👤 Huiyang Wang

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Also published as: A Wang, Ai-Ling Wang, Ai-Ting Wang, Aihua Wang, Aijun Wang, Aili Wang, Aimin Wang, Aiting Wang, Aixian Wang, Aiyun Wang, Aizhong Wang, Alexander Wang, Alice Wang, Allen Wang, Anlai Wang, Anli Wang, Annette Wang, Anni Wang, Anqi Wang, Anthony Z Wang, Anxiang Wang, Anxin Wang, Ao Wang, Aoli Wang, B R Wang, B Wang, Baihan Wang, Baisong Wang, Baitao Wang, Bangchen Wang, Banghui Wang, Bangmao Wang, Bangshing Wang, Bao Wang, Bao-Long Wang, Baocheng Wang, Baofeng Wang, Baogui Wang, Baojun Wang, Baoli Wang, Baolong Wang, Baoming Wang, Baosen Wang, Baowei Wang, Baoying Wang, Baoyun Wang, Bei Bei Wang, Bei Wang, Beibei Wang, Beilan Wang, Beilei Wang, Ben Wang, Benjamin H Wang, Benzhong Wang, Bi Wang, Bi-Dar Wang, Biao Wang, Bicheng Wang, Bijue Wang, Bin Wang, Bin-Xue Wang, Binbin Wang, Bing Qing Wang, Bing Wang, Binghai Wang, Binghan Wang, Bingjie Wang, Binglong Wang, Bingnan Wang, Bingyan Wang, Bingyu Wang, Binquan Wang, Biqi Wang, Bo Wang, Bochu Wang, Boyu Wang, Bruce Wang, C Wang, C Z Wang, Cai Ren Wang, Cai-Hong Wang, Cai-Yun Wang, Cailian Wang, Caiqin Wang, Caixia Wang, Caiyan Wang, Can Wang, Cangyu Wang, Carol A Wang, Catherine Ruiyi Wang, Cenxuan Wang, Chan Wang, Chang Wang, Chang-Yun Wang, Changduo Wang, Changjing Wang, Changliang Wang, Changlong Wang, Changqian Wang, Changtu Wang, Changwei Wang, Changying Wang, Changyu Wang, Changyuan Wang, Changzhen Wang, Chao Wang, Chao-Jun Wang, Chao-Yung Wang, Chaodong Wang, Chaofan Wang, Chaohan Wang, Chaohui Wang, Chaojie Wang, Chaokui Wang, Chaomeng Wang, Chaoqun Wang, Chaoxian Wang, Chaoyi Wang, Chaoyu Wang, Chaozhan Wang, Charles C N Wang, Chau-Jong Wang, Chen Wang, Chen-Cen Wang, Chen-Ma Wang, Chen-Yu Wang, Chenchen Wang, Chenfei Wang, Cheng An Wang, Cheng Wang, Cheng-Cheng Wang, Cheng-Jie Wang, Cheng-zhang Wang, Chengbin Wang, Chengcheng Wang, Chenggang Wang, Chenghao Wang, Chenghua Wang, Chengjian Wang, Chengjun Wang, Chenglin Wang, Chenglong Wang, Chengniu Wang, Chengqiang Wang, Chengshuo Wang, Chenguang Wang, Chengwen Wang, Chengyan Wang, Chengyu Wang, Chengze Wang, Chenji Wang, Chenliang Wang, Chenwei Wang, Chenxi Wang, Chenxin Wang, Chenxuan Wang, Chenyang Wang, Chenyao Wang, Chenyin Wang, Chenyu Wang, Chenzi Wang, Chi Chiu Wang, Chi Wang, Chi-Ping Wang, Chia-Chuan Wang, Chia-Lin Wang, Chien-Hsun Wang, Chien-Wei Wang, Chih-Chun Wang, Chih-Hao Wang, Chih-Hsien Wang, Chih-Liang Wang, Chih-Yang Wang, Chih-Yuan Wang, Chijia Wang, Ching C Wang, Ching-Jen Wang, Chiou-Miin Wang, Chong Wang, Chongjian Wang, Chonglong Wang, Chongmin Wang, Chongze Wang, Christina Wang, Christine Wang, Chu Wang, Chuan Wang, Chuan-Chao Wang, Chuan-Hui Wang, Chuan-Jiang Wang, Chuan-Wen Wang, Chuang Wang, Chuanhai Wang, Chuansen Wang, Chuansheng Wang, Chuanxin Wang, Chuanyue Wang, Chuduan Wang, Chun Wang, Chun-Chieh Wang, Chun-Juan Wang, Chun-Li Wang, Chun-Lin Wang, Chun-Ting Wang, Chun-Xia Wang, Chung-Hsi Wang, Chung-Hsing Wang, Chung-Teng Wang, Chunguo Wang, Chunhong Wang, Chuning Wang, Chunjiong Wang, Chunjuan Wang, Chunle Wang, Chunli Wang, Chunlong Wang, Chunmei Wang, Chunsheng Wang, Chunting Wang, Chunxia Wang, Chunxue Wang, Chunyan Wang, Chunyang Wang, Chunyi Wang, Chunyu Wang, Chuyao Wang, Cindy Wang, Ciyang Wang, Cong Wang, Congcong Wang, Congrong Wang, Congrui Wang, Cui Wang, Cui-Fang Wang, Cui-Shan Wang, Cuili Wang, Cuiling Wang, Cuizhe Wang, Cun-Yu Wang, Cunchuan Wang, Cunyi Wang, D Wang, Da Wang, Da-Cheng Wang, Da-Li Wang, Da-Yan Wang, Da-Zhi Wang, Dadong Wang, Dai Wang, Daijun Wang, Daiwei Wang, Daixi Wang, Dajia Wang, Dake Wang, Dali Wang, Dalong Wang, Dalu Wang, Dan Wang, Dan-Dan Wang, Danan Wang, Dandan Wang, Danfeng Wang, Dang Wang, Dangfeng Wang, Danling Wang, Danqing Wang, Danxin Wang, Danyang Wang, Dao Wen Wang, Dao-Wen Wang, Dao-Xin Wang, Daolong Wang, Daoping Wang, Daozhong Wang, Dapeng Wang, Daping Wang, Daqi Wang, Daqing Wang, David Q H Wang, David Q-H Wang, David Wang, Dawei Wang, Dayan Wang, Dayong Wang, Dazhi Wang, De-He Wang, Dedong Wang, Dehao Wang, Deli Wang, Delin Wang, Delong Wang, Demin Wang, Deming Wang, Dengbin Wang, Dennis Qing Wang, Dennis Wang, Deqi Wang, Deshou Wang, Dezhong Wang, Di Wang, Dinghui Wang, Dingting Wang, Dingxiang Wang, Dong D Wang, Dong Hao Wang, Dong Wang, Dong-Dong Wang, Dong-Jie Wang, Dong-Mei Wang, DongWei Wang, Dongdong Wang, Donggen Wang, Donghao Wang, Donghong Wang, Donghui Wang, Dongliang Wang, Donglin Wang, Dongmei Wang, Dongqin Wang, Dongshi Wang, Dongxia Wang, Dongxu Wang, Dongyan Wang, Dongyang Wang, Dongyi Wang, Dongying Wang, Dongyu Wang, Doudou Wang, Du Wang, Duan Wang, Duanyang Wang, Duo-Ping Wang, E Wang, Edward Wang, En-bo Wang, En-hua Wang, Endi Wang, Enhua Wang, Er-Jin Wang, Erfei Wang, Erika Y Wang, Ermao Wang, Erming Wang, Ertao Wang, Eryao Wang, Eunice S Wang, Exing Wang, F Wang, Fa-Kai Wang, Fan Wang, Fanchang Wang, Fang Wang, Fang-Tao Wang, Fangfang Wang, Fangjie Wang, Fangjun Wang, Fangyan Wang, Fangyong Wang, Fangyu Wang, Fanhua Wang, Fanwen Wang, Fanxiong Wang, Fei Wang, Fei-Fei Wang, Fei-Yan Wang, Feida Wang, Feifei Wang, Feijie Wang, Feimiao Wang, Feixiang Wang, Feiyan Wang, Fen Wang, Feng Wang, Feng-Sheng Wang, Fengchong Wang, Fengge Wang, Fenghua Wang, Fengliang Wang, Fenglin Wang, Fengling Wang, Fengqiang Wang, Fengyang Wang, Fengying Wang, Fengyong Wang, Fengyun Wang, Fengzhen Wang, Fengzhong Wang, Fu Wang, Fu-Sheng Wang, Fu-Yan Wang, Fu-Zhen Wang, Fubao Wang, Fubing Wang, Fudi Wang, Fuhua Wang, Fuqiang Wang, Furong Wang, Fuwen Wang, Fuxin Wang, Fuyan Wang, G Q Wang, G Wang, G-W Wang, Gan Wang, Gang Wang, Ganggang Wang, Ganglin Wang, Gangyang Wang, Ganyu Wang, Gao T Wang, Gao Wang, Gaofu Wang, Gaopin Wang, Gavin Wang, Ge Wang, Geng Wang, Genghao Wang, Gengsheng Wang, Gongming Wang, Guan Wang, Guan-song Wang, Guandi Wang, Guanduo Wang, Guang Wang, Guang-Jie Wang, Guang-Rui Wang, Guangdi Wang, Guanghua Wang, Guanghui Wang, Guangliang Wang, Guangming Wang, Guangsuo Wang, Guangwen Wang, Guangyan Wang, Guangzhi Wang, Guanrou Wang, Guanru Wang, Guansong Wang, Guanyun Wang, Gui-Qi Wang, Guibin Wang, Guihu Wang, Guihua Wang, Guimin Wang, Guiping Wang, Guiqun Wang, Guixin Wang, Guixue Wang, Guiying Wang, Guo-Du Wang, Guo-Hua Wang, Guo-Liang Wang, Guo-Ping Wang, Guo-Quan Wang, Guo-hong Wang, GuoYou Wang, Guobin Wang, Guobing Wang, Guodong Wang, Guohang Wang, Guohao Wang, Guoliang Wang, Guoling Wang, Guoping Wang, Guoqian Wang, Guoqiang Wang, Guoqing Wang, Guorong Wang, Guowen Wang, Guoxiang Wang, Guoxiu Wang, Guoyi Wang, Guoying Wang, Guozheng Wang, H J Wang, H Wang, H X Wang, H Y Wang, H-Y Wang, Hai Bo Wang, Hai Wang, Hai Yang Wang, Hai-Feng Wang, Hai-Jun Wang, Hai-Long Wang, Haibin Wang, Haibing Wang, Haibo Wang, Haichao Wang, Haichuan Wang, Haifei Wang, Haifeng Wang, Haihe Wang, Haihong Wang, Haihua Wang, Haijiao Wang, Haijing Wang, Haijiu Wang, Haikun Wang, Hailei Wang, Hailin Wang, Hailing Wang, Hailong Wang, Haimeng Wang, Haina Wang, Haining Wang, Haiping Wang, Hairong Wang, Haitao Wang, Haiwei Wang, Haixia Wang, Haixin Wang, Haixing Wang, Haiyan Wang, Haiying Wang, Haiyong Wang, Haiyun Wang, Haizhen Wang, Han Wang, Hanbin Wang, Hanbing Wang, Hanchao Wang, Handong Wang, Hang Wang, Hangzhou Wang, Hanmin Wang, Hanping Wang, Hanqi Wang, Hanying Wang, Hanyu Wang, Hanzhi Wang, Hao Wang, Hao-Ching Wang, Hao-Hua Wang, Hao-Tian Wang, Hao-Yu Wang, Haobin Wang, Haochen Wang, Haohao Wang, Haohui Wang, Haojie Wang, Haolong Wang, Haomin Wang, Haoming Wang, Haonan Wang, Haoping Wang, Haoqi Wang, Haoran Wang, Haowei Wang, Haoxin Wang, Haoyang Wang, Haoyu Wang, Haozhou Wang, He Wang, He-Cheng Wang, He-Ling Wang, He-Ping Wang, He-Tong Wang, Hebo Wang, Hechuan Wang, Heling Wang, Hemei Wang, Heming Wang, Heng Wang, Heng-Cai Wang, Hengjiao Wang, Hengjun Wang, Hequn Wang, Hesuiyuan Wang, Heyong Wang, Hezhi Wang, Hong Wang, Hong Yi Wang, Hong-Gang Wang, Hong-Hui Wang, Hong-Kai Wang, Hong-Qin Wang, Hong-Wei Wang, Hong-Xia Wang, Hong-Yan Wang, Hong-Yang Wang, Hong-Ying Wang, Hongbin Wang, Hongbing Wang, Hongbo Wang, Hongcai Wang, Hongda Wang, Hongdan Wang, Hongfang Wang, Hongjia Wang, Hongjian Wang, Hongjie Wang, Hongjuan Wang, Hongkun Wang, Honglei Wang, Hongli Wang, Honglian Wang, Honglun Wang, Hongmei Wang, Hongpin Wang, Hongqian Wang, Hongshan Wang, Hongsheng Wang, Hongtao Wang, Hongwei Wang, Hongxia Wang, Hongxin Wang, Hongyan Wang, Hongyang Wang, Hongyi Wang, Hongyin Wang, Hongying Wang, Hongyu Wang, Hongyuan Wang, Hongyue Wang, Hongyun Wang, Hongze Wang, Hongzhan Wang, Hongzhuang Wang, Horng-Dar Wang, Houchun Wang, Hsei-Wei Wang, Hsueh-Chun Wang, Hu WANG, Hua Wang, Hua-Qin Wang, Hua-Wei Wang, Huabo Wang, Huafei Wang, Huai-Zhou Wang, Huaibing Wang, Huaili Wang, Huaizhi Wang, Huajin Wang, Huajing Wang, Hualin Wang, Hualing Wang, Huan Wang, Huan-You Wang, Huang Wang, Huanhuan Wang, Huanyu Wang, Huaquan Wang, Huating Wang, Huawei Wang, Huaxiang Wang, Huayang Wang, Huei Wang, Hui Miao Wang, Hui Wang, Hui-Hui Wang, Hui-Li Wang, Hui-Nan Wang, Hui-Yu Wang, HuiYue Wang, Huie Wang, Huiguo Wang, Huihua Wang, Huihui Wang, Huijie Wang, Huijun Wang, Huilun Wang, Huimei Wang, Huimin Wang, Huina Wang, Huiping Wang, Huiquan Wang, Huiqun Wang, Huishan Wang, Huiting Wang, Huiwen Wang, Huixia Wang, Huiyan Wang, Huiyao Wang, Huiying Wang, Huiyu Wang, Huizhen Wang, Huizhi Wang, Huming Wang, I-Ching Wang, Iris X Wang, Isabel Z Wang, J J Wang, J P Wang, J Q Wang, J Wang, J Z Wang, J-Y Wang, Jacob E Wang, James Wang, Jeffrey Wang, Jen-Chun Wang, Jen-Chywan Wang, Jennifer E Wang, Jennifer T Wang, Jennifer X Wang, Jenny Y Wang, Jeremy R Wang, Jeremy Wang, Ji M Wang, Ji Wang, Ji-Nuo Wang, Ji-Yang Wang, Ji-Yao Wang, Ji-zheng Wang, Jia Bei Wang, Jia Bin Wang, Jia Wang, Jia-Liang Wang, Jia-Lin Wang, Jia-Mei Wang, Jia-Peng Wang, Jia-Qi Wang, Jia-Qiang Wang, Jia-Ying Wang, Jia-Yu Wang, Jiabei Wang, Jiabo Wang, Jiafeng Wang, Jiafu Wang, Jiahao Wang, Jiahui Wang, Jiajia Wang, Jiakun Wang, Jiale Wang, Jiali Wang, Jialiang Wang, Jialin Wang, Jialing Wang, Jiamin Wang, Jiaming Wang, Jian Wang, Jian'an Wang, Jian-Bin Wang, Jian-Guo Wang, Jian-Hong Wang, Jian-Long Wang, Jian-Wei Wang, Jian-Xiong Wang, Jian-Yong Wang, Jian-Zhi Wang, Jian-chun Wang, Jianan Wang, Jianbing Wang, Jianbo Wang, Jianding Wang, Jianfang Wang, Jianfei Wang, Jiang Wang, Jiangbin Wang, Jiangbo Wang, Jianghua Wang, Jianghui Wang, Jiangong Wang, Jianguo Wang, Jianhao Wang, Jianhua Wang, Jianhui Wang, Jiani Wang, Jianjiao Wang, Jianjie Wang, Jianjun Wang, Jianle Wang, Jianli Wang, Jianlin Wang, Jianliu Wang, Jianlong Wang, Jianmei Wang, Jianmin Wang, Jianning Wang, Jianping Wang, Jianqin Wang, Jianqing Wang, Jianqun Wang, Jianru Wang, Jianshe Wang, Jianshu Wang, Jiantao Wang, Jianwei Wang, Jianwu Wang, Jianxiang Wang, Jianxin Wang, Jianye Wang, Jianying Wang, Jianyong Wang, Jianyu Wang, Jianzhang Wang, Jianzhi Wang, Jiao Wang, Jiaojiao Wang, Jiapan Wang, Jiaping Wang, Jiaqi Wang, Jiaqian Wang, Jiatao Wang, Jiawei Wang, Jiawen Wang, Jiaxi Wang, Jiaxin Wang, Jiaxing Wang, Jiaxuan Wang, Jiayan Wang, Jiayang Wang, Jiayi Wang, Jiaying Wang, Jiayu Wang, Jiazheng Wang, Jiazhi Wang, Jie Jin