Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Transcriptomes of human bladder cells and cells in bladder cancer


ABSTRACT: Characterization of the gene expression profiles of specific cell populations of the human urinary bladder provides an important set of research tools for the study of cellular differentiation and the cancer process. The transcriptome is a definitive identifier of each individual cell types. Surgically resected tissue was digested by collagenase and the different cell types were sorted by antibodies to cluster designation (CD) cell surface antigens. The sorted cells were analyzed by DNA microarrays. The transcriptome datasets were analyzed for differentially expressed genes and plotted on a principal components analysis space for cell lineage relationship. The following bladder cell types were analyzed: CD9+ urothelial, CD104+ basal, CD13+ stromal of lamina propria, CD9+ urothelial carcinoma cancer, and CD13+ urothelial carcinoma-associated stromal. Gene expression differences between the cell types of tumor and their respective non-cancer counterpart provide biomarker candidates. Basal cells of the bladder and prostate, although sharing CD cell surface markers, are quite different in overall gene expression. Furthermore, these cells lack transcript features of stem cell signature of embryonic stem or embryonal carcinoma cells. Cell type-specific transcriptomes are more informative than bulk tissue transcriptomes. The relatedness of different cell types can be determined by transcriptome dataset comparison. Bladder cell types were sorted from tissue specimens, and analyzed by DNA microarrays. The various transcriptomes were compared by principal components analysis for cell lineage relationship.

ORGANISM(S): Homo sapiens

SUBMITTER: Alvin Liu 

PROVIDER: E-GEOD-30522 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

Similar Datasets

2011-07-09 | GSE30522 | GEO
2017-03-01 | GSE92723 | GEO
2013-06-30 | E-GEOD-41581 | biostudies-arrayexpress
2024-09-05 | GSE250523 | GEO
2010-12-31 | E-GEOD-24152 | biostudies-arrayexpress
2013-06-30 | GSE41581 | GEO
2013-05-01 | E-GEOD-42089 | biostudies-arrayexpress
2020-12-12 | GSE163029 | GEO
2016-09-03 | GSE86411 | GEO
2015-06-19 | E-GEOD-64279 | biostudies-arrayexpress