16 rhabdmyosarcoma (RMS) cases and 7 pleuropulmonary blastoma (PPB) cases.

  Study JGAS000036

• Raw sequencing data from low-input chromosome conformation capture in CD4+ T cells

  This dataset contains raw sequencing data from low-input PCHi-C in human primary CD4+ T cells isolated from healthy donors. The data are released as paired-end Illumina FASTQ files. Promoter Capture Hi-C used DpnII digestion and Tn5-based low-input library preparation, followed by targeted capture with custom-designed biotinylated RNA probes targeting most of the annotated gene promoters.

  Dataset EGAD50000001873

• TB-DAR Genotyping Study

  Active TB patients (sputum smear-positive and GeneXpert-positive) recruited at the Temeke District Hospital in Dar es Salaam, Tanzania, as part of a prospective study that ran between November 2013 and June 2022 (TB-DAR cohort).

  Study EGAS00001007216

• Celiac disease case-control North Indian Immunochip dataset

  Illumina Immunochip genotype data for coeliac disease and control samples of North Indian samples origin. Data is in PLINK binary format. Calling algorithm for genotypes is based on GenomeStudio (GenTrain), with manual clustering of selected variants.

  Study EGAS00001000849

• Breast Cancer PDTX Encyclopaedia

  Molecular data from the collection of PDTX breast cancer models described in Bruna et al, 2016. Cell. It includes whole exome sequencing, shallow whole genome sequencing, expression arrays and reduced bisulfite representation sequencing (RRBS).

  Study EGAS00001001913

• Genomic characterization of NUT midline carcinoma

  In this study, we sequenced two NUT midline carcinoma genomes. Analysis of rearrangement breakpoint provided information on the generating event of BRD-NUT rearrangements. Mutational signature analysis also revealed biological process during tumorigenesis of NUT midline carcinomas.

  Study EGAS00001001934

• Shwachman_Diamond_syndrome__SDS___Exome_sequencing

  Shwachman-Diamond syndrome (SDS) is a rare autosomal recessive disorder characterized by exocrine pancreatic insufficiency, bone marrow dysfunction, leukemia predisposition, and skeletal abnormalities. We aim to characterise the structural effects of SDS in patients with this disorder by exome sequencing.

  Study EGAS00001000264

• HCA_Thymus_Paediatric_ThyDesign_RNA_Managed_Access

  T cells are central to adaptive immunity and thus crucial for understanding and treating human disease. While extensively studied in model organisms, translating this knowledge to humans can sometimes be limited by their rapid cross-species evolution and diverse

  Study EGAS00001007687

• Whole exome and whole genome sequencing of juvenile myelomonocytic leukemia (JMML)

  To obtain a complete registry of gene mutations in JMML, whole-exome sequencing was performed for paired tumor-normal DNA from 13 JMML cases, of which 2 cases were also analyzed by whole genome sequencing.

  Study EGAS00001000521

• ChIP-seq data of Hodgkin lymphoma cell line L-428

  ChIP-seq data (H3K4Me3, H3K27Ac histone modifications) of Hodgkin lymphoma cell line L-428. Samples were processed as previously described (Sud et al., 2018). The files are in bam format, aligned to build 37.

  Study EGAS00001003033

• Metastatic_Breast_Cancer_Whole_Genome

  We propose to definitively characterise the somatic genetics of Metastatic breast cancer through generation of comprehensive catalogues of somatic mutations in Metastatic breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000902

• BASIS_RNAseq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000707

• The Druze analysis group

  To comprehensively characterize the genetic structure of the Druze population, we recruited and genotyped 40 parent-offspring trios from the Upper Galilee in Israel and the Golan Heights, attempting to capture different extended families (clans) across various geographical locations.

  Study EGAS00001000963

• Whole_Exome_PC9_and_A375

  Drug resistant population of PC9(human non-small cell lung cancer) or A375 (human melanoma) cell lines were used for this study. By exome sequencing, we will analyse mutations of cells in drug tolerent state and after drug holiday.

  Study EGAS00001002493

• Breast_Cancer_FRT_RNA_seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000420

• Discovery_of_resistance_mechanisms_to_the_BRAF_inhibitor_vemurafenib_in_metastatic_BRAF_mutant_melanoma

  Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment ‘sensitive’ to recurrence ‘resistant’ tumours to identify the genetics of drug resistance.

