Collagen and fibronectin promote an aggressive cancer phenotype in breast cancer cells but drive autonomous gene expression patterns.

• The ECM elicits functional and genetic changes in breast cancer cells. • Collagen-I and fibronectin promote aggressive breast cancer cell behaviour. • Collagen-1 and fibronectin promote similar gene expression patterns within cell lines. • Gene expression patterns in response to the ECM mayreveal novel signalling axes. • Monitoring ECM composition may provide information on cancer prognosis. Understanding how various pathologies of breast cancer respond to their environment may be imperative in the creation of novel therapeutic targets. Central to the organisation and behaviour of cells within the tumour microenvironment is the extracellular matrix (ECM), a meshwork of fibrous proteins and glycoproteins that directly influences cell behaviour and the bioavailability of signalling molecules. Our appreciation on how the composition of the ECM can influence cancer behaviour has evolved significantly and although we are highly cognisant of the dramatic impact the ECM can have on cancer cell behaviour, we continue to neglect this during diagnosis and treatment. In the following study, we aimed to identify how three breast cancer cell lines respond functionally and genetically to common components of the ECM. Using real time and end point assays we have identified similar patterns of behaviour among the three breast cancer cell lines in response to commonly found ECM components of the breast. Using a selected gene panel, we have been able to identify cell line specific changes in gene differentiation when breast cancer cells are in contact with these elements. Although the response of our cells to these elements differ at the genetic level, their functional responses are consistent. This work adds to the growing arguments that highlight a need for histologically assessing ECM composition of breast tumours. In particular monitoring of fibrous protein deposition at the site of malignancy could provide critical information during clinical assessment influencing disease prognosis and treatment decisions for breast cancer patients. [ABSTRACT FROM AUTHOR]