👤 Yongxing Yang

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Also published as: A Yang, A-Li Yang, Acong Yang, Ai-Lun Yang, Aige Yang, Airong Yang, Aiting Yang, Aizhen Yang, Albert C Yang, Alex J T Yang, An-Qi Yang, Andrew Yang, Angang Yang, Angela Wei Hong Yang, Anni Yang, Aram Yang, B Yang, Baigao Yang, Baixia Yang, Bangjia Yang, Bao Yang, Baofeng Yang, Baoli Yang, Baoxin Yang, Baoxue Yang, Bei Yang, Beibei Yang, Biao Yang, Bin Q Yang, Bin Yang, Bing Xiang Yang, Bing Yang, Bingyu Yang, Bo Yang, Bohui Yang, Boo-Keun Yang, Bowen Yang, Boya Yang, Burton B Yang, Byoung Chul Yang, Caimei Yang, Caixia Yang, Caixian Yang, Caixin Yang, Can Yang, Canchai Yang, Ce Yang, Celi Yang, Chan Mo Yang, Chan-Mo Yang, Chang Yang, Chang-Hao Yang, Changheng Yang, Changqing Yang, Changsheng Yang, Changwei Yang, Changyun Yang, Chanjuan Yang, Chao Yang, Chao-Yuh Yang, Chaobo Yang, Chaofei Yang, Chaogang Yang, Chaojie Yang, Chaolong Yang, Chaoping Yang, Chaoqin Yang, Chaoqun Yang, Chaowu Yang, Chaoyun Yang, Chaozhe Yang, Chen Die Yang, Chen Yang, Cheng Yang, Cheng-Gang Yang, Chengfang Yang, Chenghao Yang, Chengkai Yang, Chengkun Yang, Chengran Yang, Chenguang Yang, Chengyingjie Yang, Chengzhang Yang, Chensi Yang, Chensu Yang, Chenxi Yang, Chenyu Yang, Chenzi Yang, Chi Yang, Chia-Wei Yang, Chieh-Hsin Yang, Chien-Wen Yang, Chih-Hao Yang, Chih-Min Yang, Chih-Yu Yang, Chihyu Yang, Ching-Fen Yang, Ching-Wen Yang, Chongmeng Yang, Chuan He Yang, Chuan Yang, Chuanbin Yang, Chuang Yang, Chuanli Yang, Chuhu Yang, Chun Yang, Chun-Chun Yang, Chun-Mao Yang, Chun-Seok Yang, Chunbaixue Yang, Chung-Hsiang Yang, Chung-Shi Yang, Chung-Yi Yang, Chunhua Yang, Chunhui Yang, Chunjie Yang, Chunjun Yang, Chunlei Yang, Chunli Yang, Chunmao Yang, Chunping Yang, Chunqing Yang, Chunru Yang, Chunxiao Yang, Chunyan Yang, Chunyu Yang, Congyi Yang, Cui Yang, Cuiwei Yang, Cunming Yang, Dai-Qin Yang, Dan Yang, Dan-Dan Yang, Dan-Hui Yang, Dandan Yang, Danlu Yang, Danrong Yang, Danzhou Yang, Dapeng Yang, De-Hua Yang, De-Zhai Yang, Decao Yang, Defu Yang, Deguang Yang, Dehao Yang, Dehua Yang, Dejun Yang, Deli Yang, Dengfa Yang, Deok Chun Yang, Deshuang Yang, Di Yang, Dianqiang Yang, Ding Yang, Ding-I Yang, Diya Yang, Diyuan Yang, Dong Yang, Dong-Hua Yang, Dongfeng Yang, Dongjie Yang, Dongliang Yang, Dongmei Yang, Dongren Yang, Dongshan Yang, Dongwei Yang, Dongwen Yang, DuJiang Yang, Eddy S Yang, Edwin Yang, Ei-Wen Yang, Emily Yang, Enlu Yang, Enzhi Yang, Eric Yang, Eryan Yang, Ethan Yang, Eunho Yang, Fajun Yang, Fan Yang, Fang Yang, Fang-Ji Yang, Fang-Kun Yang, Fei Yang, Feilong Yang, Feiran Yang, Feixiang Yang, Fen Yang, Feng Yang, Feng-Ming Yang, Feng-Yun Yang, Fengjie Yang, Fengjiu Yang, Fengjuan Yang, Fenglian Yang, Fengling Yang, Fengping Yang, Fengying Yang, Fengyong Yang, Fu Yang, Fude Yang, Fuhe Yang, Fuhuang Yang, Fumin Yang, Fuquan Yang, Furong Yang, Fuxia Yang, Fuyao Yang, G Y Yang, G Yang, Gan Yang, Gang Yang, Gangyi Yang, Gao Yang, Gaohong Yang, Gaoxiang Yang, Ge Yang, Gong Yang, Gong-Li Yang, Grace H Y Yang, Guan Yang, Guang Yang, Guangdong Yang, Guangli Yang, Guangwei Yang, Guangyan Yang, Guanlin Yang, Gui-Zhi Yang, Guigang Yang, Guitao Yang, Guo Yang, Guo-Can Yang, Guobin Yang, Guofen Yang, Guojun Yang, Guokun Yang, Guoli Yang, Guomei Yang, Guoping Yang, Guoqi Yang, Guosheng Yang, Guotao Yang, Guowang Yang, Guowei Yang, H X Yang, H Yang, Hai Yang, Hai-Chun Yang, Haibo Yang, Haihong Yang, Haikun Yang, Hailei Yang, Hailing Yang, Haiming Yang, Haiping Yang, Haiqiang Yang, Haitao Yang, Haixia Yang, Haiyan Yang, Haiying Yang, Han Yang, Hanchen Yang, Handong Yang, Hang Yang, Hannah Yang, Hanseul Yang, Hanteng Yang, Hao Yang, Hao-Jan Yang, HaoXiang Yang, Haojie Yang, Haolan Yang, Haoqing Yang, Haoran Yang, Haoyu Yang, Harrison Hao Yang, Hee Joo Yang, Heng Yang, Hengwen Yang, Henry Yang, Heqi Yang, Heyi Yang, Heyun Yang, Hoe-Saeng Yang, Hong Yang, Hong-Fa Yang, Hong-Li Yang, HongMei Yang, Hongbing Yang, Hongbo Yang, Hongfa Yang, Honghong Yang, Hongjie Yang, Hongjun Yang, Hongli Yang, Hongling Yang, Hongqun Yang, Hongxia Yang, Hongxin Yang, Hongyan Yang, Hongyu Yang, Hongyuan Yang, Hongyue Yang, Howard H Yang, Howard Yang, Hsin-Chou Yang, Hsin-Jung Yang, Hsin-Sheng Yang, Hua Yang, Hua-Yuan Yang, Huabing Yang, Huafang Yang, Huaijie Yang, Huan Yang, Huanhuan Yang, Huanjie Yang, Huanming Yang, Huansheng Yang, Huanyi Yang, Huarong Yang, Huaxiao Yang, Huazhao Yang, Hui Yang, Hui-Ju Yang, Hui-Li Yang, Hui-Ting Yang, Hui-Yu Yang, Hui-Yun Yang, Huifang Yang, Huihui Yang, Huijia Yang, Huijie Yang, Huiping Yang, Huiran Yang, Huixia Yang, Huiyu Yang, Hung-Chih Yang, Hwai-I Yang, Hye Jeong Yang, Hyerim Yang, Hyun Suk Yang, Hyun-Sik Yang, Ill Yang, Ivana V Yang, J S Yang, J Yang, James Y Yang, Jaw-Ji Yang, Jee Sun Yang, Jenny J Yang, Jerry Yang, Ji Hye Yang, Ji Yang, Ji Yeong Yang, Ji-chun Yang, Jia Yang, Jia-Ling Yang, Jia-Ying Yang, Jiahong Yang, Jiahui Yang, Jiajia Yang, Jiakai Yang, Jiali Yang, Jialiang Yang, Jian Yang, Jian-Bo Yang, Jian-Jun Yang, Jian-Ming Yang, Jian-Ye Yang, JianHua Yang, JianJun Yang, Jianbo Yang, Jiang-Min Yang, Jiang-Yan Yang, Jianing Yang, Jianke Yang, Jianli Yang, Jianlou Yang, Jianmin Yang, Jianming Yang, Jianqi Yang, Jianwei Yang, Jianyu Yang, Jiao Yang, Jiarui Yang, Jiawei Yang, Jiaxin Yang, Jiayan Yang, Jiayi Yang, Jiaying Yang, Jiayue Yang, Jichun Yang, Jie Yang, Jie-Cheng Yang, Jie-Hong Yang, Jie-Kai Yang, Jiefeng Yang, Jiehong Yang, Jieping Yang, Jiexiang Yang, Jihong Yang, Jimin Yang, Jin Yang, Jin-Jian Yang, Jin-Kui Yang, Jin-gang Yang, Jin-ju Yang, Jinan Yang, Jinfeng Yang, Jing Yang, Jing-Quan Yang, Jing-Yu Yang, Jingang Yang, Jingfeng Yang, Jinggang Yang, Jinghua Yang, Jinghui Yang, Jingjing Yang, Jingmin Yang, Jingping Yang, Jingran Yang, Jingshi Yang, Jingwen Yang, Jingya Yang, Jingyan Yang, Jingyao Yang, Jingye Yang, Jingyu Yang, Jingyun Yang, Jingze Yang, Jinhua Yang, Jinhui Yang, Jinjian Yang, Jinpeng Yang, Jinru Yang, Jinshan Yang, Jinsong Yang, Jinsung Yang, Jinwen Yang, Jinzhao Yang, Jiong Yang, Ju Dong Yang, Ju Young Yang, Juan Yang, Juesheng Yang, Jumei Yang, Jun J Yang, Jun Yang, Jun-Hua Yang, Jun-Xia Yang, Jun-Xing Yang, Junbo Yang, Jung Dug Yang, Jung Wook Yang, Jung-Ho Yang, Junhan Yang, Junjie Yang, Junlin Yang, Junlu Yang, Junping Yang, Juntao Yang, Junyao Yang, Junyi Yang, Kai Yang, Kai-Chien Yang, Kai-Chun Yang, Kaidi Yang, Kaifeng Yang, Kaijie Yang, Kaili Yang, Kailin Yang, Kaiwen Yang, Kang Yang, Kang Yi Yang, Kangning Yang, Karen Yang, Ke Yang, Keming Yang, Keping Yang, Kexin Yang, Kuang-Yao Yang, Kui Yang, Kun Yang, Kunao Yang, Kunqi Yang, Kunyu Yang, Kuo Tai Yang, L Yang, Lamei Yang, Lan Yang, Le Yang, Lei Yang, Lexin Yang, Leyi Yang, Li Chun Yang, Li Yang, Li-Kun Yang, Li-Qin Yang, Li-li Yang, LiMan Yang, Lian-he Yang, Liang Yang, Liang-Yo Yang, Liangbin Yang, Liangle Yang, Liangliang Yang, Lichao Yang, Lichuan Yang, Licong Yang, Liehao Yang, Lihong Yang, Lihua Yang, Lihuizi Yang, Lijia Yang, Lijie Yang, Lijuan Yang, Lijun Yang, Lili Yang, Lin Sheng Yang, Lin Yang, Lina Yang, Ling Ling Yang, Ling Yang, Lingfeng Yang, Lingling Yang, Lingzhi Yang, Linlin Yang, Linnan Yang, Linqing Yang, Linquan Yang, Lipeng Yang, Liping Yang, Liting Yang, Liu Yang, Liu-Kun Yang, LiuMing Yang, Liuliu Yang, Liwei Yang, Lixian Yang, Lixue Yang, Long In Yang, Long Yang, Long-Yan Yang, Longbao Yang, Longjun Yang, Longyan Yang, Lu M Yang, Lu Yang, Lu-Hui Yang, Lu-Kun Yang, Lu-Qin Yang, Luda Yang, Man Yang, Manqing Yang, Maojie Yang, Maoquan Yang, Mei Yang, Meichan Yang, Meihua Yang, Meili Yang, Meiting Yang, Meixiang Yang, Meiying Yang, Meng Yang, Menghan Yang, Menghua Yang, Mengjie Yang, Mengli Yang, Mengliu Yang, Mengmeng Yang, Mengsu Yang, Mengwei Yang, Mengying Yang, Miaomiao Yang, Mickey Yang, Min Hee Yang, Min Yang, Mina Yang, Ming Yang, Ming-Hui Yang, Ming-Yan Yang, Minghui Yang, Mingjia Yang, Mingjie Yang, Mingjun Yang, Mingli Yang, Mingqian Yang, Mingshi Yang, Mingyan Yang, Mingyu Yang, Minyi Yang, Misun Yang, Mu Yang, Muh-Hwa Yang, Na Yang, Nan Yang, Nana Yang, Nanfei Yang, Neil V Yang, Ni Yang, Ning Yang, Ningjie Yang, Ningli Yang, Pan Yang, Pan-Chyr Yang, Paul Yang, Peichang Yang, Peiran Yang, Peiyan Yang, Peiying Yang, Peiyuan Yang, Peizeng Yang, Peng Yang, Peng-Fei Yang, PengXiang Yang, Pengfei Yang, Penghui Yang, Pengwei Yang, Pengyu Yang, Phillip C Yang, Pin Yang, Ping Yang, Ping-Fen Yang, Pinghong Yang, Pu Yang, Q H Yang, Q Yang, Qi Yang, Qi-En Yang, Qian Yang, Qian-Jiao Yang, Qian-Li Yang, QianKun Yang, Qiang Yang, Qianhong Yang, Qianqian Yang, Qianru Yang, Qiaoli Yang, Qiaorong Yang, Qiaoyuan Yang, Qifan Yang, Qifeng Yang, Qiman Yang, Qimeng Yang, Qiming Yang, Qin Yang, Qinbo Yang, Qing Yang, Qing-Cheng Yang, Qingcheng Yang, Qinghu Yang, Qingkai Yang, Qinglin Yang, Qingling Yang, Qingmo Yang, Qingqing