Epithelial to mesenchymal transition (EMT) reflects changes in cell behaviour essential for development, and physiopathological processes. The environment induces variability in cells shape and molecular markers of the EMT. Hence, there is a relevance of population cellular heterogeneity during EMT. State-of-the-art mostly reflects the impact of the microenvironment at the population scale. The questions remains: How does the microenvironment alter cell heterogeneity during EMT ? We will lift 3 main limitations hindering study of cellular heterogeneity relationship with microenvironment: measure population cell heterogeneity quantitatively, control the microenvironment, modulate cell microenvironment interactions. We choose ovarian cancer, since it is a representative model, known for heterogeneity.

Modulo-EMT will model the relationship between microenvironment and cellular heterogeneity in ovarian cancer. Modulo-EMT provides an original multidisciplinary toolbox to study heterogeneity and allow to predict cell heterogeneity depending on the microenvironment for tissue engineering or develop new drug treatments. Modulo-EMT develops a set of interdisciplinary methods to design a cell heterogeneity testing platform for biomaterials applications and also cancer treatment innovation.

We develop key innovations: First, we create a quantitative image analysis to test heterogeneity parameters associated to EMT. Second, we design tightly controlled microenvironment on-chip to test the effect of the microenvironment on cell heterogeneity. Finally, we tune in a quick and reversible fashion the ability of cells to interact with the microenvironment to test the causality between microenvironment modification and cell heterogeneity.

This framework will be resuming patient to patient differences using only on-chip methods and microenvironment mimicking with genetic engineering, offering a low cost but efficient strategy. Modulo-EMT will be key for drug treatment innovations that are efficient with different cell heterogeneity level, relevant in biomedical applications like biomaterials for which cell heterogeneity must be tighly controled and tuned for higher efficiency.