👤 Yu-Lei Huang

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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, Serina 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-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
Jo-Yu Lin, Tien-Huang Lin, Yuan-Li Huang +9 more · 2026 · Cells · MDPI · added 2026-04-24
Prostate cancer (PCa) is the most general cancer in men and is often linked with distant metastasis in its later stages. The caffeic acid (CA) derivative, N-(4-methoxyphenyl)methylcaffeamide (MPMCA), Show more
Prostate cancer (PCa) is the most general cancer in men and is often linked with distant metastasis in its later stages. The caffeic acid (CA) derivative, N-(4-methoxyphenyl)methylcaffeamide (MPMCA), demonstrates superior liver-protective effects compared to CA. Nevertheless, the functions of MPMCA on prostate cancer metastasis remain unclear. Here, we demonstrate that MPMCA blocks migration and invasion in prostate cancer cells without affecting cell viability. By suppressing the production of mesenchymal markers Vimentin, N-cadherin and β-catenin and upregulating the production of the epithelial marker Zonula Occludens-1 (ZO-1), MPMCA also controls Epithelial-Mesenchymal Transition (EMT). The Phosphoinositide 3-kinase (PI3K), Protein kinase B (AKT) and mechanistic target of rapamycin (mTOR) pathway has been documented to regulate MPMCA-inhibited cell motility. Transfection with Snail and Slug cDNA reverses MPMCA's suppression of EMT, migration, and invasion in prostate cancer cells. Importantly, our in vivo data indicates that MPMCA reduces Snail and Slug expression and prostate cancer metastasis. Our evidence suggests that MPMCA is a novel therapeutic candidate for treating metastatic prostate cancer. Show less
no PDF DOI: 10.3390/cells15050454
SNAI1
Mengqiu Wu, Mengqiu Miao, Yuting Li +12 more · 2026 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Defects in mitochondrial energy metabolism in injured tubular epithelial cells (TECs) are a well-recognized hallmark of kidney injury pathogenesis; however, the key target leading to this defect durin Show more
Defects in mitochondrial energy metabolism in injured tubular epithelial cells (TECs) are a well-recognized hallmark of kidney injury pathogenesis; however, the key target leading to this defect during the acute kidney injury (AKI)-to-chronic kidney disease (CKD) transition remains elusive. Here, we found that during the AKI-to-CKD transition, the increased WW domain containing E3 ubiquitin protein ligase 2 (WWP2) was shuttled to the mitochondria and disabled TEC mitochondrial energy metabolism by ubiquitinating and degrading complex II subunit succinate dehydrogenase complex subunit C (SDHC), leading to oxidative phosphorylation (OXPHOS) disability and aggravated TEC maladaptive repair. Preemptive and late depletion of Wwp2 both ameliorated unilateral ischemia-reperfusion (UIR) injury-induced AKI-to-CKD transition, and tubular-specific Wwp2 depletion resulted in the same protective phenotype. Furthermore, Sdhc knockdown abolished the protective effects of Wwp2 deletion in UIR mice. Conversely, SDHC overexpression attenuated OXPHOS impairment and TEC injury following WWP2 overexpression. Finally, we leveraged high-throughput virtual screening, enzyme activity assays, and binding affinity assays to identify two candidate WWP2 inhibitors. Both inhibitors significantly improved TEC maladaptive repair and deferred the AKI-to-CKD transition. Overall, we identified WWP2 as a critical regulator of mitochondrial OXPHOS integrity in maladaptive repairing TECs and identified two WWP2 inhibitors as potential drug candidates for interrupting the AKI-to-CKD transition. Show less
no PDF DOI: 10.1016/j.ymthe.2025.11.022
WWP2
Chenchen Xia, Xiao Zhang, Wanbing Dai +10 more · 2025 · Frontiers in aging neuroscience · Frontiers · added 2026-04-24
Perioperative neurocognitive disorder (PND) describes a range of cognitive impairments associated with surgery and anaesthesia, often driven by neuroinflammation. This study explored a novel adult mou Show more
Perioperative neurocognitive disorder (PND) describes a range of cognitive impairments associated with surgery and anaesthesia, often driven by neuroinflammation. This study explored a novel adult mouse model, in which preoperative subclinical infection, induced by low-dose lipopolysaccharide (LPS) in combination with surgery, led to cognitive dysfunction in adult mice. Adult male C57BL/6J mice were treated with 0.75 mg/kg LPS two hours before undergoing tibial fracture fixation or appendicectomy. Spontaneous activity and anxiety-like behaviours were tested by open field test. Cognitive outcomes were evaluated using the novel object recognition test and morris water maze. Inflammatory markers and synaptic proteins in the hippocampus were analysed through ELISA, RT-qPCR, and Western blot, while proteomics provided deeper insights into molecular changes. We found that preoperative LPS sensitised the immune system, leading to heightened neuroinflammation and microglial activation after surgery. This was accompanied by memory and learning impairments. Key synaptic proteins, including PSD-95, GAP-43, SYN and mature BDNF, were significantly reduced, indicating disrupted synaptic function. Proteomics revealed changes in pathways related to immune responses, synaptic organisation, and energy metabolism, providing a potential molecular basis for these cognitive deficits. This study provided a practical adult mouse model for PND, demonstrating that low-dose LPS followed by surgery induced an inflammatory response, leading to postoperative impairments in learning and memory. Show less
📄 PDF DOI: 10.3389/fnagi.2025.1691681
BDNF
Yi Xu, Ting-Ting Peng, Shiya Huang +10 more · 2025 · Stem cells international · added 2026-04-24
Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) ameliorate motor deficits in cerebral palsy (CP), but the effect of injection frequency remains unclear. Moreover, most studies have focu Show more
Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) ameliorate motor deficits in cerebral palsy (CP), but the effect of injection frequency remains unclear. Moreover, most studies have focused on mild CP models (unilateral carotid artery occlusion [UCAO] model). This study explored the effect and mechanism of hUC-MSCs in a rat model of moderate-to-severe CP (bilateral carotid artery occlusion [BCAO] model). On postnatal Day 4 (P4), Wistar rat pups underwent BCAO induction. Subsequently, they received either a single intrathecal injection of hUC-MSCs on P21 or repeated injections on P21, P28, P35, and P42. Motor performance was assessed using the rotarod and front-limb suspension tests, while neuronal regeneration and inflammation were evaluated via biomarkers including neuronal nuclear antigen (NeuN), ionized calcium-binding adapter molecule-1 (Iba-1), glial fibrillary acidic protein (GFAP), myelin basic protein (MBP), and brain-derived neurotrophic factor (BDNF). P18 model screening confirmed that the BCAO model resulted in more severe brain damage and motor impairment than the UCAO model. After injection of lentivirally transfected hUC-MSCs, it was found that hUC-MSCs could nest in the damaged area and survive for at least 3 days. Administration of hUC-MSCs following BCAO modeling led to notable improvements in both behavioral performance and histological outcomes. Furthermore, repeated injections offered greater therapeutic benefits compared to single injection. It indicated that the efficacy of repeated injections of hUC-MSCs in the treatment of moderate-to-severe CP was superior to that of single injection. Its mechanism was related to the improvement of damaged myelin structure, reduced immunoinflammatory responses, and increased neurotrophic support. Show less
📄 PDF DOI: 10.1155/sci/4337435
BDNF
Caifeng Gong, Jinglong Huang, Dandan Cao +10 more · 2025 · Therapeutic advances in medical oncology · SAGE Publications · added 2026-04-24
Immune checkpoint inhibitors (ICIs) combined with antiangiogenic agents have become a standard strategy for advanced hepatocellular carcinoma (HCC). There remains an urgent need for effective biomarke Show more
Immune checkpoint inhibitors (ICIs) combined with antiangiogenic agents have become a standard strategy for advanced hepatocellular carcinoma (HCC). There remains an urgent need for effective biomarkers to guide treatment, with C-reactive protein and alpha-fetoprotein in immunotherapy (CRAFITY) scores and cytokine levels representing promising candidates. We aimed to assess the efficacy, safety, and potential biomarkers of anlotinib plus TQB2450 in patients with advanced HCC. This study was a single-arm, phase Ib trial. Twenty-five patients with advanced HCC were enrolled. Patients received an intravenous infusion of TQB2450 (1200 mg, on Day 1) and oral administration of anlotinib (initiated at 10 mg, once a day, from Day 1 to Day 14), which was repeated every 3 weeks. Blood was collected at baseline for serum cytokine analysis. After a median follow-up of 41.80 months, the median progression-free survival (mPFS) was 5.49 months, and the median overall survival (mOS) was 8.94 months. Treatment-related adverse events (TRAEs) occurred in 22 patients, with grade ⩾3 TRAEs observed in 12 patients. Patients who achieved clinical benefit (CB) had higher baseline serum brain-derived neurotrophic factor (BDNF) levels than non-CB patients (median, 227.97 vs 129.26 pg/ml, Anlotinib plus TQB2450 demonstrated promising efficacy with manageable safety in advanced HCC. Elevated serum BDNF levels might serve as a potential positive prognostic marker and, together with ECOG score, may help complement the CRAFITY score in identifying subgroups that could benefit from ICIs and antiangiogenic therapy. Show less
📄 PDF DOI: 10.1177/17588359251407052
BDNF
Mengnan Huang, Yuanyuan He, Tong Yang +6 more · 2025 · Chinese herbal medicines · Elsevier · added 2026-04-24
Jiaotaiwan (JTW) is a classic traditional Chinese medicine (TCM) prescription for treating depression, but its potential mechanisms are not fully understood. The aim of this study is to detect the lev Show more
Jiaotaiwan (JTW) is a classic traditional Chinese medicine (TCM) prescription for treating depression, but its potential mechanisms are not fully understood. The aim of this study is to detect the levels of serum Short-chain fatty acids (SCFAs) and cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA)-cAMP-response element binding protein (CREB)-brain derived neurotrophic factor (BDNF) signaling pathway, further revealing the scientific connotation of the antidepressant effect of JTW. In this multicenter, randomized, controlled study, 120 patients with depression were divided into the JTW (16.5 g/d) group, JTW (16.5 g/d) + selective serotonin reuptake inhibitors (SSRIs) group, and SSRIs group. Hamilton depression Scale-24 (HAMD-24) and Self-rating depression scale (SDS) were used for efficacy evaluation. Enzyme linked immunosorbent assay (ELISA) and reverse transcription-polymerase chain reaction (RT-PCR) were used to evaluate the expression levels of cAMP-PKA-CREB-BDNF signaling pathway. Serum SCFAs concentrations were analyzed using liquid chromatograph-mass spectrometer (LC-MS) targeted metabolomics. After eight weeks of treatment, HAMD score and SDS score were significantly decreased in the three groups, and HAMD score in JTW + SSRIs group was significantly lower than that in SSRIs group. After treatment, the expression levels of cAMP-PKA-CREB-BDNF signaling pathway were significantly increased in the three group, with the JTW + SSRIs group showing more significant increase. After treatment, the levels of isobutyric, butyric, isovaleric, and valeric acids in the JTW + SSRIs groups were significantly higher than that before treatment, and the levels of isobutyric, and isovaleric acids in the JTW + SSRIs group was significantly higher than that in the JTW group and SSRIs groups. JTW can alleviate symptoms in patients with depression, and its antidepressant mechanism may be related to regulating serum SCFAs and cAMP-PKA-CREB-BDNF signaling pathway. Show less