Yang, Qingtao Yang, Qingwu Yang, Qingya Yang, Qingyan Yang, Qingyi Yang, Qingyu Yang, Qingyuan Yang, Qiong Yang, Qiu Yang, Qiu-Yan Yang, Qiuhua Yang, Qiuhui Yang, Qiulan Yang, Qiuli Yang, Qiuxia Yang, Qiwei Yang, Qiwen Yang, Quan Yang, Quanjun Yang, Quanli Yang, Qun-Fang Yang, R Yang, Ran Yang, Ren-Zhi Yang, Renchi Yang, Renhua Yang, Renjun Yang, Renqiang Yang, Renzhi Yang, Ri-Yao Yang, Richard K Yang, Robert Yang, Rong Yang, Rongrong Yang, Rongxi Yang, Rongyuan Yang, Rongze Yang, Rui Xu Yang, Rui Yang, Rui-Xu Yang, Rui-Yi Yang, Ruicheng Yang, Ruifang Yang, Ruihua Yang, Ruilan Yang, Ruili Yang, Ruiqin Yang, Ruirui Yang, Ruiwei Yang, Rulai Yang, Ruming Yang, Run Yang, Runjun Yang, Runxu Yang, Runyu Yang, Runzhou Yang, Ruocong Yang, Ruoyun Yang, Ruyu Yang, S J Yang, Se-Ran Yang, Sen Yang, Senwen Yang, Seung Yun Yang, Seung-Jo Yang, Seung-Ok Yang, Shan Yang, Shangchen Yang, Shanghua Yang, Shangwen Yang, Shanzheng Yang, Shao-Hua Yang, Shaobin Yang, Shaohua Yang, Shaoling Yang, Shaoqi Yang, Shaoqing Yang, Sheng Sheng Yang, Sheng Yang, Sheng-Huei Yang, Sheng-Qian Yang, Sheng-Wu Yang, ShengHui Yang, Shenglin Yang, Shengnan Yang, Shengqian Yang, Shengyong Yang, Shengzhuang Yang, Shenhui Yang, Shi-Ming Yang, Shiaw-Der Yang, Shifeng Yang, Shigao Yang, Shijie Yang, Shiming Yang, Shipeng Yang, Shiping Yang, Shiu-Ju Yang, Shiyi Yang, Shizhong Yang, Shizhuo Yang, Shu Yang, ShuSheng Yang, Shuai Yang, Shuaibing Yang, Shuaini Yang, Shuang Yang, Shuangshuang Yang, Shucai Yang, Shufang Yang, Shuhua Yang, Shujuan Yang, Shujun Yang, Shulan Yang, Shulin Yang, Shuming Yang, Shun-Fa Yang, Shuo Yang, Shuofei Yang, Shuping Yang, Shuqi Yang, Shuquan Yang, Shurong Yang, Shushen Yang, Shuye Yang, Shuyu Yang, Si Yang, Si-Fu Yang, Sibao Yang, Sibo Yang, Sichong Yang, Sihui Yang, Sijia Yang, Siqi Yang, Sirui Yang, Sisi Yang, Sitao Yang, Siwen Yang, Siyi Yang, Siyu Yang, Sizhen Yang, Sizhu Yang, Song Yang, Song-na Yang, Songpeng Yang, Songye Yang, Soo Hyun Yang, Su Yang, Su-Geun Yang, Suhong Yang, Sujae Yang, Sujuan Yang, Suk-Kyun Yang, Sun Kyung Yang, Suwol Yang, Suxia Yang, Suyi Yang, Suyu Yang, Tai-Hui Yang, Tailai Yang, Tao Yang, Tengyun Yang, Thomas P Yang, Ti Yang, Tian Yang, Tianbao Yang, Tianfeng Yang, Tianjie Yang, Tianmin Yang, Tianpeng Yang, Tianqiong Yang, Tiantian Yang, Tianxin Yang, Tianyou Yang, Tianyu Yang, Tianze Yang, Tianzhong Yang, Ting Yang, Ting-Xian Yang, Tingting Yang, Tingyu Yang, Tong Yang, Tong Yi Yang, Tong-Xin Yang, Tonglin Yang, Tongren Yang, Tuanmin Yang, Ueng-Cheng Yang, W Yang, Wan-Chen Yang, Wan-Jung Yang, Wang Yang, Wannian Yang, Wei Qiang Yang, Wei Yang, Wei-Fa Yang, Wei-Xin Yang, Weidong Yang, Weiguang Yang, Weihan Yang, Weijian Yang, Weili Yang, Weimin Yang, Weiran Yang, Weiwei Yang, Weixian Yang, Weizhong Yang, Wen Yang, Wen Z Yang, Wen-Bin Yang, Wen-Chin Yang, Wen-He Yang, Wen-Hsuan Yang, Wen-Ming Yang, Wen-Wen Yang, Wen-Xiao Yang, WenKai Yang, Wenbo Yang, Wenchao Yang, Wending Yang, Wenfei Yang, Wenhong Yang, Wenhua Yang, Wenhui Yang, Wenjian Yang, Wenjie Yang, Wenjing Yang, Wenjuan Yang, Wenjun Yang, Wenli Yang, Wenlin Yang, Wenming Yang, Wenqin Yang, Wenshan Yang, Wentao Yang, Wenwen Yang, Wenwu Yang, Wenxin Yang, Wenxing Yang, Wenying Yang, Wenzhi Yang, Wenzhu Yang, William Yang, Woong-Suk Yang, Wu Yang, Wu-de Yang, X Yang, X-J Yang, Xi Yang, Xi-You Yang, Xia Yang, Xian Yang, Xiang Yang, Xiang-Hong Yang, Xiang-Jun Yang, Xianggui Yang, Xianghong Yang, Xiangliang Yang, Xiangling Yang, Xiangqiong Yang, Xiangxiang Yang, Xiangyu Yang, Xiao Yang, Xiao-Dong Yang, Xiao-Fang Yang, Xiao-Hong Yang, Xiao-Jie Yang, Xiao-Juan Yang, Xiao-Meng Yang, Xiao-Ming Yang, Xiao-Qian Yang, Xiao-Yan Yang, Xiao-Ying Yang, Xiao-Yu Yang, Xiao-guang Yang, XiaoYan Yang, Xiaoao Yang, Xiaobin Yang, Xiaobo Yang, Xiaochen Yang, Xiaodan Yang, Xiaodi Yang, Xiaodong Yang, Xiaofei Yang, Xiaofeng Yang, Xiaohao Yang, Xiaohe Yang, Xiaohong R Yang, Xiaohong Yang, Xiaohuang Yang, Xiaohui Yang, Xiaojian Yang, Xiaojie Yang, Xiaojing Yang, Xiaojuan Yang, Xiaojun Yang, Xiaoli Yang, Xiaolu Yang, Xiaomeng Yang, Xiaoming Yang, Xiaonan Yang, Xiaoping Yang, Xiaoqian Yang, Xiaoqin Yang, Xiaoqun Yang, Xiaorong Yang, Xiaoshan Yang, Xiaoshi Yang, Xiaosong Yang, Xiaotian Yang, Xiaotong Yang, Xiaowei Yang, Xiaowen Yang, Xiaoxiao Yang, Xiaoxin Yang, Xiaoxu Yang, Xiaoyao Yang, Xiaoyi Yang, Xiaoyong Yang, Xiaoyu Yang, Xiaoyun Yang, Xiaozhen Yang, Xifei Yang, Xiling Yang, Ximan Yang, Xin Yang, Xin-He Yang, Xin-Yu Yang, Xin-Zhuang Yang, Xing Yang, Xinghai Yang, Xinglong Yang, Xingmao Yang, Xingming Yang, Xingsheng Yang, Xingyu Yang, Xingyue Yang, Xingzhi Yang, Xinjing Yang, Xinming Yang, Xinpu Yang, Xinwang Yang, Xinxin Yang, Xinyan Yang, Xinyi Yang, Xinyu Yang, Xinyue Yang, Xiong Ling Yang, Xiru Yang, Xitong Yang, Xiu Hong Yang, Xiuhua Yang, Xiulin Yang, Xiuna Yang, Xiuqin Yang, Xiurong Yang, Xiuwei Yang, Xiwen Yang, Xiyue Yang, Xu Yang, Xuan Yang, Xue Yang, Xue-Feng Yang, Xue-Ping Yang, Xuecheng Yang, Xuehan Yang, Xuejing Yang, Xuejun Yang, Xueli Yang, Xuena Yang, Xueping Yang, Xuesong Yang, Xuhan Yang, Xuhui Yang, Xuping Yang, Xuyang Yang, Y C Yang, Y F Yang, Y L Yang, Y P Yang, Y Q Yang, Y Yang, Y-T Yang, Ya Yang, Ya-Chen Yang, Yadong Yang, Yafang Yang, Yajie Yang, Yalan Yang, Yali Yang, Yaming Yang, Yan Yang, Yan-Bei Yang, Yan-Ling Yang, Yanan Yang, Yanfang Yang, Yang Yang, Yangfan Yang, Yangyang Yang, Yanhui Yang, Yanjianxiong Yang, Yanling Yang, Yanmei Yang, Yanmin Yang, Yanping Yang, Yanru Yang, Yanting Yang, Yanyan Yang, Yanzhen Yang, Yaorui Yang, Yaping Yang, Yaqi Yang, Yaxi Yang, Ye Yang, Yefa Yang, Yefeng Yang, Yeqing Yang, Yexin Yang, Yi Yang, Yi-Chieh Yang, Yi-Fang Yang, Yi-Feng Yang, Yi-Liang Yang, Yi-Ping Yang, Yi-ning Yang, Yibing Yang, Yichen Yang, Yidong Yang, Yifan Yang, Yifang Yang, Yifei Yang, Yifeng Yang, Yihe Yang, Yijie Yang, Yilian Yang, Yimei Yang, Yimin Yang, Yiming Yang, Yimu Yang, Yin-Rong Yang, Yinfeng Yang, Ying Yang, Ying-Hua Yang, Ying-Ying Yang, Yingdi Yang, Yingjun Yang, Yingqing Yang, Yingrui Yang, Yingxia Yang, Yingyu Yang, Yinhua Yang, Yining Yang, Yinxi Yang, Yiping Yang, Yiting Yang, Yiyi Yang, Yiying Yang, Yong Yang, Yong-Yu Yang, Yongfeng Yang, Yongguang Yang, Yonghong Yang, Yonghui Yang, Yongjia Yang, Yongjie Yang, Yongkang Yang, Yongqiang Yang, Yongsan Yang, Yongxin Yang, Yongzhong Yang, Yoon La Yang, Yoon Mee Yang, Youhua Yang, YoungSoon Yang, Yu Yang, Yu-Fan Yang, Yu-Feng Yang, Yu-Jie Yang, Yu-Shi Yang, Yu-Tao Yang, Yu-Ting Yang, Yuan Yang, Yuan-Han Yang, Yuan-Jian Yang, Yuanhao Yang, Yuanjin Yang, Yuanquan Yang, Yuanrong Yang, Yuanying Yang, Yuanzhang Yang, Yuanzhi Yang, Yuchen Yang, Yucheng Yang, Yue Yang, Yueh-Ning Yang, Yuejin Yang, Yuexiang Yang, Yueze Yang, Yufan Yang, Yuhan Yang, Yuhang Yang, Yuhua Yang, Yujie Yang, Yujing Yang, Yulin Yang, Yuling Yang, Yulong Yang, Yun Yang, YunKai Yang, Yunfan Yang, Yung-Li Yang, Yunhai Yang, Yunlong Yang, Yunmei Yang, Yunwen Yang, Yunyun Yang, Yunzhao Yang, Yupeng Yang, Yuqi Yang, Yuta Yang, Yutao Yang, Yuting Yang, Yutong Yang, Yuwei Yang, Yuxi Yang, Yuxing Yang, Yuxiu Yang, Yuyan Yang, Yuyao Yang, Yuying Yang, Z Yang, Zaibin Yang, Zaiming Yang, Zaiqing Yang, Zanhao Yang, Ze Yang, Zemin Yang, Zeng-Ming Yang, Zengqiang Yang, Zengqiao Yang, Zeyu Yang, Zhang Yang, Zhangping Yang, Zhanyi Yang, Zhao Yang, Zhao-Na Yang, Zhaojie Yang, Zhaoli Yang, Zhaoxin Yang, Zhaoyang Yang, Zhaoyi Yang, Zhehan Yang, Zheming Yang, Zhen Yang, Zheng Yang, Zheng-Fei Yang, Zheng-lin Yang, Zhenglin Yang, Zhengqian Yang, Zhengtao Yang, Zhenguo Yang, Zhengyan Yang, Zhengzheng Yang, Zhengzhong Yang, Zhenhua Yang, Zhenjun Yang, Zhenmei Yang, Zhenqi Yang, Zhenrong Yang, Zhenwei Yang, Zhenxing Yang, Zhenyun Yang, Zhenzhen Yang, Zheyu Yang, Zhi Yang, Zhi-Can Yang, Zhi-Hong Yang, Zhi-Jun Yang, Zhi-Min Yang, Zhi-Ming Yang, Zhi-Rui Yang, Zhibo Yang, Zhichao Yang, Zhifen Yang, Zhigang Yang, Zhihang Yang, Zhihong Yang, Zhikuan Yang, Zhikun Yang, Zhimin Yang, Zhiming Yang, Zhiqiang Yang, Zhitao Yang, Zhiwei Yang, Zhixin Yang, Zhiyan Yang, Zhiyong Yang, Zhiyou Yang, Zhiyuan Yang, Zhongan Yang, Zhongfang Yang, Zhonghua Yang, Zhonghui Yang, Zhongli Yang, Zhongshu Yang, Zhongzhou Yang, Zhou Yang, Zhuliang Yang, Zhuo Yang, Zhuoya Yang, Zhuoyu Yang, Zi F Yang, Zi Yang, Zi-Han Yang, Zi-Wei Yang, Zicong Yang, Zifeng Yang, Zihan Yang, Ziheng Yang, Zijiang Yang, Zishan Yang, Zixia Yang, Zixuan Yang, Ziying Yang, Ziyou Yang, Ziyu Yang, Zong-de Yang, Zongfang Yang, Zongyu Yang, Zunxian Yang, Zuozhen Yang
articles
Xueqian Wang, Shengzhuang Guan, Yiqing Gao +13 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Brachydactyly type E (BDE) is characterized by variable shortening of metacarpals or metatarsals, often involving phalanges. It may occur as an isolated anomaly or as part of congenital syndromes. Wit Show more
