16490 results for "sec+and+unspecified+malignant+neoplasm"

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• ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity

  Chronic inflammation in autoimmunity is driven by hyperactive T cells with dysregulated metabolism. ABHD11 is a mitochondrial hydrolase that supports alpha-ketoglutarate dehydrogenase function and has been associated with remission in rheumatoid arthritis. To explore its role in T cell function, we used CRISPR/Cas9 to knock down ABHD11 in Jurkat T cells and performed RNA-Seq analysis. Differential gene expression revealed widespread transcriptional changes, with sterol-related pathways among the most significantly enriched. These findings highlight ABHD11 as a potential regulator of metabolic programming in T cells with implications for autoimmunity.

  Study EGAS50000001297

• High Sensitivity ctDNA Analysis Using a Novel Panel and NOIR-SS Technology for Monitoring Advanced Urothelial Carcinoma

  This dataset contains sequencing data generated by targeted amplicon analysis using the NOIR-SS method in 15 patients with advanced urothelial carcinoma. Formalin-fixed paraffin-embedded (FFPE) tumor tissues (15 samples) and plasma cfDNA (50 samples) were analyzed. Tumor tissues were subjected to targeted panel sequencing to identify mutations in TP53, FGFR3, TERT, and KRAS/HRAS. Plasma cfDNA was analyzed using a tumor-informed approach focusing on the mutations identified in matched tumor tissues. Sequencing was performed on the Ion PGM or Ion S5 XL platform. Raw sequencing data are provided in FASTQ format under controlled access.

  Study JGAS000836

• Comprehensive genetic landscape, immune checkpoint profiling, and establishment of patient-derived xenograft (PDX) of metachronous brain tumors from constitutive mismatch repair deficiency with a biallelic variant on MSH6

  Constitutional mismatch repair deficiency (CMMRD) syndrome is a rare genetic disorder caused by biallelic pathogenic variants in mismatch repair genes (PMS2, MSH6, MLH1, or MSH2) resulting in the development of a variety of different tumors, including brain neoplasms. This study molecularly characterized a Brazilian child with CMMRD, harboring two metachronous brain tumors (medulloblastoma and high-grade glioma), and established a patient-derived xenograft (PDX) of the CMMRD-associated brain tumor. Keywords: Brazil, Constitutional mismatch repair deficiency syndrome, exome, MSH6, medulloblastoma, high-grade glioma.

  Study EGAS50000000351

• PD-associated regulatory variants in human dopaminergic neurons reveals modulators of SCARB2 and BAG3 expression

  SNPs have been associated with the risk of Parkinson’s disease but not in regulatory regions. While those potentially disrupt TFBS altering gene expression and contributing to cis-regulatory variation. To study changes in A and B compartment interactions and in topologically associated domains (TADs), we sequenced: - 3D chromatin contact using LowC, 6 samples. 3 replicates for each condition: smNPC (controls) cells and differentiated neurons after 30 days. Resulting paired-end are provided as BAM files. In order to confirm the predicted impact of the PD-associated allele of rs144814361 on BAG3 promoter, we proceeded with genome editing of the TH-REP1 cell line by using prime editing to insert the “T” allele at the position chr10:119651405 in the BAG3 promoter. - Chromatin accessibility using ATAC-seq, 9 samples of derived cell line TH-REP1. 3 replicates for each condition: 1) iPSC Wild Type 2) SNP-BAG3 variant in iPSC 3) SNP-BAG3 variant in smNPC. BAG3 variant: heterozygous for the SNP variant: rs144814361 (chr10 119651405) Resulting sequencing are provided as paired-end FASTQ files.

  Dataset EGAD50000002258

• Spatial predictors of response to immunotherapy in microsatellite stable metastatic colorectal cancer

  Microsatellite stable (MSS) colorectal cancers (CRC) are largely unresponsive to immune checkpoint inhibition (ICI), prompting investigation into strategies to enhance sensitivity. The MAYA trial, which utilized temozolomide (TMZ) in MGMT-silenced MSS mCRC, hypothesized that TMZ-induced hypermutation could sensitize tumors to ICI. This phase II trial met its primary endpoint, demonstrating durable clinical responses with TMZ combined with ipilimumab and nivolumab. To elucidate factors in uencing response heterogeneity, we conducted multi-omic spatial pro ling of samples from patients who participated in the MAYA trial, including baseline and on-treatment tissue and blood specimens. While increased neoantigen load following TMZ exposure did not consistently predict for deep responses, spatial profiling revealed key determinants. Lymphocyte proportions, particularly CD8+KI67+ cells, within stromal and tumor compartments, along with macrophage composition (CD68+CD163+ cells) at the tumor-stromal interface, were predictive of response. Treatment pressures dynamically altered the tumor microenvironment composition and activated peripheral immune cells. This study is the first to identify spatial predictors of response to this promising novel treatment approach for MSS CRC.

