12155 results for "cancer rna-seq"

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• Manchester Eye Tissue Repository Genome-Transcriptome Project

  The Manchester Eye Tissue Repository Genome-Transcriptome (METR-GT) Project comprises whole genome sequencing data and paired short read, high-depth bulk-RNA sequencing data from the neurosensory retina (NSR) and the retinal pigment epithelium (RPE) from 201 unrelated individuals that donated eye-tissue post-mortem. None of the individuals included in the cohort had phenotypic presentation, assessed post-mortem, consistent with late-stage AMD or monogenic ophthalmic disorders. In this dataset we include WGS fastq files, WGS VCF files (at an individual level and an aggregate VCF that has undergone variant-level quality control), RNASeq BAM files of the NSR and RPE, gene expression quantification files of the NSR and RPE (including raw gene counts generated by RNASeQC and estimated TPM and FPKM values generated by RSEM). Additionally, we have included the output files from eQTL mapping in both tissues, generated by tensorQTL and instances of aberrant gene expression events generated by the OUTRIDER module of the DROP pipeline.

  Dataset EGAD50000002082

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathophysiological insight. Menstrual bloodderived stem cells (MenSCs) have been implicated in disease pathogenesis, but their diagnostic potential remains unexplored. We conducted a clinical study (n=42; 19 endometriosis, 23 controls) to assess whether DNA methylation profiles of freshly isolated MenSCs can identify disease-specific biomarkers. Whole-genome methylation sequencing revealed differentially methylated regions (DMRs) enriched in genes linked to hallmarks of endometriosis (e.g., inflammation, tissue remodelling, development). These DMRs robustly distinguished cases from controls, independent of technical and clinical variables. Machine learning models trained and validated on these DMRs achieved high diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset showed that the DMRs may modulate gene expression, further supporting their biological relevance. These findings position MenSC DNA methylation profiling as a promising, non-invasive approach for early endometriosis diagnosis and personalised care.

  Dataset EGAD50000002353

• Circular RNA characterization in functionally distinct brain regions

  Circular RNAs (circRNAs) represent a class of endogenous, non-coding RNAs that are formed when exons back splice to each other and that are both highly conserved and pervasively expressed in the mammalian brain. The goal of this study was thus to systematically identify and characterize circRNA expression and as well as to evaluate the predicted impact on regulatory networks in five functionally distinct cortical regions of healthy aged human brain - cerebellum (BC), inferior parietal lobe (IPL), middle temporal gyrus (MTG), occipital cortex (OC) and superior frontal gyrus (SGF).

  Study EGAS00001003128

• Single-cell RNA sequencing data of human lymph node samples generated with BD Rhapsody

  The single cell data were generated based on four cartridges. The samples are multiplexed: 0. Sample Run Id Hash Gender Age 1. FL-6 Run1_C1 4 f 71 2. rLN-3 Run1_C1 6 f 72 3. DLBCL-4 Run1_C1 7 f 68 4. DLBCL-1 Run1_C1 8 m 66 5. FL-4 Run1_C1 9 m 41 6. DLBCL-3 Run1_C2 10 f 60 7. rLN-4 Run1_C2 11 f 58 8. rLN-5 Run1_C2 12 m 61 9. FL-1 Run2_C1 1 f 81 10. DLBCL-2 Run2_C1 2 m 80 11. rLN-2 Run2_C1 3 f 42 12. FL-5 Run2_C1 4 m 66 13. DLBCL-8 Run2_C1 5 m 64 14. DLBCL-6 Run2_C2 6 m 76 15. rLN-1 Run2_C2 7 m 39 16. FL-3 Run2_C2 8 f 76 17. DLBCL-5 Run2_C2 9 m 66 18. FL-2 Run2_C2 10 f 58 19. DLBCL-7 Run2_C2 11 f 71

  Dataset EGAD00001010044

• RNAseq from blood CD34+ cells

  This dataset contains paired-end RNA sequencing data of blood CD34+ cells from random blood donors (155 paired-end FastQ files). The data were used to perform expression quantitative trait locus (eQTL) analysis.