Wang, Jie Wang, Jieda Wang, Jieh-Neng Wang, Jiemei Wang, Jieqi Wang, Jieyan Wang, Jieyu Wang, Jifei Wang, Jiheng Wang, Jihong Wang, Jiliang Wang, Jilin Wang, Jin Wang, Jin'e Wang, Jin-Bao Wang, Jin-Cheng Wang, Jin-Da Wang, Jin-E Wang, Jin-Juan Wang, Jin-Liang Wang, Jin-Xia Wang, Jin-Xing Wang, Jincheng Wang, Jindan Wang, Jinfei Wang, Jinfeng Wang, Jinfu Wang, Jing J Wang, Jing Wang, Jing-Hao Wang, Jing-Huan Wang, Jing-Jing Wang, Jing-Long Wang, Jing-Min Wang, Jing-Shi Wang, Jing-Wen Wang, Jing-Xian Wang, Jing-Yi Wang, Jing-Zhai Wang, Jingang Wang, Jingchun Wang, Jingfan Wang, Jingfeng Wang, Jingheng Wang, Jinghong Wang, Jinghua Wang, Jinghuan Wang, Jingjing Wang, Jingkang Wang, Jinglin Wang, Jingmin Wang, Jingnan Wang, Jingqi Wang, Jingru Wang, Jingtong Wang, Jingwei Wang, Jingwen Wang, Jingxiao Wang, Jingyang Wang, Jingyi Wang, Jingying Wang, Jingyu Wang, Jingyue Wang, Jingyun Wang, Jingzhou Wang, Jinhai Wang, Jinhao Wang, Jinhe Wang, Jinhua Wang, Jinhuan Wang, Jinhui Wang, Jinjie Wang, Jinjin Wang, Jinkang Wang, Jinling Wang, Jinlong Wang, Jinmeng Wang, Jinning Wang, Jinping Wang, Jinqiu Wang, Jinrong Wang, Jinru Wang, Jinsong Wang, Jintao Wang, Jinxia Wang, Jinxiang Wang, Jinyang Wang, Jinyu Wang, Jinyue Wang, Jinyun Wang, Jinzhu Wang, Jiou Wang, Jipeng Wang, Jiqing Wang, Jiqiu Wang, Jisheng Wang, Jiu Wang, Jiucun Wang, Jiun-Ling Wang, Jiwen Wang, Jixuan Wang, Jiyan Wang, Jiying Wang, Jiyong Wang, Jizheng Wang, John Wang, Jou-Kou Wang, Joy Wang, Ju Wang, Juan Wang, Jue Wang, Jueqiong Wang, Jufeng Wang, Julie Wang, Juling Wang, Jun Kit Wang, Jun Wang, Jun Yi Wang, Jun-Feng Wang, Jun-Jie Wang, Jun-Jun Wang, Jun-Ling Wang, Jun-Sheng Wang, Jun-Sing Wang, Jun-Zhuo Wang, Jundong Wang, Junfeng Wang, Jung-Pan Wang, Junhong Wang, Junhua Wang, Junhui Wang, Junjiang Wang, Junjie Wang, Junjun Wang, Junkai Wang, Junke Wang, Junli Wang, Junlin Wang, Junling Wang, Junmei Wang, Junmin Wang, Junpeng Wang, Junping Wang, Junqin Wang, Junqing Wang, Junrui Wang, Junsheng Wang, Junshi Wang, Junshuang Wang, Junwen Wang, Junxiao Wang, Junya Wang, Junying Wang, Junyu Wang, Justin Wang, Jutao Wang, Juxiang Wang, K Wang, Kai Wang, Kai-Kun Wang, Kai-Wen Wang, Kaicen Wang, Kaihao Wang, Kaihe Wang, Kaihong Wang, Kaijie Wang, Kaijuan Wang, Kailu Wang, Kaiming Wang, Kaining Wang, Kaiting Wang, Kaixi Wang, Kaixu Wang, Kaiyan Wang, Kaiyuan Wang, Kaiyue Wang, Kan Wang, Kangli Wang, Kangling Wang, Kangmei Wang, Kangning Wang, Ke Wang, Ke-Feng Wang, KeShan Wang, Kehan Wang, Kehao Wang, Kejia Wang, Kejian Wang, Kejun Wang, Keke Wang, Keming Wang, Kenan Wang, Keqing Wang, Kesheng Wang, Kexin Wang, Keyan Wang, Keyi Wang, Keyun Wang, Kongyan Wang, Kuan Hong Wang, Kui Wang, Kun Wang, Kunhua Wang, Kunpeng Wang, Kunzheng Wang, L F Wang, L M Wang, L Wang, L Z Wang, L-S Wang, Laidi Wang, Laijian Wang, Laiyuan Wang, Lan Wang, Lan-Wan Wang, Lan-lan Wang, Lanlan Wang, Larry Wang, Le Wang, Le-Xin Wang, Ledan Wang, Lee-Kai Wang, Lei P Wang, Lei Wang, Lei-Lei Wang, Leiming Wang, Leishen Wang, Leli Wang, Leran Wang, Lexin Wang, Leying Wang, Li Chun Wang, Li Dong Wang, Li Wang, Li-Dong Wang, Li-E Wang, Li-Juan Wang, Li-Li Wang, Li-Na Wang, Li-San Wang, Li-Ting Wang, Li-Xin Wang, Li-Yong Wang, LiLi Wang, Lian Wang, Lianchun Wang, Liang Wang, Liang-Yan Wang, Liangfu Wang, Lianghai Wang, Liangli Wang, Liangliang Wang, Liangxu Wang, Lianshui Wang, Lianyong Wang, Libo Wang, Lichan Wang, Lichao Wang, Liewei Wang, Lifang Wang, Lifei Wang, Lifen Wang, Lifeng Wang, Ligang Wang, Lihong Wang, Lihua Wang, Lihui Wang, Lijia Wang, Lijin Wang, Lijing Wang, Lijuan Wang, Lijun Wang, Liling Wang, Lily Wang, Limeng Wang, Limin Wang, Liming Wang, Lin Wang, Lin-Fa Wang, Lin-Yu Wang, Lina Wang, Linfang Wang, Ling Jie Wang, Ling Wang, Ling-Ling Wang, Lingbing Wang, Lingda Wang, Linghua Wang, Linghuan Wang, Lingli Wang, Lingling Wang, Lingyan Wang, Lingzhi Wang, Linhua Wang, Linhui Wang, Linjie Wang, Linli Wang, Linlin Wang, Linping Wang, Linshu Wang, Linshuang Wang, Lintao Wang, Linxuan Wang, Linying Wang, Linyuan Wang, Liping Wang, Liqing Wang, Liqun Wang, Lirong Wang, Litao Wang, Liting Wang, Liu Wang, Liusong Wang, Liuyang Wang, Liwei Wang, Lixia Wang, Lixian Wang, Lixiang Wang, Lixin Wang, Lixing Wang, Lixiu Wang, Liyan Wang, Liyi Wang, Liying Wang, Liyong Wang, Liyuan Wang, Liyun Wang, Long Wang, Longcai Wang, Longfei Wang, Longsheng Wang, Longxiang Wang, Lou-Pin Wang, Lu Wang, Lu-Lu Wang, Lueli Wang, Lufang Wang, Luhong Wang, Luhui Wang, Lujuan Wang, Lulu Wang, Luofu Wang, Luping Wang, Luting Wang, Luwen Wang, Luxiang Wang, Luya Wang, Luyao Wang, Luyun Wang, Lynn Yuning Wang, M H Wang, M Wang, M Y Wang, M-J Wang, Maiqiu Wang, Man Wang, Mangju Wang, Manli Wang, Mao-Xin Wang, Maochun Wang, Maojie Wang, Maoju Wang, Mark Wang, Mei Wang, Mei-Gui Wang, Mei-Xia Wang, Meiding Wang, Meihui Wang, Meijun Wang, Meiling Wang, Meixia Wang, Melissa T Wang, Meng C Wang, Meng Wang, Meng Yu Wang, Meng-Dan Wang, Meng-Lan Wang, Meng-Meng Wang, Meng-Ru Wang, Meng-Wei Wang, Meng-Ying Wang, Meng-hong Wang, Mengge Wang, Menghan Wang, Menghui Wang, Mengjiao Wang, Mengjing Wang, Mengjun Wang, Menglong Wang, Menglu Wang, Mengmeng Wang, Mengqi Wang, Mengru Wang, Mengshi Wang, Mengwen Wang, Mengxiao Wang, Mengya Wang, Mengyao Wang, Mengying Wang, Mengyuan Wang, Mengyue Wang, Mengyun Wang, Mengze Wang, Mengzhao Wang, Mengzhi Wang, Mian Wang, Miao Wang, Mimi Wang, Min Wang, Min-sheng Wang, Ming Wang, Ming-Chih Wang, Ming-Hsi Wang, Ming-Jie Wang, Ming-Wei Wang, Ming-Yang Wang, Ming-Yuan Wang, Mingchao Wang, Mingda Wang, Minghua Wang, Minghuan Wang, Minghui Wang, Mingji Wang, Mingjin Wang, Minglei Wang, Mingliang Wang, Mingmei Wang, Mingming Wang, Mingqiang Wang, Mingrui Wang, Mingsong Wang, Mingxi Wang, Mingxia Wang, Mingxun Wang, Mingya Wang, Mingyang Wang, Mingyi Wang, Mingyu Wang, Mingzhi Wang, Mingzhu Wang, Minjie Wang, Minjun Wang, Minmin Wang, Minxian Wang, Minxiu Wang, Minzhou Wang, Miranda C Wang, Mo Wang, Mofei Wang, Monica Wang, Mu Wang, Mutian Wang, Muxiao Wang, Muxuan Wang, N Wang, Na Wang, Nan Wang, Nana Wang, Nanbu Wang, Nannan Wang, Nanping Wang, Neng Wang, Ni Wang, Niansong Wang, Ning Wang, Ningjian Wang, Ningli Wang, Ningyuan Wang, Nuan Wang, Oliver Wang, Ouchen Wang, P Jeremy Wang, P L Wang, P N Wang, P Wang, Pai Wang, Pan Wang, Pan-Pan Wang, Panfeng Wang, Panliang Wang, Pei Chang Wang, Pei Wang, Pei-Hua Wang, Pei-Jian Wang, Pei-Juan Wang, Pei-Wen Wang, Pei-Yu Wang, Peichang Wang, Peigeng Wang, Peihe Wang, Peijia Wang, Peijuan Wang, Peijun Wang, Peilin Wang, Peipei Wang, Peirong Wang, Peiwen Wang, Peixi Wang, Peiyao Wang, Peiyin Wang, Peng Wang, Peng-Cheng Wang, Pengbo Wang, Pengchao Wang, Pengfei Wang, Pengjie Wang, Pengju Wang, Penglai Wang, Penglong Wang, Pengpu Wang, Pengtao Wang, Pengxiang Wang, Pengyu Wang, Pin Wang, Ping Wang, Pingchuan Wang, Pingfeng Wang, Pingping Wang, Pintian Wang, Po-Jen Wang, Pu Wang, Q Wang, Q Z Wang, Qi Wang, Qi-Bing Wang, Qi-En Wang, Qi-Jia Wang, Qi-Qi Wang, Qian Wang, Qian-Liang Wang, Qian-Wen Wang, Qian-Zhu Wang, Qian-fei Wang, Qianbao Wang, Qiang Wang, Qiang-Sheng Wang, Qiangcheng Wang, Qianghu Wang, Qiangqiang Wang, Qianjin Wang, Qianliang Wang, Qianqian Wang, Qianrong Wang, Qianru Wang, Qianwen Wang, Qianxu Wang, Qiao Wang, Qiao-Ping Wang, Qiaohong Wang, Qiaoqi Wang, Qiaoqiao Wang, Qifan Wang, Qifei Wang, Qifeng Wang, Qigui Wang, Qihao Wang, Qihua Wang, Qijia Wang, Qiming Wang, Qin Wang, Qing Jun Wang, Qing K Wang, Qing Kenneth Wang, Qing Mei Wang, Qing Wang, Qing-Bin Wang, Qing-Dong Wang, Qing-Jin Wang, Qing-Liang Wang, Qing-Mei Wang, Qing-Yan Wang, Qing-Yuan Wang, Qing-Yun Wang, QingDong Wang, Qingchun Wang, Qingfa Wang, Qingfeng Wang, Qinghang Wang, Qingliang Wang, Qinglin Wang, Qinglu Wang, Qingming Wang, Qingping Wang, Qingqing Wang, Qingshi Wang, Qingshui Wang, Qingsong Wang, Qingtong Wang, Qingyong Wang, Qingyu Wang, Qingyuan Wang, Qingyun Wang, Qingzhong Wang, Qinqin Wang, Qinrong Wang, Qintao Wang, Qinwen Wang, Qinyun Wang, Qiong Wang, Qiqi Wang, Qirui Wang, Qishan Wang, Qiu-Ling Wang, Qiu-Xia Wang, Qiuhong Wang, Qiuli Wang, Qiuling Wang, Qiuning Wang, Qiuping Wang, Qiushi Wang, Qiuting Wang, Qiuyan Wang, Qiuyu Wang, Qiwei Wang, Qixue Wang, Qiyu Wang, Qiyuan Wang, Quan Wang, Quan-Ming Wang, Quanli Wang, Quanren Wang, Quanxi Wang, Qun Wang, Qunxian Wang, Qunzhi Wang, R Wang, Ran Wang, Ranjing Wang, Ranran Wang, Re-Hua Wang, Ren Wang, Rencheng Wang, Renjun Wang, Renqian Wang, Renwei Wang, Renxi Wang, Renxiao Wang, Renyuan Wang, Rihua Wang, Rikang Wang, Rixiang Wang, Robert Yl Wang, Rong Wang, Rong-Chun Wang, Rong-Rong Wang, Rong-Tsorng Wang, RongRong Wang, Rongjia Wang, Rongping Wang, Rongyun Wang, Ru Wang, RuNan Wang, Ruey-Yun Wang, Rufang Wang, Ruhan Wang, Rui Wang, Rui-Hong Wang, Rui-Min Wang, Rui-Ping Wang, Rui-Rui Wang, Ruibin Wang, Ruibing Wang, Ruibo Wang, Ruicheng Wang, Ruifang Wang, Ruijing Wang, Ruimeng Wang, Ruimin Wang, Ruiming Wang, Ruinan Wang, Ruining Wang, Ruiquan Wang, Ruiwen Wang, Ruixian Wang, Ruixin Wang, Ruixuan Wang, Ruixue Wang, Ruiying Wang, Ruizhe Wang, Ruizhi Wang, Rujie Wang, Ruling Wang, Ruming Wang, Runci Wang, Runuo Wang, Runze Wang, Runzhi Wang, Ruo-Nan Wang, Ruo-Ran Wang, Ruonan Wang, Ruosu Wang, Ruoxi Wang, Rurong Wang, Ruting Wang, Ruxin Wang, Ruxuan Wang, Ruyue Wang, S L Wang, S S Wang, S Wang, S X Wang, Sa A Wang, Sa Wang, Saifei Wang, Saili Wang, Sainan Wang, Saisai Wang, Sangui Wang, Sanwang Wang, Sasa Wang, Sen Wang, Seok Mui Wang, Seungwon Wang, Sha Wang, Shan Wang, Shan-Shan Wang, Shang Wang, Shangyu Wang, Shanshan Wang, Shao-Kang Wang, Shaochun Wang, Shaohsu Wang, Shaokun Wang, Shaoli Wang, Shaolian Wang, Shaoshen Wang, Shaowei Wang, Shaoyi Wang, Shaoying Wang, Shaoyu Wang, Shaozheng Wang, Shasha Wang, Shau-Chun Wang, Shawn Wang, Shen Wang, Shen-Nien Wang, Shenao Wang, Sheng Wang, Sheng-Min Wang, Sheng-Nan Wang, Sheng-Ping Wang, Sheng-Quan Wang, Sheng-Yang Wang, Shengdong Wang, Shengjie Wang, Shengli Wang, Shengqi Wang, Shengya Wang, Shengyao Wang, Shengyu Wang, Shengyuan Wang, Shenqi Wang, Sheri Wang, Shi Wang, Shi-Cheng Wang, Shi-Han Wang, Shi-Qi Wang, Shi-Xin Wang, Shi-Yao Wang, Shibin Wang, Shichao Wang, Shicung Wang, Shidong Wang, Shifa Wang, Shifeng Wang, Shih-Wei Wang, Shihan Wang, Shihao Wang, Shihua Wang, Shijie Wang, Shijin Wang, Shijun Wang, Shikang Wang, Shimiao Wang, Shiqi Wang, Shiqiang Wang, Shitao Wang, Shitian Wang, Shiwen Wang, Shixin Wang, Shixuan Wang, Shiyang Wang, Shiyao Wang, Shiyin Wang, Shiyu Wang, Shiyuan Wang, Shiyue Wang, Shizhi Wang, Shouli Wang, Shouling Wang, Shouzhi Wang, Shu Wang, Shu-Huei Wang, Shu-Jin Wang, Shu-Ling Wang, Shu-Na Wang, Shu-Song Wang, Shu-Xia Wang, Shu-qiang Wang, Shuai Wang, Shuaiqin Wang, Shuang Wang, Shuang-Shuang Wang, Shuang-Xi Wang, Shuangyuan Wang, Shubao Wang, Shudan Wang, Shuge Wang, Shuguang Wang, Shuhe Wang, Shuiliang Wang, Shuiyun Wang, Shujin Wang, Shukang Wang, Shukui Wang, Shun Wang, Shuning Wang, Shunjun Wang, Shunran Wang, Shuo Wang, Shuping Wang, Shuqi Wang, Shuqing Wang, Shuren Wang, Shusen Wang, Shusheng Wang, Shushu Wang, Shuu-Jiun Wang, Shuwei Wang, Shuxia Wang, Shuxin Wang, Shuya Wang, Shuye Wang, Shuyue