👤 Serina Huang

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1370
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1004
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Also published as: Ai-Chun Huang, Ai-long Huang, Aijie Huang, Ailong Huang, Aimin Huang, Alden Y Huang, An-Fang Huang, Annie Huang, Aohuan Huang, Ariane Huang, Baihai Huang, Baisong Huang, Bao-Hua Huang, Bao-Yi Huang, Baoqin Huang, Baoying Huang, Benjamin J Huang, Benlin Huang, Bevan E Huang, Bi Huang, Biao Huang, Bin Huang, Binfang Huang, Bing Huang, Bingcang Huang, Bingkun Huang, Bizhi Huang, Bo Huang, Bo-Shih Huang, Bor-Ren Huang, Bowen Huang, Boyue Huang, C Y Huang, Caihong Huang, Caiyun Huang, Can Huang, Canhua Huang, Caoxin Huang, Cathelin Huang, Catherine Huang, Chang Ming Huang, Chang X Huang, Chang-Jen Huang, Changjiang Huang, Chao Huang, Chao Wei Huang, Chao-Wei Huang, Chao-Yuan Huang, Chaolin Huang, Chaoqun Huang, Chaowang Huang, Chaoyang Huang, Chen Huang, Chen-Na Huang, Chen-Ping Huang, Cheng Huang, Chengcheng Huang, Chengrui Huang, Chenshen Huang, Chenxiao Huang, Chi-Cheng Huang, Chi-Shuan Huang, Chia-Chang Huang, Chia-Wei Huang, Chieh-Cheng Huang, Chieh-Liang Huang, Chien-Hsun Huang, Chih-Chun Huang, Chih-Hsiang Huang, Chih-Jen Huang, Chih-Ting Huang, Chih-Yang Huang, Chin-Chang Huang, Chin-Chou Huang, Ching-Shan Huang, Ching-Shin Huang, Ching-Tang Huang, Ching-Wei Huang, Chiu-Ju Huang, Chiu-Jung Huang, Chiun-Sheng Huang, Chong Huang, Chongbiao Huang, Christine S Huang, Chuan Huang, Chuanbing Huang, Chuanhong Huang, Chuanjiang Huang, Chuanjun Huang, Chuansheng Huang, Chuiguo Huang, Chun Huang, Chun-Mei Huang, Chun-Yao Huang, Chun-Yin Huang, Chunfan Huang, Chung-Hsiung Huang, Chunhong Huang, Chunjian Huang, Chunkai Huang, Chunlan Huang, Chunling Huang, Chunshuai Huang, Chunxia Huang, Chunyao Huang, Chunyi Huang, Chunying Huang, Chunyu Huang, Chuxin Huang, Chuying Huang, Congcong Huang, Cuiyu Huang, Da Huang, Dajun Huang, Dan Huang, Dane Huang, Danqing Huang, Dantong Huang, David Huang, David J Huang, De Huang, De-Jun Huang, Dejia Huang, Dengjun Huang, Dianhua Huang, Dishu Huang, Dong Huang, Donglan Huang, Dongmei Huang, Dongni Huang, Dongqin Huang, Dongqing Huang, Dongsheng Huang, Dongyu Huang, Du-Juan Huang, Emily C Huang, Enhao Huang, Enping Huang, Eric Huang, Erya Huang, F Huang, Fan Huang, Fang Huang, Fang-Ling Huang, Fangling Huang, Fei Huang, Fei Wan Huang, Feiruo Huang, Feiteng Huang, Feizhou Huang, Feng Huang, Fengxian Huang, Fengyu Huang, Franklin W Huang, Fu-Chen Huang, Fu-Mei Huang, Fubiao Huang, Fude Huang, Fuhao Huang, Furong Huang, G Huang, Gairong Huang, Gang Huang, Gao-Zhong Huang, Gaoxingyu Huang, Ge Huang, Guang-Jian Huang, Guang-Yun Huang, Guangjian Huang, Guangming Huang, Guangqian Huang, Guangrui Huang, Guanhong Huang, Guanling Huang, Guanning Huang, Guanqun Huang, Guanrong Huang, Guicheng Huang, Guodong Huang, Guohong Huang, Guoping Huang, Guoqian Huang, Guowei Huang, Guoxing Huang, Guoying Huang, Guoyong Huang, Guoyuan Huang, H Huang, H S Huang, Hai Huang, Haigang Huang, Haihong Huang, Hailin Huang, Haimiao Huang, Haixin Huang, Haiyan Huang, Han-Chang Huang, Hanxia Huang, Hao Huang, Hao-Fei Huang, Haobo Huang, Haochu Huang, Haomin Huang, Haoyu Huang, Haoyue Huang, Haozhang Huang, Haozhong Huang, He Huang, Hefeng Huang, Heguang Huang, Helen Huang, Heming Huang, Hengbin Huang, Heqing Huang, Hete Huang, Hong Huang, Hongbiao Huang, Hongcan Huang, Hongda Huang, Hongfei Huang, Hongfeng Huang, Honghui Huang, Hongou Huang, Hongqiang Huang, Hongyan Huang, Hongyang Huang, Hongyi Huang, Hongying Huang, Hongyu Huang, Hongyun Huang, Hsi-Yuan Huang, Hsien-Da Huang, Hsing-Yen Huang, Hsu Chih Huang, Hsuan-Cheng Huang, Hsuan-Ying Huang, Hu Huang, Hua Huang, Huafei Huang, Huaju Huang, Huan Huang, Huanhuan Huang, Huanliang Huang, Huapin Huang, Huashan Huang, Huayun Huang, Hui Huang, Hui-Huang Huang, Hui-Kuang Huang, Hui-Yu Huang, Huibin Huang, Huifen Huang, Huiling Huang, Huimin Huang, Huina Huang, Huiqiao Huang, Huixian Huang, Huixin Huang, Huiyan Huang, Huiyu Huang, Huizhe Huang, Huizhen Huang, Hy Huang, I-Chieh Huang, J V Huang, Janice J Huang, Jasmin Huang, Jeffrey K Huang, Jia Huang, Jia-Jia Huang, Jiaan Huang, Jiahui Huang, Jiajin Huang, Jiajun Huang, Jian Huang, Jian-Dong Huang, Jiana Huang, Jianbiao Huang, Jianbing Huang, Jianfang Huang, Jianfeng Huang, Jiangfeng Huang, Jiangtao Huang, Jiangwei Huang, Jianhua Huang, Jianlu Huang, Jianmin Huang, Jianming Huang, Jiansheng Huang, Jianzhen Huang, Jiao-Qian Huang, Jiaoti Huang, Jiaotian Huang, Jiaqi Huang, Jiawen Huang, Jiaxing Huang, Jiayu Huang, Jiayue Huang, Jie Huang, Jie Qi Huang, Jiechun Huang, Jieli Huang, Jieling Huang, Jieping Huang, Jin Huang, Jin-Di Huang, Jin-Feng Huang, Jin-Hong Huang, Jin-Yan Huang, Jinbao Huang, Jinfang Huang, Jing Huang, Jing-Fei Huang, Jingang Huang, Jinghan Huang, Jingjing Huang, Jingkun Huang, Jinglong Huang, Jingtao Huang, Jingxian Huang, Jingyong Huang, Jingyuan Huang, Jingyue Huang, Jinhua Huang, Jinling Huang, Jinlu Huang, Jinshu Huang, Jinxing Huang, Jinyan Huang, Jinzhou Huang, Jiuhong Huang, Jiyu Huang, Ju Huang, Juan Huang, Jucun Huang, Jun Huang, Jun-Hua Huang, Jun-You Huang, Junhao Huang, Junhua Huang, Junjie Huang, Junming Huang, Junning Huang, Junqi Huang, Junwen Huang, Junyuan Huang, Junyun Huang, Juxiang Huang, K Huang, K N Huang, Kai Huang, Kaipeng Huang, Kang Huang, Kangbo Huang, Kate Huang, Katherine Huang, Ke Huang, Ke-Ke Huang, Ke-Pu Huang, Kevin Huang, Kevin Y Huang, Kuan-Chun Huang, Kui-Yuan Huang, Kuiyuan Huang, Kun Huang, Kuo-Hsiang Huang, Kuo-Hung Huang, L Huang, L-B Huang, Laiqiang Huang, Lan Huang, Lanlan Huang, Lei Huang, Leijuan Huang, Li Huang, Li-Hao Huang, Li-Jiang Huang, Li-Juan Huang, Li-Jun Huang, Li-Ping Huang, Li-Rung Huang, Li-Wei Huang, Li-Yun Huang, Lian Huang, Liang Huang, Liang-Yu Huang, Liangchong Huang, Lianggui Huang, Libin Huang, Lige Huang, Lihua Huang, Lijia Huang, Lijiang Huang, Lijuan Huang, Lijun Huang, Lili Huang, Limin Huang, Liming Huang, Lin Huang, Linchen Huang, Ling Huang, Ling-Chun Huang, Ling-Jin Huang, Lingling Huang, Lining Huang, Linjing Huang, Linsheng Huang, Linxue Huang, Linyuan Huang, Liping Huang, Liqiong Huang, Lixia Huang, Lixiang Huang, Lixuan Huang, Lixue Huang, Lizhen Huang, Longfei Huang, Lu Huang, Lu-Jie Huang, Lu-Qi Huang, Luanluan Huang, Luqi Huang, Luyang Huang, Luyao Huang, Lvzhen Huang, M C Huang, Man Huang, Manning Y Huang, Manyun Huang, Mao-Mao Huang, Mei Huang, Meihua Huang, Meina Huang, Meixiang Huang, Melissa Y Huang, Meng-Chuan Huang, Meng-Fan Huang, Meng-Na Huang, MengQian Huang, Menghao Huang, Mengjie Huang, Mengjun Huang, Mengnan Huang, Mengting Huang, Mengzhen Huang, Mia L Huang, Miao Huang, Min Huang, Ming-Lu Huang, Ming-Shyan Huang, Mingjian Huang, Mingjun Huang, Minglei Huang, Mingrui Huang, Mingwei Huang, Mingxuan Huang, Mingyu Huang, Mingyuan Huang, Minjun Huang, Minqi Huang, Minxuan Huang, Minyuan Huang, N Huang, Na Huang, Nian Huang, Nianyuan Huang, Ning-Na Huang, Ning-Ping Huang, Ninghao Huang, Nongyu Huang, Pan Huang, Pang-Shuo Huang, Paul L Huang, Pei Huang, Pei-Chi Huang, Pei-Ying Huang, Peiying Huang, Peng Huang, Peng-Fei Huang, Pengyu Huang, Piao-Piao Huang, Piaopiao Huang, Pin-Rui Huang, Ping Huang, Pingping Huang, Pintong Huang, Po-Hsun Huang, Po-Jung Huang, Poyao Huang, Qi Huang, Qi-Tao Huang, Qian Huang, Qiang Huang, Qianqian Huang, Qiaobing Huang, Qibin Huang, Qidi Huang, Qin Huang, Qing Huang, Qing-yong Huang, Qingjiang Huang, Qingke Huang, Qingling Huang, Qingqing Huang, Qingsong Huang, Qingxia Huang, Qingxing Huang, Qingyu Huang, Qingzhi Huang, Qinlou Huang, Qiong Huang, Qiubo Huang, Qiumin Huang, Qiuming Huang, Qiuru Huang, Qiuyin Huang, Qiuyue Huang, Qizhen Huang, Quanfang Huang, Qun Huang, R H Huang, R Stephanie Huang, Rae-Chi Huang, Ran Huang, Renbin Huang, Renhua Huang, Renli Huang, Richard Huang, Richard S P Huang, Riqing Huang, Ritai Huang, Robert J Huang, Rong Huang, Rong Stephanie Huang, Ronghua Huang, Ronghui Huang, Rongjie Huang, Rongrong Huang, Rongxiang Huang, Ru-Ting Huang, Ruby Yun-Ju Huang, Rui Huang, Ruihua Huang, Ruijin Huang, Ruina Huang, Ruiyan Huang, Ruizhen Huang, Runyue Huang, Ruo-Hui Huang, S Huang, S Y Huang, S Z Huang, Saisai Huang, San-Yuan Huang, See-Chang Huang, Sen Huang, Shan Huang, Shang-Ming Huang, Shanhe Huang, Shanshan Huang, Shaojun Huang, Shaoxin Huang, Shaoze Huang, Shau Ku Huang, Shau-Ku Huang, Shenan Huang, Sheng-He Huang, Shengfeng Huang, Shengjie Huang, Shengnan Huang, Shengyan Huang, Shengyun Huang, Shi-Feng Huang, Shi-Shi Huang, Shi-Ying Huang, Shiang-Suo Huang, Shichao Huang, Shih-Chiang Huang, Shih-Wei Huang, Shih-Yi Huang, Shihao Huang, Shijing Huang, Shilu Huang, Shixia Huang, Shiya Huang, Shiying Huang, Shiyun Huang, Shoucheng Huang, Shu Huang, Shu-Pang Huang, Shu-Pin Huang, Shu-Qiong Huang, Shu-Wei Huang, Shu-Yi Huang, Shu-ying Huang, Shuai Huang, Shuang Huang, Shungen Huang, Shuo Huang, Shushu Huang, Shutong Huang, Shuwen Huang, Si-Yang Huang, Sidong Huang, Sihua Huang, Sijia Huang, Sinchun Huang, Sisi Huang, Sixiu Huang, Song Bin Huang, Song-Mei Huang, Songmei Huang, Songming Huang, Songqian Huang, Steven Huang, Steven Kuan-Hua Huang, Suli Huang, Sung-Ying Huang, Susan M Huang, Suwen Huang, Taiqi Huang, Tang-Hsiu Huang, Tao Huang, Te-Hsuan Huang, Tengda Huang, Tengfei Huang, Tian Hao Huang, Tianhao Huang, Tianpu Huang, Tiantian Huang, Tieqiu Huang, Tim H Huang, Ting Huang, Tinghua Huang, Tingping Huang, Tingqin Huang, Tingting Huang, Tingxuan Huang, Tingyun Huang, Tong Huang, Tongsheng Huang, Tongtong Huang, Tony T Huang, Tse-Shun Huang, Tseng-Yu Huang, Tsung-Wei Huang, Tzu-Rung Huang, Wan-Ping Huang, Way-Ren Huang, Wei Huang, Wei-Chi Huang, Weibin Huang, Weicheng Huang, Weifeng Huang, Weihua Huang, Weijun Huang, Weiqi Huang, Weisu Huang, Weiwei Huang, Weixue Huang, Weizhen Huang, Wen Huang, Wen-yu Huang, Wenbin Huang, Wenda Huang, Wenfang Huang, Wenfeng Huang, Wenhua Huang, Wenji Huang, Wenjie Huang, Wenjun Huang, Wenqiao Huang, Wenqing Huang, Wenqiong Huang, Wenshan Huang, Wentao Huang, Wenxin Huang, Wenya Huang, Wenying Huang, Wunan Huang, Wuqing Huang, X F Huang, X Huang, Xi Huang, Xian-sheng HUANG, Xiang Huang, Xianghua Huang, Xianglong Huang, Xiangming Huang, Xianping Huang, Xianqing Huang, Xiansheng Huang, Xianwei Huang, Xianxi Huang, Xianxian Huang, Xianying Huang, Xianzhang Huang, Xiao Huang, Xiao-Fang Huang, Xiao-Fei Huang, Xiao-Ming Huang, Xiao-Song Huang, Xiao-Yan Huang, Xiao-Yong Huang, Xiao-Yu Huang, XiaoFang Huang, Xiaochun Huang, Xiaofei Huang, Xiaofeng Huang, Xiaohong Huang, Xiaohua Huang, Xiaojie Huang, Xiaojing Huang, Xiaojuan Huang, Xiaolan Huang, Xiaoli Huang, Xiaolin Huang, Xiaoman Huang, Xiaomin Huang, Xiaoqing Huang, Xiaoshuai Huang, Xiaowen Huang, Xiaowu Huang, Xiaoxia Huang, Xiaoyan Huang, Xiaoying Huang, Xiaoyu Huang, Xiaoyuan Huang, Xiaoyun Huang, Xiaozhun Huang, Xiayang Huang, Xichang Huang, Xie-Lin Huang, Xin Huang, Xin-Di Huang, Xinen Huang, Xinfeng Huang, Xingguo Huang, Xingming Huang, Xingqin Huang, Xingru Huang, Xingxu Huang, Xingya Huang, Xingzhen Huang, Xinwen Huang, Xinyi Huang, Xinying Huang, Xinyue Huang, Xinzhu Huang, Xiongfeng Huang, Xionggao Huang, Xiuju Huang, Xiuyun Huang, Xiuzhen Huang, Xiwen Huang, Xu Huang, Xu-Feng Huang, Xuan Huang, Xuanzhang Huang, Xucong Huang, Xudong Huang, Xue-Ying Huang, Xue-shuang Huang, Xuehong Huang, Xuejie Huang, Xuejing Huang, Xuejun Huang, Xuemei Huang, Xueming Huang, Xueqi Huang, Xuewei Huang, Xuezhe Huang, Xuhui Huang, Xuliang Huang, Xun Huang, Xuxiong Huang, Y Huang, Y Joyce Huang, Y S Huang, Ya-Chih Huang, Ya-Dong Huang, Ya-Fang Huang, Ya-Ru Huang, Yabo Huang, Yadong Huang, Yafang Huang, Yajiao Huang, Yajuan Huang, Yali Huang, Yamei Huang, Yan Huang, Yan-Lin Huang, Yan-Qing Huang, Yan-Ting Huang, Yang Huang, Yang Zhong Huang, Yangqing Huang, Yangyang Huang, Yanhao Huang, Yani Huang, Yanjun Huang, Yanlong Huang, Yanna Huang, Yanping Huang, Yanqin Huang, Yanqing Huang, Yanqun Huang, Yanru Huang, Yanshan Huang, Yansheng Huang, Yanxia Huang, Yanyan Huang, Yanyao Huang, Yao Huang, Yao-Kuang Huang, Yaowei Huang, Yatian Huang, Yating Huang, Ye Huang, Yechao Huang, Yen-Chu Huang, Yen-Ning Huang, Yen-Tsung Huang, Yeqing Huang, Yewei Huang, Yi Huang, Yi-Chun Huang, Yi-Jan Huang, Yi-Jia Huang, Yi-Wen Huang, Yi-ping Huang, Yichao Huang, Yichuan Huang, Yicong Huang, Yifan Huang, Yihao Huang, Yiheng Huang, Yihong Huang, Yikeng Huang, Yilin Huang, Yin Huang, Yin-Tsen Huang, Ying Huang, Ying-Hsuan Huang, Ying-Jung Huang, Ying-Zhi Huang, Yinghua Huang, Yingying Huang, Yingzhen Huang, Yingzhi Huang, Yiping Huang, Yiquan Huang, Yishan Huang, Yiwei Huang, Yixian Huang, Yizhou Huang, Yong Huang, Yong-Fu Huang, Yongbiao Huang, Yongcan Huang, Yongjie Huang, Yongqi Huang, Yongsheng Huang, Yongtong Huang, Yongye Huang, Yongyi Huang, Yongzhen Huang, Youheng Huang, Youyang Huang, Yu Huang, Yu-Ching Huang, Yu-Chu Huang, Yu-Chuen Huang, Yu-Chyi Huang, Yu-Fang Huang, Yu-Han Huang, Yu-Jie Huang, Yu-Lei Huang, Yu-Ren Huang, Yu-Shu Huang, Yu-Ting Huang, Yuan Huang, Yuan-Lan Huang, Yuan-Li Huang, Yuan-Lu Huang, Yuancheng Huang, Yuanpeng Huang, Yuanshuai Huang, Yuanyu Huang, Yuanyuan Huang, Yue Huang, Yue-Hua Huang, Yuedi Huang, Yueh-Hsiang Huang, Yuehong Huang, Yuejun Huang, Yueye Huang, Yuezhen Huang, Yufang Huang, Yufen Huang, Yuguang Huang, Yuh-Chin T Huang, Yuhong Huang, Yuhua Huang, Yuhui Huang, Yujia Huang, Yujie Huang, Yulin Huang, Yumei Huang, Yumeng Huang, Yun Huang, Yun-Juan Huang, Yunchao Huang, Yung-Hsin Huang, Yung-Yu Huang, Yunmao Huang, Yunpeng Huang, Yunru Huang, Yunyan Huang, Yuping Huang, Yuqi Huang, Yuqiang Huang, Yuqiong Huang, Yusi Huang, Yutang Huang, Yuting Huang, Yutong Huang, Yuxian Huang, Yuxin Huang, Yuxuan Huang, Yuyang Huang, Yuying Huang, Z Huang, Z Z Huang, Z-Y Huang, Zebin Huang, Zebo Huang, Zehua Huang, Zeling Huang, Zengwen Huang, Zhang Huang, Zhao Huang, Zhaoxia Huang, Zhe Huang, Zhen Huang, Zhenfei Huang, Zheng Huang, Zheng-Xiang Huang, Zhengwei Huang, Zhengxian Huang, Zhengxiang Huang, Zhengyang Huang, Zhenlin Huang, Zhenrui Huang, Zhenyao Huang, Zhenyi Huang, Zhi Huang, Zhi-Ming Huang, Zhi-Qiang Huang, Zhi-Xin Huang, Zhi-xiang Huang, Zhican Huang, Zhicong Huang, Zhifang Huang, Zhifeng Huang, Zhigang Huang, Zhihong Huang, Zhilin Huang, Zhilong Huang, Zhipeng Huang, Zhiping Huang, Zhiqi Huang, Zhiqiang Huang, Zhiqin Huang, Zhiqing Huang, Zhitong Huang, Zhiwei Huang, Zhixiang Huang, Zhiying Huang, Zhiyong Huang, Zhiyu Huang, Zhongbin Huang, Zhongcheng Huang, Zhongfeng Huang, Zhonglu Huang, Zhouyang Huang, Zi-Xin Huang, Zi-Ye Huang, Zicheng Huang, Zichong Huang, Zihan Huang, Zihao Huang, Ziheng Huang, Ziling Huang, Zini Huang, Zirui Huang, Zizhan Huang, Zongjian Huang, Zongliang Huang, Zunnan Huang, Zuotian Huang, Zuxian Huang, Zuyi Huang
articles
Yaxin Zhang, Yuyan Gu, Yihao Chen +12 more · 2021 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Dingxin Recipe (DXR) is a traditional Chinese medicine formula that has been reported to be effective and safe treatment for cardiovascular diseases, such as arrhythmias, coronary heart disease. Dingx Show more
Dingxin Recipe (DXR) is a traditional Chinese medicine formula that has been reported to be effective and safe treatment for cardiovascular diseases, such as arrhythmias, coronary heart disease. Dingxin Recipe IV (DXR IV) was further improved from the DXR according to the traditional use. However, the mechanism of DXR IV in atherosclerosis is unclear. This study aimed to illustrate whether DXR IV improve atherosclerosis through modulating the lipid metabolism and gut microbiota in atherosclerosis mice. 40 male ApoE DXR IV exerted the anti-atherosclerosis effect by inhibiting the excessive cholesterol deposition in aorta and regulating the level of TG, TC, LDL-C and HDL-C. The composition of gut microbiota was changed. Interestingly, the relative abundance of Muribaculaceae and Ruminococcaceae increased after DXR IV administration, whereas the abundance of Erysipelotrichaceae decreased, which have been beneficial to lipid metabolism. Nine potential metabolic biomarkers, including acetate, butyrate, propionate, alanine, succinate, valerate, xylose, choline, glutamate, were identified, which were related to fatty acid metabolism. Further, the pathway of fatty acid was detected by the RT-qPCR and western blotting. Compared with model group, the level of LXR-α and SREBP1 decreased significantly in DXR IV group while LXR-β, SREBP2 showed no statistical significance. It indicated that DXR IV modulated lipid metabolism by LXR-α/SREBP1 but not LXRβ and SREBP2. DXR IV exhibits potential anti-atherosclerosis effect, which is closely related to lipid metabolism and the gut microbiota. This study may provide novel insights into the mechanism of DXR IV on atherosclerosis and a basis for promising clinical usage. Show less
no PDF DOI: 10.1016/j.jep.2020.113436
NR1H3
Yutian Li, Shan Deng, Xiaohong Wang +12 more · 2021 · Cardiovascular research · Oxford University Press · added 2026-04-24
Cardiac dysfunction is a prevalent comorbidity of disrupted inflammatory homeostasis observed in conditions such as sepsis (acute) or obesity (chronic). Secreted and transmembrane protein 1a (Sectm1a) Show more
Cardiac dysfunction is a prevalent comorbidity of disrupted inflammatory homeostasis observed in conditions such as sepsis (acute) or obesity (chronic). Secreted and transmembrane protein 1a (Sectm1a) has previously been implicated to regulate inflammatory responses, yet its role in inflammation-associated cardiac dysfunction is virtually unknown. Using the CRISPR/Cas9 system, we generated a global Sectm1a-knockout (KO) mouse model and observed significantly increased mortality and cardiac injury after lipopolysaccharide (LPS) injection, when compared with wild-type (WT) control. Further analysis revealed significantly increased accumulation of inflammatory macrophages in hearts of LPS-treated KO mice. Accordingly, ablation of Sectm1a remarkably increased inflammatory cytokines levels both in vitro [from bone marrow-derived macrophages (BMDMs)] and in vivo (in serum and myocardium) after LPS challenge. RNA-sequencing results and bioinformatics analyses showed that the most significantly down-regulated genes in KO-BMDMs were modulated by LXRα, a nuclear receptor with robust anti-inflammatory activity in macrophages. Indeed, we identified that the nuclear translocation of LXRα was disrupted in KO-BMDMs when treated with GW3965 (LXR agonist), resulting in higher levels of inflammatory cytokines, compared to GW3965-treated WT-cells. Furthermore, using chronic inflammation model of high-fat diet (HFD) feeding, we observed that infiltration of inflammatory monocytes/macrophages into KO-hearts were greatly increased and accordingly, worsened cardiac function, compared to WT-HFD controls. This study defines Sectm1a as a new regulator of inflammatory-induced cardiac dysfunction through modulation of LXRα signalling in macrophages. Our data suggest that augmenting Sectm1a activity may be a potential therapeutic approach to resolve inflammation and associated cardiac dysfunction. Show less
no PDF DOI: 10.1093/cvr/cvaa067
NR1H3
Yajuan Jiao, Ning Kong, Hua Wang +15 more · 2021 · Microbiology spectrum · added 2026-04-24
Emerging coronaviruses (CoVs) can cause severe diseases in humans and animals, and, as of yet, none of the currently available broad-spectrum drugs or vaccines can effectively control these diseases. Show more
Emerging coronaviruses (CoVs) can cause severe diseases in humans and animals, and, as of yet, none of the currently available broad-spectrum drugs or vaccines can effectively control these diseases. Host antiviral proteins play an important role in inhibiting viral proliferation. One of the isoforms of cytoplasmic poly(A)-binding protein (PABP), PABPC4, is an RNA-processing protein, which plays an important role in promoting gene expression by enhancing translation and mRNA stability. However, its function in viruses remains poorly understood. Here, we report that the host protein, PABPC4, could be regulated by transcription factor SP1 and broadly inhibits the replication of CoVs, covering four genera ( Show less
no PDF DOI: 10.1128/Spectrum.00908-21
PABPC4
Wenhui Guo, Jingyi Li, Haobo Huang +3 more · 2021 · Frontiers in oncology · Frontiers · added 2026-04-24
Long non-coding RNAs (LncRNA) as the key regulators in all stages of tumorigenesis and metastasis. However, the underlying mechanisms are largely unknown. Here, we report a lncRNA RP11-214F16.8, which Show more
Long non-coding RNAs (LncRNA) as the key regulators in all stages of tumorigenesis and metastasis. However, the underlying mechanisms are largely unknown. Here, we report a lncRNA RP11-214F16.8, which renamed Lnc-PCIR, is upregulated and higher RNA level of Lnc-PCIR was positively correlated to the poor survival of patients with triple negative breast cancer (TNBC) tissues. Lnc-PCIR overexpression significantly promoted cell proliferation, migration, and invasion Show less
no PDF DOI: 10.3389/fonc.2021.630300
PABPC4
Hassan S Dashti, Iyas Daghlas, Jacqueline M Lane +12 more · 2021 · Nature communications · Nature · added 2026-04-24
Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-repo Show more
Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference. Show less
no PDF DOI: 10.1038/s41467-020-20585-3
PATJ
Li-Ting Wang, Ming-Hong Lin, Kwei-Yan Liu +9 more · 2021 · Autophagy · Taylor & Francis · added 2026-04-24
We propose that beyond its role in WNT secretion, WLS/GPR177 (wntless, WNT ligand secretion mediator) acts as an essential regulator controlling protein glycosylation, endoplasmic reticulum (ER) homeo Show more
We propose that beyond its role in WNT secretion, WLS/GPR177 (wntless, WNT ligand secretion mediator) acts as an essential regulator controlling protein glycosylation, endoplasmic reticulum (ER) homeostasis, and dendritic cell (DC)-mediated immunity. WLS deficiency in bone marrow-derived DCs (BMDCs) resulted in poor growth and an inability to mount cytokine and T-cell responses Show less
no PDF DOI: 10.1080/15548627.2021.1907516
PIK3C3
Wenxin Du, Aixiao Xu, Yunpeng Huang +6 more · 2021 · Autophagy · Taylor & Francis · added 2026-04-24
Although molecular targeted therapies have recently displayed therapeutic effects in acute myeloid leukemia (AML), limited response and acquired resistance remain common problems. Numerous studies hav Show more
Although molecular targeted therapies have recently displayed therapeutic effects in acute myeloid leukemia (AML), limited response and acquired resistance remain common problems. Numerous studies have associated autophagy, an essential degradation process involved in the cellular response to stress, with the development and therapeutic response of cancers including AML. Thus, we review studies on the role of autophagy in AML development and summarize the linkage between autophagy and several recurrent genetic abnormalities in AML, highlighting the potential of capitalizing on autophagy modulation in targeted therapy for AML. Show less
no PDF DOI: 10.1080/15548627.2020.1822628
PIK3C3
Haoran Wei, Wenhao Ma, Xiaofei Lu +12 more · 2021 · Cancer communications (London, England) · Wiley · added 2026-04-24
Histone deacetylases (HDACs) engage in the regulation of various cellular processes by controlling global gene expression. The dysregulation of HDACs leads to carcinogenesis, making HDACs ideal target Show more
Histone deacetylases (HDACs) engage in the regulation of various cellular processes by controlling global gene expression. The dysregulation of HDACs leads to carcinogenesis, making HDACs ideal targets for cancer therapy. However, the use of HDAC inhibitors (HDACi) as single agents has been shown to have limited success in treating solid tumors in clinical studies. This study aimed to identify a novel downstream effector of HDACs to provide a potential target for combination therapy. Transcriptome sequencing and bioinformatics analysis were performed to screen for genes responsive to HDACi in breast cancer cells. The effects of HDACi on cell viability were detected using the MTT assay. The mRNA and protein levels of genes were determined by quantitative reverse transcription-PCR (qRT-PCR) and Western blotting. Cell cycle distribution and apoptosis were analyzed by flow cytometry. The binding of CREB1 (cAMP-response element binding protein 1) to the promoter of the KDELR (The KDEL (Lys-Asp-Glu-Leu) receptor) gene was validated by the ChIP (chromatin immunoprecipitation assay). The association between KDELR2 and protein of centriole 5 (POC5) was detected by immunoprecipitation. A breast cancer-bearing mouse model was employed to analyze the effect of the HDAC3-KDELR2 axis on tumor growth. KDELR2 was identified as a novel target of HDAC3, and its aberrant expression indicated the poor prognosis of breast cancer patients. We found a strong correlation between the protein expression patterns of HADC3 and KDELR2 in tumor tissues from breast cancer patients. The results of the ChIP assay and qRT-PCR analysis validated that HDAC3 transactivated KDELR2 via CREB1. The HDAC3-KDELR2 axis accelerated the cell cycle progression of cancer cells by protecting the centrosomal protein POC5 from proteasomal degradation. Moreover, the HDAC3-KDELR2 axis promoted breast cancer cell proliferation and tumorigenesis in vitro and in vivo. Our results uncovered a previously unappreciated function of KDELR2 in tumorigenesis, linking a critical Golgi-the endoplasmic reticulum traffic transport protein to HDAC-controlled cell cycle progression on the path of cancer development and thus revealing a potential therapeutical target for breast cancer. Show less
no PDF DOI: 10.1002/cac2.12180
POC5

Decreased

Qianli Ma, Jin Zhang, Jingjing Huang +11 more · 2021 · Translational lung cancer research · added 2026-04-24
Early-stage female lung adenocarcinoma is the most common type of lung cancer encountered in thoracic surgery departments. Tumor-node-metastasis (TNM) staging does not adequately explain a significant Show more
Early-stage female lung adenocarcinoma is the most common type of lung cancer encountered in thoracic surgery departments. Tumor-node-metastasis (TNM) staging does not adequately explain a significant stratification phenomenon in the prognosis of patients with stage I lung adenocarcinoma. We aimed to investigate the contributory role of We analyzed the microRNA (miRNA) expression level in tumor tissues (high-risk group In all, 24 miRNAs were found to be significantly different between the high-risk group and low-risk group. The expression level of The present study showed that Show less
no PDF DOI: 10.21037/tlcr-21-906
SNAI1
Marcy Martin, Jiao Zhang, Yifei Miao +17 more · 2021 · JCI insight · added 2026-04-24
Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with limited treatment options. Despite endothelial cells (ECs) comprising 30% of the lung cellular composition, the role of EC dysfun Show more
Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with limited treatment options. Despite endothelial cells (ECs) comprising 30% of the lung cellular composition, the role of EC dysfunction in pulmonary fibrosis (PF) remains unclear. We hypothesize that sterol regulatory element-binding protein 2 (SREBP2) plays a critical role in the pathogenesis of PF via EC phenotypic modifications. Transcriptome data demonstrate that SREBP2 overexpression in ECs led to the induction of the TGF, Wnt, and cytoskeleton remodeling gene ontology pathways and the increased expression of mesenchymal genes, such as snail family transcriptional repressor 1 (snai1), α-smooth muscle actin, vimentin, and neural cadherin. Furthermore, SREBP2 directly bound to the promoter regions and transactivated these mesenchymal genes. This transcriptomic change was associated with an epigenetic and phenotypic switch in ECs, leading to increased proliferation, stress fiber formation, and ECM deposition. Mice with endothelial-specific transgenic overexpression of SREBP2 (EC-SREBP2[N]-Tg mice) that were administered bleomycin to induce PF demonstrated exacerbated vascular remodeling and increased mesenchymal transition in the lung. SREBP2 was also found to be markedly increased in lung specimens from patients with IPF. These results suggest that SREBP2, induced by lung injury, can exacerbate PF in rodent models and in human patients with IPF. Show less
no PDF DOI: 10.1172/jci.insight.125635
SNAI1
Guoxu Fang, Jianhui Fan, Zongren Ding +6 more · 2021 · Frontiers in oncology · Frontiers · added 2026-04-24
Digestive system carcinoma is one of the most devastating diseases worldwide. Lack of valid clinicopathological parameters as prognostic factors needs more accurate and effective biomarkers for high-c Show more
Digestive system carcinoma is one of the most devastating diseases worldwide. Lack of valid clinicopathological parameters as prognostic factors needs more accurate and effective biomarkers for high-confidence prognosis that guide decision-making for optimal treatment of digestive system carcinoma. The aim of the present study was to establish a novel model to improve prognosis prediction of digestive system carcinoma, with a particular interest in transcription factors (TFs). A TF-related prognosis model of digestive system carcinoma with data from TCGA database successively were processed by univariate and multivariate Cox regression analyses. Then, for evaluating the prognostic prediction value of the model, ROC curve and survival analysis were performed by external data from GEO database. Furthermore, we verified the expression of TFs expression by qPCR in digestive system carcinoma tissue. Finally, we constructed a TF clinical characteristics nomogram to furtherly predict digestive system carcinoma patient survival probability with TCGA database. By Cox regression analysis, a panel of 17 TFs (NFIC, YBX2, ZBTB47, ZNF367, CREB3L3, HEYL, FOXD1, TIGD1, SNAI1, HSF4, CENPA, ETS2, FOXM1, ETV4, MYBL2, FOXQ1, ZNF589) was identified to present with powerful predictive performance for overall survival of digestive system carcinoma patients based on TCGA database. A nomogram that integrates TFs was established, allowing efficient prediction of survival probabilities and displaying higher clinical utility. The 17-TF panel is an independent prognostic factor for digestive system carcinoma, and 17 TFs based nomogram might provide implication an effective approach for digestive system carcinoma patient management and treatment. Show less
no PDF DOI: 10.3389/fonc.2021.670129
SNAI1

RNA m

Rui Huang, Lin Yang, Zhiwen Zhang +5 more · 2021 · Frontiers in cell and developmental biology · Frontiers · added 2026-04-24
Although RNA m
no PDF DOI: 10.3389/fcell.2021.724282
SNAI1
Yang Yang, Mingyang Feng, LiangLiang Bai +10 more · 2021 · Journal of translational medicine · BioMed Central · added 2026-04-24
EMT is an important biological process in the mechanism of tumor invasion and metastasis. However, there are still many unknowns about the specific mechanism of EMT in tumor. At present, a comprehensi Show more
EMT is an important biological process in the mechanism of tumor invasion and metastasis. However, there are still many unknowns about the specific mechanism of EMT in tumor. At present, a comprehensive analysis of EMT-related genes in colorectal cancer (CRC) is still lacking. All the data were downloaded from public databases including TCGA database (488 tumor samples and 52 normal samples) as the training set and the GEO database (GSE40967 including 566 tumor samples and 19 normal samples, GSE12945 including 62 tumor samples, GSE17536 including 177 tumor samples, GSE17537 including 55 tumor samples) as the validation sets. One hundred and sixty-six EMT-related genes (EMT-RDGs) were selected from the Molecular Signatures Database. Bioinformatics methods were used to analyze the correlation between EMT-RDGs and CRC prognosis, metastasis, drug efficacy, and immunity. We finally obtained nine prognostic-related EMT-RDGs (FGF8, NOG, PHLDB2, SIX2, SNAI1, TBX5, TIAM1, TWIST1, TCF15) through differential expression analysis, Unicox and Lasso regression analysis, and then constructed a risk prognosis model. There were significant differences in clinical characteristics, 22 immune cells, and immune functions between the high-risk and low-risk groups and the different states of the nine prognostic-related EMT-RDGs. The methylation level and mutation status of nine prognostic-related EMT-RDGs all affect their regulation of EMT. The Cox proportional hazards regression model was also constructed by the methylation sites of nine prognostic-related EMT-RDGs. In addition, the expression of FGF8, PHLDB2, SIX2, and SNAIL was higher and the expression level of NOG and TWIST1 was lower in the non-metastasis CRC group. Nine prognostic-related EMT-RDGs also affected the drug treatment response of CRC. Targeting these nine prognostic-related EMT-RDGs can regulate CRC metastasis and immune, which is beneficial for the prognosis of CRC patients, improve drug sensitivity in CRC patients. Show less
no PDF DOI: 10.1186/s12967-021-03065-0
SNAI1
Wenqing Huang, Jianxiong Chen, Xunhua Liu +8 more · 2021 · Experimental cell research · Elsevier · added 2026-04-24
Breast cancer is one of the most frequently diagnosed cancers and the leading cause of cancer death in women. MIER3 (Mesoderm induction early response 1, family member3) is considered as a potential o Show more
Breast cancer is one of the most frequently diagnosed cancers and the leading cause of cancer death in women. MIER3 (Mesoderm induction early response 1, family member3) is considered as a potential oncogene for breast cancer. However, the role of MIER3 in breast cancer remain largely unknown. The expression of MIER3 was detected and the relationship between its expression and clinicopathological characteristics was also analyzed. The effect of MIER3 on proliferation and migration of breast cancer cells was detected in vitro and in vivo. Western blot, IF, and Co-IP were employed to detect the relationship between MIER3, HDAC1, HDAC2, and Snail. ChIP assay was performed to determine the binding of MIER3/HDAC1/HDAC2/Snail complex to the promoter of E-cadherin. In this study, we found that MIER3 was upregulated in breast cancer tissue and closely associated with poor prognosis of patients. MIER3 could promote the proliferation, migration, and epithelial-mesenchymal transition (EMT) of breast cancer cells. Further studies showed that MIER3 interacted with HDAC1/HDAC2 and Snail to form a repressive complex which could bind to E-cadherin promoter and was related to its deacetylation. Our study concluded that MIER3 was involved in forming a co-repressor complex with HDAC1/HDAC2/Snail to promote EMT by silencing E-cadherin. Show less
no PDF DOI: 10.1016/j.yexcr.2021.112722
SNAI1
Cuei-Jyuan Lin, Way-Ren Huang, Chia-Zhen Wu +1 more · 2021 · Oncology letters · added 2026-04-24
Ovarian clear cell carcinoma (OCCC) is characterized by a poor survival of patients, which is mainly due to metastasis and treatment failure. Slit guidance ligand 2 (SLIT2), a secreted protein, has be Show more
Ovarian clear cell carcinoma (OCCC) is characterized by a poor survival of patients, which is mainly due to metastasis and treatment failure. Slit guidance ligand 2 (SLIT2), a secreted protein, has been reported to modulate the migration of neural cells and human cancer cells. However, the effect of changes in SLIT2 expression on the regulation of cell migration in OCCC remains unknown. The present study examined alterations in SLIT2 expression using OCCC cell models, including low- and high-mobility SKOV3 cells, as well as OCCC tissues. DNA methylation analysis suggested that promoter hypermethylation was responsible for the low expression levels of SLIT2 in OCCC cells. The demethylating agent 5-Aza-deoxycytosine was able to restore SLIT2 expression at both the mRNA and protein levels in high-mobility SKOV3 cells that harbored the relevant methylated promoter. Overexpression of SLIT2 inhibited the migration of high-mobility OCCC cells, as well as decreased the protein expression levels of β-catenin, phosphorylated (p)AKT and snail family transcriptional repressor 1 (SNAI1). On the other hand, knockdown of SLIT2 increased the migration of low-mobility OCCC cells, and enhanced the protein expression levels of β-catenin, pAKT and SNAI1. Overall, the results of the present study provided evidence that low expression levels of SLIT2 were associated with increased OCCC cell migration, and that SLIT2 may act as a suppressor gene of cancer cell migration. Show less
no PDF DOI: 10.3892/ol.2021.12812
SNAI1
Feng-Yen Lin, Yi-Wen Lin, Chun-Ming Shih +7 more · 2021 · International journal of molecular sciences · MDPI · added 2026-04-24
Therapeutic elevation of high-density lipoprotein (HDL) is thought to minimize atherogenesis in subjects with dyslipidemia. However, this is not the case in clinical practice. The function of HDL is n Show more
Therapeutic elevation of high-density lipoprotein (HDL) is thought to minimize atherogenesis in subjects with dyslipidemia. However, this is not the case in clinical practice. The function of HDL is not determined by its concentration in the plasma but by its specific structural components. We previously identified an index for the prediction of HDL functionality, relative HDL (rHDL) index, and preliminarily explored that dysfunctional HDL (rHDL index value > 2) failed to rescue the damage to endothelial progenitor cells (EPCs). To confirm the effectiveness of the rHDL index for predicting HDL functions, here we evaluated the effects of HDL from patients with different rHDL index values on the endothelial-mesenchymal transition (EndoMT) of EPCs. We also analyzed the lipid species in HDL with different rHDL index values and investigated the structural differences that affect HDL functions. The results indicate that HDL from healthy adults and subjects with an rHDL index value < 2 protected transforming growth factor (TGF)-β1-stimulated EndoMT by modulating Smad2/3 and Snail activation. HDL from subjects with an rHDL index value > 2 failed to restore the functionality of TGF-β1-treated EPCs. Lipidomic analysis demonstrated that HDL with different rHDL index values may differ in the composition of triglycerides, phosphatidylcholine, and phosphatidylinositol. In conclusion, we confirmed the applicability of the rHDL index value to predict HDL function and found structural differences that may affect the function of HDL, which warrants further in-depth studies. Show less
no PDF DOI: 10.3390/ijms22105210
SNAI1
Chunhua Chen, Shiheng Li, Junli Xue +6 more · 2021 · JCI insight · added 2026-04-24
Although the immune checkpoint role of programmed death ligand 1 (PD-L1) has been established and targeted in cancer immunotherapy, the tumor-intrinsic role of PD-L1 is less appreciated in tumor biolo Show more
Although the immune checkpoint role of programmed death ligand 1 (PD-L1) has been established and targeted in cancer immunotherapy, the tumor-intrinsic role of PD-L1 is less appreciated in tumor biology and therapeutics development, partly because of the incomplete mechanistic understanding. Here we demonstrate a potentially novel mechanism by which PD-L1 promotes the epithelial-mesenchymal transition (EMT) in triple-negative breast cancer (TNBC) cells by suppressing the destruction of the EMT transcription factor Snail. PD-L1 directly binds to and inhibits the tyrosine phosphatase PTP1B, thus preserving p38-MAPK activity that phosphorylates and inhibits glycogen synthase kinase 3β (GSK3β). Via this mechanism, PD-L1 prevents the GSK3β-mediated phosphorylation, ubiquitination, and degradation of Snail and consequently promotes the EMT and metastatic potential of TNBC. Significantly, PD-L1 antibodies that confine the tumor-intrinsic PD-L1/Snail pathway restricted TNBC progression in immunodeficient mice. More importantly, targeting both tumor-intrinsic and tumor-extrinsic functions of PD-L1 showed strong synergistic tumor suppression effect in an immunocompetent TNBC mouse model. Our findings support that PD-L1 intrinsically facilitates TNBC progression by promoting the EMT, and this potentially novel PD-L1 signaling pathway could be targeted for better clinical management of PD-L1-overexpressing TNBCs. Show less
no PDF DOI: 10.1172/jci.insight.131458
SNAI1
Shan-Shan Li, Dong-Mei Chen, Lu-Biao Chen +5 more · 2021 · Molecular medicine reports · added 2026-04-24
Snail family transcriptional repressor 1 (SNAIL1) is a master inducer of the epithelial‑to‑mesenchymal transition (EMT) process, contributing to tumor metastasis and recurrence. Our previous study rep Show more
Snail family transcriptional repressor 1 (SNAIL1) is a master inducer of the epithelial‑to‑mesenchymal transition (EMT) process, contributing to tumor metastasis and recurrence. Our previous study reported that G2 and S phase‑expressed‑1 (GTSE1) served a role in regulating SNAIL1 expression in hepatocellular carcinoma (HCC). However, the underlying mechanism remains unknown. Therefore, the present study aimed to reveal the regulatory mechanism of GTSE1 on SNAIL1 expression using Show less
no PDF DOI: 10.3892/mmr.2021.12093
SNAI1
Han Ping Cheng, Chiu-Jung Huang, Ming-Long Tsai +4 more · 2021 · International journal of medical sciences · added 2026-04-24
Cell migration and invasion are modulated by epithelial-to-mesenchymal transition (EMT) and the reverse MET process. Despite the detection of microRNA-362 (miR-362, both the miR-362-5p and -3p species Show more
