Kidney tumour RNA
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001002487 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:This is a bulk DNA and RNA sequencing study of human renal tumours
| EGAS00001002486 | EGA
Project description:This is an exome DNA sequencing study of human renal tumours
| EGAS00001003616 | EGA
Project description:This is a bulk DNA and RNA sequencing study of human renal tumours .
This dataset contains all the data available for this study on 2018-09-19.
| EGAD00001004346 | EGA
Project description:To investigate the role of Jag1⁺ Tregs in regulating the activity of tumours and corresponding tdLNs in the B16-F10 tumour model, we performed bulk RNA sequencing on tumours and tdLNs of wild-type mice and mice with conditional deletion of Jag1 in Tregs. Transcriptomic analysis revealed no significant changes in gene expression in tumours, whereas tdLNs exhibited downregulation of lymphatic endothelial cell (LEC)-related markers and genes related to cell junction organization in mice with Treg-specific Jag1 ablation.
2026-05-18 | GSE328772 | GEO
Project description:In this dataset, we study the role of FOXM1 in human primary renal tubular epithelial cells (hRPTECs) by first performing Foxm1 knockdown with an siRNA approach and then performing bulk RNA sequencing. We also sought to identify FOXM1 binding sites on hRPTECs using Cut&Run. These studies will help better understand the role of Foxm1 in acute kidney injury and repair.
2024-07-12 | GSE234443 | GEO
Project description:In this dataset, we study the role of FOXM1 in human primary renal tubular epithelial cells (hRPTECs) by first performing Foxm1 knockdown with an siRNA approach and then performing bulk RNA sequencing. We also sought to identify FOXM1 binding sites on hRPTECs using Cut&Run. These studies will help better understand the role of Foxm1 in acute kidney injury and repair.
2024-07-12 | GSE234442 | GEO
Project description:Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis. golub-00460 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Material Types: synthetic_RNA, organism_part, whole_organism, total_RNA Disease States: synthetic_RNA, organism_part, whole_orMedulloblastoma, renal rhabdoid tumor, Atypical Teratoid/Rhabdoid Tumor, Supratentorial PNET, Supratentorial PNET (pineoblastoma), Normal, Malignant Glioma, Extrarenal Rhabdoid Tumorganism, total_RNA
2015-05-16 | E-GEOD-68956 | biostudies-arrayexpress
Project description:Multiple tumours from the same patient were analysed for DNA methylation to assess tumour clonality. Seventy-four tumours corresponding to 37 patients were stratified into four groups based on the anatomic location of the multiple breast cancers (ipsilateral or bilateral) and time interval between the diagnoses (synchronous or metachronous). Ipsilateral was defined as tumours occurring in the same breast while bilateral was defined as the occurrence of tumours in both breasts. Metachronicity was defined as a time interval greater than six months between the diagnoses of the first and second tumours, while synchronicity specified that the two tumours occurred concurrently (BM: bilateral-metachronous; BS: bilateral-synchronous; IM: ipsilateral-metachronous; IS: ipsilateral-synchronous). A subset of 16 samples was randomly selected to represent each clinical group with four samples corresponding to two patients per group and analysed for DNA methylation using Illumina Infinium Human MethylationEPIC BeadChips.
2019-01-03 | GSE108982 | GEO
Project description:This study aimed to investigate transcriptional differences between liver tumours that were chemically-induced in five strains and species of mouse and rat. Male mice (Mus musculus domesticus C3H/HeOuJ and C57BL/6J, Mus musculus castaneus CAST/EiJ, and Mus Caroli CAROLI/EiJ) and rats (Fischer F344) were treated with diethylnitrosamine (DEN) to induce liver tumours. After tumour dissection, genomic DNA and RNA were simultaneously isolated and purified for library preparation and sequencing. Additional liver tissue samples were collected and processed in parallel: untreated liver from infant mice (15-day old, P15) and juvenile rats (56-day old, P56); untreated adult liver tissue; DEN-exposed adult liver tissue; spontaneous liver tumours.
2026-05-07 | E-MTAB-16391 | biostudies-arrayexpress
Project description:A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of human kidney, we performed a method to obtain single-cell suspension of kidney rapidly, and conducted single-cell RNA sequencing (scRNA-seq). We present scRNA-seq data of 23,366 high quality cells from human kidneys of 3 donors. In this dataset, we show 10 clusters of normal human renal cells. Due to the high quality of single cell transcriptomic information, proximal tubule (PT) cells were classified into 3 subtypes and collecting ducts cells into 2 subtypes. Collectively, our data will provide a reliable reference for the studies of renal cell biology and kidney diseases.
2019-05-30 | GSE131685 | GEO