15016 results for "cancer studies using rna-seq"

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• The_Genomic_Advances_in_Sepsis__GAinS__RNA_seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Study EGAS00001003772

• Dataset for Stromal-induced epithelial-mesenchymal transition induces drug resistance in acute lymphoblastic leukemia

  RNA-seq was performed to compare gene expression profiles between 11 patient adherent ALL samples and nonadherent ALL samples.

  Dataset EGAD00001009056

• 20210729_EGA_BrainMet Saunus et al J Path (2015)

  Exome sequencing on HiSeq platform of 36 brain metastases with matched normal samples, 32 having matched RNA seq. Published Saunus et al J Path, (2015); https://doi.org/10.1002/path.4583

  Dataset EGAD00001007973

• Dataset contains all Single cell RNAseq data of human neurons from the study Bouwen et al Nat Comm 2025

  These documents contain the patch seq data presented in the Bouwen et al Nat Comm 2025. Human brain samples were gathered during surgery, neurons were isolated using patch clamp glass pipette. Isolated cells were processed using Smartseq2 pipeline, and sequenced using an Illumina 2500. Files are formatted in fastq format. There are a total of 12 patient samples, each with 2 replication runs.

  Dataset EGAD50000001979

• GATA1 scD&D-seq integrated with Multiome

  Ex vivo differentiation experiments were performed using human CD34+ hematopoietic stem and progenitor cells along the erythropoietic trajectory at multiple timepoints (differentiation days 0, 5, 8, 18, and 24). Simultaneous profiling of transcriptome, chromatin accessibility, and GATA1 binding were performed by integrating D&D-seq with 10X Multiome.

  Dataset EGAD50000002299

• Human tumor scMultiome

  We profile 10 high-grade gliomas patient brain tumor samples by single-cell multiome ATAC + gene expression, using the 10X Chromium technology. 3 sets of fastq are provided for each samples: R1 and R2 for gene expression, R1 and R2 for ATAC-seq as well as index1 and index2 for ATAC-seq.

  Dataset EGAD00001008349

• Whole exome sequencing of SarBC-01- and UroBC-01-related samples.

  This dataset contains raw FASTQ files from DNA of SarBC-01-related samples (SarBC-01 patient Germline, SarBC-01 patient Urothelial tumor, SarBC-01 patient Sarcomatoid tumor, SarBC-01 Passage 6 organoids, SarBC-01 Passage 20 organoids) and UroBC-01 related samples (UroBC-01 patient Germline, UroBC-01 patient Urothelial tumor, UroBC-01 Passage 19 organoids, UroBC-01 Passage 6 organoids). DNA was extracted from FFPE tissue, using RecoverAll RNA/DNA extraction kit (Invitrogen, Carlsbad, CA, USA, AM1975) followed by incubation with Uracil-DNA Glycosylase, and fresh or flash frozen tissue, using Quick-DNA/RNA Miniprep kit (Zymo Research, Irvine, CA, USA, D7001). Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience, 102031) was used for the whole exome capturing. Sequencing was performed on Illumina NovaSeq 6000 using paired-end 100-bp reads.

  Dataset EGAD00001011157

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• Dataset for head_and_neck_cancer-RNA

  Rare cancer sequencing data of 92 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008861

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694