title: Stochastic modeling suggests that noise reduces differentiation efficiency by inducing a heterogeneous drug response in glioma differentiation therapy.
abstract: Glioma differentiation therapy is a novel strategy that has been used to induce glioma cells to differentiate into glia-like cells. Although some advances in experimental methods for exploring the molecular mechanisms involved in differentiation therapy have been made, a model-based comprehensive analysis is still needed to understand these differentiation mechanisms and improve the effects of anti-cancer therapeutics. This type of analysis becomes necessary in stochastic cases for two main reasons: stochastic noise inherently exists in signal transduction and phenotypic regulation during targeted therapy and chemotherapy, and the relationship between this noise and drug efficacy in differentiation therapy is largely unknown.
  
  
  
  In this study, we developed both an additive noise model and a Chemical-Langenvin-Equation model for the signaling pathways involved in glioma differentiation therapy to investigate the functional role of noise in the drug response. Our model analysis revealed an ultrasensitive mechanism of cyclin D1 degradation that controls the glioma differentiation induced by the cAMP inducer cholera toxin (CT). The role of cyclin D1 degradation in human glioblastoma cell differentiation was then experimentally verified. Our stochastic simulation demonstrated that noise not only renders some glioma cells insensitive to cyclin D1 degradation during drug treatment but also induce heterogeneous differentiation responses among individual glioma cells by modulating the ultrasensitive response of cyclin D1. As such, the noise can reduce the differentiation efficiency in drug-treated glioma cells, which was verified by the decreased evolution of differentiation potential, which quantified the impact of noise on the dynamics of the drug-treated glioma cell population.
  
  
  
  Our results demonstrated that targeting the noise-induced dynamics of cyclin D1 during glioma differentiation therapy can increase anti-glioma effects, implying that noise is a considerable factor in assessing and optimizing anti-cancer drug interventions.
authors: Zhong-shan School of Medicine, Sun Yat-Sen University, Guangzhou, 510089, China. dongbusun@163.com.|School of Mathematical and Computational Science, Sun Yat-Sen University, Guangzhou, 510275, China. dongbusun@163.com.
authors: Xiaoqiang
authors: X
authors: Sun
authors: School of Mathematical and Computational Science, Sun Yat-Sen University, Guangzhou, 510275, China.
authors: Jiajun
authors: J
authors: Zhang
authors: School of Mathematics, Liaoning University, Shenyang, 110036, China.|Research Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China.
authors: Qi
authors: Q
authors: Zhao
authors: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China.
authors: Xing
authors: X
authors: Chen
authors: Zhong-shan School of Medicine, Sun Yat-Sen University, Guangzhou, 510089, China. zhuwenbo@mail.sysu.edu.cn.
authors: Wenbo
authors: W
authors: Zhu
authors: Zhong-shan School of Medicine, Sun Yat-Sen University, Guangzhou, 510089, China.
authors: Guangmei
authors: G
authors: Yan
authors: School of Mathematical and Computational Science, Sun Yat-Sen University, Guangzhou, 510275, China. mcszhtsh@mail.sysu.edu.cn.
authors: Tianshou
authors: T
authors: Zhou
mesh_terms: D002454:Cell Differentiation / Q000187:drug effects*; D019938:Cyclin D1 / Q000378:metabolism; D025461:Feedback, Physiological / Q000187:drug effects; D005910:Glioma / Q000188:drug therapy* / Q000378:metabolism / Q000473:pathology*; D008954:Models, Biological; D058990:Molecular Targeted Therapy; D010641:Phenotype; D015398:Signal Transduction / Q000187:drug effects; D013269:Stochastic Processes; D016896:Treatment Outcome
chemical_list: D019938:Cyclin D1
keywords: Differentiation efficiency; Drug resistance; Glioma differentiation therapy; Noise; Stochastic modeling; Ultrasensitivity