📄 PDF DOI: 10.1016/j.chmed.2025.03.002
BDNF
Shuang Wang, Yun Liu, Zhiming Yan +8 more · 2025 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
Triple activation of the glucagon-like peptide 1 receptor (GLP-1R), the GIP receptor (GIPR), and the glucagon receptor (GCGR) is an innovative strategy for treating obesity and diabetes. We report the Show more
Triple activation of the glucagon-like peptide 1 receptor (GLP-1R), the GIP receptor (GIPR), and the glucagon receptor (GCGR) is an innovative strategy for treating obesity and diabetes. We report the rational design of triple GLP-1R/GCGR/GIPR agonists, featuring potent GLP-1R and GCGR activity with weaker GIPR activation. Using sequence analysis, molecular dynamics simulations, docking, and amino acid optimization, we developed xGLP-1-based triagonists, with xGLP/GCG/GIP-32 exhibiting a unique activation profile. It shows superior weight loss effects compared to tirzepatide and similar metabolic efficacy to retatrutide, despite significantly less potent GIPR activity. Preliminary mechanistic studies revealed that xGLP/GCG/GIP-32 exhibits biased agonism toward the GIPR and GCGR. These activity data suggest it may not be imperative to focus solely on potent activation of all three receptors. Especially for triple agonists with receptor-biased agonism, there may be room to explore optimal receptor activation ratios. Show less
no PDF DOI: 10.1021/acs.jmedchem.5c02032
GIPR
Zichong Huang, Limin Du, Xulei Fu +3 more · 2025 · Journal of molecular graphics & modelling · Elsevier · added 2026-04-24
G protein-coupled receptors (GPCRs) are transmembrane receptors that regulate intracellular signaling by interacting with G proteins and other effectors, influencing various physiological processes. T Show more
G protein-coupled receptors (GPCRs) are transmembrane receptors that regulate intracellular signaling by interacting with G proteins and other effectors, influencing various physiological processes. The Glucose-dependent Insulinotropic Polypeptide Receptor (GIPR), a class B1 GPCR family member activated by GIP, regulates postprandial glycaemia by augmenting glucose-dependent insulin secretion, delaying gastric emptying, and suppressing appetite. Recent studies highlight the transmembrane domain (TMD) as the primary interface for dimerization, allowing GPCR to form homodimers or heterodimers with distinct physiological roles. However, the transient nature of these dimers challenges structural analysis, hindering experimental exploration and drug development. Computational methods now offer powerful tools for predicting such interactions. This study employs a hybrid approach, combining multiple protein docking software and dynamic structural optimization, to generate potential homodimeric models of GIPR-TMD. In addition, Next, validated models will provide insights into dimer activation mechanisms and support novel therapeutic discoveries. Show less
no PDF DOI: 10.1016/j.jmgm.2025.109150
GIPR
Yuxin Fan, Jiandong Yuan, Lichun Dong +12 more · 2025 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24
Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims Show more
Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims to investigate its safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) in Chinese healthy volunteers. A randomized, double-blind, placebo-controlled and dose-escalation Phase I study was conducted as follows: a single dose (2.5 mg) and once-weekly administration for 2 weeks to reach target doses (5, 10 and 15 mg) by titration. A total of 40 volunteers received at least one dose of BGM0504 or placebo. The PK profile of BGM0504 was investigated over a wide dose range and supported once-weekly administration. It was observed that C BGM0504 was generally safe and well tolerated with favourable PK profile and potential role in weight loss was also confirmed. These findings support subsequent development of BGM0504 for type 2 diabetes mellitus (T2DM) and obesity. Show less
no PDF DOI: 10.1111/dom.16203
GIPR
Yanping Wang, Xiaoru Ma, Zhixin Qiao +16 more · 2025 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
Astrocytes are key regulators of neuroinflammation in multiple sclerosis (MS). Electroacupuncture (EA), a safe and cost-effective adjuvant therapy, has shown benefits in neurodegenerative diseases, bu Show more
Astrocytes are key regulators of neuroinflammation in multiple sclerosis (MS). Electroacupuncture (EA), a safe and cost-effective adjuvant therapy, has shown benefits in neurodegenerative diseases, but its astrocyte-related mechanisms remain unclear. Here, we demonstrated that EA at ST36 alleviated blood-brain barrier (BBB) disruption and neuroinflammation during the peak period of experimental autoimmune encephalomyelitis (EAE). Additionally, EA at ST36 upregulated the expression of α-melanocyte-stimulating hormone (α-MSH) and its receptor melanocortin-4 receptor (MC4R) in spinal astrocytes. Pharmacological studies showed that MC4R agonist RO27-3225 mimicked the therapeutic effects of EA, whereas MC4R antagonist TCMCB07 weakened EA-mediated BBB protection and neuroinflammation suppression. Moreover, astrocyte-specific silencing of MC4R via adeno-associated virus (AAV) weakened EA-mediated BBB protection and neuroinflammation suppression. RNA-sequencing (RNA-seq) and western blot (WB) revealed that EA exerts neuroprotective effects by activating MC4R to inhibit MAPK and NF-κB signaling pathways. Moreover, in MC4R-overexpressing astrocytes, α-MSH and RO27-3225 reduced inflammation responses, while TCMCB07 reversed the effects by MAPK/NF-κB signaling pathways. Collectively, our findings identify astrocytic MC4R as a critical mediator of EA-driven neuroprotection by suppressing MAPK/NF-κB signaling, providing mechanistic insight and a promising therapeutic target for EAE and other neuroinflammatory disorders. Show less