  Study EGAS00001000551

• Breast_Cancer_Whole_Genome_Sequencing

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000210

• Triple_Negative_Breast_Cancer_RNA_Sequencing

  We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000377

• BLUEPRINT Epigenetic characterization of megakaryocytes and erythroblasts

  Megakaryocytes and erythroblasts derive from the same progenitor cell type but carry out very different functions. In order to understand how the different functional phenotypes arise we have characterised the epigenetic landscape of these cells.

  Study EGAS00001001641

• Blueprint RNAseq profile of purified plasma cells from multiple myeloma patients and tonsils of healthy donors

  In the context of an epigenomic study of multiple myeloma, a have generated RNAseq profiles of purified plasma cells from 11 multiple myeloma patients and tonsils of 4 healthy donors

  Study EGAS00001001110

• BCL11B enhancer hijacking defines a subtype of lineage ambiguous stem cell leukemia

  Hijacking of primitive hematopoietic enhancers, or generation of a neo-enhancer by genomic amplification, results in deregulation of BCL11B as the defining feature of a subset of T/myeloid leukemia

  Study EGAS00001004810

• arrayCGH for copy number profiling on tumor DNA from pediatric cancer tissue samples

  This dataset contains arrayCGH (HumanCytoSNP 850k and HumanCytoSNP v12.1) data from tumor DNA samples of various pediatric cancer entities. Files are provided in IDAT format and as text files processed with GenomeStudio 2.0.

  Study EGAS00001005197

• COIN CRC GWAS data

  Genotype data from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

  Study EGAS00001005421

• Molecular programs of melanoma brain metastases (MBM)

  We performed paired-end whole transcriptome sequencing of fresh frozen or intraoperative brain metastases of therapeutically treated stage IV melanoma patients. In addition, we analysed the epigenetic landscape of tumors usind Illumina 850k bead chip technology.

  Study EGAS00001005976

• Dedifferentiated_Melanoma

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up.

  Study EGAS00001003471

• Hepatitis B Viral sequence reads

  Deep sequencing of viral samples (average ~9,000x coverage) from patients chronically infected with Hepatitis B (HBV). Whole HBV genome sequencing of 1467 patients (1102 in discovery and 365 in validation cohort) chronically infected with HBV at baseline. The patient population contained HBV genotypes A (98), B (285), C (716), D (356), E (7), and F (5) with 977 HBeAg-positive and 490 HBeAg-negative patients.

  Dataset EGAD00001005075

• Mate Pair Sequencing data for Molecular Characterization of ETMRs

  This dataset contains Mate Pair Sequencing data from 15 samples from 13 patients. Mate pair DNA library preparation was carried out using the Illumina MP v.2 reagents and protocol. In brief, fragmentation of genomic DNA was performed using a Hydroshear device to an insert size of 4.5 kb followed by sequencing with Illumina HiSeq 2000 instruments resulting in 30 Fastq files (paired end).

  Dataset EGAD00001006207

• Whole genome sequencing of HSPCs and pAML

  Whole genome sequencing data (Illumina HiSeq and NovaSeq) of clonal cultures derived from pediatric human bone marrow-derived hematopoietic stem and multipotent progenitor cells (in total 44 samples from 10 donors) and bulk pediatric acute myeloid leukemia blasts (in total 6 samples from 6 patients) to study the mutation accumulation.

  Dataset EGAD00001006338

• Bulk RNAseq data of scrambled and siRNA-mediated knock-down of the minor spliceosome snRNA U6atac

  Bulk RNAseq data of scrambled and siRNA-mediated knock-down of the minor spliceosome snRNA U6atac in androgen-sensitive LNCaP cells (L), androgen-insensitive C4-2 (C) and 22Rv1 (R) cells and in patient derived neuroendocrine organoids PM154 (P).

  Dataset EGAD00001008034

• RNAseq Atlas in HCC tumors

  The atlas provides a comprehensive exploration of genetic and transcriptomic landscapes within HCC, offering insights into key genomic alterations and gene expression patterns. The integration of DNA sequencing and RNAseq data enhances our understanding of the molecular complexity underlying HCC, potentially paving the way for targeted therapeutic strategies and biomarker discovery in the context of hepatocellular carcinoma.

