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Transcriptomes of human bladder cells and cells in bladder cancer

Dataset 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.

The following additional information has been defined for this dataset. The information has been provided by the Principal Investigator or staff from his or her laboratory.

Transcriptomes of human bladder cells and cells in bladder cancer
Alvin Liu
Alvin Liu
Prostate and Urologic
Voided urine samples are collected and processed within a short time. Cells are centrifuged and lysed for RNA. RNA is isolated and amplified by in vitro transcription. The amplified RNA is hybridized to nanoString probesets for quantification. Output is digital gene counts presented in Excel. Counts are compared to those of “housekeeping” genes like B2M.
Multi-marker information provides for better diagnosis of cancer in organs along the urinary tract (prostate, bladder, kidney) as well as aggressive potential of the detected cancer based on the amounts of biomarker RNA (urine RNA signature).
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