  Dataset EGAD50000002244

• Stage-specific gene and transcript dynamics in human male germ cells

  The testis is one of the most transcriptionallyactive organs, however how germ cell differentiation is controlled at the molecular level remains largely unknown. To study global transcriptional dynamics during human spermatogenesis we sequenced total RNA of human testicular biopsies with 5 specific histological phenotypes: Sertoli cell-only (SCO, n=3), spermatogenic arrests at the spermatogonial (SPG, n=4), spermatocyte (SPC, n=3), and spermatid (SPD, n=3) level, as well as normal spermatogenesis (Normal, n=3). To our knowledge, this work provides the most complete capture of the transcriptome and its dynamics during human spermatogenesis to date.

  Study EGAS00001006135

• Pancreatic cancer organoids recapitulate disease and allow personalized drug screening

  We report derivation of 30 Patient-Derived Organoid lines (PDOs) from tumors arising in the pancreas and distal bile duct. PDOs recapitulate tumor histology and contain genetic alterations typical for pancreatic cancer. In vitro testing of a panel of 76 therapeutic agents revealed sensitivities currently not exploited in the clinic. The PRMT5 inhibitor EZP015556, shown to target MTAP negative tumors, was validated as such, but also appeared to constitute an effective therapy for a subset of MTAP+ tumors. Taken together, the work presented here provides a platform to identify novel therapeutics to target pancreatic tumor cells using PDOs.

  Study EGAS00001003369

• Novel Epigenetic Markers for Toxicity after Intraoperative and Conventional Radiotherapy for Breast Cancer

  Ionizing radiation is a common treatment option for cancer but its use is limited by the unpredictable and highly heterogeneous onset of late side effects, especially radiation-induced fibrosis. Clinically applicable biomarkers and effective treatments for radiation fibrosis are currently unavailable. In order to identify novel markers we ran a genome-wide DNA methylation screen in primary dermal fibroblasts obtained from breast cancer patients before intraoperative radiotherapy. Cells from patients developing fibrosis within a three-year follow up were compared to those without fibrosis (12 individuals per group). Illumina Infinium HumanMethylation450 BeadChip Technology was used.

  Study EGAS00001001279

• A WTCCC2 genome-wide association study for psychosis endophenotype (PE) in individuals from UK, Germany, Holland, Spain and Australia.

  A WTCCC2 project genome-wide association study for psychosis endophenotype (PE) in 5831 individuals from UK, Germany, Holland, Spain and Australia, genotyped on the Affymetrix 6.0 array. Information about the family structure of the samples can be found in the .info file which accompanies the data. It should be noted that a number of samples in this study have no phenotype information including sex, case status and family membership. Details of the WTCCC2 analysis can be found in Bramon et al. [Biol Psychiatry. 2014 Mar 1;75(5):386-97].

  Study EGAS00001000817

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• Alloreactive T-cell receptor (TCR) repertoire in kidney transplantation

  We analyzed the T-cell receptor (TCR) repertoires from twelve kidney transplant recipients. Six out of the twelve kidney transplant recipients experienced a cellular rejection after kidney transplantation. TCR repertoires of CD4+ and CD8+ positive T-cells were assessed prior to transplantation and after transplantation at time of allograft biopsy using RNA based T-cell receptor beta next generation sequencing (NGS). In addition, the pre-formed alloreactive TCR repertoire for each kidney transplant recipient was identified using mixed lymphocyte reaction and donor reactive T-cells were subjected to TCR beta sequencing. In two out of the six patients with cellular rejection the TCR repertoire of graft infiltrating T-cells was additionally captured. This dataset comprises a total of 98 samples. NGS TCR beta libraries of all samples were sequenced on an Illumina NextSeq 500 and raw sequencing data (in the form of fastq files) as well assembled clonotypes and their counts (in the form of clonotype tables) are provided.