  Dataset EGAD00001015341

• Transcriptome Changes in ASD (NRXN1α+/-) iPSC-derived neurons

  This dataset contains 10 fastq files from 10 cell lines (4 cell lines from 3 patients and 6 cell lines from 4 controls) that have undergone 50bp single end sequencing with PolyA enrichment strategy (BGI project number HUMpcsN). *please note one of the samples (Patient_4) was named in error and should be corrected to Patient_3 during analysis

  Dataset EGAD00001007993

• A Single Complex Agpat2 Allele In A Patient With Partial Lipodystrophy data

  The dataset contains data from a single patient sample with partial lipodystrophy. The data is supplied in the form of 2 files. , a BAM file containing the (raw) sequencing data and a VCF file containing the called variants. The data is limited to a region consisting of the AGPAT2 gene on chromosome 9 and 1MB on both sides.

  Dataset EGAD00001004314

• ChIP sequencing data to study therapeutic targeting of ependymoma

  This dataset contains ChIP sequencing data from 24 patients. ChIP of 5–10 mg flash-frozen primary ependymoma tumour was performed using 5 mg H3K27ac antibody per ChIP experiment. The enriched DNA has been sequenced on a Illumina HiSeq2000 instrument in paired-end mode. Up to two lanes per sample have been sequenced resulting in 70 Fastq files.

  Dataset EGAD00001003979

• Isotype-resolved sequencing of B-cell receptor in health and disease (2017-09-13)

  Sequencing of B-cell receptor repertoires in healthy individuals and patients with chronic lymphocytic leukemia. 1) 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 please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-09-13.

  Dataset EGAD00001003748

• Cholangiocarcinoma whole genome sequencing data 12 samples

  This dataset contains whole genome sequencing FASTQ data for 12 cholangiocarcinoma tumor samples, and their matched normal samples. These 12 samples are in addition to 59 samples available in dataset EGAD00001001988, and consist of patients from Thailand, Romania, and Singapore. Paired-end sequencing data was generated by Illumina Hiseq 2000 and 2500, with insert sizes of 170 and 350.

  Dataset EGAD00001003834

• Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq), targeted TCR sequencing in RNA (RNA-TCRseq) from breast cancer samples.

  Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq) bam files. Targeted TCR sequencing in RNA (RNA-TCRseq) cram files.

  Dataset EGAD00001003933

• Ewing's Sarcoma RNA-Seq

  28 Pretreated Ewing sarcoma tumor blood samples were collected from the Hospital for Sick Children (SickKids) and Mount Sinai Hospital in Toronto, Canada in accordance with each institution’s Research Ethical Board (REB) guidelines. Detailed clinical information (age at presentation, gender, tumor site, stage, etc.) were obtained from the corresponding institutional tumor banks. Transcriptome (RNA-Seq) sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001004188

• Bam files from whole exome sequencing (WES)from multiple laser microdissected regions from tumor and paired biopsies from metastatic lesions.

  In this study we characterized genomic alterations in three bladder cancer patients with metastatic disease courses. Multiple regions were procured by laser microdissection or punctures from primary tumor, lymph node metastases and from distant metastases. Data provided here consist of 35 Bam files for WES (32 Tumors and 2 blood, 1 adjacent normal)

  Dataset EGAD00001002772

• RNA-seq data of Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Patient-matched normal kidney organoid (103H) and MRT tumoroid (103T2) models were treated for 24h with either DMSO (ctrl), 400nM MTX, or 50nM BAY to investigate the direct effects of drug treatment on the expression of key metabolic enzymes in the nucleotide biosynthesis pathways.