Brachydactyly type E (BDE) is characterized by variable shortening of metacarpals or metatarsals, often involving phalanges. It may occur as an isolated anomaly or as part of congenital syndromes. With advancements in molecular diagnostic technologies, how genetic testing enhances the precise diagnosis of BDE remains unclear. Our aims were to establish an algorithm for molecular genetic diagnostics in Chinese children with BDE and to explore the phenotype-genotype correlations of Chinese patients with BDE. We reviewed left-hand wrist X-rays from children visiting Children's Hospital of Soochow University (Jun 2021-Dec 2023). From 60,650 films, 135 BDE cases were identified, and their comprehensive phenotypes were collected. Whole-exome sequencing (WES) with copy number variation (CNV) analysis was performed on 60 patients and their parents. Sanger sequencing was used to validate single nucleotide variants (SNV) and indels. Causative variants were found in 19 patients. SNVs and indels affecting 10 genes were identified in 15 patients, and CNVs in four. Through comprehensive evaluation of genotype-phenotype correlations, we propose a diagnostic algorithm for precise molecular diagnosis in Chinese children with BDE. Show less
📄 PDF DOI: 10.3389/fendo.2025.1571136
EXT1
Fu-Hui Xiao, Hao-Tian Wang, Long Zhao +4 more · 2025 · Cell reports · Elsevier · added 2026-04-24
Men, despite having a lower likelihood of longevity compared to women, generally exhibit better health status when they achieve longevity. The role of DNA methylation in this paradox remains unclear. Show more
Men, despite having a lower likelihood of longevity compared to women, generally exhibit better health status when they achieve longevity. The role of DNA methylation in this paradox remains unclear. We performed whole-genome bisulfite sequencing on long-lived men (LLMs), long-lived women (LLWs), younger men (YMs) and younger women (YWs) to explore specific methylation characteristics in LLMs. Despite an accelerated methylation aging rate in LLMs compared to LLWs, we identify thousands of differentially methylated genomic units (DMUs) in LLMs independent of age and sex. These DMUs, validated by an elastic net classifier, can serve as methylation markers for discriminating longevity potential in men. Many are located near health-related genes. Genes like PIWIL1 and EXT1, with promoters featuring DMUs, exemplify the potential role of LLM-specific methylation patterns in suppressing age-related diseases by regulating gene transcription. Our findings provide evidence of a distinct methylation feature contributing to healthy aging and longevity of LLMs. Show less
no PDF DOI: 10.1016/j.celrep.2024.115158
EXT1
Lan Zhou, Xin Li, Zihan Ji +9 more · 2025 · Molecular biotechnology · Springer · added 2026-04-24
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are li Show more
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are linked to HME pathogenesis, with EXT1 mutation being the most frequent. The aim of this study was to generate a mice model with Ext1 gene editing to simulate human EXT1 mutation and investigate the genetic pathogenicity of Ext1 through phenotypic analyses. We designed a pair of dual sgRNAs targeting exon 1 of the mice Ext1 gene for precise deletion of a 46 bp DNA fragment, resulting in frameshift mutation of the Ext1 gene. The designed dual sgRNAs and Cas9 proteins were injected into mice zygotes cytoplasm. A total of 14 mice were obtained via embryo transfer, among which two genotypic chimera mice had a deletion of the 46 bp DNA fragment in exon 1 of the Ext1 gene. By hybridization and breeding, we successfully generated heterozygous mice with edited Ext1 gene (Ext Show less
📄 PDF DOI: 10.1007/s12033-024-01325-0
EXT1
Tiankai Xie, Josey C Sorenson, Logan G Spector +15 more · 2025 · Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · added 2026-04-24
Hepatoblastoma (HB) is a rare embryonal liver tumor, with an increasing global incidence that underscores the need to understand its genetic etiology. Utilizing the ancestry-matched expression quantit Show more
Hepatoblastoma (HB) is a rare embryonal liver tumor, with an increasing global incidence that underscores the need to understand its genetic etiology. Utilizing the ancestry-matched expression quantitative loci data, we performed a HB transcriptome-wide association study (TWAS) on 4,539 Europeans, 1,047 Latinos, and 378 African Americans (∼1:10 case-control ratio). We conducted a meta-analysis of multiancestry transcriptome-wide analysis (METRO), followed by METRO-Egger sensitivity analysis and ancestry-specific gene set enrichment analyses. We further explored genes with additional evidence gathered from independent cohorts and databases. Across the three ancestries, the discovered genes shared the same effect direction across ancestries. A meta-analysis of the three ancestries identified 28 genes significantly associated with HB risk, and 15 were nominally significant for at least two ancestries. Our post-TWAS analyses highlighted 8 genes among these 28, including OXER1 (meta-analysis P value = 7.34 × 10-6), FADS1 (P value = 4.01 × 10-6), and UGDH (P value = 5.29 × 10-8), which were expressed in fetal liver hepatoblast cells and were differentially expressed in tumor and normal tissues in an independent Japanese HB study (P values = 2.61 × 10-13, 3.62 × 10-3, and 1.95 × 10-9, respectively). We pinpointed eight potential genes associated with HB using data from an ongoing multiancestry genome-wide association study. We conducted the largest HB TWAS to date, prompting further exploration of genes. Show less
no PDF DOI: 10.1158/1055-9965.EPI-24-1553
FADS1
Jiaqi Wei, Zhen Yang, Xiaojin Wu +2 more · 2025 · Thrombosis journal · BioMed Central · added 2026-04-24
Coagulation defects, including purpura and other haemorrhagic conditions, are a critical area of medical research because of their significant health effects worldwide. Understanding the metabolic bas Show more
Coagulation defects, including purpura and other haemorrhagic conditions, are a critical area of medical research because of their significant health effects worldwide. Understanding the metabolic basis of these conditions may improve therapeutic strategies. A two-sample Mendelian randomization (MR) approach was employed to evaluate the causal relationships between the levels of 1,400 metabolites and coagulation defects. Colocalization analysis confirmed significant shared genetic influences. Pathway and protein‒protein interaction (PPI) analyses identified rate-limiting enzymes and drug targets. The impacts of lifestyle factors on metabolite levels were also explored through MR. MR analysis revealed four metabolites whose abundance was significantly associated with coagulation defects: docosapentaenoate n3 DPA 22:5n3 (DPA) (OR: 1.594, 95% CI: 1.263-2.011, P < 0.001), 1-palmitoyl-2-stearoyl-gpc (PSPC) (16:0/18:0) (OR: 1.294, 95% CI: 1.134-1.477, P < 0.001), 1-stearoyl-2-docosahexaenoyl-gpc (SDPC) (18:0/22:6) (OR: 1.232, 95% CI: 1.101-1.380, P < 0.001) and hydroxypalmitoyl sphingomyelin (HPSM) (d18:1/16:0 (OH)) (OR: 0.803, 95% CI: 0.719-0.896, P < 0.001). Colocalization analysis provided robust evidence for shared genetic loci. Pathway analysis highlighted the importance of lipid metabolism, identifying key enzymes such as FADS1, FADS2 and TCP1. PPI analysis revealed an interaction between TCP1 and plasminogen, indicating potential therapeutic synergy. Further analysis revealed that lifestyle factors, including dried fruit and oily fish intake, were linked to the abundance of metabolites associated with coagulation risk. This study identifies specific metabolites and metabolic pathways involved in coagulation defects, proposes novel therapeutic targets and highlights the roles of dietary and lifestyle interventions in the management of these conditions. These findings pave the way for personalized strategies to manage coagulation-related conditions. Show less
📄 PDF DOI: 10.1186/s12959-025-00731-x
FADS1
Jun Cheng, Jiafan Cao, Yalan Yang +16 more · 2025 · Cancer letters · Elsevier · added 2026-04-24
Tumorigenesis is typically accompanied by cellular dedifferentiation and the acquisition of stem cell-like attributes. However, few studies have comprehensively evaluated the putative relationships be Show more
