Protrusion force and cell-cell adhesion play a critical role in collective tumor cluster migration

Abstract

Collective migration refers to the coordinated movement of cells as a single unit during migration. While collective migration enhances invasive and metastatic potential in cancer, the mechanisms driving this behavior and regulating tumor migration plasticity remain poorly understood. This study provides a mechanistic model explaining the emergence of different modes of collective migration under hypoxia-induced secretome. We focus on the interplay between cellular protrusion force and cell-cell adhesion using collectively migrating three-dimensional microtumors as models with well-defined microenvironments. Large microtumors show directional migration due to intrinsic hypoxia, while small microtumors exhibit radial migration when exposed to hypoxic secretome. Here, we developed an in silico multi-scale microtumor model (MSMM) based on the cellular Potts model and implemented in CompuCell3D to elucidate underlying mechanisms. We identified distinct migration modes within specific regions of protrusion force and cell-cell adhesion parameter space and studied these modes using in vitro experimental microtumor models. We show that sufficient cellular protrusion force is crucial for radial and directional collective microtumor migration. Radial migration emerges when sufficient cellular protrusion force is generated, driving neighboring cells to move collectively in diverse directions. Within migrating tumors, strong cell-cell adhesion enhances the alignment of cell polarity, breaking the symmetric angular distribution of protrusion forces and leading to directional microtumor migration. The integrated results from the experimental and computational models provide fundamental insights into collective migration in response to different microenvironmental stimuli. Our computational and experimental models can adapt to various scenarios, providing valuable insights into cancer migration mechanisms. Statement of SignificanceWhile single-cell metastasis is well-studied, mechanisms of collective cluster migration are less understood. Significant challenges include the lack of a fundamental physics perspective on collective cluster migration mechanisms and suitable physiologically relevant three-dimensional (3D) in vitro models that can recapitulate collective cluster migration. In this article, we developed a computational model depicting microtumor migration behaviors. Collective cell migration, with varying correlation lengths, exhibits different migratory modes such as directional and radial migration. These modes are predicted by in silico models and confirmed using experimental microtumor models. Machine learning methods were exploited to identify migratory modes. Our computational and experimental models are flexible in various circumstances, offering insights into cancer migration mechanisms.