At the Intersection of Computer Predictive Modelling and Cancer Researches

We constructed a 3D assembling model of the branched actin network. We revealed how intracellular proteins regulate the elastic properties of the network and then affect cell migration, providing greater insight into the fundamental physical mechanisms of published experimental observations.
Published in Cancer

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At the beginning of PhD study, I told myself that I should spend my PhD time on a valuable research topic, which can benefit human beings. After discussion with my supervisor Dr. Hanxing Zhu, we decided to study cell migrations with the backgrounds of computational mechanics and simulations. I spent about three months reading literatures to learn the lamellipodia-based cell migrations and the latest researches. Meanwhile, I wrote a 40-page review draft from over 150 research papers, which built a strong foundation for this research.

The highly dynamic lamellipodial branched actin network supports cell migration through heterogeneous mechanical extracellular microenvironments. Thus, its elastic properties play essential roles in determining cell migration 1. However, we found that it is unclear about how various intracellular proteins regulate the elastic properties of the network and then affect cell migration. The major challenge to investigate this question is that the highly dynamic and stochastic remodeling behaviors hinder one from performing an adequate number of biological experiments to study the quantitative relationships between the macroscopic elastic properties of the network and the microscopic structures regulated by various intracellular proteins.

To address the above question, we developed a 5000-line computer code tool to construct the realistic stochastic self-assembling multi-scale model of the in vivo lamellipodial branched actin network. Our computer codes take into account of five types of key proteins, i.e., filamentous actin, Arp2/3 complex, capping protein, filamin-A and α-actinin, and their mechano-chemical assembling interactions, such as filament polymerizing, Arp2/3 complex branching, capping protein inhibiting polymerization and actin-crosslinking proteins binding and unbinding. The spatiotemporal remodeling architectures of the lamellipodial branched actin network during driving cell migration are obtained over more than 4000 different stochastic models. Then, with 24000 finite element simulations, the role of each type of intracellular proteins in adapting the elastic properties of the network and then affecting cell migration is deciphered quantitatively. More importantly, we reveal a resistance-adaptive intracellular physical mechanism of the elastic properties of the lamellipodial branched actin network for cell migration. Our simulations predict many experimental observations 1-12. The revealed quantitative results have important clinical values for cancer cell metastasis. For example, our results suggest that creating intracellular inhibitors for Arp2/3 complex might be more effective for reducing cancer cell invasion and metastasis. Besides, the revealed physical mechanisms also provide insights into the understanding of endocytosis, phagocytosis, vesicle trafficking, intracellular pathogen transport and dendritic spine formation, where branched actin networks are generated.

Finally, we highlight that constructing predictive multiscale models at the intersection of biology, computer science, physics and chemistry is an effective way to study the highly dynamic, stochastic and complex physiological activities and pathological mechanism 13. It not only can get massive amount of data, but also can capture the quantitative relationships between various factors/behaviors to analyze the underlying biophysical mechanism, which is extremely important for drug developments. As one of the reviewers of the paper points out, biological insights can be gained from this engineering-based approach.

The article is published in Communications Biology


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