Collective migration and phenotypic plasticity in cancer metastasis

Abstract

Cancer metastasis, the spread of cancer to distant organs, is the major cause of cancerrelated mortality. Hence, understanding the mechanisms underlying cancer metastasis is crucial to improve clinical interventions. Despite intensive efforts, the driving mechanisms remain ill-understood due to the difficulties posed by studying the different steps of the metastatic cascade in patients. Two established models have been proposed to underlie the driving mechanisms of metastasis are phenotypic plasticity and collective migration. Phenotypic plasticity, i.e. the capacity of the migrating cancer cell to adapt to the different cellular contexts that it encounters en route to form a metastasis, revolves around reversable transitions from epithelial to mesenchymal (EMT and MET) identities. The collective migration model denotes migrating cancer cells can overcome barriers by coordinated cooperation. Recently, these views have been integrated in a model where partial (EMT) is believed to mediate collective migration. Here, we will investigate critical assumptions of this integrated model by focusing on different steps along the invasion-metastasis cascade. Using an unsupervised approach based on complete transcriptomes, we unravel single cell EMT-related transcriptional differences in colorectal cancer cell lines and map different phenotypes on the EMT spectrum to identify E/M sub-states that might underlie collective invasion. Next, we have developed and evaluated 3D collagen models to facilitate collective migration studies both in vitro and ex vivo. Preliminary data obtained using this approach highlights how EMT induction can alter the dominating tumor migration type. Taken together, our results support a case for phenotypic plasticity and collective migration as complementary and functionally correlated mechanisms, and could serve as point of engagement for further studies aimed at clarifying the role of partial EMT in collective migration.