Project description:Purpose: The goals of this study are to compare 1. The transcription profile in KDM6A wildtype and KDM6A mutated urothelial bladder carcinoma. 2. The transcriptional changes in KDM6A mutated urothelial bladder carcinoma upon EZH2 inhibitor treatment.
Project description:Objectives: Much of the information to date in terms of subtypes and function of bladder urothelial cells were derived from anatomical location or by the expression of a small number of marker genes. To have a comprehensive map of the cellular anatomy of bladder urothelial cells, we performed single-cell RNA-sequencing to thoroughly characterize mouse bladder urothelium. Materials and methods: A total of 18,917 single cells from mouse bladder urothelium was analyzed by unbiased single-cell RNA sequencing. The expression of the novel cell marker was confirmed by immunofluorescence using urinary tract infections models. Results: Unsupervised clustering analysis identified 8 transcriptionally distinct cell subpopulations from mouse bladder urothelial cells. We discovered a novel type of bladder urothelial cells marked by Plxna4 that may be involved with host response and wound healing. We also found a group of basal-like cells labeled by ASPM that could be the progenitor cells of adult bladder urothelium. ASPM+ urothelial cells are significantly increased after injury by UPEC. In addition, specific transcription factors were found to be associated with urothelial cell differentiation. At the last, a number of interstitial cystitis/bladder pain syndrome-regulating genes were found differentially expressed among different urothelial cell subpopulations. Conclusions: Our study provides a comprehensive characterization of bladder urothelial cells, which is fundamental to understanding the biology of bladder urothelium and associated bladder disease.
Project description:Thiele2013 - Urinary bladder urothelial cells
The model of urinary bladder urothelial cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110035
.
To cite BioModels Database, please use: BioModels Database: An enhanced,
curated and annotated resource for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer
to CC0 Public Domain Dedication
for more information.
Project description:Expression profiling by arrays Urothelial carcinoma (UC) can arise at any location along the urothelial tract, including the urethra, bladder, ureter or renal pelvis. Although tumors arising in these various locations demonstrate similar morphology, it is unclear whether the gene expression profiles are similar in the upper tract (ureter and renal pelvis) or in the lower tract (bladder and urethra) carcinomas, especially given their different embryologic origins. As differences may facilitate potentially different screening and treatment modalities, we sought to examine the relationship between urothelial carcinoma of the renal pelvis (rUC) and urothelial carcinoma of the bladder (bUC). Fresh tumor tissue was collected from patients with bUC (n=10) and benign mucosa from the bladder (n=7) was collected from individuals undergoing resection for non-UC conditions for comparison. Gene expression profiles from these samples were determined using high-throughput Affymetrix gene expression microarray chips. Bioinformatic approaches were used to compare gene expression profiles of these samples and those of rUC (n= 14) and normal kidney (n=14) that were mostly used in our previous publication. Using unsupervised analytic approaches, rUC and bUC were indistinguishable. When supervised analytic approach was used, a very small number of potentially differentially expressed genes was identified; these differences were most likely to be limited to a single pathway - the chloride ion binding activity pathway -which was more frequently activated in rUC than in bUC. We found that the gene expression profiles of UCs from the upper and lower tract were extremely similar, suggesting that similar pathogenic mechanisms likely function in the development of these tumors. The differential expression of genes in the identified pathway may represent a potential new avenue for detection of upper tract tumors. Tissue samples with urothelial cell carcinoma from lower tract (bladder) as well as normal references were collected and the gene expression profiles were compared with gene expression profiles of samples in our previously published data set . No technical replicates.
Project description:Some studies have demonstrated the heterogeneity of bladder epithelium and fibroblasts, as well as their crosstalk during bladder development and regeneration. However, due to the limitations of techniques, a comprehensive understanding of cellular heterogeneity and crosstalk during bladder regeneration is still lacking. Here, we used droplet-based scRNA-seq to recover the heterogeneity of urothelial cells, cell cycle characteristic of proliferative cell population and proliferative niches after acute and chronic injury induced by cyclophosphamide.
Project description:This is a comprehensive genomic characterization of 40 urothelial bladder carcinoma (UBC) cell lines including information on origin, mutation status of genes implicated in bladder cancer (FGFR3, PIK3CA, TP53, and RAS), copy number alterations assessed using high density SNP arrays, uniparental disomy (UPD) events, and gene expression. Based on gene mutation patterns and genomic changes we identify lines representative of the FGFR3-driven tumor pathway and of the TP53/RB tumor suppressor-driven pathway. High-density array copy number analysis identified significant focal gains (1q32, 5p13.1-12, 7q11, and 7q33) and losses (i.e. 6p22.1) in regions altered in tumors but not previously described as affected in bladder cell lines. We also identify new evidence for frequent regions of UPD, often coinciding with regions reported to be lost in tumors. Previously undescribed chromosome X losses found in UBC lines also point to potential tumor suppressor genes. Cell lines representative of the FGFR3-driven pathway showed a lower number of UPD events. Overall, there is a predominance of more aggressive tumor subtypes among the cell lines. We provide a cell line classification that establishes their relatedness to the major molecularly-defined bladder tumor subtypes. The compiled information should serve as a useful reference to the bladder cancer research community and should help to select cell lines appropriate for the functional analysis of bladder cancer genes, for example those being identified through massive parallel sequencing. Expression levels were assessed in 20 bladder cell lines, included in the UBC-40 Urothelial Bladder Cell Line Index, with Affymetrix U133 array platform