Wang, Shuzhe Wang, Shuzhen Wang, Shuzhong Wang, Shyi-Gang P Wang, Si Wang, Sibo Wang, Sidan Wang, Sihua Wang, Sijia Wang, Silas L Wang, Silu Wang, Simeng Wang, Siqi Wang, Siqing Wang, Siwei Wang, Siyang Wang, Siyi Wang, Siying Wang, Siyu Wang, Siyuan Wang, Siyue Wang, Song Wang, Songjiao Wang, Songlin Wang, Songping Wang, Songsong Wang, Songtao Wang, Sophie H Wang, Stephani Wang, Su'e Wang, Su-Guo Wang, Su-Hua Wang, Sufang Wang, Sugai Wang, Sui Wang, Suiyan Wang, Sujie Wang, Sujuan Wang, Suli Wang, Sun Wang, Supeng Perry Wang, Suxia Wang, Suyun Wang, Suzhen Wang, T Q Wang, T Wang, T Y Wang, Taian Wang, Taicheng Wang, Taishu Wang, Tammy C Wang, Tao Wang, Taoxia Wang, Teng Wang, Tengfei Wang, Theodore Wang, Thomas T Y Wang, Tian Wang, Tian-Li Wang, Tian-Lu Wang, Tian-Tian Wang, Tian-Yi Wang, Tiancheng Wang, Tiange Wang, Tianhao Wang, Tianhu Wang, Tianhui Wang, Tianjing Wang, Tianjun Wang, Tianlin Wang, Tiannan Wang, Tianpeng Wang, Tianqi Wang, Tianqin Wang, Tianqing Wang, Tiansheng Wang, Tiansong Wang, Tiantian Wang, Tianyi Wang, Tianying Wang, Tianyuan Wang, Tielin Wang, Tienju Wang, Tieqiao Wang, Timothy C Wang, Ting Chen Wang, Ting Wang, Ting-Chen Wang, Ting-Hua Wang, Ting-Ting Wang, Tingting Wang, Tingye Wang, Tingyu Wang, Tom J Wang, Tong Wang, Tong-Hong Wang, Tongsong Wang, Tongtong Wang, Tongxia Wang, Tongxin Wang, Tongyao Wang, Tony Wang, Tzung-Dau Wang, Victoria Wang, Vivian Wang, W Wang, Wanbing Wang, Wanchun Wang, Wang Wang, Wangxia Wang, Wanliang Wang, Wanxia Wang, Wanyao Wang, Wanyi Wang, Wanyu Wang, Wayseen Wang, Wei Wang, Wei-En Wang, Wei-Feng Wang, Wei-Lien Wang, Wei-Qi Wang, Wei-Ting Wang, Wei-Wei Wang, Weicheng Wang, Weiding Wang, Weidong Wang, Weifan Wang, Weiguang Wang, Weihao Wang, Weihong Wang, Weihua Wang, Weijian Wang, Weijie Wang, Weijun Wang, Weilin Wang, Weiling Wang, Weilong Wang, Weimin Wang, Weina Wang, Weining Wang, Weipeng Wang, Weiqin Wang, Weiqing Wang, Weirong Wang, Weiwei Wang, Weiwen Wang, Weixiao Wang, Weixue Wang, Weiyan Wang, Weiyu Wang, Weiyuan Wang, Weizhen Wang, Weizhi Wang, Weizhong Wang, Wen Wang, Wen-Chang Wang, Wen-Der Wang, Wen-Fei Wang, Wen-Jie Wang, Wen-Jun Wang, Wen-Qing Wang, Wen-Xuan Wang, Wen-Yan Wang, Wen-Ying Wang, Wen-Yong Wang, Wen-mei Wang, Wenbin Wang, Wenbo Wang, Wence Wang, Wenchao Wang, Wencheng Wang, Wendong Wang, Wenfei Wang, Wengong Wang, Wenhan Wang, Wenhao Wang, Wenhe Wang, Wenhui Wang, Wenjie Wang, Wenjing Wang, Wenju Wang, Wenjuan Wang, Wenjun Wang, Wenkai Wang, Wenkang Wang, Wenke Wang, Wenming Wang, Wenqi Wang, Wenqiang Wang, Wenqing Wang, Wenran Wang, Wenrui Wang, Wentao Wang, Wentian Wang, Wenting Wang, Wenwen Wang, Wenxia Wang, Wenxian Wang, Wenxiang Wang, Wenxiu Wang, Wenxuan Wang, Wenya Wang, Wenyan Wang, Wenyi Wang, Wenying Wang, Wenyu Wang, Wenyuan Wang, Wenzhou Wang, William Wang, Won-Jing Wang, Wu-Wei Wang, Wuji Wang, Wuqing Wang, Wusan Wang, X E Wang, X F Wang, X O Wang, X S Wang, X Wang, X-T Wang, Xi Wang, Xi-Hong Wang, Xi-Rui Wang, Xia Wang, Xian Wang, Xian-e Wang, Xianding Wang, Xianfeng Wang, Xiang Wang, Xiang-Dong Wang, Xiangcheng Wang, Xiangding Wang, Xiangdong Wang, Xiangguo Wang, Xianghua Wang, Xiangkun Wang, Xiangrong Wang, Xiangru Wang, Xiangwei Wang, Xiangyu Wang, Xianna Wang, Xianqiang Wang, Xianrong Wang, Xianshi Wang, Xianshu Wang, Xiansong Wang, Xiantao Wang, Xianwei Wang, Xianxing Wang, Xianze Wang, Xianzhe Wang, Xianzong Wang, Xiao Ling Wang, Xiao Qun Wang, Xiao Wang, Xiao-Ai Wang, Xiao-Fei Wang, Xiao-Hui Wang, Xiao-Jie Wang, Xiao-Juan Wang, Xiao-Lan Wang, Xiao-Li Wang, Xiao-Lin Wang, Xiao-Ming Wang, Xiao-Pei Wang, Xiao-Qian Wang, Xiao-Qun Wang, Xiao-Tong Wang, Xiao-Xia Wang, Xiao-Yi Wang, Xiao-Yun Wang, Xiao-jian WANG, Xiao-liang Wang, Xiaobin Wang, Xiaobo Wang, Xiaochen Wang, Xiaochuan Wang, Xiaochun Wang, Xiaodan Wang, Xiaoding Wang, Xiaodong Wang, Xiaofang Wang, Xiaofei Wang, Xiaofen Wang, Xiaofeng Wang, Xiaogang Wang, Xiaohong Wang, Xiaohu Wang, Xiaohua Wang, Xiaohui Wang, Xiaojia Wang, Xiaojian Wang, Xiaojiao Wang, Xiaojie Wang, Xiaojing Wang, Xiaojuan Wang, Xiaojun Wang, Xiaokun Wang, Xiaole Wang, Xiaoli Wang, Xiaoliang Wang, Xiaolin Wang, Xiaoling Wang, Xiaolong Wang, Xiaolu Wang, Xiaolun Wang, Xiaoman Wang, Xiaomei Wang, Xiaomeng Wang, Xiaomin Wang, Xiaoming Wang, Xiaona Wang, Xiaonan Wang, Xiaoning Wang, Xiaoqi Wang, Xiaoqian Wang, Xiaoqin Wang, Xiaoqing Wang, Xiaoqiu Wang, Xiaoqun Wang, Xiaorong Wang, Xiaorui Wang, Xiaoshan Wang, Xiaosong Wang, Xiaotang Wang, Xiaoting Wang, Xiaotong Wang, Xiaowei Wang, Xiaowen Wang, Xiaowu Wang, Xiaoxia Wang, Xiaoxiao Wang, Xiaoxin Wang, Xiaoxin X Wang, Xiaoxuan Wang, Xiaoya Wang, Xiaoyan Wang, Xiaoyang Wang, Xiaoye Wang, Xiaoying Wang, Xiaoyu Wang, Xiaozhen Wang, Xiaozhi Wang, Xiaozhong Wang, Xiaozhu Wang, Xichun Wang, Xidi Wang, Xietong Wang, Xifeng Wang, Xifu Wang, Xijun Wang, Xike Wang, Xin Wang, Xin Wei Wang, Xin-Hua Wang, Xin-Liang Wang, Xin-Ming Wang, Xin-Peng Wang, Xin-Qun Wang, Xin-Shang Wang, Xin-Xin Wang, Xin-Yang Wang, Xin-Yue Wang, Xinbo Wang, Xinchang Wang, Xinchao Wang, Xinchen Wang, Xincheng Wang, Xinchun Wang, Xindi Wang, Xindong Wang, Xing Wang, Xing-Huan Wang, Xing-Jin Wang, Xing-Jun Wang, Xing-Lei Wang, Xing-Ping Wang, Xing-Quan Wang, Xingbang Wang, Xingchen Wang, Xingde Wang, Xingguo Wang, Xinghao Wang, Xinghui Wang, Xingjie Wang, Xingjin Wang, Xinglei Wang, Xinglong Wang, Xingqin Wang, Xinguo Wang, Xingxin Wang, Xingxing Wang, Xingye Wang, Xingyu Wang, Xingyue Wang, Xingyun Wang, Xinhui Wang, Xinjing Wang, Xinjun Wang, Xinke Wang, Xinkun Wang, Xinli Wang, Xinlin Wang, Xinlong Wang, Xinmei Wang, Xinqi Wang, Xinquan Wang, Xinran Wang, Xinrong Wang, Xinru Wang, Xinrui Wang, Xinshuai Wang, Xintong Wang, Xinwen Wang, Xinxin Wang, Xinyan Wang, Xinyang Wang, Xinye Wang, Xinyi Wang, Xinying Wang, Xinyu Wang, Xinyue Wang, Xinzhou Wang, Xiong Wang, Xiongjun Wang, Xiru Wang, Xitian Wang, Xiu-Lian Wang, Xiu-Ping Wang, Xiufen Wang, Xiujuan Wang, Xiujun Wang, Xiurong Wang, Xiuwen Wang, Xiuyu Wang, Xiuyuan Hugh Wang, Xixi Wang, Xixiang Wang, Xiyan Wang, Xiyue Wang, Xizhi Wang, Xu Wang, Xu-Hong Wang, Xuan Wang, Xuan-Ren Wang, Xuan-Ying Wang, Xuanwen Wang, Xuanyi Wang, Xubo Wang, Xudong Wang, Xue Wang, Xue-Feng Wang, Xue-Hua Wang, Xue-Lei Wang, Xue-Lian Wang, Xue-Rui Wang, Xue-Yao Wang, Xue-Ying Wang, Xuebin Wang, Xueding Wang, Xuedong Wang, Xuefei Wang, Xuefeng Wang, Xueguo Wang, Xuehao Wang, Xuejie Wang, Xuejing Wang, Xueju Wang, Xuejun Wang, Xuekai Wang, Xuelai Wang, Xuelian Wang, Xuelin Wang, Xuemei Wang, Xuemin Wang, Xueping Wang, Xueqian Wang, Xueqin Wang, Xuesong Wang, Xueting Wang, Xuewei Wang, Xuewen Wang, Xuexiang Wang, Xueyan Wang, Xueyi Wang, Xueying Wang, Xueyun Wang, Xuezhen Wang, Xuezheng Wang, Xufei Wang, Xujing Wang, Xuliang Wang, Xumeng Wang, Xun Wang, Xuping Wang, Xuqiao Wang, Xuru Wang, Xusheng Wang, Xv Wang, Y Alan Wang, Y B Wang, Y H Wang, Y L Wang, Y P Wang, Y Wang, Y Y Wang, Y Z Wang, Y-H Wang, Y-S Wang, Ya Qi Wang, Ya Wang, Ya Xing Wang, Ya-Han Wang, Ya-Jie Wang, Ya-Long Wang, Ya-Nan Wang, Ya-Ping Wang, Ya-Qin Wang, Ya-Zhou Wang, Yachen Wang, Yachun Wang, Yadong Wang, Yafang Wang, Yafen Wang, Yahong Wang, Yahui Wang, Yajie Wang, Yajing Wang, Yajun Wang, Yake Wang, Yakun Wang, Yali Wang, Yalin Wang, Yaling Wang, Yalong Wang, Yan Ming Wang, Yan Wang, Yan-Chao Wang, Yan-Chun Wang, Yan-Feng Wang, Yan-Ge Wang, Yan-Jiang Wang, Yan-Jun Wang, Yan-Ming Wang, Yan-Yang Wang, Yan-Yi Wang, Yan-Zi Wang, Yana Wang, Yanan Wang, Yanbin Wang, Yanbing Wang, Yanchun Wang, Yancun Wang, Yanfang Wang, Yanfei Wang, Yanfeng Wang, Yang Wang, Yang-Yang Wang, Yange Wang, Yanggan Wang, Yangpeng Wang, Yangyang Wang, Yangyufan Wang, Yanhai Wang, Yanhong Wang, Yanhua Wang, Yanhui Wang, Yani Wang, Yanjin Wang, Yanjun Wang, Yankun Wang, Yanlei Wang, Yanli Wang, Yanliang Wang, Yanlin Wang, Yanling Wang, Yanmei Wang, Yanming Wang, Yanni Wang, Yanong Wang, Yanping Wang, Yanqing Wang, Yanru Wang, Yanting Wang, Yanwen Wang, Yanxia Wang, Yanxing Wang, Yanyang Wang, Yanyun Wang, Yanzhe Wang, Yanzhu Wang, Yao Wang, Yaobin Wang, Yaochun Wang, Yaodong Wang, Yaohe Wang, Yaokun Wang, Yaoling Wang, Yaolou Wang, Yaoxian Wang, Yaoxing Wang, Yaozhi Wang, Yapeng Wang, Yaping Wang, Yaqi Wang, Yaqian Wang, Yaqiong Wang, Yaru Wang, Yatao Wang, Yating Wang, Yawei Wang, Yaxian Wang, Yaxin Wang, Yaxiong Wang, Yaxuan Wang, Yayu Wang, Yazhou Wang, Ye Wang, Ye-Ran Wang, Yefu Wang, Yeh-Han Wang, Yehan Wang, Yeming Wang, Yen-Feng Wang, Yen-Sheng Wang, Yeou-Lih Wang, Yeqi Wang, Yezhou Wang, Yi Fan Wang, Yi Lei Wang, Yi Wang, Yi-Cheng Wang, Yi-Chuan Wang, Yi-Ming Wang, Yi-Ni Wang, Yi-Ning Wang, Yi-Shan Wang, Yi-Shiuan Wang, Yi-Shu Wang, Yi-Tao Wang, Yi-Ting Wang, Yi-Wen Wang, Yi-Xin Wang, Yi-Xuan Wang, Yi-Yi Wang, Yi-Ying Wang, Yi-Zhen Wang, Yi-sheng Wang, YiLi Wang, Yian Wang, Yibin Wang, Yibing Wang, Yichen Wang, Yicheng Wang, Yichuan Wang, Yifan Wang, Yifei Wang, Yigang Wang, Yige Wang, Yihan Wang, Yihao Wang, Yihe Wang, Yijin Wang, Yijing Wang, Yijun Wang, Yikang Wang, Yike Wang, Yilin Wang, Yilu Wang, Yimeng Wang, Yiming Wang, Yin Wang, Yin-Hu Wang, Yinan Wang, Yinbo Wang, Yindan Wang, Ying Wang, Ying-Piao Wang, Ying-Wei Wang, Ying-Zi Wang, Yingbo Wang, Yingcheng Wang, Yingchun Wang, Yingfei Wang, Yingge Wang, Yinggui Wang, Yinghui Wang, Yingjie Wang, Yingmei Wang, Yingna Wang, Yingping Wang, Yingqiao Wang, Yingtai Wang, Yingte Wang, Yingwei Wang, Yingwen Wang, Yingxiong Wang, Yingxue Wang, Yingyi Wang, Yingying Wang, Yingzi Wang, Yinhuai Wang, Yining E Wang, Yinong Wang, Yinsheng Wang, Yintao Wang, Yinuo Wang, Yinxiong Wang, Yinyin Wang, Yiou Wang, Yipeng Wang, Yiping Wang, Yiqi Wang, Yiqiao Wang, Yiqin Wang, Yiqing Wang, Yiquan Wang, Yirong Wang, Yiru Wang, Yirui Wang, Yishan Wang, Yishu Wang, Yitao Wang, Yiting Wang, Yiwei Wang, Yiwen Wang, Yixi Wang, Yixian Wang, Yixuan Wang, Yiyan Wang, Yiyi Wang, Yiying Wang, Yizhe Wang, Yong Wang, Yong-Bo Wang, Yong-Gang Wang, Yong-Jie Wang, Yong-Jun Wang, Yong-Tang Wang, Yongbin Wang, Yongdi Wang, Yongfei Wang, Yongfeng Wang, Yonggang Wang, Yonghong Wang, Yongjie Wang, Yongjun Wang, Yongkang Wang, Yongkuan Wang, Yongli Wang, Yongliang Wang, Yonglun Wang, Yongmei Wang, Yongming Wang, Yongni Wang, Yongqiang Wang, Yongqing Wang, Yongrui Wang, Yongsheng Wang, Yongxiang Wang, Yongyi Wang, Yongzhong Wang, You Wang, Youhua Wang, Youji Wang, Youjie Wang, Youli Wang, Youzhao Wang, Youzhi Wang, Yu Qin Wang, Yu Tian Wang, Yu Wang, Yu'e Wang, Yu-Chen Wang, Yu-Fan Wang, Yu-Fen Wang, Yu-Hang Wang, Yu-Hui Wang, Yu-Ping Wang, Yu-Ting Wang, Yu-Wei Wang, Yu-Wen Wang, Yu-Ying Wang, Yu-Zhe Wang, Yu-Zhuo Wang, Yuan Wang, Yuan-Hung Wang, Yuanbo Wang, Yuanfan Wang, Yuanjiang Wang, Yuanli Wang, Yuanqiang Wang, Yuanqing Wang, Yuanyong Wang, Yuanyuan Wang, Yuanzhen Wang, Yubing Wang, Yubo Wang, Yuchen Wang, Yucheng Wang, Yuchuan Wang, Yudong Wang, Yue Wang, Yue-Min Wang, Yue-Nan Wang, YueJiao Wang, Yuebing Wang, Yuecong Wang, Yuegang Wang, Yuehan Wang, Yuehong Wang, Yuehu Wang, Yuehua Wang, Yuelong Wang, Yuemiao Wang, Yueshen Wang, Yueting Wang, Yuewei Wang, Yuexiang Wang, Yuexin Wang, Yueying Wang, Yueze Wang, Yufei Wang, Yufeng Wang, Yugang Wang, Yuh-Hwa