We are looking for candidates for a PhD position wishing to work in an interdisciplinary environment, and we will consider a variety of profiles for this project with backgrounds either in chemistry, polymer, biomaterials, or material sciences.

The mechanical, geometrical and chemical properties of the 3D fibrous extracellular matrix play a key role in cancer initiation and progression, by controlling the movement and fate of tumor cells as well as surrounding fibroblasts or immune cells. A strong emphasis has been put recently in the community on the development of matrices with controllable fiber properties, as tools to understand cell mechanical behavior and migration. However, while numerous biomaterials have been engineered to obtain the desired properties at the multicellular scale, controlling the 3D architecture and the chemistry of fibers at a subcellular scale necessitates specific techniques like two-photon polymerization. Our team has developed over the years a full toolbox to produce at will complex 3D geometries and fiber networks 1,2, in hybrid polymers, hydrogels or protein materials, which also includes an innovative measurement of 3D forces exerted by cells. Now our system provides an ideal tool to understand finely the dynamic adaptation of cell individual and collective migration to the microenvironment, including migration behaviors and cell shape changes in tumors.
This project aims to characterize the dynamic behavior of cancer cells and surrounding cells, in relation to the fine geometry and to local mechanical and chemical properties of their 3D fiber microenvironments. Two-photon polymerization will be used to build a variety of 3D generic architectures of fiber grids characteristic of the tumor extracellular matrix, like structures with gradients of stiffness, fiber density or different fiber cross-linkings. In these different architectures, the migration biases, the dynamic morphology of cells and of their nuclei and membrane protrusions (including filopodia) and the local 3D forces will be systematically analyzed, and the results integrated in a general framework in link with the local physical and chemical cues of the grid. Cell lines studied will be fluorescently-labeled tumor cells models of breast or renal cancer, fibroblasts or cancer-associated fibroblasts, or immune cells. Image acquisition will be performed by advanced optical tools, spinning disk or Lattice Light Sheet Microscopy. An important part of the project will be to develop from previous tools of the group and from the existing literature automated image analysis pipelines with Artificial Intelligence-based techniques, and to integrate these results in a general frame.
This project is based on the expertise of the consortium on chemistry, two-photon polymerization and cell dynamics, including image analysis and 3D force measurements. It will highly benefit from synergy with parallel collaborative projects developed in the team in various 3D architectures. The system developed, from microstructures to cell dynamic datasets and automated image analysis development, will be of general interest for the community, and will pave the way to future applications in the domain of cancer treatments, for example targeting matrix organization.