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      저자 : Hecheng Li (검색결과 3 건)
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        RBPJ contributes to acquired docetaxel resistance in prostate cancer cells

        Li Xue,Zhenlong Wang,Hecheng Li,Zhaolun Li,Qi Chen,Peng Zhang,Haiwen Chen,Ziming Wang,Tie Chong,T. Chong 대한독성 유전단백체 학회 2017 Molecular & cellular toxicology Vol.13 No.3

        Our previous work has shown that depletion of recombination signal-binding protein J (RBPJ) results in reduced cell growth in prostate cancer cells. In this study, we aimed to investigate the function of RBPJ in the chemoresistance of prostate cancer. The expression of RBPJ was quantified in docetaxel-resistant and parental prostate cancer cells. Loss- and gainof- function experiments were conducted to explore the regulatory role of RBPJ in prostate cancer sensitivity to docetaxel. The pro-apoptotic effect of RBPJ silencing was checked in docetaxel-resistant prostate cancer cells. We found that docetaxel-resistant PC3-DR and DU145- DR cells expressed 3-5-fold high levels of RBPJ than parental PC3 and DU145 cells. Short hairpin RNAmediated knockdown of RBPJ inhibited cell proliferation and colony formation and reversed docetaxel resistance in docetaxel-resistant prostate cancer cells. In contrast, overexpression of RBPJ promoted cell growth, colony formation, and docetaxel resistance in parental prostate cancer cells. Downregulation of RBPJ induced apoptosis in docetaxel-resistant cells, which was accompanied by enhanced cleavage of caspase-3. In addition, RBPJ silencing or overexpression markedly modulated the expression of the Bcl-2 family members including Bcl-2, Bcl-xL, Mcl-1, Bax, and Bak. Altogether, RBPJ contributes to acquisition of docetaxel resistance in prostate cancer cells and may thus represent a potential target for overcoming chemotherapeutic resistance in this malignancy.

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        A GENETIC ALGORITHM BASED ON OPTIMALITY CONDITIONS FOR NONLINEAR BILEVEL PROGRAMMING PROBLEMS

        Li, Hecheng,Wang, Yuping The Korean Society for Computational and Applied M 2010 Journal of applied mathematics & informatics Vol.28 No.3

        For a class of nonlinear bilevel programming problems in which the follower's problem is linear, the paper develops a genetic algorithm based on the optimality conditions of linear programming. At first, we denote an individual by selecting a base of the follower's linear programming, and use the optimality conditions given in the simplex method to denote the follower's solution functions. Then, the follower's problem and variables are replaced by these optimality conditions and the solution functions, which makes the original bilevel programming become a single-level one only including the leader's variables. At last, the single-level problem is solved by using some classical optimization techniques, and its objective value is regarded as the fitness of the individual. The numerical results illustrate that the proposed algorithm is efficient and stable.

      • KCI등재

        A GENETIC ALGORITHM BASED ON OPTIMALITY CONDITIONS FOR NONLINEAR BILEVEL PROGRAMMING PROBLEMS

        Hecheng Li,Yuping Wang 한국전산응용수학회 2010 Journal of applied mathematics & informatics Vol.28 No.3

        For a class of nonlinear bilevel programming problems in which the follower's problem is linear, the paper develops a genetic algorithm based on the optimality conditions of linear programming. At first,we denote an individual by selecting a base of the follower's linear programming, and use the optimality conditions given in the simplex method to denote the follower's solution functions. Then, the follower's problem and variables are replaced by these optimality conditions and the solution functions, which makes the original bilevel programming become a single-level one only including the leader's variables. At last, the single-level problem is solved by using some classical optimization techniques, and its objective value is regarded as the fitness of the individual. The numerical results illustrate that the proposed algorithm is efficient and stable.

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