Proceedings of the National Academy of Sciences · 2016 · 152 citations · 23 references
MedicineCell BiologyOncologyGene Regulatory NetworksMolecular OncologyTumor HeterogeneityCell Population DynamicsCell-state HeterogeneityNetwork DynamicsAttractor DynamicsAttractor NetworksCancer Cell-state HeterogeneityDynamic Network DynamicsRegulatory Gene NetworksRobustnessSystem RobustnessVolatility
The observed intercellular heterogeneity within a clonal cell population can be mapped as dynamical states clustered around an attractor point in gene expression space, owing to a balance between homeostatic forces and stochastic fluctuations. These dynamics have led to the cancer cell attractor conceptual model, with implications for both carcinogenesis and new therapeutic concepts. Immortalized and malignant EBV-carrying B-cell lines were used to explore this model and characterize the detailed structure of cell attractors. Any subpopulation selected from a population of cells repopulated the whole original basin of attraction within days to weeks. Cells at the basin edges were unstable and prone to apoptosis. Cells continuously changed states within their own attractor, thus driving the repopulation, as shown by fluorescent dye tracing. Perturbations of key regulatory genes induced a jump to a nearby attractor. Using the Fokker-Planck equation, this cell population behavior could be described as two virtual, opposing influences on the cells: one attracting toward the center and the other promoting diffusion in state space (noise). Transcriptome analysis suggests that these forces result from high-dimensional dynamics of the gene regulatory network. We propose that they can be generalized to all cancer cell populations and represent intrinsic behaviors of tumors, offering a previously unidentified characteristic for studying cancer.
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Stochastic State Transitions Give Rise to Phenotypic Equilibrium in Populations of Cancer Cells
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