15037 results for "cancer studies using rna-seq"

in 22.19 milliseconds.

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015712

• The impact of mutational clonality in predicting the response to anti-PD-L1/PD-L1 in advanced urothelial cancer

  The advent of immune checkpoint inhibitors (ICI) has radically changed the management and therapeutic treatment landscape for patients with cancer. It has been shown that the use of these inhibitors can result in long-term complete remissions even in cases with advanced stages of the disease. However, only a small fraction of patients respond to the treatment. A better understanding of which factors could drive this clinical benefit is fundamental to building more accurate predictive biomarkers and developing alternative therapeutic options for patients who are unlikely to benefit. In order to address this issue, we have generated and analyzed whole exome sequencing (WES) and RNA sequencing (RNASeq) data from a cohort of metastatic urothelial carcinoma patients (N = 27) treated with ICI such as anti-PD-(L)1 monoclonal antibodies.

  Study EGAS00001007086

• Ultrasensitive Detection and Monitoring of Circulating Tumor DNA using Structural Variants in Early-Stage Breast Cancer

  Circulating tumor DNA (ctDNA) detection has an emerging role in the management of breast cancer, offering a non-invasive means to monitor disease status and detect recurrence. This study demonstrates that longitudinal monitoring of tumor-specific structural variants - frequent alterations observed across many tumor types including all subtypes of breast cancer derived from Whole Genome Sequencing data - allows for ctDNA detection in nearly all participants in this cohort with untreated early breast cancer prior to starting neoadjuvant therapy. On-treatment ctDNA monitoring enabled the early identification of patients at high risk of recurrence and ctDNA was detected prior to relapse in participants across all receptor subtypes. These findings demonstrate the clinical validity of this assay approach for ultrasensitive ctDNA monitoring.

  Study EGAS50000000799

• Count Me In (CMI): The Metastatic Breast Cancer (MBC) Project (CMI-MBCproject)

  Count Me In - The Metastatic Breast Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Breast Cancer Research The Metastatic Breast Cancer Project is a research study that directly engages patients with metastatic breast cancer via social media and advocacy groups and empowers them to accelerate cancer research by sharing their samples and clinical information. Our goal is to create a publicly available dataset of genomic, molecular, clinical, and patient-reported data to enable research. Patients in the US or Canada may register online. Registered patients are sent an online consent form that asks for permission to obtain and analyze their medical records, tumor tissue, saliva, and blood samples. Once enrolled, patients are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. Study staff contact participants' medical providers and obtain medical records and a portion of their stored tumor biopsies. Patients may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific patient cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data, including genomic, clinical, and patient-reported data, are shared via public databases on a pre-publication and recurring basis as it is generated. The latest data release in cBioPortal is available here. Study updates are shared with participants regularly.

  Study phs001709

• Genomewide association studies in ankylosing spondylitis

  The aim of this study was to identify genes associated with ankylosing spondylitis susceptibility in British and Australian individuals of European descent.

  Study EGAS00000000104

• EFFORT occupationally exposed human stool metagenomes (148 samples)

  Metagenomes of stool samples from 54 pig farmers, 24 broiler farmers and 70 slaughter line workers. Note: Access to the data will only be granted for antibiotic resistance studies in accordance with the EFFORT consents issued by the participants.

  Dataset EGAD00001005444

• Dataset for LCPlus_WES

  WES/WGS sequencing data of 86 chromothriptic tumor and control runs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001009273

• Single-cell RNA-sequencing of CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) from a Phase I clinical study in paediatric ALL: CARPALL

  Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. Previously, we generated a novel low-affinity CAR incorporating a CD19-specific single-chain variable fragment (scFV) called CAT, displaying a faster off-rate of interaction than the FMC63 CD19 binder used in prior clinical studies. Here, we systematically analysed CD19 CAR T-cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). To characterize persisting CD19 CAR T-cells, we performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We isolated CAR T-cells from peripheral blood or bone marrow by flow cytometry for CD3 and CAR expression, prior to single cell sequencing (Chromium 10X) platform.

  Dataset EGAD00001010018

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We analyzed pulmonary monocyte and macrophage responses as well as and pulmonary pathology in two cohorts of patients with COVID-19 associated ARDS. Monocyte-derived macrophages accumulated in the lung during ARDS and acquired a profibrotic signature, characterized by high expression of known fibrogenic factors like TGFB1, SPP1 and LGMN. COVID-19 associated macrophages showed highly significant transcriptional similarity with profibrotic macrophage populations identified in idiopathic pulmonary fibrosis (IPF). Notably, overnight exposure to SARS-CoV-2, but not influenza A virus or viral RNA analogues, induced a similar phenotype in human monocytes from healthy volunteers in vitro. Patients with severe COVID-19 associated ARDS showed clear clinical, radiographic and histopathological features of scarring and fibrotic tissue remodeling. In conclusion, SARS-CoV-2 triggers profibrotic macrophage responses, fibroproliferative ARDS, and lung fibrosis

  Study EGAS00001004928

• A super-enhancer associated with CD47 links pro-inflammatory signaling to CD47 upregulation in breast cancer

  CD47 is a cell surface molecule that inhibits phagocytosis of cells that express it by binding to its receptor, SIRPα, on macrophages and other immune cells. CD47 is expressed at different levels in normal cells, however, in cancer cells, CD47 transcript and protein expression is aberrantly increased. Here we sought to uncover the regulators of CD47 transcription, including active enhancers that increase its aberrant expression in cancer cells, in order to reveal mechanisms by which different neoplastic cells generate this dominant 'don't eat me' signal. Enhancers are genomic regions, often referred to as "switches", that can turn on or off the transcription of target genes. Recently the discovery of super-enhancers (SEs) has given more insight into the regulatory architecture of key genes that are highly expressed in a specific cell type, during a particular developmental stage or in disease. By analyzing the CD47 regulatory genomic landscape, we discovered: i) A distinct super-enhancer (SE) is associated with CD47 upregulation in breast cancer cells ii) Disruption of CD47 SEs by using the BRD4 inhibitor JQ1 robustly reduces CD47 gene expression; and iii) The TNF-NFKB1 signaling pathway is directly involved in the regulation of CD47 by interacting with a distal downstream constituent enhancer located within a CD47-associated SE specific to breast cancer. Our results describe a novel mechanism that cancer cells have evolved to drive CD47 overexpression to escape immune surveillance.

  Study phs001264