Abstract
Cell plasticity, also known as lineage plasticity, refers to the ability of a cell to reprogram and change its phenotypic identity in response to various cues. This phenomenon is context-dependent, playing a crucial role in embryonic development, tissue regeneration, and wound healing. However, when dysregulated, cell plasticity contributes to cancer initiation, progression, metastasis, and therapeutic resistance. Throughout different stages of tumor development, cancer cells exploit various forms of plasticity to evade normal regulatory mechanisms that govern cell division and homeostasis. Recent evidence highlights the complex interplay between genetic and epigenetic factors, the tumor microenvironment, and epithelial-to-mesenchymal transition in driving cancer cell plasticity. This dynamic reprogramming suggests that "deregulated cell plasticity" could be considered an additional hallmark of cancer. Advancements in next-generation sequencing and single-cell RNA analysis, combined with artificial intelligence technologies such as deep learning, along with Google's AlphaFold may help predict the trajectories of cancer cells. By predicting protein three-dimensional structures and identifying both active and potential allosteric binding sites, AlphaFold 2 can accelerate the development of new cancer drugs and therapies. For example, allosteric drugs, bind to the allosteric rather than the active sites, can induce conformational changes in proteins, affecting their activities. This can then alter the conformation of an active site that a drug-resistant mutation has created, permitting a blocked orthosteric drug to bind and this enables the design of more effective drugs that can synergize with traditional orthosteric drugs to bind and regain its efficacy. These innovations could provide deeper insights into the intricate mechanisms of cancer progression and resistance, ultimately paving the way for more precise, durable, and personalized oncologic treatments.