Specific genetic mutations serve as clues to cancer emergence. However, non-genetic cell state shift mechanisms—such as the epithelial-to-mesenchymal transition (EMT)—drive swift, reversible drug tolerance and metastasis. Unlike the slow process of acquiring mutations, this plasticity allows rapid, drug-tolerant cells to revert to previous states upon withdrawal of the drug, thereby driving pharmacological resistance. Insight into the evolution of cell states in cancer is critical for optimizing drug regimens. Here we propose dynamic conformational heterogeneity as an untapped fundamental driver of adaptive resistance. Proteins do not function as simple binary switches; rather, they exist as dynamic ensembles. Cancer arises when their conformational distribution shifts permanently towards an active state. Drugs operate by selecting specific (oncogenic) 3D conformer shapes and reverse-shifting the population back to a stabilized inactive state. Epigenetic dysregulation in cancer cells amplifies expression levels of these proteins, shifting the ensemble toward the oncogenic state. The increased abundance of the active state saturates the networks, overcoming feedback controls. We propose that effectively countering cancer evolution requires drug combinations that target oncogenic conformations at both molecular and systems levels, including adaptive phenotypic plasticity factors, shifting focus from individual static targets to dynamic population states.
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Nussinov et al. (2026) studied this question.
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