📄 PDF DOI: 10.1186/s12974-025-03667-1
MC4R
Mainak Bardhan, Ayush Anand, Amaan Javed +10 more · 2025 · Diseases (Basel, Switzerland) · MDPI · added 2026-04-24
Melanocortin receptors (MCRs) are responsible for various functions ranging from skin pigmentation, regulation of appetite, stress response and cognition, steroid synthesis, and energy balance to cell Show more
Melanocortin receptors (MCRs) are responsible for various functions ranging from skin pigmentation, regulation of appetite, stress response and cognition, steroid synthesis, and energy balance to cellular regeneration and immunomodulation. The genetic polymorphism with tissue distribution ranging from the brain, limbic system, and adrenal cortex to neutrophils, monocytes, and macrophages is evident in MCRs. The mutations in MC1R, MC2R, MC3R, and MC4R genes are associated with risk of melanoma, familial glucocorticoid deficiency, obesity, and type 2 diabetes mellitus, respectively. Meanwhile, MC1R, MC2R, and MC5R genes are involved in the risk of major depressive disorder. Melanocortin receptors are involved in different inflammatory disorders, i.e., atopic dermatitis, autoimmune uveitis, sarcoidosis, respiratory diseases, multiple sclerosis, scleroderma, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer's disease, arthritis, and reperfusion injury. Several newer therapeutic agents related to MCRs have numerous advantages over the current anti-inflammatory drugs, demonstrating therapeutic relevance. Among them, α-MSH analogs play a role in atopic dermatitis and scleroderma, and MC1R agonist Dersimelagon has shown effectiveness in systemic sclerosis. The FDA has recently approved the repository corticotropin injection (RCI) to treat sarcoidosis. The FDA has also approved various melanocortin agonists, i.e., Bremelanotide, Afamelanotide, and Setmelanotide, for the treatment of hypoactive sexual desire disorder, Erythropoietic protoporphyria, and obesity, due to pro-opiomelanocortin and leptin receptor deficiency, respectively. Therefore, this review aims to summarize the function and genetic polymorphism of melanocortin receptors, regulatory pathways involving MCRs, and the existing evidence of the prime effect of MCRs on inflammatory responses via different mechanisms and their potential therapeutic use in inflammatory diseases. Show less
📄 PDF DOI: 10.3390/diseases13090305
MC4R
Junfang Jiang, Xiaowei Zhang, Pei Xiong +5 more · 2025 · Scientific reports · Nature · added 2026-04-24
This study established a polymerase chain reaction-lateral flow dipstick (PCR-LFD) method for the visual detection of SNP genotypes. Targeting the MC4R gene SNP g.732 C > G, highly specific primers we Show more
This study established a polymerase chain reaction-lateral flow dipstick (PCR-LFD) method for the visual detection of SNP genotypes. Targeting the MC4R gene SNP g.732 C > G, highly specific primers were designed for the mutation site, incorporating a Locked Nucleic Acid (LNA) modification at the 3' terminal nucleotide of the SNP, a BIOTIN modification at the 5' end of the upstream primer, and a fluorescein isothiocyanate (FITC) modification at the 5' end of the downstream primer. The detection primers were used for PCR amplification with the sample, and the reaction system was optimized. The amplification products were subsequently detected using LFD. The results demonstrated that the optimized reaction system and modified primers effectively distinguished among CC, CG, and GG genotypes at the g.732 C > G. Blood samples from 24 Hu sheep were analyzed using the PCR-LFD assay specific to this SNP. The genotyping results from PCR-LFD were completely consistent with those obtained from the mutation analysis of the same blood samples. The PCR-LFD method established in this study did not require genomic DNA extraction; whole blood could be directly used as a template for PCR amplification combined with LFD, enabling on-site visual detection. This positions PCR-LFD as a rapid, simple, and visually interpretable tool for on-site SNP genotyping. Show less
📄 PDF DOI: 10.1038/s41598-025-16207-x
MC4R
Cheng-Li Liu, Tao Ren, Peng-Cheng Ruan +5 more · 2025 · Veterinary sciences · MDPI · added 2026-04-24
Growth traits are among the most important economic phenotypes targeted in the genetic improvement of beef cattle. To understand the genetic basis of growth traits in Huaxi cattle, we performed a geno Show more
Growth traits are among the most important economic phenotypes targeted in the genetic improvement of beef cattle. To understand the genetic basis of growth traits in Huaxi cattle, we performed a genome-wide association study (GWAS) on body weight, eye muscle area, and back fat thickness across five developmental stages in a population of 202 Huaxi cattle. Additionally, publicly available RNA-seq data from the longissimus dorsi muscle of both young and adult cattle were analyzed to identify key genes and genetic markers associated with growth in Huaxi cattle. In total, 7.19 million high-quality variant loci (SNPs and INDELs) were identified across all samples. In the GWAS, the three multilocus models (FarmCPU, MLMM, and BLINK) outperformed the conventional single-locus models (CMLM, GLM, and MLM). Consequently, GWAS analysis was conducted using multilocus models, which identified 99 variant loci significantly associated with growth traits and annotated a total of 83 candidate genes (CDGs). Additionally, 23 of the 83 CDGs overlapped with significantly differentially expressed genes identified from public RNA-seq datasets of longissimus dorsi muscle between young and adult cattle. Furthermore, gene functional enrichment (KEGG and GO) analyses revealed that over 30% of the pathways and GO terms were associated with muscle development and fat deposition, crucial factors for beef production. Specifically, key genes identified included Show less
📄 PDF DOI: 10.3390/vetsci12020109
AKAP6
Panlong Li, Xirui Zhu, Chun Huang +6 more · 2025 · IBRO neuroscience reports · Elsevier · added 2026-04-24
To investigate the impact of obesity on brain structure and cognition using large neuroimaging and genetic data. Associations between body mass index (BMI), gray matter volume (GMV), whiter matter hyp Show more
To investigate the impact of obesity on brain structure and cognition using large neuroimaging and genetic data. Associations between body mass index (BMI), gray matter volume (GMV), whiter matter hyper-intensities (WMH), and fluid intelligence score (FIS) were estimated in 30283 participants from the UK Biobank. Longitudinal data analysis was conducted. Genome-wide association studies were applied to explore the genetic loci associations among BMI, GMV, WMH, and FIS. Mendelian Randomization analyses were applied to further estimate the effects of obesity on changes in the brain and cognition. The observational analysis revealed that BMI was negatively associated with GMV (r = -0.15, p < 1 The phenotypic and genetic association between obesity and aging brain and cognitive decline suggested that weight control could be a promising strategy for slowing the aging brain. Show less
📄 PDF DOI: 10.1016/j.ibneur.2025.01.001
AKAP6
Wenyin Luo, Shaojun Huang, Guanglve Li +7 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ani15243541
ANGPTL4
Jian Huang · 2025 · Circulation · added 2026-04-24
no PDF DOI: 10.1161/CIRCULATIONAHA.125.074087
ANGPTL4
Dongxu Zhu, Xinrui Zhu, Yingze Zhang +1 more · 2025 · Stem cell research & therapy · BioMed Central · added 2026-04-24
The intact tendon-bone interface (TBI) consists of four histological layers-tendon, fibrocartilage, calcified fibrocartilage, and bone-that gradually merge into each other, making complete structural Show more
The intact tendon-bone interface (TBI) consists of four histological layers-tendon, fibrocartilage, calcified fibrocartilage, and bone-that gradually merge into each other, making complete structural restoration after injury challenging. Osteoporosis poses a significant risk for rotator cuff tears (RCTs) and re-tears after arthroscopic rotator cuff repair (ARCR). Activating Leptin receptor (Lepr) mediated Stat3 signaling transduction facilitates the transcription of Runx2 and Sox9, respectively, and promotes osteogenesis and chondrogenesis. Sixty-five female Sprague Dawley rats were used. Animal models-ovariectomy (OVX) and rotator cuff tear and repair (RC)-were employed to simulate typical tendon-bone healing and TBI reconstruction under deficient bone-forming capability. And, grip strength, transcriptome, ELISA, histochemistry, and qPCR were performed to reveal the distinct functional recovery between RC and OVX + RC rats, as well as pathophysiologic exhibition in the TBI at 2-week and 8-week. RC rats exhibited better functional recovery during the proliferative phase of TBI reconstruction, i.e., 2-week, compared to OVX + RC rats, while both RC and OVX + RC rats showed a lower grip strength in the upper limbs during the remodeling phase, i.e., 8-week. In RCTs, where adipogenesis was suppressed in RCT healing, the osteoblast-derived Leptin (Lep) and Angiopoietin like 4 (Angptl4), the Lepr ligands, facilitate osteogenesis and chondrogenesis, resulting in an obvious mineralized band in the reconstructed TBI and a transit cartilage band during the proliferative phase in RC rats. In osteoporosis-comorbid RCTs, where osteogenesis was suppressed while adipogenesis was activated, the adipocyte-derived Lep and Angptl4, particularly Angptl4, facilitated Stat3 phosphorylation and nucleus transfer, Sox9 transcription, and chondrogenesis, which was observed in OVX + RC rats and led to excessive cartilage regeneration. This study demonstrated the role of Lep and Angptl4 in TBI reconstruction, via activating Lepr-mediated Stat3-Sox9 and Stat3-Runx2 signaling pathways, differentially regulating osteogenesis and chondrogenesis, and leading to the distinct clinical outcomes post-ARCR in RCTs and osteoporosis-comorbid RCTs. This study provides fundamental support for increasing Angptl4 in situ for chronogenesis in RCTs and lowering Angptl4 to Lep ratio for osteogenesis in RCTs with osteoporosis comorbidity. Show less
📄 PDF DOI: 10.1186/s13287-025-04586-x
ANGPTL4
Ruihao Zhang, Qi Sun, Lixia Huang +1 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Cholesterol stress profoundly modulates cellular processes, but its underlying mechanisms remain incompletely understood. To investigate cholesterol-responsive networks, we performed integrated transc Show more
Cholesterol stress profoundly modulates cellular processes, but its underlying mechanisms remain incompletely understood. To investigate cholesterol-responsive networks, we performed integrated transcriptome (RNA-seq) and metabolome (LC-MS) analyses on HeLa cells treated with cholesterol for 6 and 24 h. Through transcriptomic analysis of cholesterol-stressed HeLa cells, we identified stage-specific responses characterized by early-phase stress responses and late-phase immune-metabolic coordination. This revealed 1340 upregulated and 976 downregulated genes after a 6 h cholesterol treatment, including induction and suppression of genes involved in cholesterol efflux and sterol biosynthesis, respectively, transitioning to Nuclear Factor kappa-B (NF-κB) activation and Peroxisome Proliferator-Activated Receptor (PPAR) pathway modulation by 24 h. Co-expression network analysis prioritized functional modules intersecting with differentially expressed genes. We also performed untargeted metabolomics using cells treated with cholesterol for 6 h, which demonstrated extensive remodeling of lipid species. Interestingly, integrated transcriptomic and metabolic analysis uncovered GFPT1-driven Uridine Diphosphate-N-Acetylglucosamine (UDP-GlcNAc) accumulation and increased taurine levels. Validation experiments confirmed Show less
📄 PDF DOI: 10.3390/ijms26157108
ANGPTL4
Xiangwu Zhang, Rongxian Zhou, Guangqiang Zhao +5 more · 2025 · Discover oncology · Springer · added 2026-04-24
This study aims to establish a hypoxia-immune-related gene signature within the tumor microenvironment (TME) to reliably predict prognosis in non-small cell lung cancer (NSCLC). Transcriptomic profile Show more
This study aims to establish a hypoxia-immune-related gene signature within the tumor microenvironment (TME) to reliably predict prognosis in non-small cell lung cancer (NSCLC). Transcriptomic profiles and clinical data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases (GSE74777, GSE68465). Hypoxia- and immune-related genes were curated from MSigDB, ImmPort, and INATDB. Prognostic genes were identified via Cox and LASSO regression analyses, and a risk model was constructed. Model validity was assessed through Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, and external validation. An eight-gene prognostic signature (AKAP12, MT2A, SERPINE1, CD1E, CD79A, CXCL13, XCL2, ANGPTL4) was established. The model demonstrated significant predictive accuracy for NSCLC survival (AUC: 0.643/0.649/0.620 at 1/3/5 years in TCGA cohort). Patients with high immune activity exhibited superior survival outcomes compared to those with low-immune counterparts (log-rank P < 0.001). Multivariate Cox regression confirmed the risk score as an independent prognostic factor (HR = 1.82, 95% CI: 1.44-2.30, P < 0.001). The hypoxia-immune microenvironment signature serves as a robust prognostic classifier for NSCLC, providing a quantitative framework for personalized risk stratification and clinical decision support. Show less
📄 PDF DOI: 10.1007/s12672-025-03319-z
ANGPTL4
Deyu Zuo, Yuce Peng, Guozhi Zhao +8 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Hypoglycemia is a commonly neglected complication in elderly diabetic patients, which can lead to cardiovascular events. Endothelial cell dysfunction is the primary inducer of cardiovascular events, a Show more
Hypoglycemia is a commonly neglected complication in elderly diabetic patients, which can lead to cardiovascular events. Endothelial cell dysfunction is the primary inducer of cardiovascular events, and it is associated with hypoglycemia-triggered cytokine release and inflammatory programmed cell death. A comprehensive understanding of lineage-specific variations in pathological vascular changes is essential to mitigate cardiovascular events and ensure therapeutic efficacy. Herein, unbiased clustering analyses and single-nucleus RNA sequencing are performed on cells of the thoracic aorta in db/db and insulin-induced hypoglycemic db/db mice. Comparative analyses show changes in lineage-specific genes, subpopulation composition, intercellular communication, and molecular biology in hypoglycemic diabetic mice. The analyses also revealed the changes of different cells, particularly endothelial cell PANoptosis, macrophage inflammatory polarization, and vascular smooth muscle cell (VSMC) fibrosis. Pseudo-time sequencing, differential expression, and regulation network analyses revealed the association of potential hub genes Klf2, ETS2, Elavl1, C3, and Nr4a1 with the mentioned pathological processes. It is demonstrated that hypoglycemia induces VSMC fibrosis in vivo, whereas Angptl4 knockdown can attenuate VSMC fibrosis in vitro. These findings demonstrate the hypoglycemic macroangiopathy mechanism and provide important references for future disease intervention and treatment. Show less
📄 PDF DOI: 10.1002/advs.202414530
ANGPTL4
Dou Yin, Nana Fang, Yaling Zhu +8 more · 2025 · Journal of experimental & clinical cancer research : CR · BioMed Central · added 2026-04-24
The adipocyte-rich tumor microenvironment (TME) is recognized as a key factor in promoting cancer progression. A distinct characteristic of peritumoral adipocytes is their reduced lipid content and th Show more
The adipocyte-rich tumor microenvironment (TME) is recognized as a key factor in promoting cancer progression. A distinct characteristic of peritumoral adipocytes is their reduced lipid content and the acquisition of a proinflammatory phenotype. However, the underlying mechanisms by which adipocytes rewire metabolism and boost tumor progression in triple-negative breast cancer (TNBC) remain poorly understood. We utilized transcriptomic analysis, bioinformatic analysis, metabolic flux analysis, protein-protein docking, gene and protein expression profiling, in vivo metastasis analysis and breast cancer specimens to explore how adipocytes reprogram tumor metabolism and progression in TNBC. Our findings reveal that Angiopoietin-like 4 (ANGPTL4) exhibits significantly higher expression levels in adipocyte-rich tumor circumstance compared to the symbiotic environment lacking of adipocyte. Furthermore, ANGPTL4 expression in tumor cells is essential for adipocyte-driven glycolysis and metastasis. Interleukin 6 (IL-6), enriched in cancer-associated adipocytes, and lipolysis-derived free fatty acids (FFAs) released from adipocytes, amplify ANGPTL4-mediated glycolysis and metastasis through activation of STAT3 and PPARα pathways in TNBC cells. Additionally, ANGPTL4 interacts with transcription factor KLF4 and enhances KLF4 activity, which further drives glycolysis and metastasis, whereas KLF4 knockdown attenuates migration and glycolysis in TNBC cells. Importantly, Elevated ANGPTL4 and KLF4 expression was observed in metastatic breast cancer specimens compared to non-metastatic cases and was positively correlated with poor prognosis. Collectively, our results uncover a complex metabolic interaction between adipocytes and TNBC cells that promotes tumor aggressiveness. ANGPTL4 emerges as a key mediator in this process, making it a promising therapeutic target to inhibit TNBC progression. Show less
📄 PDF DOI: 10.1186/s13046-025-03458-9
ANGPTL4
Yang Zhang, Xuyang Yang, Su Zhang +10 more · 2025 · JCI insight · added 2026-04-24
The prognosis for colorectal cancer (CRC) patients with liver metastasis remains poor, and the molecular mechanisms driving CRC liver metastasis are not fully understood. Tumor-derived hypoxia-induced Show more
The prognosis for colorectal cancer (CRC) patients with liver metastasis remains poor, and the molecular mechanisms driving CRC liver metastasis are not fully understood. Tumor-derived hypoxia-induced extracellular vesicles have emerged as key players in inducing angiogenesis by transferring noncoding RNAs. However, the specific role of CRC-derived hypoxic extracellular vesicles (H-EVs) in regulating premetastatic microenvironment (PMN) formation by inducing angiogenesis remains unclear. Our study demonstrates that H-EVs induce angiogenesis and liver metastasis. Through microRNA microarray analysis, we identified a reduction in miR-6084 levels within H-EVs. We found that miR-6084 inhibited angiogenesis by being transferred to endothelial cells via EVs. In endothelial cells, miR-6084 directly targeted angiopoietin like 4 (ANGPTL4) mRNA, thereby suppressing angiogenesis through the ANGPTL4-mediated JAK2/STAT3 pathway. Furthermore, we uncovered that specificity protein 1 (SP1) acted as a transcription factor regulating miR-6084 transcription, while hypoxia-inducible factor 1A (HIF1A) decreased miR-6084 expression by promoting SP1 protein dephosphorylation and facilitating ubiquitin-proteasome degradation in SW620 cells. In clinical samples, we observed low expression of miR-6084 in plasma-derived EVs from CRC patients with liver metastasis. In summary, our findings suggest that CRC-derived H-EVs promote angiogenesis and liver metastasis through the HIF1A/SP1/miR-6084/ANGPTL4 axis. Additionally, miR-6084 holds promise as a diagnostic and prognostic biomarker for CRC liver metastasis. Show less
📄 PDF DOI: 10.1172/jci.insight.189503
ANGPTL4
Jun Chen, Xinyan Yang, Manman Cui +7 more · 2025 · Biochimica et biophysica acta. Molecular basis of disease · Elsevier · added 2026-04-24
Male germline development is crucial for the proper establishment of spermatogonial stem cell pool and life-long production of spermatozoa, but the full-term developmental profiling of human male germ Show more
Male germline development is crucial for the proper establishment of spermatogonial stem cell pool and life-long production of spermatozoa, but the full-term developmental profiling of human male germline is not fully understood. Here, by integrating 92,488 human testicular cells spanning from six-week-old embryos to old men, we constructed a comprehensive human male germ cell atlas. Further analysis found that the precursor of undifferentiated spermatogonia underwent regulatory network reconfiguration starting from week 7 post-fertilization, accompanied by WNT6-FZD3/LRP6-JUN/MYC signaling axis. And JUN and MYC were revealed to be candidate core transcription factors that might inhibit spermatogonia differentiation. In addition, the activation of ANGPTL signaling played a role in the maintenance of human spermatogonial stem cells. Finally, by interrogating the scRNA-seq datasets from idiopathic non-obstructive azoospermia (iNOA) patients, we identified several iNOA-dysregulated genes such as CAPN3, FTMT, IZUMO2 and LACE1, which were significantly down-regulated in round spermatids of iNOA patients. Collectively, our work established an atlas of human male germ cell development, revealing the factors that might regulate male germline development and providing iNOA-dysregulated genes for future clinical diagnosis. Show less
no PDF DOI: 10.1016/j.bbadis.2025.167918
ANGPTL4
Hongwei Wang, Yu-Nan Zhu, Sifan Zhang +5 more · 2025 · Molecular medicine (Cambridge, Mass.) · BioMed Central · added 2026-04-24
The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biologi Show more
The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biological functions remain elusive. Transcriptome and genome data of breast cancer patients from TCGA database was downloaded. Patients were classified into different clusters by using non-negative matrix factorization (NMF) based on signatures of ECM components and regulators. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify core genes related to ECM clusters. Additional 10 independent public cohorts including Metabric, SCAN_B, GSE12276, GSE16446, GSE19615, GSE20685, GSE21653, GSE58644, GSE58812, and GSE88770 were collected to construct Training or Testing cohort, following machine learning calculating ECM correlated index (ECI) for survival analysis. Pathway enrichment and correlation analysis were used to explore the relationship among ECM clusters, ECI and TME. Single-cell transcriptome data from GSE161529 was processed for uncovering the differences among ECM clusters. Using NMF, we identified three ECM clusters in the TCGA database: C1 (Neuron), C2 (ECM), and C3 (Immune). Subsequently, WGCNA was employed to pinpoint cluster-specific genes and develop a prognostic model. This model demonstrated robust predictive power for breast cancer patient survival in both the Training cohort (n = 5,392, AUC = 0.861) and the Testing cohort (n = 1,344, AUC = 0.711). Upon analyzing the tumor microenvironment (TME), we discovered that fibroblasts and B cell lineage were the core cell types associated with the ECM cluster phenotypes. Single-cell RNA sequencing data further revealed that angiopoietin like 4 (ANGPTL4) We identified distinct ECM clusters in breast cancer patients, irrespective of molecular subtypes. Additionally, we constructed an effective prognostic model based on these ECM clusters and recognized ANGPTL4 Show less
