Integrin α6 and EGFR signaling converge at mechanosensitive calpain 2.

Cells sense and respond to mechanical cues from the extracellular matrix (ECM) via integrins. ECM stiffness is known to enhance integrin clustering and response to epidermal growth factor (EGF), but we lack information on when or if these mechanosensitive growth factor receptors and integrins converge intracellularly. Towards closing this knowledge gap, we combined a biomaterial platform with transcriptomics, molecular biology, and functional assays to link integrin-mediated mechanosensing and epidermal growth factor receptor (EGFR) signaling. We found that high integrin α6 expression controlled breast cancer cell adhesion and motility on soft, laminin-coated substrates, and this mimicked the response of cells to EGF stimulation. The mechanisms that drove both mechanosensitive cell adhesion and motility converged on calpain 2, an intracellular protease important for talin cleavage and focal adhesion turnover. EGF stimulation enhanced adhesion and motility on soft substrates, but required integrin α6 and calpain 2 signaling. In sum, we identified a new role for integrin α6 mechanosensing in breast cancer, wherein cell adhesion to laminin on soft substrates mimicked EGF stimulation. We identified calpain 2, downstream of both integrin α6 engagement and EGFR phosphorylation, as a common intracellular signaling node, and implicate integrin α6 and calpain 2 as potential targets to inhibit the migration of cancer cells in stiff tumor environments.

The Predictive Link between Matrix and Metastasis.

Cancer spread (metastasis) is responsible for 90% of cancer-related fatalities. Informing patient treatment to prevent metastasis, or kill all cancer cells in a patient's body before it becomes metastatic is extremely powerful. However, aggressive treatment for all non-metastatic patients is detrimental, both for quality of life concerns, and the risk of kidney or liver-related toxicity. Knowing when and where a patient has metastatic risk could revolutionize patient treatment and care. In this review, we attempt to summarize the key work of engineers and quantitative biologists in developing strategies and model systems to predict metastasis, with a particular focus on cell interactions with the extracellular matrix (ECM), as a tool to predict metastatic risk and tropism.

A cell-ECM screening method to predict breast cancer metastasis.

Breast cancer preferentially spreads to the bone, brain, liver, and lung. The clinical patterns of this tissue-specific spread (tropism) cannot be explained by blood flow alone, yet our understanding of what mediates tropism to these physically and chemically diverse tissues is limited. While the microenvironment has been recognized as a critical factor in governing metastatic colonization, the role of the extracellular matrix (ECM) in mediating tropism has not been thoroughly explored. We created a simple biomaterial platform with systematic control over the ECM protein density and composition to determine if integrin binding governs how metastatic cells differentiate between secondary tissue sites. Instead of examining individual behaviors, we compiled large patterns of phenotypes associated with adhesion to and migration on these controlled ECMs. In combining this novel analysis with a simple biomaterial platform, we created an in vitro fingerprint that is predictive of in vivo metastasis. This rapid biomaterial screen also provided information on how ß1, α2, and α6 integrins might mediate metastasis in patients, providing insights beyond a purely genetic analysis. We propose that this approach of screening many cell-ECM interactions, across many different heterogeneous cell lines, is predictive of in vivo behavior, and is much simpler, faster, and more economical than complex 3D environments or mouse models. We also propose that when specifically applied toward the question of tissue tropism in breast cancer, it can be used to provide insight into certain integrin subunits as therapeutic targets.