Cell migration and invasion are modulated by epithelial-to-mesenchymal transition (EMT) and the reverse MET process. Despite the detection of microRNA-362 (miR-362, both the miR-362-5p and -3p species) in cancers, none of the identified miR-362 targets is a mesenchymal or epithelial factor to link miR-362 with EMT/MET and metastasis. Focusing on the TGF-β/SMAD signaling pathway in this work, luciferase assays and western blot data showed that miR-362 targeted and negatively regulated expression of SMAD4 and E-cadherin, but not SNAI1, which is regulated by SMAD4. However, miR-362 knockdown also down-regulated SMAD4 and SNAI1, but up-regulated E-cadherin expression. Wound-healing and transwell assays further showed that miR-362 knockdown suppressed cell migration and invasion, effects which were reversed by over-expressing SMAD4 or SNAI1, or by knocking down E-cadherin in the miR-362 knockdown cells. In orthotopic mice, miR-362 knockdown inhibited metastasis, and displayed the same SMAD4 and E-cadherin expression profiles in the tumors as in the Show less
no PDF DOI: 10.7150/ijms.50871
SNAI1
Ruimei Zhou, Jiashun Liao, Dunpeng Cai +5 more · 2021 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Renal interstitial fibrosis (RIF) is a pathological process that fibrotic components are excessively deposited in the renal interstitial space due to kidney injury, resulting in impaired renal functio Show more
Renal interstitial fibrosis (RIF) is a pathological process that fibrotic components are excessively deposited in the renal interstitial space due to kidney injury, resulting in impaired renal function and chronic kidney disease. The molecular mechanisms controlling renal fibrosis are not fully understood. In this present study, we identified Nuclear protein 1 (Nupr1), a transcription factor also called p8, as a novel regulator promoting renal fibrosis. Unilateral ureteral obstruction (UUO) time-dependently induced Nupr1 mRNA and protein expression in mouse kidneys while causing renal damage and fibrosis. Nupr1 deficiency (Nupr1 Show less
no PDF DOI: 10.1096/fj.202000926RR
SNAI1
Ge Yang, Xianyong Li, Jingbo Liu +5 more · 2021 · Oncology reports · added 2026-04-24
The biological functions of circular RNAs in liver tumorigenesis have been well demonstrated by a number of studies. Nevertheless, to the best of our knowledge, the role and mechanism of action of hsa Show more
The biological functions of circular RNAs in liver tumorigenesis have been well demonstrated by a number of studies. Nevertheless, to the best of our knowledge, the role and mechanism of action of hsa_circ₀₀₀₈₅₃₇ (circ₀₀₀₈₅₃₇₎ in liver cancer pathogenesis remain undetermined. In the present study, circ₀₀₀₈₅₃₇ expression was associated with the GLI3 gene and was markedly increased in liver cancer tissue specimens and cells. High expression levels of circ₀₀₀₈₅₃₇ exhibited a poor prognosis. In addition, circ₀₀₀₈₅₃₇ overexpression resulted in an increased proliferation, migration and invasion of liver cancer cells, whereas circ₀₀₀₈₅₃₇ knockdown exhibited opposite effects. circ₀₀₀₈₅₃₇ acted as a sponge of microRNA‑153‑3p (miR‑153‑3p), and a negative correlation was observed between circ₀₀₀₈₅₃₇ and miR‑153‑3p expression in liver cancer. Transfection with miR‑153‑3p further abolished the effects of circ₀₀₀₈₅₃₇ on the malignant behavior of liver cancer cells. Furthermore, circ₀₀₀₈₅₃₇ indirectly affected the expression levels of pro‑survival protein myeloid cell leukemia 1 (MCL1) and snail family zinc finger 1 (Snail1) via miR‑153‑3p in liver cancer cells. In conclusion, the data indicated that circ₀₀₀₈₅₃₇ facilitated liver carcinogenesis by indirectly regulating miR‑153‑3p and leading to the release of MCL1 and Snail1. Show less
no PDF DOI: 10.3892/or.2021.7941
SNAI1
Shan Xing, Zhi Tian, Wenying Zheng +9 more · 2021 · Molecular cancer · BioMed Central · added 2026-04-24
MicroRNAs (miRNAs) show considerable promise as therapeutic agents to improve tumor treatment, as they have been revealed as crucial modulators in tumor progression. However, our understanding of thei Show more
MicroRNAs (miRNAs) show considerable promise as therapeutic agents to improve tumor treatment, as they have been revealed as crucial modulators in tumor progression. However, our understanding of their roles in gastric carcinoma (GC) metastasis is limited. Here, we aimed to identify novel miRNAs involved in GC metastasis and explored their regulatory mechanisms and therapeutic significance in GC. The microRNA expression profiles of GC tumors at different stages and at different metastasis statuses were compared respectively using the stomach adenocarcinoma (STAD) miRNASeq dataset in TCGA. Using the above method, miR-4521 was picked out for further study. miR-4521 expression in GC tissues was examined by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and in situ hybridization (ISH). Highly and lowly invasive cell sublines were established using a repetitive transwell assay. Gain-of-function and loss-of-function analyses were performed to investigate the functions of miR-4521 and its upstream and downstream regulatory mechanisms in vitro and in vivo. Moreover, we investigated the therapeutic role of miR-4521 in a mouse xenograft model. In this study, we found that miR-4521 expression was downregulated in GC tissues compared with adjacent normal tissues and that its downregulation was positively correlated with advanced clinical stage, metastasis status and poor patient prognosis. Functional experiments revealed that miR-4521 inhibited GC cell invasion and metastasis in vitro and in vivo. Further studies showed that hypoxia repressed miR-4521 expression via inducing ETS1 and miR-4521 mitigated hypoxia-mediated metastasis, while miR-4521 inactivated the AKT/GSK3β/Snai1 pathway by targeting IGF2 and FOXM1, thereby inhibiting the epithelial-mesenchymal transition (EMT) process and metastasis. In addition, we demonstrated that therapeutic delivery of synthetic miR-4521 suppressed gastric carcinoma progression in vivo. Our results suggest an important role for miR-4521 in regulating GC metastasis and hypoxic response of tumor cells as well as the therapeutic significance of this miRNA in GC. Show less
no PDF DOI: 10.1186/s12943-020-01295-2
SNAI1
Houyu Zhao, Junjun Ling, Yi Huang +2 more · 2021 · Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology · Blackwell Publishing · added 2026-04-24
SNAI1 is an epithelial-mesenchymal transition (EMT) inducer, which has been indicated to play a role in the progression of cancers. We aimed to evaluate the expression and prognostic roles of SNAI1 in Show more
