MR imaging guided iron-based nanoenzyme for synergistic Ferroptosis−Starvation therapy in triple negative breast cancer
MR imaging guided iron-based nanoenzyme for synergistic Ferroptosis−Starvation therapy in triple negative breast cancer
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磁共振成像引导铁基纳米酶用于三阴性乳腺癌的协同铁死亡和饥饿疗法
DOI:
10.1016/j.smaim.2021.12.008
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发表时间:
2021-12
影响因子:
--
通讯作者:
Xiao Zeyu
中科院分区:
文献类型:
--
作者:
Wang Duo;Fang Weimin;Huang Cuiqing;Chen Zerong;Nie Tianqi;Wang Jinghao;Luo Liangping;Xiao Zeyu
Triple negative breast cancer (TNBC), as the most aggressive BC, accounts for the leading cause of worldwide women death. Owing to the deficiency of related hormone receptors, the efficacy of hormone therapy on TNBC is significantly confined in clinical treatment. Ferroptosis, a newly emerging antitumor strategy through enhancing iron-dependent lipid peroxides level to induce cancer cell death without the mediation of cell receptors, has been proved to be feasible in various cancer treatments. However, the high glutathione (GSH) level in tumor microenvironment limits the anti-tumor efficacy of ferroptosis. Herein, superparamagnetic iron oxide (SPIO) based nanoenzyme modified with Avastin (Ava) was designed and successfully prepared for synergistic ferroptosis and starvation therapy of TNBC. Through downregulating the GSH and glutathione peroxidase 4 (GPX4), the as-prepared SPIO-based nanoenzyme efficiently improved the ferroptosis efficacy on MDA-MB-231 cells. Besides that, the integration of starvation therapy based on Ava modification greatly decreased the expression of CD31, resulted to a nutrient-deprived status and thus significantly enhanced ferroptosis efficacy in a synergistic manner. Concluded from the antitumor investigation on an MDA-MB-231 cells xenograft mice model, the systemic administration of this nanoenzyme effectively inhibited the tumor growth and successfully enhanced the mice survival rate. Overall, we believe this biocompatible synergistic ferroptosis-starvation nanoenzyme may provide a refreshing scope to the clinical treatment of TNBC.
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影响因子:
7
作者:
Xiao, Zeyu;Chan, Leung;Luo, Liangping
通讯作者:
Luo, Liangping
影响因子:
64.5
作者:
Dixon SJ;Lemberg KM;Lamprecht MR;Skouta R;Zaitsev EM;Gleason CE;Patel DN;Bauer AJ;Cantley AM;Yang WS;Morrison B 3rd;Stockwell BR
通讯作者:
Stockwell BR
影响因子:
16.6
作者:
Wang G;Xie L;Li B;Sang W;Yan J;Li J;Tian H;Li W;Zhang Z;Tian Y;Dai Y
通讯作者:
Dai Y
DOI:
10.1126/science.aaw9872
发表时间:
2020-04-03
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Badgley MA;Kremer DM;Maurer HC;DelGiorno KE;Lee HJ;Purohit V;Sagalovskiy IR;Ma A;Kapilian J;Firl CEM;Decker AR;Sastra SA;Palermo CF;Andrade LR;Sajjakulnukit P;Zhang L;Tolstyka ZP;Hirschhorn T;Lamb C;Liu T;Gu W;Seeley ES;Stone E;Georgiou G;Manor U;Iuga A;Wahl GM;Stockwell BR;Lyssiotis CA;Olive KP
通讯作者:
Olive KP
影响因子:
18.9
作者:
Wang D;Zhou J;Fang W;Huang C;Chen Z;Fan M;Zhang MR;Xiao Z;Hu K;Luo L
通讯作者:
Luo L