Tumorigenesis is typically accompanied by cellular dedifferentiation and the acquisition of stem cell-like attributes. However, few studies have comprehensively evaluated the putative relationships between these characteristics and various cancers. Here, we integrated gene expression and DNA methylation quantitative trait loci (cis-eQTL and cis-mQTL) data from the blood to perform multi-omics Mendelian randomization analysis. Our analyses revealed 967 stem cell-associated genes (P < 0.05) and 11,262 methylation sites (P < 0.01) significantly related to 12 cancers. SMAD7 (cg14321542) in colon cancer, IGF2 (cg13508136) in prostate cancer, and FADS1 (cg07005513) in rectal cancer were prioritized as candidate causal genes and regulatory elements. Notably, using cis-eQTL data from the corresponding tissue sites, we detected 16 stem cell-associated genes dramatically causally associated with six cancers (FDR<0.2). The gene THBS3 was particularly common in both blood and stomach tissues and exhibited prognostic significance. Furthermore, it was markedly associated with one microbial metabolic pathway and four immunophenotypes. Functional validation using the ECC12 gastric cancer cell line revealed that the inhibition of its expression could accelerate oxidative phosphorylation and reactive oxygen species production, reduce clonal proliferation ability, and promote the apoptosis of stomach tumor cells. Additionally, based on spatial transcriptomic data from gastrointestinal cancers, the results demonstrated the clusters enriched with the most stem cell-associated genes exhibited significantly enhanced tumor-promoting potency, and the THBS3-expressing cells displayed suppressed oxidative phosphorylation. Overall, this study enhances our understanding of tumorigenic mechanisms and aids in the identification of therapeutic targets. Show less
no PDF DOI: 10.1016/j.canlet.2025.217816
FADS1
Haoze Ding, Kan Xiao, Zhengyong Wen +7 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Fatty acyl desaturases (Fads) are known to play critical roles in the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFAs) in fish species. To date, research on Fads in fish has predomina Show more
Fatty acyl desaturases (Fads) are known to play critical roles in the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFAs) in fish species. To date, research on Fads in fish has predominantly focused on Fads2, while studies on Fads1 have been rarely reported. Acipenseriformes, commonly known as Chondrostei, are an ancient fish lineage with unique evolutionary history. However, the biological roles and evolutionary status of Fads1 in Chondrostei remain unclear, which constrains our understanding of the evolutionary processes shaping LC-PUFA biosynthesis in this lineage. In this study, we identified and characterized a fads1 gene from Chinese sturgeon (Acipenser sinensis), a critically endangered Chondrostei, using molecular cloning and multiple bioinformatic analyses. The spatio-temporal expression patterns, functional characteristics, and transcriptional regulation in response to dietary fatty acids were investigated. The coding sequence of the fads1 gene was 1317 bp in length, encoding a protein of 438 amino acids. Bioinformatic analyses suggested high conservation of fads genes across Chondrostei despite their complex evolutionary history. Functional characterization in yeast showed that Chinese sturgeon Fads1 exhibited Δ5 desaturation activity, efficiently converting 20:3n-6 to arachidonic acid (ARA) and 20:4n-3 to eicosapentaenoic acid (EPA). Fatty acid composition analysis indicated that Chinese sturgeon could biosynthesize LC-PUFAs when they are deficient in their diets. Taken together, these results suggest that fads1 plays a crucial role in LC-PUFA biosynthesis in Chinese sturgeon, which provides solid theoretical basis for dietary LC-PUFA requirement of Chinese sturgeon. Furthermore, our findings provide novel insights into evolutionary diversification of fads genes in fish species. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.143664
FADS1
Tianmin Yang, Kai SUN, Fan Peng +4 more · 2025 · Discover oncology · Springer · added 2026-04-24
Kidney renal clear cell carcinoma (KIRC), the predominant subtype of renal cell carcinoma, poses significant health risks. The rapid progression and resistance to targeted therapies highlight the need Show more
Kidney renal clear cell carcinoma (KIRC), the predominant subtype of renal cell carcinoma, poses significant health risks. The rapid progression and resistance to targeted therapies highlight the need for new tumor markers and therapeutic targets. FADS1, part of the fatty acid desaturase family, regulates fatty acid synthesis and participates in lipid metabolism. However, its role in KIRC is not well-studied. The study utilized bioinformatics analysis through the TCGA database and other platforms to identify FADS1 expression levels in KIRC. Twenty pairs of KIRC clinical tissue samples were used for qPCR verification. Meanwhile, eight pairs of KIRC clinical tissue samples were used for Western blot verification. Conduct statistical evaluation, including Wilcoxon rank sum test and Kaplan-Meier analysis, to explore the correlation between FADS1 expression and clinical pathological features and immune infiltration. In addition, in vitro experiments were conducted to confirm the biological function of FADS1. The findings indicated that FADS1 is highly expressed in KIRC and contributes to tumor development. FADS1's role in lipid metabolism leads to lipid accumulation within tumor cells, which may influence the occurrence and progression of KIRC. TIMER analysis revealed a correlation between FADS1 expression and the infiltration levels of various immune cells, indicating its potential role in modulating immune characteristics. FADS1 could serve as a prognostic biomarker associated with immunity in KIRC, highlighting its potential as a diagnostic and therapeutic target. The study underscores the importance of further research into FADS1's role in lipid metabolism and immune infiltration to develop effective therapeutic strategies. Show less
📄 PDF DOI: 10.1007/s12672-025-02255-2
FADS1
Sheng Dou, Yi Wei, Zongyun Lin +7 more · 2025 · Functional & integrative genomics · Springer · added 2026-04-24
Endometriosis is caused by the migration of endometrial cells to locations outside the uterine lining. Despite the increasing prevalence of endometriosis, there has been limited research on genetic ef Show more
Endometriosis is caused by the migration of endometrial cells to locations outside the uterine lining. Despite the increasing prevalence of endometriosis, there has been limited research on genetic effects, and its molecular mechanisms remain unclear. This study aimed to investigate the mechanisms underlying the development of endometriosis and to identify new genetic targets for endometriosis by integrating data from gene chips, single-cell mapping, and genome-wide association study databases. Using the Gene Expression Omnibus database, we downloaded data on normal endometrium, eutopic endometrium, and ectopic lesion tissues to explore the differentially expressed genes (DEGs) between normal and eutopic endometrium, and between eutopic and ectopic endometrium. Assessment of the relationships between DEGs and endometriosis involved differential expression, expression quantitative trait loci (eQTL), and Mendelian randomization (MR) analyses. Two single-cell atlas datasets were then analyzed to explore the mechanisms underlying disease development and progression. Intersection of MR results with DEGs between normal and eutopic endometrium highlighted 28 candidate biomarker genes (17 upregulated and 11 downregulated). Similarly, we identified two additional candidate biomarker genes by intersecting the DEGs between eutopic and ectopic endometrium with MR results. Among these 30 candidates, further filtering using single-cell datasets revealed that the histamine N-methyltransferase (HNMT), coiled-coil domain containing 28 A (CCDC28A), fatty acid desaturase 1 (FADS1) and mahogunin ring finger 1 (MGRN1) genes were differentially expressed between the normal and eutopic groups, consistent with transcriptomic and MR results. Our findings suggested that eutopic endometrium exhibits epithelial-mesenchymal transition (EMT). Cell communication analysis focused on ciliated epithelial cells expressing CDH1 and KRT23 revealed that, in the eutopic endometrium, ciliated epithelial cells are strongly correlated and interact with natural killer cells, T cells, and B cells. We identified four novel biomarker genes and found evidence for EMT in the eutopic endometrium. The mechanism of endometriosis progression may be closely related to EMT and changes in the immune microenvironment triggered by damage to ciliated epithelial cells. Show less
📄 PDF DOI: 10.1007/s10142-025-01543-y
FADS1
Yinggui Wang, Lian Huang, JiangJiang Zhu +6 more · 2025 · PloS one · PLOS · added 2026-04-24
Endothelial lipase (LIPG), a member of the triglyceride lipase family, plays an essential role in human diseases and lipid metabolism. However, its function in goat intramuscular fat (IMF) deposition Show more