Wang, Yuhan Wang, Yuhang Wang, Yuhua Wang, Yuhuai Wang, Yuhuan Wang, Yuhui Wang, Yujia Wang, Yujiao Wang, Yujie Wang, Yujiong Wang, Yulai Wang, Yulei Wang, Yuli Wang, Yuliang Wang, Yulin Wang, Yuling Wang, Yulong Wang, Yumei Wang, Yumeng Wang, Yumin Wang, Yuming Wang, Yun Wang, Yun Yong Wang, Yun-Hui Wang, Yun-Jin Wang, Yun-Xing Wang, Yunbing Wang, Yunce Wang, Yunchao Wang, Yuncong Wang, Yunduan Wang, Yunfang Wang, Yunfei Wang, Yunhan Wang, Yunhe Wang, Yunong Wang, Yunpeng Wang, Yunqiong Wang, Yuntai Wang, Yunzhang Wang, Yunzhe Wang, Yunzhi Wang, Yupeng Wang, Yuping Wang, Yuqi Wang, Yuqian Wang, Yuqiang Wang, Yuqin Wang, Yusha Wang, Yushe Wang, Yusheng Wang, Yutao Wang, Yuting Wang, Yuwei Wang, Yuwen Wang, Yuxiang Wang, Yuxing Wang, Yuxuan Wang, Yuxue Wang, Yuyan Wang, Yuyang Wang, Yuyin Wang, Yuying Wang, Yuyong Wang, Yuzhong Wang, Yuzhou Wang, Yuzhuo Wang, Z P Wang, Z Wang, Z-Y Wang, Zai Wang, Zaihua Wang, Ze Wang, Zechen Wang, Zehao Wang, Zehua Wang, Zekun Wang, Zelin Wang, Zeneng Wang, Zengtao Wang, Zeping Wang, Zexin Wang, Zeying Wang, Zeyu Wang, Zeyuan Wang, Zezhou Wang, Zhan Wang, Zhang Wang, Zhanggui Wang, Zhangshun Wang, Zhangying Wang, Zhanju Wang, Zhao Wang, Zhao-Jun Wang, Zhaobo Wang, Zhaofeng Wang, Zhaofu Wang, Zhaohai Wang, Zhaohui Wang, Zhaojing Wang, Zhaojun Wang, Zhaoming Wang, Zhaoqing Wang, Zhaosong Wang, Zhaotong Wang, Zhaoxi Wang, Zhaoxia Wang, Zhaoyu Wang, Zhe Wang, Zhehai Wang, Zhehao Wang, Zhen Wang, ZhenXue Wang, Zhenbin Wang, Zhenchang Wang, Zhenda Wang, Zhendan Wang, Zhendong Wang, Zheng Wang, Zhengbing Wang, Zhengchun Wang, Zhengdong Wang, Zhenghui Wang, Zhengkun Wang, Zhenglong Wang, Zhenguo Wang, Zhengwei Wang, Zhengxuan Wang, Zhengyang Wang, Zhengyi Wang, Zhengyu Wang, Zhenhua Wang, Zhenning Wang, Zhenqian Wang, Zhenshan Wang, Zhentang Wang, Zhenwei Wang, Zhenxi Wang, Zhenyu Wang, Zhenze Wang, Zhenzhen Wang, Zheyi Wang, Zheyue Wang, Zhezhi Wang, Zhi Wang, Zhi Xiao Wang, Zhi-Gang Wang, Zhi-Guo Wang, Zhi-Hao Wang, Zhi-Hong Wang, Zhi-Hua Wang, Zhi-Jian Wang, Zhi-Long Wang, Zhi-Qin Wang, Zhi-Wei Wang, Zhi-Xiao Wang, Zhi-Xin Wang, Zhibo Wang, Zhichao Wang, Zhicheng Wang, Zhicun Wang, Zhidong Wang, Zhifang Wang, Zhifeng Wang, Zhifu Wang, Zhigang Wang, Zhige Wang, Zhiguo Wang, Zhihao Wang, Zhihong Wang, Zhihua Wang, Zhihui Wang, Zhiji Wang, Zhijian Wang, Zhijie Wang, Zhijun Wang, Zhilun Wang, Zhimei Wang, Zhimin Wang, Zhipeng Wang, Zhiping Wang, Zhiqi Wang, Zhiqian Wang, Zhiqiang Wang, Zhiqing Wang, Zhiren Wang, Zhiruo Wang, Zhisheng Wang, Zhitao Wang, Zhiting Wang, Zhiwu Wang, Zhixia Wang, Zhixiang Wang, Zhixiao Wang, Zhixin Wang, Zhixing Wang, Zhixiong Wang, Zhixiu Wang, Zhiying Wang, Zhiyong Wang, Zhiyou Wang, Zhiyu Wang, Zhiyuan Wang, Zhizheng Wang, Zhizhong Wang, Zhong Wang, Zhong-Hao Wang, Zhong-Hui Wang, Zhong-Ping Wang, Zhong-Yu Wang, ZhongXia Wang, Zhongfang Wang, Zhongjing Wang, Zhongli Wang, Zhonglin Wang, Zhongqun Wang, Zhongsu Wang, Zhongwei Wang, Zhongyi Wang, Zhongyu Wang, Zhongyuan Wang, Zhongzhi Wang, Zhou Wang, Zhou-Ping Wang, Zhoufeng Wang, Zhouguang Wang, Zhuangzhuang Wang, Zhugang Wang, Zhulin Wang, Zhulun Wang, Zhuo Wang, Zhuo-Hui Wang, Zhuo-Jue Wang, Zhuo-Xin Wang, Zhuowei Wang, Zhuoying Wang, Zhuozhong Wang, Zhuqing Wang, Zi Wang, Zi Xuan Wang, Zi-Hao Wang, Zi-Qi Wang, Zi-Yi Wang, Zicheng Wang, Zifeng Wang, Zihan Wang, Ziheng Wang, Zihua Wang, Zihuan Wang, Zijian Wang, Zijie Wang, Zijue Wang, Zijun Wang, Zikang Wang, Zikun Wang, Ziliang Wang, Zilin Wang, Ziling Wang, Zilong Wang, Zining Wang, Ziping Wang, Ziqi Wang, Ziqian Wang, Ziqiang Wang, Ziqing Wang, Ziqiu Wang, Zitao Wang, Ziwei Wang, Zixi Wang, Zixia Wang, Zixian Wang, Zixiang Wang, Zixu Wang, Zixuan Wang, Ziyi Wang, Ziying Wang, Ziyu Wang, Ziyun Wang, Zongbao Wang, Zonggui Wang, Zongji Wang, Zongkui Wang, Zongqi Wang, Zongwei Wang, Zou Wang, Zulong Wang, Zumin Wang, Zun Wang, Zunxian Wang, Zuo Wang, Zuoheng Wang, Zuoyan Wang, Zusen Wang
articles
Dandan Wu, Yumin Ke, Rongrong Xiao +3 more · 2021 · Experimental cell research · Elsevier · added 2026-04-24
Epithelial ovarian cancer (EOC) is a highly fatal gynecological cancer. A long noncoding RNA (lncRNA) gastric cancer-associated lncRNA1 (GClnc1) has been revealed to play critical roles in metastasis. Show more
Epithelial ovarian cancer (EOC) is a highly fatal gynecological cancer. A long noncoding RNA (lncRNA) gastric cancer-associated lncRNA1 (GClnc1) has been revealed to play critical roles in metastasis. Therefore, the present study aims to explore the correlation between GClnc1 and the metastasis and progression of EOC. First, 57 paired EOC and paracancerous tissues were collected to detect GClnc1 expression by RT-qPCR. Subsequently, OVC1 and SKOV3 cells with GClnc1 silencing/overexpression were developed to detect changes in cell activity, apoptosis, migration and invasion abilities. Then, the subcellular localization of GClnc1 was detected by nuclear/cytoplasmic fractionation, ISH and FISH assays. The binding relationships between GClnc1 and forkhead box protein C2 (FOXC2), and between FOXC2 and NOTCH1 were predicted and verified. GClnc1 was significantly overexpressed in EOC tissues, and knockdown of GClnc1 inhibited cell viability and promoted apoptosis. Moreover, GClnc1 in the nucleus bound to the transcription factor FOXC2, thereby activating the transcription of NOTCH1. NOTCH1 overexpression enhanced the proliferation and epithelial-mesenchymal transition of SKOV3 and OVC1 cells. Moreover, NOTCH1 activated the NF-κB/Snail signaling. Finally, in vivo experiments demonstrated that GClnc1 knockdown suppressed the growth and metastasis of SKOV3 and OVC1 cells in vivo. GClnc1 promoted NOTCH1 transcription by recruiting FOXC2, thereby activating the NF-κB/Snail signaling and promoting EOC cell growth and metastasis. Show less
no PDF DOI: 10.1016/j.yexcr.2020.112422
SNAI1
Xin Tian, Hua Yu, Dong Li +5 more · 2021 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Epigenetic deregulation, especially mutagenesis or the abnormal expression of epigenetic regulatory factors (ERFs), plays an important role in malignant tumorigenesis. To screen natural inhibitors of Show more
Epigenetic deregulation, especially mutagenesis or the abnormal expression of epigenetic regulatory factors (ERFs), plays an important role in malignant tumorigenesis. To screen natural inhibitors of breast cancer metastasis, we adopted small interfering RNAs (siRNAs) to transiently knock down 591 ERF-coding genes in luminal breast cancer MCF-7 cells and found that depletion of AF9 significantly promoted MCF-7 cell invasion and migration. A mouse model of metastasis further confirmed the suppressive role of AF9 in breast cancer metastasis. RNA profiling revealed enrichment of AF9 targets genes in the epithelial-mesenchymal transition (EMT). Mechanistically, tandem mass spectrometry showed that AF9 interacts with Snail, which hampers Snail transcriptional activity in basal-like breast cancer (BLBC) cells. AF9 reconstitutes an activated state on the promoter of Snail, which is a master regulator of EMT, and derepresses genes by recruiting CBP or GCN5. Additionally, microRNA-5694 (miR-5694) targeted and degraded AF9 messenger RNA (mRNA) in BLBC cells, further enhancing cell invasion and migration. Notably, AF9 and miR-5694 expression in BLBC clinical samples correlated inversely. Hence, miR-5694 mediates downregulation of AF9 and provides metastatic advantages in BLBC. Restoring expression of the metastasis suppressor AF9 is a possible therapeutic strategy against metastatic breast cancer. Show less
no PDF DOI: 10.1016/j.ymthe.2020.11.022
SNAI1
Yuanbin Chen, Ting Xu, Fei Xie +8 more · 2021 · Oncology reports · added 2026-04-24
The prognosis‑associated genes of urinary bladder cancer have been systematically investigated in the Pathology Atlas project based on The Cancer Genome Atlas data. However, the biological functions o Show more
The prognosis‑associated genes of urinary bladder cancer have been systematically investigated in the Pathology Atlas project based on The Cancer Genome Atlas data. However, the biological functions of most genes in bladder cancer remain unknown. The present study investigated the biological function of 12 of the most significant survival‑associated genes (ABRACL, MITD1, ZNF524, EMP1, HSPB6, CXorf38, TRIM38, ZNF182, ZNF195, SPRN, PTPN6 and LIPT1) in urothelial cancer reported by the Pathology Atlas project, with respect to cell proliferation and migration. In vitro, proliferation and migration analyses of T24 cells were performed following the transfection of the 12 prognostic genes. The results were validated with a small interfering (si)RNA library. Immunohistochemistry (IHC) analysis of clinical samples was performed to determine the association between gene expression and tumor metastasis. Furthermore, RNA sequencing was used to investigate the downstream signals. Among the 12 prognostic genes, MIT‑domain containing protein 1 (MITD1) transfection was demonstrated to inhibit T24 cell migration to a certain degree. Experiments performed with a 7‑gene siRNA library demonstrated that MITD1 knockdown markedly upregulated cell migratory abilities. Mechanistically, the influence of MITD1 on cell signal transduction was assessed via RNA sequencing. Cell migration‑associated genes, including KISS1, SPANXB1, SPINT1, PIWIL2, SNAI1, APLN and CTHRC1 were dysregulated. IHC analysis demonstrated that MITD1 protein expression was notably lower in metastatic lymph nodes compared with the primary tumors. Taken together, the results of the present study suggest that the prognostic gene, MITD1 may serve as a migration inhibitor, and be developed as a potential therapeutic target for improving the prognosis of bladder cancer. Show less
no PDF DOI: 10.3892/or.2020.7853
SNAI1
Lisha Chang, Jingyue Wang, Fuling Zhou +4 more · 2021 · Journal of neuro-oncology · Springer · added 2026-04-24
Long noncoding RNAs (LncRNAs) are essential epigenetic regulators with critical roles in tumor initiation and malignant progression; however, the mechanism by which aberrantly expressed lncRNA RP11-84 Show more
Long noncoding RNAs (LncRNAs) are essential epigenetic regulators with critical roles in tumor initiation and malignant progression; however, the mechanism by which aberrantly expressed lncRNA RP11-84E24.3 regulates the pathogenesis of glioma is not fully understood. Here, we investigate the function of lncRNA RP11-84E24.3 in glioma onset and progression as well as identify a molecular pathway regulated by this lncRNA. Differentially expressed lncRNAs related to glioma were identified. The aberrant expression of lncRNA RP11-84E24.3 was verified in samples from patients with glioma as well as glioma cell lines. The role of lncRNA RP11-8424.3 in proliferation, apoptosis, migration, and invasion was assessed using gain- and loss-of function approaches, EdU incorporation, flow cytometry, wound healing and Transwell invasion assays. Western blot analysis was utilized to examine the expression of proteins associated with epithelial-to-mesenchymal transition (EMT). The interaction between lncRNA RP11-84E24.3, TFAP2C and SNAI1 was confirmed using RNA pull-down, ChIP and luciferase reporter assays. LncRNA RP11-84E24.3 was up-regulated in both glioma tissues and cell lines. LncRNA RP11-84E24.3 overexpression enhanced the proliferation, migration and invasion of glioma cells while reducing apoptosis. This was associated with a decrease in E-cadherin expression and an increase in N-cadherin and Vimentin expression. LncRNA RP11-84E24.3 directly targeted TFAP2C protein, resulting in increased SNAI1 expression. Knockdown of TFAP2C or SNAI1 reversed the effects of lncRNA RP11-84E24.3 overexpression, while silencing lncRNA RP11-84E24.3 inhibited tumor formation of glioma cells in vivo. LncRNA RP11-84E24.3 increased SNAI1 expression by forming a complex with TFAP2C protein, promoting EMT in glioma cells and tumor formation. Show less
no PDF DOI: 10.1007/s11060-020-03624-3
SNAI1
H-Y Piao, S Guo, Y Wang +1 more · 2021 · Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · Springer · added 2026-04-24
Clinically, hypoxia is associated with increased distant metastasis and poor survival in gastric cancer (GC). In this study, we set out from the cellular interaction to further explain the molecular m Show more
Clinically, hypoxia is associated with increased distant metastasis and poor survival in gastric cancer (GC). In this study, we set out from the cellular interaction to further explain the molecular mechanism of invasion in GC cells under hypoxic conditions. Gastric cancer cells were cultured under 1% O HGC-medium induced NGC dissociated. Long non-coding RNA (lncRNA) prostate cancer gene expression marker 1 (PCGEM1) was specifically expressed in HGC exosomes. HGC-derived PCGEM1-riched exosomes could promote the invasion and migration of NGC. On the mechanism, PCGEM1 maintained stability and reduced the degradation of SNAI1, which could induce the epithelial-mesenchymal transition of GC. LncRNA PCGEM1 was overexpressed in GC cells. And part of the PCGEM1 can be encapsulated into exosomes. These exosomes promoted invasion and migration of other GC cells. We considered PCGEM1 might act as a "scaffold" combined with SNAI1 and prompt the invasion and migration of GC. Show less
no PDF DOI: 10.1007/s12094-020-02412-9
SNAI1
Tian Hua, Rui-Min Wang, Xiao-Chong Zhang +4 more · 2021 · Bioscience reports · added 2026-04-24
Ovarian cancer (OV) is the most lethal gynecologic malignancy. One major reason of the high mortality of the disease is due to platinum-based chemotherapy resistance. Increasing evidence reveal the im Show more
Ovarian cancer (OV) is the most lethal gynecologic malignancy. One major reason of the high mortality of the disease is due to platinum-based chemotherapy resistance. Increasing evidence reveal the important biological functions and clinical significance of zinc finger proteins (ZNFs) in OV. In the present study, the relationship between the zinc finger protein 76 (ZNF76) and clinical outcome and platinum resistance in patients with OV was explored. We further analyzed ZNF76 expression via multiple gene expression databases and identified its functional networks using cBioPortal. RT-qPCR and IHC assay shown that the ZNF76 mRNA and protein expression were significantly lower in OV tumor than that in normal ovary tissues. A strong relationship between ZNF76 expression and platinum resistance was determined in patients with OV. The low expression of ZNF76 was associated with worse survival in OV. Multivariable analysis showed that the low expression of ZNF76 was an independent factor predicting poor outcome in OV. The prognosis value of ZNF76 in pan-cancer was validated from multiple cohorts using the PrognoScan database and GEPIA 2. A gene-clinical nomogram was constructed by multivariate cox regression analysis, combined with clinical characterization and ZNF76 expression in TCGA. Functional network analysis suggested that ZNF76 was involved in several biology progressions which associated with OV. Ten hub genes (CDC5L, DHX16, SNRPC, LSM2, CUL7, PFDN6, VARS, HSD17B8, PPIL1, and RGL2) were identified as positively associated with the expression of ZNF76 in OV. In conclusion, ZNF76 may serve as a promising prognostic-related biomarker and predict the response to platinum in OV patients. Show less
no PDF DOI: 10.1042/BSR20212026
SNRPC
Xun Tian, Xin Wang, Zifeng Cui +24 more · 2021 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Neoadjuvant chemotherapy (NACT) remains an attractive alternative for controlling locally advanced cervical cancer. However, approximately 15-34% of women do not respond to induction therapy. To devel Show more
Neoadjuvant chemotherapy (NACT) remains an attractive alternative for controlling locally advanced cervical cancer. However, approximately 15-34% of women do not respond to induction therapy. To develop a risk stratification tool, 56 patients with stage IB-IIB cervical cancer are included in 2 research centers from the discovery cohort. Patient-specific somatic mutations led to NACT non-responsiveness are identified by whole-exome sequencing. Next, CRISPR/Cas9-based library screenings are performed based on these genes to confirm their biological contribution to drug resistance. A 15-gene classifier is developed by generalized linear regression analysis combined with the logistic regression model. In an independent validation cohort of 102 patients, the classifier showed good predictive ability with an area under the curve of 0.80 (95% confidence interval (CI), 0.69-0.91). Furthermore, the 15-gene classifier is significantly associated with patient responsiveness to NACT in both univariate (odds ratio, 10.8; 95% CI, 3.55-32.86; Show less
no PDF DOI: 10.1002/advs.202001978
VPS13C
Bin Li, Guihu Zhao, Qiao Zhou +19 more · 2021 · Frontiers in neuroscience · Frontiers · added 2026-04-24
Parkinson's disease (PD) is a complex neurodegenerative disorder with a strong genetic component. A growing number of variants and genes have been reported to be associated with PD; however, there is Show more
Parkinson's disease (PD) is a complex neurodegenerative disorder with a strong genetic component. A growing number of variants and genes have been reported to be associated with PD; however, there is no database that integrate different type of genetic data, and support analyzing of PD-associated genes (PAGs). By systematic review and curation of multiple lines of public studies, we integrate multiple layers of genetic data (rare variants and copy-number variants identified from patients with PD, associated variants identified from genome-wide association studies, differentially expressed genes, and differential DNA methylation genes) and age at onset in PD. We integrated five layers of genetic data (8302 terms) with different levels of evidences from more than 3,000 studies and prioritized 124 PAGs with strong or suggestive evidences. These PAGs were identified to be significantly interacted with each other and formed an interconnected functional network enriched in several functional pathways involved in PD, suggesting these genes may contribute to the pathogenesis of PD. Furthermore, we identified 10 genes were associated with a juvenile-onset (age ≤ 30 years), 11 genes were associated with an early-onset (age of 30-50 years), whereas another 10 genes were associated with a late-onset (age > 50 years). Notably, the AAOs of patients with loss of function variants in five genes were significantly lower than that of patients with deleterious missense variants, while patients with Show less
no PDF DOI: 10.3389/fnins.2021.679568
VPS13C
Qiguo Zhang, Wenyu Gong, Hongyan Wu +11 more · 2021 · Carcinogenesis · Oxford University Press · added 2026-04-24
Bortezomib-based chemotherapy represents the most prevalent regimens for multiple myeloma (MM), whereas acquired drug resistance remains a major obstacle. Myeloma cells often produce excessive amount Show more
Bortezomib-based chemotherapy represents the most prevalent regimens for multiple myeloma (MM), whereas acquired drug resistance remains a major obstacle. Myeloma cells often produce excessive amount of dickkopf-1 (DKK1), giving rise to myeloma bone disease. However, it remains obscure about the effects and mechanisms of DKK1 in the progression and bortezomib responsiveness of MM cells. In the current study, we found WWP2, an E3 ubiquitin-protein ligase, was downregulated in the bortezomib-resistant cells along with high expression of DKK1. Further investigation revealed that WWP2 was a direct target of Wnt/β-catenin signaling pathway, and DKK1 suppressed the expression of WWP2 via canonical Wnt signaling. We further identified that WWP2 mediated the ubiquitination and degradation of GLI2, a main transcriptional factor of the Hedgehog (Hh) pathway. Therefore, DKK1-induced WWP2 downregulation improved GLI2 stability and activation of Hh signaling pathway, contributing to the resistance to bortezomib of MM cells. Clinical data also validated that WWP2 expression was associated with the treatment response and clinic outcomes of MM patients. WWP2 overexpression restricted MM progression and enhanced cell sensitivity to bortezomib treatment in vitro and in vivo. Taken together, our findings demonstrate that DKK1 facilitates the generation of bortezomib resistance in MM via downregulating WWP2 and activating Hh pathway. Thus, the manipulation of DKK1-WWP2-GLI2 axis might sensitize myeloma cells to proteasome inhibitors. Show less
no PDF DOI: 10.1093/carcin/bgab086
WWP2
Wen Zhang, Shou-Song Tao, Ting Wang +11 more · 2021 · FEBS letters · Wiley · added 2026-04-24
BRCA1/BRCA2-containing complex subunit 3 (BRCC3) is a lysine 63-specific deubiquitinase involved in multiple biological processes, such as DNA repair and immune responses. However, the regulation mech Show more
BRCA1/BRCA2-containing complex subunit 3 (BRCC3) is a lysine 63-specific deubiquitinase involved in multiple biological processes, such as DNA repair and immune responses. However, the regulation mechanism for BRCC3 protein stability is still unknown. Here, we demonstrate that BRCC3 is mainly degraded through the ubiquitin-proteasome pathway. The HECT-type E3 ubiquitin ligase WWP2 modulates BRCC3 ubiquitination and degradation. ABRO1, a subunit of the BRCC36 isopeptidase complex (BRISC), competes with WWP2 to bind to BRCC3, thereby preventing WWP2-mediated BRCC3 ubiquitination and enhancing BRCC3 stability. Functionally, we show that lentivirus-mediated overexpression of WWP2 in murine macrophages inhibits NLRP3 inflammasome activation by decreasing BRCC3 protein level. This study provides the first insights into the regulation of BRCC3 stability and expands our knowledge about the physiological function of WWP2. Show less
no PDF DOI: 10.1002/1873-3468.13970
WWP2
Sanaz Darbalaei, Elita Yuliantie, Antao Dai +6 more · 2020 · Biochemical pharmacology · Elsevier · added 2026-04-24
Metabolic diseases such as obesity, diabetes, and their comorbidities have converged as one of the most serious health concerns on a global scale. Selective glucagon-like peptide-1 (GLP-1) receptor (G Show more
Metabolic diseases such as obesity, diabetes, and their comorbidities have converged as one of the most serious health concerns on a global scale. Selective glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) agonists are one of the major therapeutics for type 2 diabetes and obesity. Polypharmacological approaches that enable modulation of multiple metabolic targets in a single drug have emerged as a potential avenue to improve therapeutic outcomes. Among numerous peptides under development are those targeting the GLP-1R and either the glucagon receptor (GCGR), glucose-dependent insulinotropic peptide receptor (GIPR) or all 3 receptors, as dual- or tri- peptide agonists. Despite many of them entering into clinical trials, current development has been based on only a limited understanding of the spectrum of potential pharmacological properties of these ligands beyond binding selectivity. In the present study, we examined the potential for agonists that target both GLP-1R and GCGR to exhibit biased agonism, comparing activity across proximal activation of Gs protein, cAMP accumulation, pERK1/2 and β-arrestin recruitment. Three distinct dual agonists that have different relative cAMP production potency for GLP-1R versus GCGR, "peptide 15", MEDI0382 and SAR425899, and one triagonist of the GLP-1R, GCGR and GIPR were examined. We demonstrated that all novel peptides have distinct biased agonism profiles relative to either of the cognate agonists of the receptors, and to each other. This is an important feature of the pharmacology of this drug class that needs to be considered alongside selectivity, bioavailability and pharmacokinetics for rational optimization of new therapeutics. Show less
no PDF DOI: 10.1016/j.bcp.2020.114150
GIPR
Yumin Wu, Tiemei Ji, Jie Lv +1 more · 2020 · Life sciences · Elsevier · added 2026-04-24
Glucagon-like peptide-1 receptor (GLP-1R) and glucose-dependent insulinotropic polypeptide receptor (GIPR) co-agonists have emerged as treatment options for reversing diabetes and obesity. Here, we sc Show more
Glucagon-like peptide-1 receptor (GLP-1R) and glucose-dependent insulinotropic polypeptide receptor (GIPR) co-agonists have emerged as treatment options for reversing diabetes and obesity. Here, we screened the high potency receptor-biased GLP-1R agonists via a newly designed high-throughput GLP-1R extracellular domain (ECD)-based system and demonstrated its in vitro and in vivo therapeutic characters. Twelve 9-mer peptides (named XEL1-XEL12) which were screened from a large phage-displayed peptide library were fused to the N-terminus of GIP (3-30) to generate another twelve fusion peptides, termed XEL13-24. Using the six lysine-altered XEL17 as leading sequences, eighteen fatty chain modified fusion peptides were further assessed via in vitro GLP-1R/GIPR-based cell assay. Moreover, the acute and long-acting in vivo effects of selected candidate on diabetic db/db mice and diet-induced obesity (DIO) rats were both carefully evaluated. XEL17 exhibited balanced activation potency on GLP-1R/GIPR in stable cell lines, and further assessment was performed to evaluate the XEL32, a fatty chain modified XEL17 derivative. Preclinical pharmacodynamic results in diabetic db/db mice demonstrated that XEL32 held outstanding insulinotropic and glucose-lowering activities. In addition, protracted antidiabetic effects of XEL32 were also proved by the hypoglycemic test and multiple oral glucose tolerance test. Furthermore, chronic treatment of XEL32 in DIO rats exhibited outstanding beneficial effects on body weight control, fat loss, food intake control, hemoglobin A1C (HbA1C) reduction as well as the glucose tolerance. XEL32, as a novel GLP-1/GIP dual receptor agonist, may supply efficient glycemic control and weight loss. Show less
no PDF DOI: 10.1016/j.lfs.2020.118025
GIPR
Elita Yuliantie, Sanaz Darbalaei, Antao Dai +5 more · 2020 · Biochemical pharmacology · Elsevier · added 2026-04-24
Glucose-dependent insulinotropic peptide (GIP) is an incretin hormone with physiological roles in adipose tissue, the central nervous system and bone metabolism. While selective ligands for GIP recept Show more
Glucose-dependent insulinotropic peptide (GIP) is an incretin hormone with physiological roles in adipose tissue, the central nervous system and bone metabolism. While selective ligands for GIP receptor (GIPR) have not been advanced for disease treatment, dual and triple agonists of GIPR, in conjunction with that of glucagon-like peptide-1 (GLP-1) and glucagon receptors, are currently in clinical trials, with an expectation of enhanced efficacy beyond that of GLP-1 receptor (GLP-1R) agonist monotherapy for diabetic patients. Consequently, it is important to understand the pharmacological behavior of such drugs. In this study, we have explored signaling pathway specificity and the potential for biased agonism of mono-, dual- and tri-agonists of GIPR using human embryonic kidney 293 (HEK293) cells recombinantly expressing human GIPR or GLP-1R. Compared to GIP(1-42), the GIPR mono-agonists Pro3GIP and Lys3GIP are biased towards ERK1/2 phosphorylation (pERK1/2) relative to cAMP accumulation at GIPR, whereas the triple agonist at GLP-1R/GCGR/GIPR is biased towards pERK1/2 relative to β-arrestin2 recruitment. Moreover, the dual GIPR/GLP-1R agonist, LY3298176, is biased towards pERK1/2 relative to cAMP accumulation at both GIPR and GLP-1R compared to their respective endogenous ligands. These data reveal novel pharmacological properties of potential therapeutic agents that may impact on diversity in clinical responses. Show less
no PDF DOI: 10.1016/j.bcp.2020.114001
GIPR
Xiaoshan Min, Junming Yie, Jinghong Wang +15 more · 2020 · mAbs · Taylor & Francis · added 2026-04-24
Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone involved in regulating glucose and lipid metabolism. GIP receptor (GIPR) antagonism is believed to offer therapeutic potential Show more
Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone involved in regulating glucose and lipid metabolism. GIP receptor (GIPR) antagonism is believed to offer therapeutic potential for various metabolic diseases. Pharmacological intervention of GIPR, however, has limited success due to lack of effective antagonistic reagents. Previously we reported the discovery of two mouse anti-murine GIPR monoclonal antibodies (mAbs) with distinctive properties in rodent models. Here, we report the detailed structural and biochemical characterization of these two antibodies, mAb1 and mAb2. Show less
📄 PDF DOI: 10.1080/19420862.2019.1710047
GIPR
Ruijuan Guo, Yuqing Sun, Huili Li +2 more · 2020 · Neurochemistry international · Elsevier · added 2026-04-24
It is unclear whether glucose-dependent insulinotropic polypeptide receptor (GIPR) signaling plays an important role in spinal nociception. We hypothesized that the spinal GIPR is implicated in centra Show more
It is unclear whether glucose-dependent insulinotropic polypeptide receptor (GIPR) signaling plays an important role in spinal nociception. We hypothesized that the spinal GIPR is implicated in central sensitization of postoperative pain. Our data showed that the cumulative pain scores peaked at 3 h, kept at a high level at 1 d after incision, gradually decreased afterwards and returned to the baseline values at 5 d after incision. Correspondingly, the expression of GIPR in spinal cord dorsal horn peaked at 1 d after incision, and returned to the baseline value at 5 d after incision. The double-labeling immunofluorescence demonstrated that spinal GIPR was expressed in dorsal horn neurons, but not in astrocyte or microglial cells. At 1 d after incision, the effects of intrathecal saline, GIPR antagonist (Pro3)GIP on pain behaviors were investigated. Our data showed that at 30 min and 60 min following intrathecal treatments of 300 ng (Pro3)GIP, the cumulative pain scores were decreased and paw withdrawal thresholds to mechanical stimuli were increased when compared to those immediately before intrathecal treatments. Accordingly, at 30 min after intrathecal injections, the membrane translocation levels of PKCγ and the GluR1 expression in postsynaptic membrane in ipsilateral dorsal horns to the incision were significantly upregulated in rats with intrathecal saline injections, as compared to normal control group. At 30 min after intrathecal treatment, (Pro3)GIP inhibited the membrane translocation levels of PKCγ and the GluR1 expression in postsynaptic membrane in ipsilateral dorsal horns. Our study indicates that upregulation of spinal GIPR may contribute to pain hypersensitivity through inducing membrane translocation level of PKCγ and synaptic target of AMPA receptor GluR1 subunits in ipsilateral dorsal horns of rats with plantar incision. Show less
no PDF DOI: 10.1016/j.neuint.2019.104651
GIPR
Kun Wang, Wei Mao, Xiaoyu Zhang +7 more · 2020 · Open life sciences · added 2026-04-24
Melanocortin-4 receptors (MC4Rs) are key regulators of energy homeostasis and adipose deposition in the central nervous system. Considering that MC4R expression regions and function-related research m Show more
Melanocortin-4 receptors (MC4Rs) are key regulators of energy homeostasis and adipose deposition in the central nervous system. Considering that MC4R expression regions and function-related research mainly focus on the paraventricular nucleus (PVN), little is known about their distribution throughout the mouse brain, although its messenger RNA distribution has been analyzed in the rat. Therefore, MC4R protein localization in mouse neurons was the focus of this study. MC4R protein distribution was assessed in mice through immunofluorescence and Western blotting. MC4R was differentially expressed throughout the arcuate nucleus (ARC), nucleus of the solitary tract (NTS), raphe pallidus (RPa), medial cerebellar nucleus, intermediolateral nucleus, and brainstem. The highest MC4R protein levels were found in the ARC and ventromedial hypothalamic nucleus, while they were significantly lower in the parabrachial nucleus and NTS. The lowest MC4R protein levels were found in the PVN; there was no difference in the protein levels between the area postrema and RPa. These data provide a basic characterization of MC4R-expressing neurons and protein distribution in the mouse brain and may aid further research on its role in energy homeostasis. Show less
📄 PDF DOI: 10.1515/biol-2020-0063
MC4R
Hui Bi, Min Zhang, Jialin Wang +1 more · 2020 · PeerJ · added 2026-04-24
This study aims to identify potential biomarkers associated with acute kidney injury (AKI) post kidney transplantation. Two mRNA expression profiles from Gene Expression Omnibus repertory were downloa Show more
