Metastasis is a hallmark of cancer. Cancer cells can utilize epithelial-mesenchymal transition (EMT) to facilitate metastasis. During metastasis, cells do not always undergo a complete EMT, instead a partial EMT, leading to a hybrid epithelial/mesenchymal (E/M) phenotype has often been observed. Cells in the hybrid E/M phenotype tend to migrate as clusters of circulating tumor cells, that serve as the 'chief instigators' of metastasis. Typically, the hybrid E/M phenotype was assumed to be transient. Here we identify mechanisms underlying EMT tristability – epithelial, hybrid E/M, mesenchymal - through integrated theoretical and experimental approach. We further identify several phenotypic stability factors that may stabilize the hybrid E/M phenotype, and associate it with stem-like properties. To extend our understanding of EMT dynamics, we develop a new computational method, generalized random circuit perturbation (RACIPE), by which multiple hybrid E/M phenotypes are characterized.

Abnormal metabolism is another hallmark of cancer. Cancer cells were considered to utilize primarily glycolysis for ATP production even in the presence of oxygen, referred to as the Warburg effect. Increasing evidence shows that mitochondria are actively functioning in cancer cells and oxidative phosphorylation (OXPHOS) may be specifically associated with metastasis. However, it remains elusive how cancer cells take advantage of both glycolysis and OXPHOS to facilitate malignancy. Through integrating mathematical modeling with bioinformatics, we show that cancer cells can acquire a stable hybrid metabolic phenotype, characterized by high activity of AMPK and HIF-1, and high metabolic activity of glycolysis and glucose/fatty acid oxidation. Guided by the model, we develop the AMPK and HIF-1 signatures by evaluating the expression of their downstream targets, to quantify the activity of AMPK and HIF-1. The AMPK and HIF-1 signatures can capture the significant metabolic features of both bulk tumors and single cells.

In summary, our systems biology analysis of EMT and metabolic reprogramming serves as a platform to identify certain underlying basic principles pertaining to different hallmarks of cancer and design therapies targeting cancer cell plasticity.