Endothelial lipase (LIPG), a member of the triglyceride lipase family, plays an essential role in human diseases and lipid metabolism. However, its function in goat intramuscular fat (IMF) deposition remains unclear. In this study, we investigated the role of the LIPG gene in IMF deposition by knocking down and overexpressing it in goat intramuscular preadipocytes. We successfully cloned the full-length LIPG gene, which spans 2,131 bp, including a 94 bp 5' untranslated region (5'UTR), a 1,503 bp coding sequence (CDS), and a 534 bp 3' untranslated region (3'UTR). Tissue expression profiles showed that LIPG is expressed in the heart, liver, spleen, Kidney, longest dorsal muscle, and small intestine tissues of goats. LIPG knockdown significantly inhibited both the proliferation of intramuscular preadipocytes and lipid deposition. Moreover, LIPG knockdown markedly decreased mRNA expression of FASN, LPL, CPT1A, CPT1B, FABP3, while increasing the mRNA expression of ATGL, ACOX1, FADS1, and ELOVL6. These findings were further corroborated through LIPG overexpression experiments. Using RNA sequencing (RNA-seq), we identified 1695 differentially expressed genes (DEGs) between the negative control (NC) and LIPG knockdown (Si-LIPG) groups, with KEGG pathway analysis revealing significant enrichment in the PPAR signaling pathway. Additionally, LIPG knockdown significantly upregulated the expression of both mRNA and protein levels of PPARα. The PPARα agonist WY14643 was able to reverse the enhanced lipid deposition induced by LIPG overexpression. In conclusion, our study highlights a key role for LIPG in the regulation of goat intramuscular preadipocyte proliferation and lipid deposition, potentially through the PPARα signaling pathway. These findings provide new insights into the regulatory mechanisms governing IMF deposition and suggest potential strategies for improving goat meat quality. Show less
📄 PDF DOI: 10.1371/journal.pone.0317953
FADS1
Anum Saeed, Chris McKennan, Jiaxuan Duan +11 more · 2025 · EBioMedicine · Elsevier · added 2026-04-24
Preclinical data have shown that low levels of metabolites with anti-inflammatory properties may impact metabolic disease processes. However, the association between mid-life levels of such metabolite Show more
Preclinical data have shown that low levels of metabolites with anti-inflammatory properties may impact metabolic disease processes. However, the association between mid-life levels of such metabolites and long-term ASCVD risk is not known. We characterised the plasma metabolomic profile (1228 metabolites) of 1852 participants (58.1 ± 7.5 years old, 69.6% female, 43.6% self-identified as Black) enrolled in the Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) study. Logistic regression was used to assess the impact of metabolite levels on ASCVD risk (nonfatal MI, revascularisation, and cardiac mortality). We additionally explored the effect of genetic variants neighbouring ASCVD-related genes on the levels of metabolites predictive of ASCVD events. The Atherosclerosis Risk in Communities (ARIC) study (n = 4790; 75.5 ± 5.1 years old, 57.4% female, 19.5% self-identified as Black) was used as an independent validation cohort. In fully adjusted models, alpha-ketobutyrate [AKB] (OR 0.62 [95% CI, 0.49-0.80]; p < 0.001), and 1-palmitoyl-2-linoleoyl-GPI [OR, 0.62, 95% CI, 0.47-0.83; p < 0.001], two metabolites in amino acid and phosphatidylinositol lipid pathways, respectively, showed a significant protective association with incident ASCVD risk in both Heart SCORE and ARIC cohorts. Three plasmalogens and a bilirubin derivative, whose levels were regulated by genetic variants neighbouring FADS1 and UGT1A1, respectively, exhibited a significant protective association with ASCVD risk in the Heart SCORE only. Higher mid-life levels of AKB and 1-palmitoyl-2-linoleoyl-GPI metabolites may be associated with lower risk late-life ASCVD events. Further research can determine the causality and therapeutic potential of these metabolites in ASCVD. This study was funded by the Pennsylvania Department of Health (ME-02-384). The department specifically disclaims responsibility for any analyses, interpretations, or conclusions. Additional funding was provided by National Institutes of Health (NIH) grant R01HL089292 and UL1 TR001857 (Steven Reis). Further, NIH funded R01HL141824 and R01HL168683 were used for the ARIC study validation (Bing Yu). Show less
📄 PDF DOI: 10.1016/j.ebiom.2024.105551
FADS1
Kai SUN, Hongju Ling, Fan Peng +6 more · 2025 · International journal of surgery (London, England) · added 2026-04-24
The abnormal accumulation of lipid droplets in clear cell renal cell carcinoma (ccRCC) is related to metabolic reprogramming. However, the mechanism between metabolic reprogramming and tumor progressi Show more
The abnormal accumulation of lipid droplets in clear cell renal cell carcinoma (ccRCC) is related to metabolic reprogramming. However, the mechanism between metabolic reprogramming and tumor progression in ccRCC remains to be explored. Utilize multiple omics technologies to predict the relationship between fatty acid metabolism and tumor progression, and identify the key regulatory proteins and mechanisms. The role of proteins in influencing tumor progression and fatty acid metabolism was explored from both in vivo and in vitro. The mechanism of the regulatory protein was analyzed and verified by co-immunoprecipitation and mass spectrometry. Multimodal analysis revealed that fatty acid desaturase 3 (FADS3), as a key molecule connecting fatty acid metabolism and Epithelial-mesenchymal transition (EMT), was upregulated in clinical samples of ccRCC and participated in the immune regulation, and was positively correlated with clinical stage and poor prognosis. Functionally, FADS3 promoted cell proliferation and EMT in vivo and in vitro as well as sunitinib resistance, and induced fatty acid synthesis and lipid droplet storage. Mechanistically, FADS3 activates the phosphorylation of Smad2/3 through autocrine Transforming Growth Factor-β (TGF-β). The lipid droplets induced by FADS3 could act as a reservoir of acetyl-CoA, promoting the acetylation of Smad2 and inducing the upregulation of TGF-β receptors, thereby promoting the proliferation and EMT. Our study confirmed FADS3 as a key intermediate protein regulating fatty acid metabolism and tumor progression, which was expected to be a potential diagnostic and prognostic biomarker for ccRCC. Show less
no PDF DOI: 10.1097/JS9.0000000000004094
FADS3
Sisi Yan, Ying Liu, Yin Zhang +8 more · 2025 · Journal of agricultural and food chemistry · ACS Publications · added 2026-04-24
Microcystin-LR (MC-LR) is a toxin that causes hepatic steatosis. Our previous study found that exposure to 60 μg/L MC-LR for 9 months resulted in liver lipid accumulation, but the underlying mechanism Show more
Microcystin-LR (MC-LR) is a toxin that causes hepatic steatosis. Our previous study found that exposure to 60 μg/L MC-LR for 9 months resulted in liver lipid accumulation, but the underlying mechanisms remain elusive. Herein, for the first time, fatty acid-targeted metabolome and RNA-seq were combined to probe the effect and mechanism of chronic (12-month) MC-LR treatment on mice lipid metabolism at environmental-related levels (1, 60, and 120 μg/L). It was found that MC-LR dose-dependently raised serum and liver lipid levels. The total cholesterol (TC) levels in the liver were significantly increased following treatment with 1 μg/L MC-LR (equivalent to 0.004 μ/L in human). Treatment with 60 and 120 μg/L MC-LR significantly elevated TC and triglyceride (TG) levels in both serum and liver. Serum fatty acid-targeted metabolome analysis demonstrated that exposure to 1, 60, and 120 μg/L MC-LR caused significant alterations in the fatty acid profile. Chronic 1, 60, and 120 μg/L MC-LR treatment significantly increased serum polyunsaturated fatty acids (PUFAs), including conjugated linoleic acid and eicosapentaenoic acid, which positively correlated with serum or liver TG levels. Chronic exposure to 120 μg/L MC-LR led to a significant decrease in the accumulation of saturated fatty acids, including citramalic acid, pentadecanoic acid, and docosanoic acid, which were negatively correlated with serum or liver lipid levels. These findings suggested that 1 μg/L MC-LR exposure caused mild lipid metabolism disruption, while 60 and 120 μg/L MC-LR treatment resulted in pronounced hepatic steatosis in mice. Transcriptome analysis revealed that chronic environmental MC-LR treatment regulated the expression of genes involved in the phosphatidylinositol 3-kinase (PI3K) complex and fatty acid metabolism. Western blotting and RT-qPCR confirmed that chronic environmental MC-LR exposure activated the PI3K/AKT/mTOR signaling pathway, the downstream of Show less
