Identification of genes regulating migration and invasion using a new model of metastatic prostate cancer.

BACKGROUND: Understanding the complex, multistep process of metastasis remains a major challenge in cancer research. Metastasis models can reveal insights in tumor development and progression and provide tools to test new intervention strategies. METHODS: To develop a new cancer metastasis model, we used DU145 human prostate cancer cells and performed repeated rounds of orthotopic prostate injection and selection of subsequent lymph node metastases. Tumor growth, metastasis, cell migration and invasion were analyzed. Microarray analysis was used to identify cell migration- and cancer-related genes correlating with metastasis. Selected genes were silenced using siRNA, and their roles in cell migration and invasion were determined in transwell migration and Matrigel invasion assays. RESULTS: Our in vivo cycling strategy created cell lines with dramatically increased tumorigenesis and increased ability to colonize lymph nodes (DU145LN1-LN4). Prostate tumor xenografts displayed increased vascularization, enlarged podoplanin-positive lymphatic vessels and invasive margins. Microarray analysis revealed gene expression profiles that correlated with metastatic potential. Using gene network analysis we selected 3 significantly upregulated cell movement and cancer related genes for further analysis: EPCAM (epithelial cell adhesion molecule), ITGB4 (integrin ß4) and PLAU (urokinase-type plasminogen activator (uPA)). These genes all showed increased protein expression in the more metastatic DU145-LN4 cells compared to the parental DU145. SiRNA knockdown of EpCAM, integrin-ß4 or uPA all significantly reduced cell migration in DU145-LN4 cells. In contrast, only uPA siRNA inhibited cell invasion into Matrigel. This role of uPA in cell invasion was confirmed using the uPA inhibitors, amiloride and UK122. CONCLUSIONS: Our approach has identified genes required for the migration and invasion of metastatic tumor cells, and we propose that our new in vivo model system will be a powerful tool to interrogate the metastatic cascade in prostate cancer.

Regulation of epithelial plasticity by miR-424 and miR-200 in a new prostate cancer metastasis model.

Using an in vivo cycling strategy, we selected metastatic cancer cells from the lymph nodes (LN) of mice bearing orthotopic DU145 human prostate tumors. Repeated rounds of metastatic selection (LN1-LN4) progressively increased the epithelial phenotype, resulting in a new model of tumor cell mesenchymal-epithelial transition (MET). DU145-LN4 showed increased cell-cell adhesions, higher expression of multiple epithelial markers, such as E-cadherin, EpCAM and cytokeratin 18, and reduced expression of mesenchymal markers such as vimentin. The MET in DU145-LN4 cells was accompanied by increased expression of the miR-200 family, and antimiRs to miR-200c and miR-141 induced an EMT. MET also correlated with the loss of miR-424. Ectopic transient and stable miR-424 expression induced EMT, with reduced epithelial marker expression and increased cell scattering. Our model provides evidence for spontaneous MET in vivo. We show that this cellular plasticity can be mediated through the combined action of miR-424 and the miR-200 family.

Stromal and epithelial networks: Temporal gene expression profiling during invasive neoplasia.

The interaction between tumor cells and the stromal microenvironment is a critical factor in cancer development and progression. A recent study from the Khavari group profiled the expression changes during progression to invasion in a Ras-inducible model of human epithelial neoplasia and used network modeling to analyze the molecular interactions. Human dermis was seeded with H-Ras- and IkappaBalpha-expressing keratinocytes then grafted on to immune-deficient mice. The epithelial and stromal gene expression profiles were captured during progression from quiescent epithelial tissue to in situ neoplasia to invasive neoplasia. A subset of these altered genes was compiled into a "core tumor progression signature" (CTPS), which was shown to have clinical relevance in several cancer types. Network modeling of the CTPS revealed highly interconnected "hubs", which was dominated by extracellular matrix-related genes, including beta(1) integrin. Targeting integrin beta(1) functionality reduced Ras-driven tumorigenesis in vivo and validated the network modeling strategy for predicting genes essential to neoplasia. By integrating temporal analysis of both the epithelial and stromal compartments with network modeling of molecular interactions, this work has described an effective strategy for identifying highly interconnected targets essential to tumor development.

Current molecular diagnostics of breast cancer and the potential incorporation of microRNA.

Although comprehensive molecular diagnostics and personalized medicine have sparked excitement among researchers and clinicians, they have yet to be fully incorporated into today's standard of care. This is despite the discovery of disease-related oncogenes, tumor-suppressor genes and protein biomarkers, as well as other biological anomalies related to cancer. Each year, new tests are released that could potentially supplement or surpass standard methods of diagnosis, including serum, protein and gene expression analyses. All of these novel approaches have shown great promise, but initial enthusiasm has diminished as difficulties in reproducibility, expense, standardization and proof of significance beyond current protocols have emerged. This review will focus on current and novel molecular diagnostic tools applied to breast cancer with special attention to the exciting new field of microRNA analysis.