The project involved an interdisciplinary research program, bringing together forefront knowledge on tumor-immune crosstalk, biophysical measurements and mathematical modeling. The activities carried out over the course of the project were directed along two main objectives:
I. Characterize the migratory behavior of macrophages in a three-dimensional environment and subjected to a mechanical stimulus. To pursue this objective, we established an experimental methodology that allowed us to embed macrophages and aggregates of cancer cells in a synthetic extracellular matrix. We were able to scatter cancer spheroids in a collagen matrix and use them as generators of mechanical alterations. This was done by exploiting the natural ability of cancer cells to contract collagen fibers and consequently generate mechanical strains in the environment in which the macrophages were placed. We also developed an experimental method that allowed us to produce spatially and temporally controlled changes in the strain pattern generated by the spheroids, by inducing cellular damage to the cancer cells using a UV laser source. We collected data about macrophage response to the change in their external environment and characterized their motion with ad-hoc devised scientific codes.
II. Develop a quantitative and predictive mathematical model. To better understand the crosstalk between cells and their mechanical environment, we developed a theoretical framework in which our experimental observations could be described. We started from models already present in the literature and we complemented them with equations that describe the interactions between the cells and the fibers in the collagen. Also, we proposed a mechanism by which cells could control the contractile forces that they exert on the matrix by preserving some information about their past mechanical state. The equations of the model were numerically integrated in a scientific code and could be adapted to describe different scenarios. In particular, we used the model to check the consistency of our biological assumptions. When model results were too different from the experimental observations, we had to modify our assumptions on the biological mechanisms that were taking place in the experiments – and consequently modify the equations in the model. Also, we used the model to extend the range of biophysical stimuli to which cells could be subject. As the number of experiments is limited by time and costs, using an in-silico approach allows to broaden the solicitations accessible only from experiments. Finally, we used the model to classify the experimental variables for their importance in determining cell response. By running multiple model runs with different parameters, it was possible to determine which variables had the largest impact and develop ad-hoc experiments to further investigate those.
During the course of the project, we extended our research network by collaborating with different researchers in the EU research space. The results of the project were communicated in a workshop and two conferences, and provided material for a scientific publication that is currently in preparation. We were also involved in an outreach activity through the initiative “Science is Wonderful!” organized for MSCA researchers. Important steps of the project were also shared through the Twitter account of the fellow, always including reference to the EU contribution.