This study aims to identify potential biomarkers associated with acute kidney injury (AKI) post kidney transplantation. Two mRNA expression profiles from Gene Expression Omnibus repertory were downloaded, including 20 delayed graft function (DGF) and 68 immediate graft function (IGF) samples. Differentially expressed genes (DEGs) were identified between DGF and IGF group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis of DEGs were performed. Then, a protein-protein interaction analysis was performed to extract hub genes. The key genes were searched by literature retrieval and cross-validated based on the training dataset. An external dataset was used to validate the expression levels of key genes. Receiver operating characteristic curve analyses were performed to evaluate diagnostic performance of key genes for AKI. A total of 330 DEGs were identified between DGF and IGF samples, including 179 up-regulated and 151 down-regulated genes. Of these, Show less
📄 PDF DOI: 10.7717/peerj.10441
MC4R
Yu Wang, Dengfeng Bi, Guosong Qin +7 more · 2020 · Frontiers in genetics · Frontiers · added 2026-04-24
Pig is an important agricultural economic animal, providing large amount of meat products. With the development of functional genomics and bioinformatics, lots of genes and functional single nucleotid Show more
Pig is an important agricultural economic animal, providing large amount of meat products. With the development of functional genomics and bioinformatics, lots of genes and functional single nucleotide polymorphisms (SNPs) related to disease resistance and (or) economic traits in pigs have been identified, which provides the targets for genetic improvement by genome editing. Base editors (BEs), combining Cas9 nickase and cytidine or adenine deaminase, achieve all four possible transition mutations (C-to-T, A-to-G, T-to-C, and G-to-A) efficiently and accurately without double strand breaks (DSBs) under the protospacer adjacent motif (PAM) sequence of NGG. However, the NGG PAM in canonical CRISPR-Cas9 can only cover approximately 8.27% in the whole genome which limits its broad application. In the current study, hA3A-BE3-NG system was constructed with the fusion of SpCas9-NG variant and hA3A-BE3 to create C-to-T conversion at NGN PAM sites efficiently. The editing efficiency and scope of hA3A-BE3-NG were confirmed in HEK293T cells and porcine fetal fibroblast (PFF) cells. Results showed that the efficiency of hA3A-BE3-NG was much higher than that of hA3A-BE3 on NGH (H = A, C, or T) PAM sites (21.27 vs. 2.81% at average). Further, nonsense and missense mutations were introduced efficiently and precisely Show less
📄 PDF DOI: 10.3389/fgene.2020.592623
MC4R
Xin-Jian Li, Mingyu Wang, Yahui Xue +6 more · 2020 · AMB Express · BioMed Central · added 2026-04-24
Intestinal microorganisms have been shown to be important factors affecting the growth performance of pigs. Therefore, to investigate the effect of the intestinal microflora structure on the growth pe Show more
Intestinal microorganisms have been shown to be important factors affecting the growth performance of pigs. Therefore, to investigate the effect of the intestinal microflora structure on the growth performance of pigs, samples from Duroc (n = 10), Landrace (n = 9) and Yorkshire (n = 21) pigs under the same diet and feeding conditions were collected. The fecal microbial composition was profiled via 16S ribosomal RNA (rRNA) gene sequencing. We also analyzed their growth performance. We found that Duroc and Landrace pigs had significant differences in average daily gain (ADG), feed efficiency ratio (FER), growth index (GI), and number of days taken to reach 100 kg (P < 0.05). Moreover, through analysis of the intestinal flora, we also identified 18 species of intestinal flora with significant differences between Duroc and Landrace pigs (P < 0.05). To eliminate the influence of genetic background, the differential intestinal flora of 21 Yorkshire pigs with differences in growth performance was analyzed. The results showed that there were significant correlations between Barnesiella, Dorea, Clostridium and Lactobacillus and pig growth performance. To explore the effect of the intestinal flora on the growth performance of pigs at the molecular level, Lactobacillus, which is the most abundant in the intestine, was selected for isolation and purification and cocultured with intestinal epithelial cells. qPCR was used to determine the effect of Lactobacillus on MC4R gene expression in intestinal epithelial cells. The results showed that Lactobacillus inhibited MC4R gene expression in these cells. The results provide a useful reference for further study of the relationship between the intestinal flora and pig growth performance. Show less
📄 PDF DOI: 10.1186/s13568-020-01130-3
MC4R
Tianqiang Liu, Yue Deng, Zheng Zhang +7 more · 2020 · International journal of molecular sciences · MDPI · added 2026-04-24
The melanocortin receptor 4 (MC4R) signaling system consists of MC4R, MC4R ligands [melanocyte-stimulating hormone (MSH), adrenocorticotropin (ACTH), agouti-related protein (AgRP)], and melanocortin-2 Show more
The melanocortin receptor 4 (MC4R) signaling system consists of MC4R, MC4R ligands [melanocyte-stimulating hormone (MSH), adrenocorticotropin (ACTH), agouti-related protein (AgRP)], and melanocortin-2 receptor accessory protein 2 (MRAP2), and it has been proposed to play important roles in feeding and growth in vertebrates. However, the expression and functionality of this system have not been fully characterized in teleosts. Here, we cloned tilapia Show less
📄 PDF DOI: 10.3390/ijms21197036
MC4R
Tian Zeng, Jing Zhao, Yu Kang +2 more · 2020 · Medicine · added 2026-04-24
Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) near the melanocortin 4 receptor (MC4R), gene which are associated with risk of obesity. Since obesity is an esta Show more
Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) near the melanocortin 4 receptor (MC4R), gene which are associated with risk of obesity. Since obesity is an established risk factor of cancer, several studies have examined the association between SNPs near the MC4R gene and cancer risk, but the findings are inconsistent. The present study aimed to perform a meta-analysis to clarify the association between SNPs near MC4R and cancer risk. The PubMed and Embase databases were searched for potentially eligible publications. All studies that evaluated the association between MC4R rs17782313 SNP (or its proxy rs12970134) and cancer risk were included. The pooled odds ratios with 95% confidence intervals (CIs) were calculated using the random-effects model. And subgroup analysis by cancer type (colorectal cancer, endometrial cancer and breast cancer) was conducted for further investigate the association. A total of 6 eligible studies (6517 cases and 16,886 controls) were included in the present meta-analysis. The results indicated that MC4R rs17782313 SNP was moderately associated with cancer risk (odds ratio = 1.12, 95% CI = 1.01-1.24). However, the subgroup analysis between different cancer types shows that rs17782313 is only associated with colorectal cancer but not the endometrial cancer and breast cancer. Risk factor in colorectal cancer was both significantly associated with rs17782313 with and without adjustment for body mass index; while the risk factor of the endometrial cancer and breast cancer were both not associated with the rs17782313 with and without adjustment for body mass index. There was no publication bias for the association between MC4R rs17782313 and cancer risk. The present meta-analysis confirmed the moderate association between MC4R rs17782313 and cancer risk. Show less
📄 PDF DOI: 10.1097/MD.0000000000022003
MC4R
Yingzhu Feng, Jiuhong Huang, Chuanhua Qu +6 more · 2020 · Analytical and bioanalytical chemistry · Springer · added 2026-04-24
Pathogen-host cell interactions play an important role in many human infectious and inflammatory diseases. Several pathogens, including Escherichia coli (E. coli), Mycobacterium tuberculosis (M. tb), Show more
Pathogen-host cell interactions play an important role in many human infectious and inflammatory diseases. Several pathogens, including Escherichia coli (E. coli), Mycobacterium tuberculosis (M. tb), and even the recent 2019 novel coronavirus (2019-nCoV), can cause serious breathing and brain disorders, tissue injury and inflammation, leading to high rates of mortality and resulting in great loss to human physical and mental health as well as the global economy. These infectious diseases exploit the microbial and host factors to induce serious inflammatory and immunological symptoms. Thus the development of anti-inflammatory drugs targeting bacterial/viral infection is an urgent need. In previous studies, YojI-IFNAR2, YojI-IL10RA, YojI-NRP1,YojI-SIGLEC7, and YojI-MC4R membrane-protein interactions were found to mediate E. coli invasion of the blood-brain barrier (BBB), which activated the downstream anti-inflammatory proteins NACHT, LRR and PYD domains-containing protein 2(NLRP2), using a proteomic chip conjugated with cell immunofluorescence labeling. However, the studies of pathogen (bacteria/virus)-host cell interactions mediated by membrane protein interactions did not extend their principles to broad biomedical applications such as 2019-nCoV infectious disease therapy. The first part of this feature article presents in-depth analysis of the cross-talk of cellular anti-inflammatory transduction signaling among interferon membrane protein receptor II (IFNAR2), interleukin-10 receptor subunit alpha (IL-10RA), NLRP2 and [Ca Show less
📄 PDF DOI: 10.1007/s00216-020-02894-0
MC4R
Zhi Liu, Fuyun Sun, Zitian Liu +8 more · 2020 · Medical science monitor : international medical journal of experimental and clinical research · added 2026-04-24
BACKGROUND The mechanism by which sleeve gastrectomy (SG) improves glycometabolism has remained unclear so far. Increasing evidence has demonstrated that bone is a regulator of glucose metabolism, and Show more
BACKGROUND The mechanism by which sleeve gastrectomy (SG) improves glycometabolism has remained unclear so far. Increasing evidence has demonstrated that bone is a regulator of glucose metabolism, and osteoblast-derived forkhead box O1 (FoxO1) and lipocalin-2 (LCN2) are regulators of energy metabolism. The aim of this study was to investigate whether the FOXO1/LCN2 signaling pathway is involved in the anti-diabetic effect of SG. MATERIAL AND METHODS Insulin resistance was induced in Wistar rats, which were then intraperitoneally injected with streptozotocin to induce a type 2 diabetic state. Levels of fasting blood glucose, serum insulin, HbA1c, and LCN2 were analyzed at corresponding time points after SG and sham surgeries. The expressions of FOXO1, LCN2, and the melanocortin 4 receptor (MC4R) in bone and hypothalamus were detected by immunofluorescence. FOXO1 siRNA was applied to downregulate FOXO1 expression in osteoblasts of rats. The influence of FOXO1 gene on expression of LCN2 was investigated in cultured osteoblasts by western blot and PCR. RESULTS Glucose metabolism in the SG group was significantly improved. The LCN2 expression in bone in the SG group was higher than that in the sham group, whereas FOXO1 expression in the SG group was lower than that in the sham group. The binding rate of LCN2 and MC4R in the hypothalamus was also higher in the SG group compared with that in the sham group. The downregulation of FOXO1 expression in osteoblasts was accompanied by upregulation of LCN2 expression. CONCLUSIONS These results suggest that the FOXO1/LCN2 signaling pathway participates in the anti-diabetic effect of SG. Show less