SNAI1 is an epithelial-mesenchymal transition (EMT) inducer, which has been indicated to play a role in the progression of cancers. We aimed to evaluate the expression and prognostic roles of SNAI1 in head and neck carcinoma (HNC). The study involved two major phases. In the in silico phase, the SNAI1 expression and its association with clinical features as well as its prognostic values were assessed; then, the target genes of SNAI1 were predicted and the relationship between SNAI1 expression and immune cell infiltration was evaluated. In the validation phase, a cohort of a tissue microarray (47 cases) and a cohort of HNC patients (68 cases) were enrolled. SNAI1 was detected by using an immunochemistry assay. The in silico analysis showed that overexpression of SNAI1 in HNC tissues may be correlated with metastatic lymph node numbers and may predict poor outcomes. Six genes, including CREB3L1, MITF, KLF9, RARA, KLF7, and ETV1, were predicted to be the target genes of SNAI1. The expression of SNAI1 was negatively correlated with tumor purity of HNC, while it was positively correlated with the infiltration of diverse immune cells, such as B cells and macrophages. In the validation phase, the relationships of SNAI1 expression with lymph node metastasis and poor prognosis were verified. Overexpression of SNAI1 might promote lymph node metastasis through complex molecular mechanisms and act as a prognostic indicator in HNC. SNAI1 expression may have a correlation with immune cell infiltrates. Future studies are needed to address these points. Show less
no PDF DOI: 10.1111/jop.13111
SNAI1
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
Naijin Zhang, Ying Zhang, Boquan Wu +8 more · 2021 · Redox biology · Elsevier · added 2026-04-24
Poly(ADP-ribose) polymerase 1 (PARP1) has a major regulatory role in cardiovascular disease. However, inhibiting PARP1 activity does not significantly improve clinical outcomes of cardiovascular disea Show more
Poly(ADP-ribose) polymerase 1 (PARP1) has a major regulatory role in cardiovascular disease. However, inhibiting PARP1 activity does not significantly improve clinical outcomes of cardiovascular disease, which suggests that the regulatory mechanism of PARP1 in cardiovascular disease is unclear. Here, we focused on deacetylation regulatory mechanisms of PARP1 and crosstalk of PARP1 post-translational modifications. We uncovered the crucial molecular interactions and protein modifications of deacetylase Sirtuin 2 (SIRT2) and PARP1 in vascular damage. The results showed that SIRT2 was involved in this process and oxidative stress damage factor PARP1 was a novel physiological substrate of SIRT2. SIRT2 interacted with PARP1 at the PARP-A-helical domain and deacetylated the K249 residue of PARP1. Furthermore, SIRT2 promoted ubiquitination of the K249 residue of PARP1 via mobilization of the E3 ubiquitin ligase WW domain-containing protein 2 (WWP2), which led to proteasome-mediated degradation of PARP1. Knockout of SIRT2 in mice and cells increased PARP1 acetylation and decreased PARP1 ubiquitination, which in turn aggravated oxidative stress-induced vascular injury and remodeling. Conversely, overexpression of SIRT2 in mice and cells decreased PARP1 acetylation, increased PARP1 ubiquitination, and relieved oxidative stress-induced vascular injury and remodeling. Overall, this study revealed a previously unrecognized mechanistic link between SIRT2 and PARP1 in the regulation of oxidative stress-induced vascular injury. Show less
no PDF DOI: 10.1016/j.redox.2021.102141
WWP2
Xiaoguang Fang, Zhi Huang, Kui Zhai +10 more · 2021 · Science translational medicine · Science · added 2026-04-24
Glioblastoma (GBM), a lethal primary brain tumor, contains glioma stem cells (GSCs) that promote malignant progression and therapeutic resistance. SOX2 is a core transcription factor that maintains th Show more
Glioblastoma (GBM), a lethal primary brain tumor, contains glioma stem cells (GSCs) that promote malignant progression and therapeutic resistance. SOX2 is a core transcription factor that maintains the properties of stem cells, including GSCs, but mechanisms associated with posttranslational SOX2 regulation in GSCs remain elusive. Here, we report that DNA-dependent protein kinase (DNA-PK) governs SOX2 stability through phosphorylation, resulting in GSC maintenance. Mass spectrometric analyses of SOX2-binding proteins showed that DNA-PK interacted with SOX2 in GSCs. The DNA-PK catalytic subunit (DNA-PKcs) was preferentially expressed in GSCs compared to matched non-stem cell tumor cells (NSTCs) isolated from patient-derived GBM xenografts. DNA-PKcs phosphorylated human SOX2 at S251, which stabilized SOX2 by preventing WWP2-mediated ubiquitination, thus promoting GSC maintenance. We then demonstrated that when the nuclear DNA of GSCs either in vitro or in GBM xenografts in mice was damaged by irradiation or treatment with etoposide, the DNA-PK complex dissociated from SOX2, which then interacted with WWP2, leading to SOX2 degradation and GSC differentiation. These results suggest that DNA-PKcs-mediated phosphorylation of S251 was critical for SOX2 stabilization and GSC maintenance. Pharmacological inhibition of DNA-PKcs with the DNA-PKcs inhibitor NU7441 reduced GSC tumorsphere formation in vitro and impaired growth of intracranial human GBM xenografts in mice as well as sensitized the GBM xenografts to radiotherapy. Our findings suggest that DNA-PK maintains GSCs in a stem cell state and that DNA damage triggers GSC differentiation through precise regulation of SOX2 stability, highlighting that DNA-PKcs has potential as a therapeutic target in glioblastoma. Show less
no PDF DOI: 10.1126/scitranslmed.abc7275
WWP2
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
Ting Huang, Xuan Huang, Yumin Nie +2 more · 2020 · BioMed research international · added 2026-04-24
Obesity is directly associated with the risk of cancer in different organs, including breast, colon, and kidney. However, adipocytes could be utilized to control progression for some types of cancer, Show more
Obesity is directly associated with the risk of cancer in different organs, including breast, colon, and kidney. However, adipocytes could be utilized to control progression for some types of cancer, such as leukemia and breast cancer. To explore the potential correlation between adipocytes and cancer, the combined effect of expression levels of obesity-related genes and clinical factors (i.e., gender, race, menopausal status, history of smoking, tumor grade, body mass index (BMI), and history of drinking) on cancer survival rate was systemically studied. The expression levels of obesity-related genes in cancer tissues and normal tissues were downloaded from The Cancer Genome Atlas (TCGA). Kaplan-Meier curves were plotted using R programming language. The log-rank test was applied to explore the correlation between different clinical subgroups. The overexpression of the nine obesity-related genes ( Show less
📄 PDF DOI: 10.1155/2020/8838676
MC4R
Min Tao, Ren-Lei Ji, Lu Huang +4 more · 2020 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Melanocortin-4 receptor (MC4R) plays important roles in regulation of multiple physiological processes, and interaction of MC4R and melanocortin receptor accessory protein 2 (MRAP2) is suggested to pl Show more
Melanocortin-4 receptor (MC4R) plays important roles in regulation of multiple physiological processes, and interaction of MC4R and melanocortin receptor accessory protein 2 (MRAP2) is suggested to play pivotal role in energy balance of vertebrates. Topmouth culter ( Show less
📄 PDF DOI: 10.3389/fendo.2020.00538
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