  Dataset EGAD00001015391

• A Randomized Trial of Combined PD-L1 and CTLA-4 Inhibition with Targeted Low-Dose or Hypofractionated Radiation for Patients with Metastatic Colorectal Cancer

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal (CRC) or non-small cell lung cancer (NSCLC) that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 2. Please see phs003295 for Cohort 1COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies/AssaysIHCmIFOlinkCyTOFRNAseqWES

  Study phs003294

• A body map of somatic mutagenesis in morphologically normal human tissues (WES)

  Study EGAS00001005459

• DAC for the study of response to EGFR Blockade in Colorectal Cancer

  Dac EGAC00001000360

• DAC Genomic and transcriptomic profiling of signalling networks in follicular lymphoma

  Dac EGAC00001000577

• DAC for study: Frequent mutation of the FOXA1 untranslated region in prostate cancer

  Dac EGAC00001000962

• The molecular landscape of glioma in patients with Neurofibromatosis 1

  Dac EGAC00001001004

• DAC for study: Evaluation of commercial Guardant360 ctDNA test in metastatic prostate cancer

  Dac EGAC00001001082

• snRNA-seq in white matter post-mortem tissue from MS and controls - DAC

  Dac EGAC00001001105

• DAC for Enhancer-gene rewiring in the pathogenesis of Quebec Platelet Disorder

  Dac EGAC00001001529

• Inherited CD28 deficiency in otherwise healthy patients with disseminated warts and giant horns

  Dac EGAC00001001835

• AGECAN - DAC (Interespecies conservation of brain specific DNA methylation in aging and cancer)

  Dac EGAC00001001840

• COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

  Dac EGAC00001002480

• Follicular lymphoma at diagnosis, treated in first line with immunochemotherapy Data Acces Comitee

  Dac EGAC00001002912

• DAC for ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA

  Dac EGAC00001003141

• Ychromosome_dataset

  Genotyping of Y chromosome in Polish population

  Dataset EGAD00010001807

• COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

  Dac EGAC00001003435

• Data Access Committee for study Positive Selection in Peruvians from Three Ecological Regions

  Dac EGAC00001002414

• Nanopore Cas9 Targeted Long Read Sequencing in adults with autism spectrum disorder

  Dac EGAC50000000349

• Nicola Valeri ICR

  WGS data from primary CRCs tissues in ctDNA positive patients

  Dac EGAC50000000395

• Genomic profiling of patient-derived xenografts and organoids in prostate cancer

  Study EGAS00001004673

• Transcriptomic profiling of patient-derived xenografts and organoids in prostate cancer

  Study EGAS00001004675

• AGECAN - Interespecies conservation of brain specific DNA methylation in aging and cancer

  Study EGAS00001004851

• Somatic mutations increase hepatic clonal fitness and regeneration in chronic liver disease

  Study EGAS00001003496

• Measuring minimal residual disease in acute myeloid leukemia with MASQ

  Study EGAS00001003732

• Association of DNA-methylation profiles with immune responses in breast cancer patients

  Study EGAS00001004211

• HDAC3 mediates the inflammatory response and LPS tolerance in human monocytes and macrophages

  Study EGAS00001004218

• The impact of urbanization and diet on innate immune responses in healthy Tanzanians

  Study EGAS00001004284

• Profiling Genome-Wide DNA Methylation Patterns in Human Aortic and Mitral Valves

  Study EGAS00001004559

• Selective Elimination of Immunosuppressive T cells in Patients with Multiple Myeloma

  Study EGAS00001004915

• Mutational consequences of hematopoietic stem cell transplantation in humans

  Study EGAS00001004926

• Searching for genetic modulators of the phenotypic heterogeneity in Brugada Syndrome

  Study EGAS00001005848

• Validation study of genome-wide polygenic score for body mass index in South Asians

  Dac EGAC00001003593

• Genome-wide somatic variants in CRC (GRCh38)

  Study EGAS00001004710

• Illumina Human Exome (ExomeChip) genotype data from the Pomak villages in Greece (HELIC Pomak Isolate). 1040 samples all >=16 years old.

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina HumanExome Beadchip. The HELIC (Hellenic Isolated Cohorts) Pomak collection focuses on the Pomak villages in Greece. Recruitment of this population-based sample was primarily carried out at the village medical centres. www.helic.org

  Study EGAS00001000658

• Mutations in GNAI2 Cause Developmental and Immune Dysregulation

  To define a genetic syndrome of dysmorphism, brain malformations, skeletal defects, endocrine and immune dysfunction, 11 patients from 11 unrelated families who had similar features were studied. Whole exome sequencing was performed to identify disease-causing mutations. A disease segregated with de-novo or autosomal dominant mutations in a single gene, GNAI2, encoding the G&#945;i2 protein. We define a new Congenital Disorder associated with G&#945;i2 mutations and downstream functional effects.