  Dataset EGAD00001007695

• PopCol 16S gut microbiome sequencing

  PopCol is a cohort study in Stockholm, Sweden that includes a data-rich set of individuals with data available from bowel symptoms questionnaires, gastroenterology visits and biospecimens (genotype and 16S sequencing from blood and stool samples, respectively). Genotyping was carried out using the Illumina HumanOmniExpressExome-8v1 arrays at the SciLifeLab NGI facility in Uppsala, Sweden. Fecal DNA was extracted from samples kept at -80°C using Qiagen 5 QIAamp DNA Stool Mini Kits and analyzed using 16S rRNA gene amplicon sequencing (in the V1-V2 hypervariable region). This was performed on the Illumina MiSeq platform at the Institute of Clinical Molecular Biology (IKMB) in Kiel, Germany. Of these, six PopCol participants were PPI users and 12 used antibiotics. The study was approved by the local Committee of Research Ethics (Forskningskommitté Syd) at Karolinska Institutet, Stockholm, in November 2001. Written informed consent was obtained from all participants

  Dataset EGAD00001007071

• The long term effects of chemotherapy on normal blood - Nanoseq dataset

  In developed countries, ~10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, hence triggering cell death. However, there is limited understanding of the extent and consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

  Dataset EGAD00001015340

• SINGLE CELL ANALYSIS OF IN VITRO ERYTHROPOIESIS

  We are developing a protocol to differentiate mouse and human induced pluripotent stem (IPS) and embryonic stem (ES) cells towards the haematopoietic pathway to generate erythrocytes in vitro. This system has many applications such as the study of the role of specific genes and human polymorphisms in infectious diseases such as malaria, as well as haematological diseases such as myelodysplastic syndrome. The nature of the in vitro differentiation process means that a heterogeneous population of cells is generated. In order to understand the types of cells produced with our protocol, we have performed a single cell analysis, which has the power to reveal the different populations of cells and their characteristics. For this, a cDNA library has been made that needs to be sequenced to obtain the gene expression profiles of the different cells. With this information we will be able to assess the quality of the differentiation protocol and improve it in order to produce better cells for the downstream applications.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/

  Dataset EGAD00001000979

• All you need to know about our new DAC Portal

  With the DAC Portal, it is possible to streamline the process of managing access to sensitive data, ensuring that researchers have the necessary resources to advance scientific discovery while maintaining the highest standards of data protection and privacy. We know that, as a new tool, its first use can be complex. For this reason, in this article we will try to show all the elements of interest. Enjoy! Credentials: who needs to create a new user to access the DAC Portal and who doesn't? Only new users (since September the 12th) need to create an EGA account to access the DAC Portal. The EGA team went one step ahead by creating EGA accounts for former DAC members to login to the DAC Portal. These accounts are linked to the personal email used in the DAC structure: To check the linked email, DAC members can paste the DAC ID right after this link: https://metadata.ega-archive.org/dacs/ (e.g. https://metadata.ega-archive.org/dacs/EGAC00001002543) In case of password oblivion, it is possible to set a new one. All the process is channelled through the personal email. Some DAC members may be interested in updating the DAC email. This action can be done contacting our Helpdesk team. For the correct functioning of the DAC Portal, users must add the missing information of the DAC Profile. For a deeper dive, check out our documentation. The first step: knowing your workspace on the Portal Once logged in to the platform using the EGA User credentials, note the sections available: DACs and Policies. In the first one it is possible to check all user's registered DACs by default. It provides a comprehensive overview of each DAC, including its EGA accessions (EGAC), title, status, and the number of data access requests associated with each DAC. Whereas the Policies section is where users can manage and view all their registered policies, along with their associated EGA accessions, links, and titles. A drop-down menu is available with shortcuts to the most useful pages in the top right corner. It is possible to check DACs and policies, as well as creating new ones. In this menu, users can also contact the Helpdesk team using the “Need Help?” section to make inquiries about DACs and policies. Comprehending the DACs list & making the most of all the features Colours are crucial in the DAC's section as they will indicate the user role and the status in every committee, namely: Yellow: you are the administrator of the DAC and have full control to add other contacts, modify the content, and manage data access requests. Orange: you are a member of the DAC and have the authority to manage data access requests but cannot make any changes to the content. Blue: you have been invited to join the DAC and need to either accept or decline the invitation. Grey: the DAC is currently pending validation by the EGA Helpdesk team. Red: the DAC has been declined by the EGA Helpdesk team. Discover more information on how to view the message from Helpdesk containing the declination reason or how to validate or reject a DAC invitation by taking the tour of the DAC Portal. How to create, register and edit a DAC Creating a DAC is an easy process that only requires users to complete the necessary information. After that, the EGA Helpdesk team will review the proposal and validate the proposal. Once the DAC is validated it is possible for authorised users with admin role to edit it at any time, ensuring that all information and contacts associated with the committee is accurate and up to date. Membership management is controlled by searching for the EGA user looking for their username, email, or organisation. Please, note that for a person's details to appear in this search engine, they must have registered as a EGA user. Data Access Committee administrators manage two types of permissions that apply to contacts: Main contact and Role. Both can be modified at any time: Main contact refers to the primary person we firstly contact for any inquiry about the DAC (please, note that we can contact all DAC members, and this refers to the person we will contact first). Role defines the actions that can be taken by each contact. There are two possible status, admin and member, details of which can be found in the Take the Tour. Keep in mind that, to save the modifications, it is always necessary to click on “Update”. Moreover, it is also possible to delete any contact in a DAC whenever it is needed. The data request process: how to manage access requests The data request process is now channelled through the EGA website. Once a user sends a request access, the petition will go directly to the DAC Portal profile of the DAC members liked to the requested dataset. Whenever a request is received, a sand clock symbol will be displayed next to the DAC responsible for the dataset involved. By clicking on the DAC, it is possible to discover more information about requester(s). In this section, DAC Portal users will also be able to modify the display of the data access requests. It is possible to group requests by dataset accession or username, depending on the user preferences. Additionally, it is possible to isolate specific requests by user or dataset. To accept a request, users must slide the button to the right. Once the button turns green, it signifies that the request is accepted; the requester will be granted access to the requested dataset. To make lives easier, we have implemented a “Select all” button to easily accept or revoke multiple requests at once. To decline requests, it is necessary to slide the button to the left. A red button means the requester will not be granted access to the dataset. The DAC Portal will always ask to submit the reason why the data access was denied. Please, note that any decision, grant or denial, must be confirmed clicking the "Apply" button. This will update the status of the request and notify the requester accordingly. Taking control of the activity in the DAC Portal: checking the requests history The History button is a useful feature that allows users to access a list of all the requests that have been granted. This is especially useful for auditing purposes, as it enables to keep track of who has been granted access to the data and when. To facilitate control for those users with several requests we have included a filtering option. It allows to filter requests by user, mail, dataset, EGA ID, and date (these are combinable to boost the search). Don't forget about policies: creation, management, and update Similarly to the DACs section, in the Policies one users can manage and view all their registered policies. By clicking on any policy, it is possible to view its details as well as making any necessary updates or modifications. The sheets symbol and its adjacent number indicate the quantity of objects using a policy. By clicking in the location symbol users will go directly to the DAC page on the DAC Portal to see more information about that DAC. DAC Portal users can create new policies. The first step requires to link the policy to a registered DAC. After defining the title, users can either add a link to an external URL containing terms & conditions or write the policy content directly on the DAC Portal. Keep in mind that both options can be included. Data Use Ontology (DUO) codes can be added to new policies. These codes are used to specify the permitted and prohibited uses of the data. Please, note that some of them require a modifier to provide additional specificity. Find out more by checking out this specific content on the DAC Portal Tour. Policies can be modified at any given time by clicking on one registered policy, which will display the current information.

