Loic Binan

Research in our lab aims to develop technologies to investigate the mechanisms by which gene networks control the self-organization of cells into complex 3-D tissues during development, as well as the modifications to this organization that take place in disease. This includes approaches to collect new types of data as well as algorithms to analyze these data. The techniques we use include gene editing (CRISPR), spatial transcriptomics, single cell RNA sequencing, microscopy, and computational methods for image analysis and statistics. We develop our tools in tissues like the brain or tumors. 

Cancer metastasis

Understanding the mechanisms of metastasis initiation with spatial transcriptomics and genetic perturbations.

The majority of cells at the primary site of a tumor have an epithelial phenotypes, but many cells undergo partial, transient transitions to mesenchymal-like phenotypes. While epithelial, tumor cells proliferate fast and are well adhered to their neighbors, but when they become mesenchymal, proliferation slows down and cells start migrating. In this state, they can reach new sites, where they revert to epithelial traits and restart proliferating, forming a metastatic lesion. This process is highly dynamic, and strongly influenced by the microenvironment. We are investigating the genetic mechanisms that allow cells to reversibly transition between epithelial and mesenchymal phenotypes.

Isoforms and non-coding regions 

Many genes can be expressed as a variety of isoforms that contain different fragments, or exons, of the sequence of the same gene. Beyond differences in total number of molecules of RNA from a given gene, the function of alternatively spliced genes strongly depends on differences in their sequence. We develop technologies to understand the regulation and effect of alternative splicing in the context of neurodegenerative diseases. 

Influence of past cell-cell interactions 

Spatial technologies are designed to allow interrogating the influence of cellular neighborhoods on genetic pathways and resulting phenotypes. This analysis is limited to a snapshot of the spatial environment of the sample at the moment it was collected, and the information about past interactions of cells with their environment is lost. We develop tools to investigate how past cell-cell interactions shape present transcriptional activity in cells during development.