Energy landscape reveals the underlying mechanism of cancer-adipose conversion with gene network models

Cancer is a systemic heterogeneous disease involving complex molecular networks. Tumor formation involves epithelial-mesenchymal transition (EMT), which promotes both metastasis and plasticity of cancer cells. Recent experiments proposed that cancer cells can be transformed into adipocytes with combination drugs. However, the underlying mechanisms for how these drugs work from molecular network perspective remain elusive. To reveal the mechanism of cancer-adipose conversion (CAC), we adopt a systems biology approach by combing mathematical modeling and molecular experiments based on the underlying molecular regulatory network. We identified four types of attractors which correspond to epithelial (E), mesenchymal (M), adipose (A) and partial/intermediate EMT (P) cell states on the CAC landscape. Landscape and transition path results illustrate that the intermediate states play critical roles in cancer to adipose transition. Through a landscape control strategy, we identified two new therapeutic strategies for drug combinations to promote CAC. We further verified these predictions by molecular experiments in different cell lines. Our combined computational and experimental approach provides a powerful tool to explore molecular mechanisms for cell fate transitions in cancer networks. Our results revealed the underlying mechanism for intermediate cell states governing the CAC, and identified new potential drug combinations to induce cancer adipogenesis.