no PDF DOI: 10.1021/acs.jafc.4c07085
FADS3
Man Wu, Lin Huang, Yibin Yao +4 more · 2025 · Annals of hematology · Springer · added 2026-04-24
8p11 myeloproliferative syndrome (EMS) is a rare aggressive hematologic malignancy with a poor prognosis that can rapidly develop into acute leukemia. It is characterized by the translocation of fibro Show more
8p11 myeloproliferative syndrome (EMS) is a rare aggressive hematologic malignancy with a poor prognosis that can rapidly develop into acute leukemia. It is characterized by the translocation of fibroblast growth factor receptor-1 (FGFR1), and there is still a lack of effective and reliable treatment methods at present. This report provides a new therapeutic strategy for EMS patients diagnosed with BCR-FGFR1 fusion. This report describes a case of EMS patient with a positive BCR-FGFR1 fusion gene, whose manifestations are similar to those of chronic myeloid leukemia (CML). After diagnosis by fluorescence in situ hybridization (FISH) and RNA sequencing (RNA-seq), olverembatinib, the third-generation tyrosinase inhibitor (TKI) developed in China, was used for treatment. After monotherapy and follow-up for more than one year, partial molecular response (PR) was achieved. During this period, hematologic remission and cytogenetic remission were achieved. The treatment safety of the entire process was excellent. In summary, olverembatinib provides more treatment options for rare diseases such as 8p11 myeloproliferative syndrome. Show less
📄 PDF DOI: 10.1007/s00277-025-06522-8
FGFR1
Haixiong Tang, Lin Fu, Changyun Yang +9 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Cadherin-11 (CDH11), a specialized cell-cell adhesion protein, plays an essential role in tissue injury, inflammation and repair. This study aimed to investigate the role of CDH11 in severe asthma. Br Show more
Cadherin-11 (CDH11), a specialized cell-cell adhesion protein, plays an essential role in tissue injury, inflammation and repair. This study aimed to investigate the role of CDH11 in severe asthma. Bronchial biopsy specimens were obtained from healthy subjects and patients with severe asthma. Two murine models of severe asthma were established using either TDI (toluene diisocyanate) or OVA (ovalbumin)/CFA (complete Freund's adjuvants). A selective CDH11 antagonist SD133 (100 mg/kg) was given to allergen-exposed mice after airway challenge. The effects of recombinant CDH11 were also tested in vivo, and FGFR1 inhibition was used to explore a possible mechanism for CDH11-induced inflammatory responses in the lung. We detected upregulated expression of CDH11 in the airway mucosa of severe asthma patients when compared with the healthy control. In the OVA/CFA-induced model, though CDH11 expression in the lung remained unchanged, pharmacological antagonism of CDH11 with SD133 dramatically decreased airway neutrophil accumulation, as well as IL-6 production, but had no effect on eosinophilic infiltration, type 2 inflammation (IL-4 and IL-5) nor airway hyperresponsiveness. In the TDI model, pulmonary CDH11 expression was upregulated. Treatment with SD133 inhibited TDI-induced airway hyperresponsiveness and neutrophilic inflammation, decreased IL-6 and TNF-α production, with no effect on airway eosinophil counts and type 2 inflammatory cytokines. In addition, intratracheal instillation of recombinant CDH11 led to neutrophil recruitment in the lungs of mice, which could be attenuated by inhibition of FGFR1 signaling. CDH11 contributes to airway neutrophilic inflammation in severe asthma through the FGFR1 pathway. Show less
no PDF DOI: 10.1096/fj.202501899RR
FGFR1
Xianqi Feng, Xueting Bai, Hong Zhang +7 more · 2025 · Journal of hematopathology · Springer · added 2026-04-24
Background Myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1(MLN-FGFR1), also referred to as 8p11 myeloproliferative syndrome (EMS), arises from aberrant FGFR1 gene rearrangement Show more
Background Myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1(MLN-FGFR1), also referred to as 8p11 myeloproliferative syndrome (EMS), arises from aberrant FGFR1 gene rearrangement in bone marrow hematopoietic stem cells, resulting in the transformation of myeloid/lymphoid cells into neoplastic growths. The clinical and laboratory features of affected individuals are influenced by the specific partner genes. Purpose This article aims to report a case of MLN-FGFR1 involving a novel CNTRL::FGFR1 splicing variant and to discuss its clinicopathological characteristics and treatment challenges. Methods/Results We report a case of MLN-FGFR1 in a 35-year-old male patient presenting with leukocytosis, lymphadenopathy, hepatosplenomegaly, and a mixed population of B lymphoblasts, T lymphoblasts, and monoblasts in the bone marrow and lymph nodes. Comprehensive molecular profiling, including chromosomal karyotyping, fluorescence in situ hybridization (FISH), targeted transcriptome sequencing, reverse transcription polymerase chain reaction (RT-PCR), and Sanger sequencing, identified a novel splicing variant of the CNTRL::FGFR1 fusion, resulting from a t(8;9)(p11;q33) translocation. This novel splicing variant involves an in-frame fusion between exon 38 of CNTRL and exon 11 of FGFR1, retaining the kinase domain of FGFR1 and leading to its constitutive activation. Despite multiple treatment regimens, the patient failed to achieve complete remission (CR). Conclusion The findings highlight the urgent need for targeted therapies, such as FGFR inhibitors, to improve outcomes in patients with FGFR1-rearranged malignancies. Show less
📄 PDF DOI: 10.1007/s12308-025-00670-6
FGFR1
Yicheng Yan, Tianyi Liu, Xiaopeng He +2 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
Bats are natural reservoirs for diverse viruses, yet they rarely develop disease, suggesting unique antiviral adaptations. In this study, we performed a comprehensive genome-wide analysis in the commo Show more
Bats are natural reservoirs for diverse viruses, yet they rarely develop disease, suggesting unique antiviral adaptations. In this study, we performed a comprehensive genome-wide analysis in the common vampire bat ( Show less
📄 PDF DOI: 10.3390/ani15213063
FGFR1
Zhuo Liu, Dandan Zhao, Baoming Wang +14 more · 2025 · The oncologist · Oxford University Press · added 2026-04-24
Despite the increasing approval and ongoing clinical trials of FGFR-targeted therapies, accurately detecting FGFR fusions remains a challenge due to limited research, low incidence rates, complex fusi Show more
Despite the increasing approval and ongoing clinical trials of FGFR-targeted therapies, accurately detecting FGFR fusions remains a challenge due to limited research, low incidence rates, complex fusion partner distribution, and unique kinase domain distribution. We conducted a multicenter study to comprehensively profile FGFR fusions in the largest Chinese pan-cancer cohort to date, comprising 118 FGFR fusions from 114 individuals. Both DNA- and RNA-based sequencing approaches were utilized to reveal novel and fundamental features of FGFR fusion. Our research reveals an incidence rate of 0.96% for FGFR rearrangements within this Chinese cohort, including a high incidence rate of FGFR fusions (40%) in parotid gland carcinoma. However, this is based on a small sample size of 5 tumors and should be interpreted cautiously pending validation in larger cohorts. We also uncovered distinct breakpoint distribution patterns across various FGFR rearrangements. For example, a primary breakpoint in intron17 of FGFR2 was predominant (21/22), while FGFR1/3 breakpoints displayed substantial diversity. For the first time, we identified "hot" breakpoints in FGFR1 intron17, exon18, and FGFR3's 3' untranslated region. These findings underline the importance of incorporating these regions in targeted sequencing to ensure comprehensive detection of FGFR1/3 fusions. Notably, we observed a predilection for intrachromosomal distribution in common FGFR1/2/3 fusions. In contrast, most novel fusions (12/15) exhibited an interchromosomal distribution pattern, indicating variations in the fusion formation mechanism. Importantly, our study demonstrates the substantial incremental value of RNA-NGS or other orthogonal methods in confirming the functionality of FGFR rearrangements initially identified by DNA sequencing. In our cohort, 46% (6/13) of rare FGFR1/2/3 fusions lacked detectable RNA transcripts; however, this does not definitively indicate non-functionality as factors such as low RNA quality, expression below detection limits, or nonsense-mediated decay may contribute. Therefore, RNA-based validation is critical for accurately identifying potentially targetable FGFR fusions and guiding therapy. Our findings offer critical novel insights into functional FGFR fusions and bear considerable clinical implications for identifying individuals whose tumors are most likely to respond favorably to FGFR-targeted therapies. Show less