  Study phs002817

• Genetics of Schizophrenia in an Ashkenazi Jewish Case-Control Cohort

  Schizophrenia is characterized by high heritability (&#126;80&#37;), yet the identification of susceptibility genes has proven extremely challenging. The Ashkenazi Jewish population, derived from a limited number of founders, may be enriched for a subset of susceptibility alleles, which may also have higher odds ratios than those detected by previous studies. GWAS was conducted in a large Ashkenazi case-control cohort, derived from the Hebrew University Genetic Resource, using the Illumina HumanOmni1-Quad BeadChip.

  Study phs000448

• Improved T Cell Immunity Following Neoadjuvant Chemotherapy in Ovarian Cancer

  This study characterized the evolution of the peripheral immune cell function and composition across the course of standard of care platinum and taxane chemotherapy in ovarian cancer using bulk and single cell transcriptomic approaches. Serial blood samples were collected from ten patients with advanced high-grade serous ovarian cancer treated with chemotherapy. Single cell sequencing was performed on five patients&#39; samples collected before the initiation of chemotherapy and after the third cycle of chemotherapy.

  Study phs002862

• A Pilot Study of NKTR-214 and Nivolumab in Selected Patients with Locally Advanced/Metastatic Sarcoma

  Study cohort comprises samples derived from patients that received treatment on an open-label, non-randomized, non-comparative pilot study of bempegaldesleukin, a CD122-preferential interleukin-2 pathway agonist, with nivolumab in refractory sarcoma at Memorial Sloan Kettering/MD Anderson Cancer Centers (NCT03282344). Patient tumors include a variety of sarcoma subtypes. Samples include whole exome sequencing of tumor/normal pairs, poly-A RNA and TCR sequencing of tumors.

  Study phs002852

• Reference Profiles of ExRNAs in Normal Human Pregnancy

  In this study, we did a comprehensive exRNA profiling of plasma and serum specimens from healthy pregnant women, sampled at different gestational time points, and including subjects with diverse geographical and ethnic backgrounds. This study also contains samples from male and female healthy donors to provide a baseline. The aim of this study is to identify miRNAs that can predict the gestation age and to build a miRNA profile across gestation using small RNA-seq data.

  Study phs003182

• Single cell analysis reveals new evolutionary complexity in uveal melanoma

  Uveal melanoma (UM) is a rare eye cancer that is highly aggressive and leads to metastatic death in up to half of patients. Here, we conduct droplet-based single-cell RNA sequencing of 59,915 neoplastic and non-neoplastic cells from 8 primary and 3 metastatic UMs. Single-cell VDJ sequencing of RNA is conducted to determine clonally expanded B/T- cell populations. Single-cell DNA sequencing of 1 primary and 1 metastasis is utilized.

  Study phs001861

• Platinum-based chemotherapy induces opposing effects on immunotherapy response-related spatial and stromal biomarkers in the bladder cancer microenvironment

  The goal of the current project was to investigate the modulation of the tumor-immune microenvironment (TME) by neo-adjuvant platinum-based chemotherapy in muscle-invasive bladder cancer. Furthermore, we aimed to focus on how this modulation affects biomarkers of response to immune checkpoint inhibitors. Additionally, we aimed to explore the differences between MVAC and gemcitabine-containing platinum-based regimens regarding their effects on the bladder TME.

  Study EGAS50000000309

• Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

  Here, we applied single-cell RNA-sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same pediatric classical Hodgkin Lymphoma (cHL) tumors. Specifically, 13 cHL patients and 3 reactive lymph node control samples were included in this cohort. This allowed us to identify genes of cell surface proteins that are consistently overexpressed in HRS cells and can potentially be used as targets for antibody-drug conjugates or CAR T cells. Finally, we identify potential interactions by which HRS cells inhibit T cells, among which the Galectin-1/CD69 and HLA-DRA/LAG3 interactions. However, high levels of inter-patient heterogeneity of the interaction strength were observed. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets.

  Dataset EGAD50000000626