  Dataset EGAD00001008194

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Adult RNA (2025-10-14)

  Animal studies have demonstrated that resident memory T (Trm) cells provide enhanced protective responses to a broad array of tissue-tropic pathogens, thus making Trm cells promising targets for novel vaccination strategies. However, the biological pathways that enable the long-term survival of Trm cells are poorly understood in humans. Here, we will employ a unique human intestinal transplantation setting that allows us to study the retention of persistent T cells in the grafts and the temporal development of resident T-cell populations from recruited recipient T cells. We will integrate high resolution transcriptomics, epigenetics, proteomics and immune repertoire single-cell data from purified intestinal T cells. These single-cell multiomics approaches will uncover the diversity and differentiation of the T cell populations in the human intestine, allowing us to temporally resolve the generation and maintenance of gut resident T cells. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015739

• A non-canonical lymphoblast in refractory childhood T-cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms or represent distinct disease states. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we perform single cell mRNA sequencing of T-ALL from 58 children (84 samples) who did, or did not respond to initial treatment. We identify a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralds refractory disease across independent datasets and is associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease with the potential for immediate clinical utility. This dataset contains 56 single-cell RNA sequencing data files with corresponding single-cell T cell receptor sequencing data files. The data here form the validation cohort in our paper.

  Dataset EGAD00001015673

• 10x dataset of an obese human subject

  Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from an obese individual with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donor underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the Chromium platform (10x genomics), and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

  Dataset EGAD00001005101

• Molecular Determinants of Esophageal Cancer in Tanzania

  We describe the genomic profiles of 61 esophageal squamous cell carcinoma (ESCC) cases from Tanzania and compare them to profiles from an existing cohort of ESCC cases from Malawi. We also provide a comparison to ESCC tumors in The Cancer Genome Atlas Program (TCGA). Despite a high burden of ESCC in Eastern Africa, investigations into the genomics in this region are nascent. This represents the largest comprehensive genomic analysis of ESCC from sub-Saharan Africa to date. We observed substantial transcriptional overlap with other squamous histologies via comparison with TCGA PanCan dataset. DNA analysis revealed known mutational patterns, both genome-wide as well as in genes known to be commonly mutated in ESCC. TP53 mutations were the most common somatic mutation in tumors from both Tanzania and Malawi but were detected at lower frequencies than previously reported in ESCC cases from other settings. In a combined analysis, two unique transcriptional clusters were identified: a proliferative/epithelial cluster and an invasive/migrative/mesenchymal cluster. Mutational signature analysis of the Tanzanian cohort revealed common signatures associated with aging and cytidine deaminase activity and an absence of signature 29, which was previously reported in the Malawi cohort.

  Study phs003217

• Yale SPORE in Skin Cancer Project 2

  Understanding the relationship between tumor and peripheral immune environments could allow longitudinal immune monitoring in cancer. Here, we examined whether T cells that share the same TCRab and are found in both tumor and blood can be interrogated to gain insight into the ongoing tumor T cell response. Paired transcriptome and TCRab repertoire of circulating and tumor-infiltrating T cells were analyzed at the single cell level from matched tumor and blood from patients with metastatic melanoma. The data shared here consist of gene expression matrix and fastq files obtained from sequencing single-cell libraries generated with the Chromium (TM) 5' technique. For each of 18 immunotherapy naive and 11 previously treated melanoma patients, T cells (Live/CD45+/TcRab+) were FACS-sorted from PBMCs and freshly resected tumors. Metadata associated with each individual cell consist of Patient I.D., biological sex, immunotherapy status, amino acid and nucleotide CDR3 sequence of the TCR alpha and beta chain (obtained from matched VDJ region enriched libraries), and sequencing batch. Further details about previous treatment history and other clinical parameters can be found in the associated manuscripts (Lucca et al., 2021: PMID: 33651881; Lu et al., PMID: 39609626).

  Study phs002289