Gene expression profiling of human prostate cancer stem cells reveals a pro-inflammatory phenotype and the importance of extracellular matrix interactions

Abstract

Background: The tumor-initiating capacity of many cancers is considered to reside in a small subpopulation of cells (cancer stem cells). We have previously shown that rare prostate epithelial cells with a CD133+/alpha2beta1hi phenotype have the properties of prostate cancer stem cells. We have compared gene expression in these cells relative to their normal and differentiated (CD133-/alpha2beta1low) counterparts, resulting in an informative cancer stem cell gene-expression signature.

Results: Cell cultures were generated from specimens of human prostate cancers (n = 12) and non-malignant control tissues (n = 7). Affymetrix gene-expression arrays were used to analyze total cell RNA from sorted cell populations, and expression changes were selectively validated by quantitative RT-PCR, flow cytometry and immunocytochemistry. Differential expression of multiple genes associated with inflammation, cellular adhesion, and metastasis was observed. Functional studies, using an inhibitor of nuclear factor kappaB (NF-kappaB), revealed preferential targeting of the cancer stem cell and progenitor population for apoptosis whilst sparing normal stem cells. NF-kappaB is a major factor controlling the ability of tumor cells to resist apoptosis and provides an attractive target for new chemopreventative and chemotherapeutic approaches.

Conclusion: We describe an expression signature of 581 genes whose levels are significantly different in prostate cancer stem cells. Functional annotation of this signature identified the JAK-STAT pathway and focal adhesion signaling as key processes in the biology of cancer stem cells.

Figure 1

Distinctive stem cell and tumor signatures are found in human prostate cancers containing a minimum Gleason score 7 pathology. Clustering analysis (derived from the Pearson correlation) using the expression data for the probesets (from 28 samples) define a cancer stem cell signature. Blue tiles indicate down-regulated genes, and red tiles indicate up-regulated genes. (a) The combined signature clustered samples as benign (blue bar) and malignant (red bar). Cell type (stem, CD133⁺/α₂β₁^hi; and committed, CD133^-/α₂β₁^low) was also defined within each disease state. (b) The differentiation signature. One sample in which a clear differentiation signature 'breakthrough' was evident in the combined signature is indicted by an asterisk. (c) Sample clustering according to the malignancy signature. (d) Hierarchical clustering with the Gleason 6 samples and a single hormone treated sample included in the analysis. Note that the clear distinction between non-malignant and malignant biopsies is lost by including this data.

Figure 2

Nested RT-PCR for the detection of the TMPRSS2:ERG fusion. Samples from the microarray data set, where sufficient material was available, were subjected to nested RT-PCR to detect the presence of the TMPRSS2:ERG fusion product. The fusion product was detected in 6 of 10 samples and undetectable in the remainder (samples marked ND). cDNA from the fusion positive cell line VCaP was used as a positive control, water was substituted in place of cDNA for the negative control.

Figure 3

Validation of selected genes by quantitative real time PCR. (a) RT-PCR confirmation of Affymetrix array data on genes associated with prostate cancer (all changes in expression were significant at p < 0.05). Changes between stem and committed cells are indicated in blue, while malignant versus benign changes are indicated in red. (b) Validation of average changes in gene expression between stem and committed basal populations detected by Affymetrix array (red bars) and RT-PCR techniques (blue bars). (c) Validation of average changes in gene expression between malignant and benign stem cell populations detected by Affymetrix (red bars) and RT-PCR techniques (blue bars).

Figure 4

Validation of selected genes by flow cytometry and immunocytochemistry. (a) Flow cytometry analysis of prostate cancer cells co-stained with antibodies to CD133 and the NF-κB p65 subunit. (b) Confocal image of sorted CD133⁺ cancer cells stained with an antibody to the NF-κB p65 subunit (green) counterstained with DAPI (blue). Nuclear concurrence of two signals is indicated by a cyan colour. (c-e) Flow cytometry analysis of prostate cancer cells co-stained with antibodies to CD133 and ZO1/TJP1 (c) or ZO2/TJP2 (d) or PAPPA (e).

Figure 5

PTL induces apoptosis in primitive cancer cells. Percent viability of prostate cancer cells and cells from a patient with BPH treated with increasing concentrations of PTL. Cells were cultured for 1 h with 100 ng/ml TNFα prior to treatment with PTL for 18 h. Cells were subsequently labeled with CD133-APC, Annexin-V-FITC and DAPI. Viability was defined as annexin-V^-/DAPI^- on total cells. Three prostate cancer patients' samples were analyzed and a representative profile is shown of normal CD133⁺ (open circles), cancer CD133⁺ (filled squares), normal progenitor (filled circles) and cancer progenitor (open squares).

Figure 6

Functional annotation of the cancer stem cell expression signature. (a,b) Functional concepts over-represented in cancer relative to BPH within the stem cell population (a) or within the committed basal population (b) derived from the GO. Over-represented terms are shown in red, and under-represented terms are shown in blue. (c) Examples of key pathways and related genes involved in over represented gene ontology functions.