  Blog new-dac-portal

• Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Pilot study Pilocytic Astrocytoma ICGC PedBrain, whole genome sequencing of 5 tumors and matched blood

  Dataset EGAD00001000271

• Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

  Dataset EGAD00001000308

• Oncoscan SNP arrays for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 82 Oncoscan SNP tumor initial samples, zipped Affymetrix CEL file types, Oncoscan CNV FFPE Assay Kit, Thermo Fisher Scientific GeneChipTM Scanner 3000 7G

  Dataset EGAD00010001978

• med-pchic-dac

  The data are accessible under the terms of the following Data Access Agreement that needs to be filled in, signed (by yourself and your institution’s official contact) and returned by email to med-pchic-dac@lists.cam.ac.uk

  Dac EGAC00001000523

• IMpower133 (GO30081) clinical data and biomarker data

  Relevant clinical data for IMpower133 (GO30081) including treatment arm, overall survival, progression-free survival, best overall response, PD-L1 IHC, molecular subtype, and baseline clinical features.

  Dataset EGAD50000000195

• Sequence-Based Analysis of Human Breast Tumors

  The goal of this study is to study gene expression patterns in tumors, normal tissues, and cell lines.

  Study phs000676

• T-ALL and Thymus 10x genomics immune profiling

  10x Genomics immune profiling including sequenced libraries of: 5'-end mRNA transcriptomics Beta and alpha chain VDJ transcripts Cell surface expression by 204 DNA barcoded antibodies

  Dataset EGAD50000000533

• MBD4 targeted sequencing

  We sequenced a gene of interest, MBD4, in both germline (n=1099) and tumor (n=192) sample from Uveal Melanoma patients.

  Study EGAS00001005012

• scRNA and spatial-seq of human skin wound healing

  Human skin acute wound healing contains 12 samples of scRNA-seq and 16 samples of spatial transcriptomics, Human skin chronic wound data contains 9 samples scRNA-seq.

  Dataset EGAD50000000813

• Tissue Site

  Tissue site for RNAsequencing data. Tissue site is associated with the clinical biomarker data and be linked to the biomarker data using the SAMPLE and PAT identifiers.

  Dataset EGAD50000000931