Abstract
Invasion of surrounding stroma is an early event in breast cancer metastatic progression, and involves loss of cell polarity, loss of myoepithelial layer, epithelial-mesenchymal transition (EMT) and remodeling of the extracellular matrix (ECM). Integrins are transmembrane receptors responsible for cell-ECM binding, which triggers signals that regulate many aspects of cell behavior and fate. Changes in the expression, localization and pairing of integrins contribute for abnormal responses found in transformed epithelia. We analyzed 345 human breast cancer samples in tissue microarrays (TMA) from cases diagnosed with invasive breast carcinoma to assess the expression and localization pattern of integrin αV and correlation with clinical parameters. Patients with lower levels of integrin αV staining showed reduced cancer specific survival. A subset of cases presented a peripheral staining of integrin αV surrounding tumor cell clusters, possibly matching the remaining myoepithelial layer. Indeed, the majority of ductal carcinoma in situ (DCIS) components found in the TMA presented integrin αV at their periphery, whereas this pattern was mostly lost in invasive components, even in the same sample. The lack of peripheral integrin αV correlated with decreased cancer specific survival. In addition, we observed that the presence of integrin αV in the stroma was an indicative of poor survival and metastatic disease. Consistently, by interrogating publicly available datasets we found that, although patients with higher mRNA levels of integrin αV had increased risk of developing metastasis, high co-expression of integrin αV and a myoepithelial cell marker (MYH11) mRNA levels correlated with better clinical outcomes. Finally, a 3D cell culture model of non-malignant and malignant cells reproduced the integrin αV pattern seen in patient samples. Taken together, our data indicate that both the expression levels of integrin αV and its tissue localization in primary tumors have prognostic value, and thus, could be used to help predict patients at higher risk of developing metastasis.