📄 PDF DOI: 10.1093/oncolo/oyaf347
FGFR1
Mei Peng, Weifan Wang, Di Xiao +7 more · 2025 · Cancer biology & medicine · added 2026-04-24
Osimertinib (OSI) therapy, a cornerstone in treating non-small cell lung cancer (NSCLC), has been severely limited by rapidly developing acquired resistance. Inhibition of bypass activation using a co Show more
Osimertinib (OSI) therapy, a cornerstone in treating non-small cell lung cancer (NSCLC), has been severely limited by rapidly developing acquired resistance. Inhibition of bypass activation using a combination strategy holds promise in overcoming this resistance. Biguanides, with excellent anti-tumor effects, have recently attracted much attention for this potential. The current study investigated whether novel biguanide compounds developed by our team could overcome OSI resistance and the underlying mechanisms were explored. A comprehensive screening assay using OSI-resistant cells identified the optimal combination of biguanide compounds with OSI. Proteomics, co-immunoprecipitation mass spectrometry, RNA sequencing, and homologous recombination assays were used to elucidate the molecular mechanisms underlying combination therapy. NSCLC tumor tissues, especially OSI-resistant tissues, obtained from our clinic were used to assess the correlations between key proteins and OSI resistance. SMK-010, a highly potent biguanide compound, effectively overcame OSI resistance These findings highlight the crucial role of the BMI1/FGFR1 axis in OSI resistance and provide a rational basis for the future clinical application of the biguanide, SMK-010, in combination with OSI. Show less
📄 PDF DOI: 10.20892/j.issn.2095-3941.2025.0209
FGFR1
Jiyu Huang, Zihan Wang, Fei Zhao +7 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
This article aims to analyze the safety and efficacy of Erdafitinib in the treatment of patients with advanced solid tumors harboring FGFR1-4 mutations. Search for relevant articles in databases such Show more
This article aims to analyze the safety and efficacy of Erdafitinib in the treatment of patients with advanced solid tumors harboring FGFR1-4 mutations. Search for relevant articles in databases such as PubMed, Embase, The Cochrane Library, Web of Science, and CNKI, covering the period from their establishment to October 25, 2024. Summarize the adverse drug reaction (AE) data, overall survival (OS), median progression-free survival (PFS), objective response rate (ORR), and other relevant data for patients with advanced solid tumors treated with Erdafitinib for FGFR1-4 mutations. Conduct a meta-analysis on the corresponding summarized data using the software Stata 18.0. Through our search, we identified a total of 10 articles involving 1019 patients. In urothelial carcinoma, the most prevalent adverse reactions are hyperphosphatemia (78.5%), diarrhea (56.5%), and stomatitis (51.1%). The most frequently reported adverse reactions in other solid tumors are hyperphosphatemia (66.5%), dry mouth (48.5%), and diarrhea (44.9%). Patients with urothelial carcinoma treated with Erdafitinib exhibit higher median progression-free survival (PFS) and objective response rate (ORR) compared to those treated with other solid tumor therapies. Current evidence indicates that Erdafitinib exhibits certain therapeutic efficacy in the treatment of advanced solid tumors harboring FGFR1-4 mutations, with the most pronounced therapeutic effect observed in urothelial carcinoma. The efficacy of Erdafitinib in treating other solid tumors requires further confirmation through larger-scale studies involving a broader range of FGFR1-4 mutant tumors. Show less
📄 PDF DOI: 10.3389/fonc.2025.1571434
FGFR1
Jongpil Shin, Hyeonsik Oh, Ji Hye Park +5 more · 2025 · Experimental & molecular medicine · Nature · added 2026-04-24
Major depressive disorder (MDD) is a complex psychological disorder with a sophisticated molecular etiology. Although its connection with fibroblast growth factor receptor 1 (FGFR1) in the hippocampus Show more
Major depressive disorder (MDD) is a complex psychological disorder with a sophisticated molecular etiology. Although its connection with fibroblast growth factor receptor 1 (FGFR1) in the hippocampus is known, the precise mechanisms underlying its pathophysiology remain unclear. Here we conduct a comprehensive analysis of the molecular profile of the hippocampus in patients with MDD. We identified a distinct overexpression of FGFR1 specifically within the dentate gyrus of patients with MDD. Through the use of optogenetic techniques for the in vivo spatiotemporal dissection of FGFR1 signaling, we uncovered a sequential FGFR1-Notch-brain-derived neurotrophic factor (BDNF) pathway within the dentate gyrus, which can ultimately induce adult hippocampal neurogenesis, significantly contributing to antidepressant effects. We discovered that the dysregulation of this axis by the protein Numb, which demonstrates an age-related increase in individuals with MDD, is closely associated with the development of depressive phenotypes. Remarkably, targeting Numb to restore this axis effectively reversed the depressive phenotype, thus offering new insights into potential therapeutic strategies. Show less
📄 PDF DOI: 10.1038/s12276-025-01519-9
FGFR1
Hong Luo, Liwei Wang, Hui Gao +13 more · 2025 · Biomedicines · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/biomedicines13071667
FGFR1
Kun Lian, Wei Yang, Runxu Yang +2 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Schizophrenia (SCZ) is a chronic, relapsing mental disorder with a complex and poorly understood etiology. Identifying novel therapeutic targets is essential for advancing treatment options. Druggable Show more
Schizophrenia (SCZ) is a chronic, relapsing mental disorder with a complex and poorly understood etiology. Identifying novel therapeutic targets is essential for advancing treatment options. Druggable genes were sourced from the eQTLGen consortium and integrated with SCZ-related GWAS data. Two-sample Mendelian randomization (MR) and co-localization analyses assessed the likelihood of shared pathogenic variants between the expression quantitative trait loci (eQTL) of these genes and SCZ. Positive results were further validated using Summary-based MR (SMR). Phenome-wide association studies, drug prediction, and molecular docking analyses were also conducted to identify potential therapeutic targets among these genes. SMR analysis revealed six druggable genes significantly associated with SCZ: NMB, IK, FGFR1, SERPING1, EDEM2, and CTSS. Molecular docking studies demonstrated favorable binding energies for PD 173074-FGFR1 (- 8.1407 kcal/mol), WZ-7043-FGFR1 (- 7.8027 kcal/mol), and lenvatinib-FGFR1 (- 7.3075 kcal/mol). Single-cell expression analysis further indicated that FGFR1 is predominantly expressed in mural cells, suggesting its potential role in SCZ pathogenesis. This study identifies six druggable genes as potential therapeutic targets for SCZ, with FGFR1 emerging as a particularly promising candidate. These findings provide valuable insights for SCZ treatment development and position FGFR1 as a viable target for future therapeutic strategies. Show less
📄 PDF DOI: 10.1007/s12035-025-05221-9
FGFR1
Xiaoyu Yang, Wenlong Liang, Zhenchu Feng +3 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Polychlorinated biphenyls (PCBs) are environmental pollutants associated with various health issues, including breast cancer. This study investigates potential molecular mechanisms by which PCBs may i Show more