📄 PDF DOI: 10.1186/s10020-025-01237-y
ANGPTL4
Xingyu Liu, Rong Qiu, Pengcheng Gui +7 more · 2025 · iScience · Elsevier · added 2026-04-24
Dormant lung adenocarcinoma (LUAD) cells in the bone microenvironment can re-emerge as metastatic disease through osteoclast interactions. Using a 3D dormancy model and a mouse bone metastasis model, Show more
Dormant lung adenocarcinoma (LUAD) cells in the bone microenvironment can re-emerge as metastatic disease through osteoclast interactions. Using a 3D dormancy model and a mouse bone metastasis model, this study reveals that arachidonic acid (AA) is the initiating molecule transferred from osteoclasts to dormant LUAD cells, triggering their activation. Dormant LUAD cells uptake AA through CD36, which activates the PPARγ-ANGPTL4 pathway and activates tumor cells. There is a dose-response relationship in the activation effect of AA, and inhibiting AA metabolism prevents this reactivation. The study also finds that the serum levels of AA and ANGPTL4 are significantly elevated in patients with clinical bone metastases compared to those without. This research confirms that osteoclasts transmit AA via the CD36-PPARγ-ANGPTL4 axis to activate dormant LUAD cells, suggesting that AA and ANGPTL4 may serve as valuable biomarkers and potential clinical applications in treatment and prediction of LUAD bone metastasis. Show less
📄 PDF DOI: 10.1016/j.isci.2025.112167
ANGPTL4
Shiyuan Liu, Mingyao Meng, Chunkai Huang +16 more · 2025 · Journal of diabetes research · added 2026-04-24
In this study, we investigated the therapeutic effects and mechanisms of umbilical cord mesenchymal stem cells (UCMSCs) in diabetic nephropathy (DN) ZDF (FA/FA) rats. The therapeutic effects were asse Show more
In this study, we investigated the therapeutic effects and mechanisms of umbilical cord mesenchymal stem cells (UCMSCs) in diabetic nephropathy (DN) ZDF (FA/FA) rats. The therapeutic effects were assessed by renal function tests, the urinary albumin-creatinine ratio, PAS staining, electron microscopy, and TGF- Show less
📄 PDF DOI: 10.1155/jdr/6683126
ANGPTL4
Quanzhong Liu, Miao Yu, Zihan Lin +9 more · 2025 · Cancer letters · Elsevier · added 2026-04-24
Gastric cancer (GC) is an aggressive and heterogeneous disease with poor survival outcomes. The progression of GC involves complex, multi-step processes. Endothelial cells (ECs) play a crucial role in Show more
Gastric cancer (GC) is an aggressive and heterogeneous disease with poor survival outcomes. The progression of GC involves complex, multi-step processes. Endothelial cells (ECs) play a crucial role in tumor angiogenesis, proliferation, invasion, and metastasis, particularly through the process of endothelial-to-mesenchymal transition (EndoMT). However, the specific role and mechanisms of EndoMT in gastric cancer remain unclear. Based on 6 GC single-cell RNA-sequencing (scRNA-seq) cohorts (samples = 97), we established an EndoMT-related gene signature, termed EdMTS. Leveraging this gene signature, ssGSEA was applied to calculate sample scores across multiple bulk RNA-seq datasets, which include information on immunotherapy, metastasis, GC progression, and survival. Moreover, we applied the Monocle2 method to calculate cell pseudotime and used CellChat to analyze interactions between malignant and EC cells. We verified the molecular mechanism by multiple immunofluorescence and cell function experiments. Findings In this study, we established a single-cell atlas of ECs in GC and identified a subpopulation of COL1A1 Show less
no PDF DOI: 10.1016/j.canlet.2025.217731
ANGPTL4
Jia Chen, Ying Yang, Shu Su +5 more · 2025 · International ophthalmology · Springer · added 2026-04-24
no PDF DOI: 10.1007/s10792-025-03522-5
ANGPTL4
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Yiliang Zhang, Shengyang Zhou, Runming Zhao +4 more · 2025 · Journal of lipid research · Elsevier · added 2026-04-24
Triglyceride-rich lipoproteins carry lipids in the bloodstream, where the fatty acid moieties are liberated by lipoprotein lipase (LPL) and taken up by peripheral tissues such as brown adipose tissue Show more
Triglyceride-rich lipoproteins carry lipids in the bloodstream, where the fatty acid moieties are liberated by lipoprotein lipase (LPL) and taken up by peripheral tissues such as brown adipose tissue (BAT) and white adipose tissue (WAT), whereas the remaining cholesterol-rich remnant particles are cleared mainly by the liver. Elevated triglyceride (TG) levels and prolonged circulation of cholesterol-rich remnants are risk factors for cardiovascular diseases. Acute cold exposure decreases postprandial TG levels and is a potential therapeutic approach to treat hypertriglyceridemia. However, how acute cold exposure regulates TG metabolism remains incompletely understood. In the current study, we found that acute cold exposure simultaneously increases postprandial very-low-density lipoprotein production and TG clearance, with the latter playing a dominant role and resulting in decreased TG levels. Acute cold exposure increases LPL activity and TG uptake in BAT, while suppressing LPL activity and TG uptake in WAT. Mechanistically, acute cold exposure increases BAT LPL activity through transcriptional upregulation of Lpl and posttranscriptional regulation via inhibiting the hepatic insulin-ANGPTL8-ANGPTL3 axis, while suppressing WAT LPL activity through upregulation of ANGPTL4. Angptl8 knockout mice have dramatically decreased levels of circulating TG. In the absence of ANGPTL8, acute cold exposure increases rather than decreases circulating TG levels. Thus, our study reveals multilayered regulation of acute cold response and postprandial TG metabolism, highlighting the key functions of ANGPTL3, 4, and 8 in response to acute cold exposure. Show less
📄 PDF DOI: 10.1016/j.jlr.2025.100751
ANGPTL4