Preclinical comparison of regorafenib and sorafenib efficacy for hepatocellular carcinoma using multimodality molecular imaging
文献类型:期刊论文
作者 | Liu, Shengnan1,2; Du, Yang2,3,4![]() ![]() ![]() |
刊名 | CANCER LETTERS
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出版日期 | 2019 |
卷号 | 453页码:74-83 |
关键词 | Hepatocellular carcinoma Regorafenib Sorafenib Molecular imaging Therapeutic effects |
ISSN号 | 0304-3835 |
DOI | 10.1016/j.canlet.2019.03.037 |
通讯作者 | Ma, He(mahe@bmie.neu.edu.cn) ; Zhu, Xu(drzhuxu@163.com) ; Tian, Jie(jie.tian@ia.ac.cn) |
英文摘要 | Sorafenib has been used as a clinical targeted therapy for hepatocellular carcinoma (HCC) for more than a decade. In 2017, regorafenib was approved for HCC treatment and has since been reported to prolong the survival of advanced HCC patients after treatment failure with sorafenib. However, there has been no direct systematic comparison of the therapeutic effects of regorafenib and sorafenib against HCC. In this study, we comprehensively compared the therapeutic effects of sorafenib and regorafenib against HCC in vitro and in vivo using multimodality molecular imaging, which can show molecular and cellular differences at early stages. The side effects of sorafenib and regorafenib were also systematically evaluated. The data showed that compared with sorafenib treatment, regorafenib exerted stronger antitumor and antiangiogenic effects and significantly increased the survival rate of HCC mice. Sorafenib but not regorafenib treatment caused body weight loss and liver and kidney dysfunction, while regorafenib but not sorafenib treatment caused hypertension. Our study may provide an experimental basis for the guidance of clinical HCC targeted treatment with regorafenib and sorafenib. |
WOS关键词 | BAY 73-4506 ; APOPTOSIS ; THERAPY ; CANCER ; TUMOR |
资助项目 | National Key Research and Development Plan of China[2017YFA0205200] ; National Natural Science Foundation of China[81871514] ; National Natural Science Foundation of China[81470083] ; National Natural Science Foundation of China[81227901] ; Strategic Priority Research Program from Chinese Academy of Sciences[XDB02060010] ; International Innovation Team of CAS[20140491524] ; Beijing Municipal Science and Technology Commission[Z161100002616022] |
WOS研究方向 | Oncology |
语种 | 英语 |
WOS记录号 | WOS:000467511100007 |
出版者 | ELSEVIER IRELAND LTD |
资助机构 | National Key Research and Development Plan of China ; National Natural Science Foundation of China ; Strategic Priority Research Program from Chinese Academy of Sciences ; International Innovation Team of CAS ; Beijing Municipal Science and Technology Commission |
源URL | [http://ir.ia.ac.cn/handle/173211/24585] ![]() |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
通讯作者 | Ma, He; Zhu, Xu; Tian, Jie |
作者单位 | 1.Northeastern Univ, Sinodutch Biomed & Informat Engn Sch, Shenyang, Liaoning, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 3.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100080, Peoples R China 5.Peking Univ, Sch Oncol, Key Lab Carcinogenesis & Translat Res, Dept Intervent Therapy,Minist Educ Beijing, 52 Fucheng Rd, Beijing 100142, Peoples R China 6.Beihang Univ, Sch Med, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China 7.Xidian Univ, Sch Life Sci & Technol, Minist Educ, Engn Res Ctr Mol & Neuro Imaging, Xian 710126, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Shengnan,Du, Yang,Ma, He,et al. Preclinical comparison of regorafenib and sorafenib efficacy for hepatocellular carcinoma using multimodality molecular imaging[J]. CANCER LETTERS,2019,453:74-83. |
APA | Liu, Shengnan,Du, Yang,Ma, He,Liang, Qian,Zhu, Xu,&Tian, Jie.(2019).Preclinical comparison of regorafenib and sorafenib efficacy for hepatocellular carcinoma using multimodality molecular imaging.CANCER LETTERS,453,74-83. |
MLA | Liu, Shengnan,et al."Preclinical comparison of regorafenib and sorafenib efficacy for hepatocellular carcinoma using multimodality molecular imaging".CANCER LETTERS 453(2019):74-83. |
入库方式: OAI收割
来源:自动化研究所
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