3930 results for "RNA AND sequencing OR transcriptome"

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• Diversity of the immune microenvironment and response to checkpoint inhibitor immunotherapy in mucosal melanoma

  Mucosal melanoma (MucM) is a rare cancer with a poor prognosis and low response rate to immune checkpoint inhibition (ICI) compared to cutaneous melanoma (CM). To explore the immune microenvironment and potential drivers of MucM’s relative resistance to ICI drugs, we characterized 101 MucM tumors (43 head and neck, 31 female urogenital, 13 male urogenital, 11 anorectal, and 3 other gastro-intestinal) using bulk RNA-sequencing (RNAseq). The original publication is written by JL Vos, JJH Traets, et al. and published in JCI Insight in 2024.

  Study EGAS50000000631

• PROMETEO

  The SOLTI-1503 PROMETEO trial was a single-arm, preoperative, window-of-opportunity phase II study conducted at four sites in Spain between December 2018 and February 2022. It enrolled female patients with operable HER2-negative breast cancer (triple-negative or Luminal B-like) and residual disease after neoadjuvant chemotherapy. Tumor biopsies were collected at five time points (baseline, post-NAC screening, C2D1, C3D1, and surgery) for translational research. This dataset includes raw paired-end RNA sequencing data (~110M reads per library) generated from the 113 biopy samples, archived in FASTQ format.

  Study EGAS50000001499

• Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature

  To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki Disease (KD), bacterial infections and viral infections. Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020-April 2021 were prospectively recruited. Whole blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C to those from children with KD, definite bacterial and viral infections. Data deposited here comprises samples from patients recruited into the DIAMONDS study.

  Study EGAS00001007409

• Discovery of new fusion transcripts in a cohort of pediatric solid cancers at relapse

  This study aims to dissect further the complexity of fusion landscape in recurrent pediatric cancers. A retrospective study on RNA-sequencing data of 48 pediatric patients at relapse with different malignancies was conducted in order to detect and validate several fusions and predict their probable oncogenic potential and targetability. We obtained a high validation rate of 90% of selected candidates which will serve both clinical and research needs to detect and prioritize experimental validation studies leading to the development of new therapeutic options.

  Study EGAS00001003236

• ScRNA-seq of PBMC and whole blood samples reveals a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Study EGAS00001004571

• ImmunoAgeing_Longitudinal

  The objective is to establish whether immunosenescence is associated with the development of clonal haematopoiesis in a healthy ageing population. This will be addressed in collaboration with the European consortium running the ImmunoAgeing project (www.immunoageing.eu). Genomic DNA derived from the peripheral blood of 394 individuals at 3-5 time-points over a 20-year period will be analysed. RNA bait pulldown (Agilent) will be used to perform targeted sequencing of genes known to be recurrently mutated in myeloid malignancies The presence, size and nature of clonal haematopoiesis will be correlated with quantitative measures of immunosenescence.

  Study EGAS00001003183

• An epigenetic single-cell atlas of IDH-mutant glioma reveals the role of ATRX in shaping tumor composition

  Recent single-cell RNA-sequencing studies have identified a hierarchy of cell types that is common to all isocitrate dehydrogenase (IDH) -mutant gliomas. This finding is somewhat paradoxical since the genetic differences between IDH-mutant astrocytomas and IDH-mutant oligodendrogliomas are prognostic, predictive of therapeutic response, and correlated with differences in immune infiltrates. To integrate these disparate findings, we constructed a single-cell atlas of 22 human IDH-mutant primary untreated grade-II/III gliomas.

  Study EGAS00001004523

• RNAseq data from human colon organoid infected by KP

  The aim of this study is to identify the specific bacteria that are responsible for pathological bacterial translocation and subsequent Th17 priming in the liver in primary sclerosing cholangitis (PSC). To clarify the mechanism of how microbiota interacts with the intestinal epithelial barrier, monolayered human intestinal organoids were cultured with the specific bacteria. Gene expression analysis using RNA sequencing in epithelial cells cultured with Klebsiella pneumoniae derived from a PSC patient (KP-P1) or commercially obtained Klebsiella pneumoniae strain (KP JCM1662) was performed in this study.

  Study EGAS00001003332

• scRNA-seq and scTCR-seq data IMCISION

  We performed single cell RNA and TCR sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and on-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset.

  Study EGAS00001007368

• QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

  We describe a new method, QSEA, for analyzing methylation enrichment data. We generated a benchmark experiment consisting of MeDIP-seq enrichment data, targeted BS-seq validation data, and RNA-seq data on five pairs of tumor and adjacent normal samples of non-small cell lung cancer patients. Details of the method and its performance on the data have been described in Lienhard et al. (2016).

  Study EGAS00001001822