📄 PDF DOI: 10.12659/MSM.927458
MC4R
J Zhang, J Li, C Wu +6 more · 2020 · Animal genetics · Blackwell Publishing · added 2026-04-24
In humans and mice, melanocortin receptor 4 (MC4R) and melanocortin receptor accessory protein 2 (MRAP2) can form a complex and control energy balance, thus regulating body weight and obesity. In pigs Show more
In humans and mice, melanocortin receptor 4 (MC4R) and melanocortin receptor accessory protein 2 (MRAP2) can form a complex and control energy balance, thus regulating body weight and obesity. In pigs, a missense variant (p.Asp298Asn) of MC4R has been suggested to be associated with growth and fatness; however, the effect of Asp298Asn substitution on MC4R function is controversial, limiting its application in animal breeding. Here we examined the effect of this polymorphism on MC4R constitutive activity, cell surface expression and signaling, and its interaction with MRAP2 in pigs. We found that: (i) both pig MC4R Show less
no PDF DOI: 10.1111/age.12986
MC4R
Ying Zhang, Hai-Shen Wen, Yun Li +6 more · 2020 · Gene · Elsevier · added 2026-04-24
Melanocortin-4 receptor (MC4R) is a G protein-coupled receptor with multiple functions in mammals. However, the functions of MC4R in fish have not been investigated extensively. The purpose of this st Show more
Melanocortin-4 receptor (MC4R) is a G protein-coupled receptor with multiple functions in mammals. However, the functions of MC4R in fish have not been investigated extensively. The purpose of this study was to determine potential regulation of reproduction by the MC4R. We cloned the black rockfish MC4R and analyzed its tissue distribution and function. The results showed that black rockfish mc4r cDNA consisted of 981 nucleotides encoding a protein of 326 amino acids. The quantitative PCR data showed that mc4r mRNA was primarily expressed in the brain, gonad, stomach and intestine. In the brain, mc4r was found to be primarily located in the hypothalamus. Both α-MSH and β-MSH increased gnih expression and decreased sgnrh and cgnrh expression (P < 0.05). α-MSH and β-MSH had opposite effects on kisspeptin expression. In contrast, α-MSH and β-MSH increased the expression of cyp11, cyp19, 3β-hsd and star. In summary, our study shows that MC4R in black rockfish might regulate reproductive function and that the effects of α-MSH and β-MSH might differ. Show less
no PDF DOI: 10.1016/j.gene.2020.144541
MC4R
Mitsuharu Matsumoto, Hiroaki Yashiro, Hitomi Ogino +7 more · 2020 · PloS one · PLOS · added 2026-04-24
Acetyl-CoA carboxylase (ACC) catalyzes the rate-limiting step in de novo lipogenesis, which is increased in the livers of patients with nonalcoholic steatohepatitis. GS-0976 (firsocostat), an inhibito Show more
Acetyl-CoA carboxylase (ACC) catalyzes the rate-limiting step in de novo lipogenesis, which is increased in the livers of patients with nonalcoholic steatohepatitis. GS-0976 (firsocostat), an inhibitor of isoforms ACC1 and ACC2, reduced hepatic steatosis and serum fibrosis biomarkers such as tissue inhibitor of metalloproteinase 1 in patients with nonalcoholic steatohepatitis in a randomized controlled trial, although the impact of this improvement on fibrosis has not fully been evaluated in preclinical models. Here, we used Western diet-fed melanocortin 4 receptor-deficient mice that have similar phenotypes to nonalcoholic steatohepatitis patients including progressively developed hepatic steatosis as well as fibrosis. We evaluated the effects of ACC1/2 inhibition on hepatic fibrosis. After the confirmation of significant hepatic fibrosis with a 13-week pre-feeding, GS-0976 (4 and 16 mg/kg/day) treatment for 9 weeks lowered malonyl-CoA and triglyceride content in the liver and improved steatosis, histologically. Furthermore, GS-0976 reduced the histological area of hepatic fibrosis, hydroxyproline content, mRNA expression level of type I collagen in the liver, and plasma tissue metalloproteinase inhibitor 1, suggesting an improvement of hepatic fibrosis. The treatment with GS-0976 was also accompanied by reductions of plasma ALT and AST levels. These data demonstrate that improvement of hepatic lipid metabolism by ACC1/2 inhibition could be a new option to suppress fibrosis progression as well as to improve hepatic steatosis in nonalcoholic steatohepatitis. Show less
📄 PDF DOI: 10.1371/journal.pone.0228212
MC4R
Keping Yu, Li Li, Lan Zhang +2 more · 2020 · Gene · Elsevier · added 2026-04-24
Obesity is a huge burden of the world. It is commonly recognized that dietary structure and physical inactivity is essential in the progress of obesity. However, some individuals still face the troubl Show more
Obesity is a huge burden of the world. It is commonly recognized that dietary structure and physical inactivity is essential in the progress of obesity. However, some individuals still face the trouble of obese even though they live a healthy life. Except for the combination of diseases, the operation of both lifestyle and genetic features contributes to obesity. Melanocortin-4-receptor (MC4R) gene is one of the known hereditary factors of obesity. rs17782313, a single nucleotide variant in MC4R gene, has been reported unclear results in whether it plays a role in obesity. This meta-analysis is to estimate the association between MC4R rs17782313 genotype and obesity. A systematic literature retrieval was conducted in four databases: PubMed, Embase, Web of Science and Cochrane Library with specific search strategy. Select qualified studies to identify relevant studies. Odds ratios (ORs) with 95% confidence intervals (CI), P value and I 6 eligible studies involving 3133 obese cases and 3123 normal-weight participants were selected from 378 articles. Allele B of MC4R rs17782313 present a statistically significant association with obesity under allele contrast model (OR = 1.325, 95%CI: 1.219-1.439), dominant model (OR = 1.320, 95%CI: 1.184-1.472), recessive model (OR = 1.690, 95%CI: 1.420-2.011) and homozygous type of co-dominant model (OR = 1.925, 95%CI: 1.590-2.330), respectively, and P < 0.05. Mutated MC4R rs17782313 is associated with higher risk of obesity. People with homozygous mutant genotype of MC4R rs17782313 would be more likely to suffer from obesity, while heterozygous mutant genotype needs further studies to clarify. Show less
no PDF DOI: 10.1016/j.gene.2020.144372
MC4R
Lili Zhang, Shang-Jun Yin, Xiaoying Zheng +5 more · 2020 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Agouti signaling protein (ASP) is a secreted paracrine protein that has been widely reported to function in melanogenesis and obesity and could potentially be a core protein that regulates the color a Show more
Agouti signaling protein (ASP) is a secreted paracrine protein that has been widely reported to function in melanogenesis and obesity and could potentially be a core protein that regulates the color and fatty phenotype of P. sinensis. In this study, we screened out interacting proteins of ASP by combined co-immunoprecipitation mass spectrometry (CoIP-MS), yeast two hybrid (Y2H) analysis, and computational predictions. We performed docking of ASP with its well-known receptor melanocortin receptor 4 (MC4R) to predict the binding capacity and to screen out actual ASP interacting proteins, CoIP-MS was performed where identified 32 proteins that could bind with ASP and Y2H confirmed seven proteins binding with ASP directly. CoIP-MS and Y2H screening results including PPI prediction revealed that vitronectin (VTN), apolipoprotein A1 (APOA1), apolipoprotein B (APOB), and filamin B (FLNB) were the key interacting proteins of ASP. VTN, APOA1, and APOB are functional proteins in lipid metabolism and various skin disorders, suggesting ASP may function in lipid metabolism through these partners. This study provided protein-protein interaction information of ASP, and the results will promote further research into the diverse roles of ASP, as well as its binding partners, and their function in different strains of P. sinensis. Show less
no PDF DOI: 10.1016/j.ijbiomac.2019.11.229
MC4R
Apurva S Chitre, Oksana Polesskaya, Katie Holl +24 more · 2020 · Obesity (Silver Spring, Md.) · Wiley · added 2026-04-24
Obesity is influenced by genetic and environmental factors. Despite the success of human genome-wide association studies, the specific genes that confer obesity remain largely unknown. The objective o Show more
Obesity is influenced by genetic and environmental factors. Despite the success of human genome-wide association studies, the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify the genetic loci underlying obesity and related morphometric and metabolic traits. This study measured obesity-relevant traits, including body weight, body length, BMI, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat genome-wide association study to date. Genetic loci were identified using a linear mixed model to account for the complex family relationships of the HS and using covariates to account for differences among the three phenotyping centers. This study identified 32 independent loci, several of which contained only a single gene (e.g., Epha5, Nrg1, Klhl14) or obvious candidate genes (e.g., Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and there was extensive pleiotropy at individual loci. This study demonstrates the utility of HS rats for investigating the genetics of obesity-related traits across institutions and identify several candidate genes for future functional testing. Show less
📄 PDF DOI: 10.1002/oby.22927
ADCY3
Zheng Li, Cheng-Yin Ye, Li Wang +2 more · 2020 · International journal of environmental research and public health · MDPI · added 2026-04-24
Lifestyle choices such as the intake of sweets, history of diseases, and genetic variants seem to play a role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). To explore which genetic Show more
Lifestyle choices such as the intake of sweets, history of diseases, and genetic variants seem to play a role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). To explore which genetic and environmental factors are associated with NAFLD in a Chinese Han population, we conducted this study. We collected the medical reports, lifestyle details, and blood samples of individuals and used the polymerase chain reaction-ligase detection reaction method to genotype the single-nucleotide polymorphism (SNPs) from the 2113 eligible people. The GG genotype of the additive model of rs7493 in the PON2, the CC genotype of the additive and recessive models of rs7593130 in the ADCY3, together with dyslipidemia, regular intake of egg and sweets and hypertension, increased the risk of NAFLD (adjusted OR > 1, Show less
📄 PDF DOI: 10.3390/ijerph17145217
ADCY3