Pten in the breast tumor microenvironment: modeling tumor-stroma coevolution

Abstract

Solid human tumors and their surrounding microenvironment are hypothesized to coevolve in a manner that promotes tumor growth, invasiveness, and spread. Mouse models of cancer have focused on genetic changes in the epithelial tumor cells and therefore have not robustly tested this hypothesis. We have recently developed a murine breast cancer model that ablates the PTEN tumor suppressor pathway in stromal fibroblasts. Remarkably, the model resembles human breast tumors both at morphologic and molecular levels. We propose that such models reflect subtypes of tumor-stromal coevolution relevant to human breast cancer, and will therefore be useful in defining the mechanisms that underpin tumor-stroma cross-talk. Additionally, these models should also aid in molecularly classifying human breast tumors on the basis of both the microenvironment subtypes they contain as well as on the tumor subtype.

Figure 1. Modeling Tumor-Stroma Co-Evolution: Spontaneous Development of Tumor Subtypes and Stromal Subtypes in Human Breast Cancer

Collaboration of both the epithelial and stromal compartments during tumor development contributes to the biological diversity in breast cancer and could be associated with various clinical parameters and patient outcomes, i.e. a basal like tumor developing in combination with stromal subtype 1 may be more aggressive or more resistant to treatment than the same basal like tumor developing simultaneously with stromal subtype 4. Conversely, the presence of a particular subtype of stroma might adversely affect growth of a particular tumor subtype, thereby predicting a better patient outcome. By examining the effects of stromal Pten signaling in several models of breast cancer in mice, we were able to show cooperation between Pten and both ErbB2 and c-myc, however not between Pten and Ras. Similar experiments are underway to examine the collaboration of p53 in stromal fibroblasts with various oncogenes in mammary epitheial cells. Using gene signatures from various cell types in these and other models currently being developed, we will have a powerful tool in predictive biomarkers for both human tumor and stromal samples.