The ability of cancer cells to migrate is essential for cancer invasion and metastasis, and, as such, is responsible for the majority of the lethality of this devastating disease. In order to migrate, cancer cells have a particular cellular machinery defined by their nature and environment, resulting in a particular biomechanical configuration that enables them to effectively invade surrounding tissues. As such, an accurate understanding of cancer cell migration requires an analysis of the variety of migratory phenotypes, including the study of the biomechanical features that allow cell migration and invasion.
The goal of this project is to reveal the biomechanical landscape of cancer cell migration and elucidate the gene regulatory networks that define different migration strategies. To do so, three different aims are set: Aim 1: To perform a biomechanical analysis of cancer cell migration within an array of selected cancer cells. A mid-throughput screening of 25 different cancer cell lines of different tissue origins will be performed, generating unique data on morphological, kinematic, and, importantly, mechanical features, including the forces exerted by cells on the substrate. Furthermore, genetic expression data of the studied cells with equivalent experimental conditions will be generated for subsequent analysis. Recognizing the great value of open data ecosystems for scientific research, generated data will be made available by the MULTIMOT repository, enabling its further use and meta-analysis, thus maximizing the impact. Aim II: To unveil the intrinsic relationships between motion and forces that allow cancer cell migration. A multiparametric analysis will be used to obtain clusters of cells presenting specific biomechanical phenotypes. A detailed analysis will be performed in order to obtain the relationship between traction forces and motion within these phenotypes using the multiparametric analysis strategies recently developed by the host lab. Aim III: To identify gene regulatory networks determining cancer cell migration behaviors. Using the genetic expression data of the studied cell lines, a bioinformatic analysis will be conducted to identify the genetic signatures characteristic to each of the migration phenotypes. Finally, the functionality of these expression signatures for maintaining the migratory phenotype will be experimentally tested.
The project will be conducted at the Clinical molecular biology research group at the Department of Biosciences and Nutrition of the Karolinska Institutet, led by Prof. Staffan Strömblad.