RESUMO
BACKGROUND: Identification and characterization of the prostate stem cell is important for understanding normal prostate development and carcinogenesis. The flow cytometry-based side population (SP) technique has been developed to isolate putative adult stem cells in several human tissue types including the prostate. This phenotype is mainly mediated by the ATP-binding cassette membrane transporter ABCG2. METHODS: Immunolocalization of ABCG2 was performed on normal prostate tissue obtained from radical prostatectomies. Normal human prostate SP cells and ABCG2+ cells were isolated and gene expression was determined with DNA array analysis and RT-PCR. Endothelial cells were removed by pre-sorting with CD31. RESULTS: ABCG2 positive cells were localized to the prostate basal epithelium and endothelium. ABCG2+ cells in the basal epithelium constituted less than 1% of the total basal cell population. SP cells constituted 0.5-3% of the total epithelial fraction. The SP transcriptome was essentially the same as ABCG2+ and both populations expressed genes indicative of a stem cell phenotype, however, the cells also expressed many genes in common with endothelial cells. CONCLUSION: These results provide gene expression profiles for the prostate SP and ABCG2+ cells that will be critical for studying normal development and carcinogenesis, in particular as related to the cancer stem cell concept.
Assuntos
Transportadores de Cassetes de Ligação de ATP/genética , Transportadores de Cassetes de Ligação de ATP/isolamento & purificação , Perfilação da Expressão Gênica , Proteínas de Neoplasias/genética , Proteínas de Neoplasias/isolamento & purificação , Próstata/química , Próstata/citologia , Membro 2 da Subfamília G de Transportadores de Cassetes de Ligação de ATP , Linhagem Celular , Células Epiteliais , Humanos , Masculino , Células-TroncoRESUMO
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 beta4), luminal secretory (dipeptidyl peptidase IV), stromal fibromuscular (integrin alpha 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.
Assuntos
Perfilação da Expressão Gênica , Próstata/metabolismo , Proteínas Morfogenéticas Ósseas/metabolismo , Células Cultivadas , Análise por Conglomerados , Perfilação da Expressão Gênica/métodos , Humanos , Separação Imunomagnética , Masculino , Modelos Biológicos , Análise de Sequência com Séries de Oligonucleotídeos , Especificidade de Órgãos , Fenótipo , Neoplasias da Próstata/metabolismo , RNA Mensageiro/metabolismo , Transdução de Sinais , Células Estromais/metabolismo , Fator de Crescimento Transformador beta/metabolismoRESUMO
BACKGROUND: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. METHODS: Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. RESULTS: Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. CONCLUSION: Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases.