Our Research interests
Our research aims to elucidate the mechanisms by which cancer cells spread through the body.
Cancer is a leading cause of death worldwide and accounts for 8.2 million deaths per year.
The formation of metastases is responsible for 90% of deaths in patients with solid tumours.
Video: Cancer cells (purple) invading through collagen (green). Credit : Guillaume Jacquemet and Emilia Peuhu
Our research aims to elucidate the molecular mechanisms by which cells move.
The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance and wound healing.
In order for cells to migrate, they must interact with their environment using adhesion receptors, such as integrins, and form specialized adhesion complexes that mediate responses to different extracellular cues.
Video: Two populations (Red and Green) of cancer cells migrating. Credit : Guillaume Jacquemet
Filopodia and other protrusions
Our research aims to unravel how cells can sense their environement.
Filopodia are actin-rich “antenna-like” protrusions that are responsible for constantly probing the cellular environment.
In cancer cells, filopodia contribute to single cell migration and invasion, and filopodia-like structures have been implicated in cancer cell survival at metastatic sites.
Video: Cancer cell labelled with lifeact-mTurquoise to observe actin-based protrusions. Credit : Guillaume Jacquemet
ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy
ZeroCostDL4Mic allows the use of popular Deep Learning neural networks capable of carrying out tasks such as image segmentation and object detection (using U-Net, StarDist and YOLOv2), image denoising and restoration (using CARE and, Noise2Void), super-resolution microscopy (using Deep-STORM) and image-to-image translations (using Label-free prediction fnet, pix2pix and CycleGAN). With ZeroCostDL4Mic, researchers with little or no coding expertise are able to train (and re-train), validate, and use DL networks, though a browser and for free, thanks to the Google Collab engine the platform uses.
This project initiated as a collaboration between the Jacquemet and Henriques laboratories, considerably expanding with the help of laboratories spread across the planet. There is a long list of contributors associated with the project acknowledged in our preprint and the wiki page.
Automated cell tracking using StarDist and TrackMate
High/resolution microscopy and image analysis
We use multiple type of microscopy approaches in our work and continously develop tools to analyse images
Image: Time projection illustrating the dynamics of focal adhesions in human endothelial cells. Credit : Martina Lerche and Guillaume Jacquemet