1. Transcriptomes of human prostate cells
- Author
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Alvin Y. Liu, Carrie M Sorensen, Laura S Walashek, Lawrence D. True, Dave S. Campbell, and Asa J. Oudes
- Subjects
Male ,Cell type ,Stromal cell ,lcsh:QH426-470 ,lcsh:Biotechnology ,Cell ,Biology ,Proteomics ,Models, Biological ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,Transforming Growth Factor beta ,lcsh:TP248.13-248.65 ,Gene expression ,Genetics ,medicine ,Cluster Analysis ,Humans ,RNA, Messenger ,Cells, Cultured ,Oligonucleotide Array Sequence Analysis ,030304 developmental biology ,0303 health sciences ,Immunomagnetic Separation ,Gene Expression Profiling ,Prostate ,Prostatic Neoplasms ,Cell sorting ,Molecular biology ,lcsh:Genetics ,Phenotype ,medicine.anatomical_structure ,Organ Specificity ,030220 oncology & carcinogenesis ,Bone Morphogenetic Proteins ,Stromal Cells ,DNA microarray ,Signal Transduction ,Research Article ,Biotechnology - Abstract
Background The gene expression profiles of most human tissues have been studied by determining the transcriptome of whole tissue homogenates. Due to the solid composition of tissues it is difficult to study the transcriptomes of individual cell types that compose a tissue. To overcome the problem of heterogeneity we have developed a method to isolate individual cell types from whole tissue that are a source of RNA suitable for transcriptome profiling. Results Using monoclonal antibodies specific for basal (integrin β4), luminal secretory (dipeptidyl peptidase IV), stromal fibromuscular (integrin α 1), and endothelial (PECAM-1) cells, respectively, we separated the cell types of the prostate with magnetic cell sorting (MACS). Gene expression of MACS-sorted cell populations was assessed with Affymetrix GeneChips. Analysis of the data provided insight into gene expression patterns at the level of individual cell populations in the prostate. Conclusion In this study, we have determined the transcriptome profile of a solid tissue at the level of individual cell types. Our data will be useful for studying prostate development and cancer progression in the context of single cell populations within the organ.
- Published
- 2006