Polychlorinated biphenyls (PCBs) are environmental pollutants associated with various health issues, including breast cancer. This study investigates potential molecular mechanisms by which PCBs may influence breast cancer progression using computational and preliminary experimental approaches. We conducted a differential expression analysis using the TCGA-BRCA dataset. PCBs-related toxicological targets were collected from the Comparative Toxicogenomics Database (CTD). Enrichment and pathway analyses identified candidate biological processes and pathways. Protein-protein interaction (PPI) networks were constructed to identify hub genes. Single-cell expression levels of key targets were analyzed (GSE114727 dataset). Molecular docking predicted binding affinities of PCBs congeners with key targets. Cell experiments assessed gene expression changes upon PCBs exposure. We identified 52 upregulated and 24 downregulated PCBs-related toxicological targets in breast cancer. Enrichment analysis highlighted potential associations with pathways such as PI3K-Akt, MAPK, and HIF-1, including genes like BRCA1, FGFR1, IGF1, AKT1, and EGF. PPI network analysis identified key hub genes like EZH2, EGF, BRCA1, AKT1, IL6, and TNF. Single-cell analysis suggested variable expression of key targets across immune cell types. Molecular docking predicted strong binding affinities of PCB 105 with EZH2 and EGF Our integrated analysis proposes that PCBs exposure may perturb key molecular pathways in breast cancer. Computational findings implicate targets like EZH2 and EGF, while preliminary cell experiments support further investigation. These results highlight a need for mechanistic studies to confirm PCB-induced effects and their therapeutic relevance, underscoring environmental pollutants as potential risk factors in cancer. Show less
📄 PDF DOI: 10.3389/fphar.2025.1604993
FGFR1
Dongchen Xu, Min Wen, Bingwa Lebohang Anesu +10 more · 2025 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
Ischemic stroke (IS) remains a leading cause of mortality and disability, with limited therapeutic options due to poor drug delivery to ischemic lesions. To address this challenge, an engineered Salmo Show more
Ischemic stroke (IS) remains a leading cause of mortality and disability, with limited therapeutic options due to poor drug delivery to ischemic lesions. To address this challenge, an engineered Salmonella based therapeutic method for targeted drug delivery and long-term treatment is herein designed to mitigate ischemic damage. We engineered an attenuated luminescent Salmonella typhimurium (S.t -ΔpG) strain with an L-arabinose-inducible pBAD system to secrete bioactive FGF21. C57BL/6 mice were used to to measure neuron apoptosis and the activity of immune cells following IS induction plus S.t-ΔpG injection. Bioluminescence imaging was applied for bacterial colonization. ELISA and glucose uptake assays were performed to detect FGF21 secretion and the bioactivity. Neurological tests, TTC staining, and TUNEL labeling were used to assess the therapeutic effects of barterially secreted FGF21. Immunofluorescence assay of FGF21/FGFR1 dominant pathway was explored to investigate neuroprotective mechanism, while IBA-1 staining, CD3/CD68 immunostaining, cytokine profiling, and hepatorenal histopathology were detected to evaluate biosecurity. S.t-ΔpG Our study presents a novel, Salmonella - based platform for targeted and sustained FGF21 delivery, offering a promising therapeutic strategy for ischemic stroke with robust efficacy and minimal systemic toxicity. Show less
📄 PDF DOI: 10.1186/s12974-025-03498-0
FGFR1
Yue Yang, Yunhan Wang, Zhou Zheng +2 more · 2025 · General physiology and biophysics · added 2026-04-24
Bladder cancer (BLCA) is a prevalent urological malignancy. We aim to identify novel biomarkers for BLCA and elucidate the specific regulatory mechanisms of polo-like kinase 1 (PLK1). Using differenti Show more
Bladder cancer (BLCA) is a prevalent urological malignancy. We aim to identify novel biomarkers for BLCA and elucidate the specific regulatory mechanisms of polo-like kinase 1 (PLK1). Using differentially expressed genes (DEGs) screened from GSE38264 and GSE130598 datasets, we constructed protein-protein interaction networks to identify hub genes, whose expression was validated using reverse transcription-quantitative polymerase chain reaction. The malignant phenotype of BLCA cells was assessed by Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine, Transwell, and wound-healing assays. Hematoxylin-eosin and immunohistochemical staining were employed to evaluate BLCA development in mouse xenograft models. The protein expression was detected by Western blot. PLK1, AURKA, AURKB, CDK1, ERBB2, ERBB3, FGFR1, FYN, ABL1, and PRKDC were hub genes with predictive value for BLCA. Among them, PLK1 was selected as a key target of BLCA. PLK1 knockdown inhibited the viability, proliferation, migration, and invasion of BLCA cells. In vivo, PLK1 knockdown inhibited tumor growth. Silencing PLK1 activated the Hippo pathway in BLCA cells and tumor tissues. The Hippo pathway inhibitor reversed the inhibitory effects of PLK1 silencing on malignant phenotype of BLCA cells. PLK1 knockdown exerts an inhibitory effect on BLCA via activating the Hippo pathway, which presents promising therapeutic strategies for BLCA. Show less
no PDF DOI: 10.4149/gpb_2025015
FGFR1
Ivan Li, Yuchen Huo, Ting Yang +3 more · 2025 · Cancer drug resistance (Alhambra, Calif.) · added 2026-04-24
📄 PDF DOI: 10.20517/cdr.2024.208
FGFR1
Yujie Shi, Lexia Chen, Qiong Cheng +3 more · 2025 · Cancer drug resistance (Alhambra, Calif.) · added 2026-04-24
📄 PDF DOI: 10.20517/cdr.2024.181
FGFR1
Yanzhen Yang, Qu Xie, Chuankai Shang +4 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumor with a poor prognosis, despite the emergence of chemotherapies such as gemcitabine plus albumin-bound paclitaxel (nab-paclitaxel, A Show more
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumor with a poor prognosis, despite the emergence of chemotherapies such as gemcitabine plus albumin-bound paclitaxel (nab-paclitaxel, AG), unmet medical needs still exist for patients with metastatic PDAC (mPDAC). Surufatinib is a small-molecule tyrosine kinase inhibitor targets vascular endothelial growth factor (VEGFR) 1, 2, 3, fibroblast growth factor receptor 1 (FGFR1), and colony stimulating factor 1 receptor (CSF-1R). This single-center, retrospective study evaluates the potential efficacy of combination therapy containing Surufatinib in advanced or metastatic pancreatic cancer. We conducted a real world retrospective study of mPDAC patients who received the Surufatinib between July 2022 and July 2023 at Zhejiang Cancer Hospital. In addition, patients who received first line chemotherapy at the same period were analyzed as comparison. As of November 20, 2024, 20 eligible patients were identified in this retrospective study. The median progression-free survival (mPFS) of patients who received Surufatinib treatment was 5.27 months (95% CI, 2.55-7.98), and the median overall survival(mOS) was 9.93 months (95% CI,6.55-13.32). For fist line treatment, 9 patients received Surufatinib combined with immune checkpoint inhibitors (ICIs) and chemo and the mPFS was 7.5 months (95% CI, 3.14-11.85), compared with an mPFS of 5.43 months (95% CI, 3.89-6.96) for 52 mPDAC patients received chemotherapy at the same period. Grade 3 or above Treatment Related Adverse Event (TRAE) were neutrophil count decreased (10%), and white blood cell count decreased (5%). Preliminary data suggest that surufatinib shows potential therapeutic benefit in mPDAC, but its efficacy needs to be further validated. This combination strategy may provide a new treatment option for patients, especially in the first-line setting. Future studies will expand the sample size and include additional evaluation parameters to fully assess its efficacy and safety. ClinicalTrials, identifier NCT06378580. Show less
📄 PDF DOI: 10.3389/fonc.2025.1574934
FGFR1
Heqi Yang, Yuhang Ma, Chenyan Zhang +4 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Pancreatic cancer is characterized by a poor prognosis and limited responsiveness to conventional therapies, presenting a substantial therapeutic challenge. Although chemotherapy remains the cornersto Show more
Pancreatic cancer is characterized by a poor prognosis and limited responsiveness to conventional therapies, presenting a substantial therapeutic challenge. Although chemotherapy remains the cornerstone of systemic treatment, options become scarce once frontline therapies fail. While targeted therapies and immunotherapies have emerged as potential alternatives, their efficacy in pancreatic cancer is not well established. As research advances, exploring the tumor immune microenvironment (TiME) of pancreatic cancer is crucial and holds significant potential for developing novel treatment strategies.We report a case of a pancreatic cancer patient who, after the failure of frontline and second-line treatments, was treated with a pioneering combination of targeted therapy and immunotherapy to modulate the unique TiME. The targeted agent, surufatinib, is a tyrosine kinase inhibitor (TKI) that targets vascular endothelial growth factor receptor (VEGFR) 1-3, fibroblast growth factor receptor 1 (FGFR1), and colony-stimulating factor 1 receptor (CSF-1R). The immunotherapy agent, toripalimab, is an immune checkpoint inhibitor targeting programmed cell death protein 1 (PD-1). Remarkably, the patient benefitted from this regimen, exhibiting stable disease, improved clinical symptoms, and prolonged progression-free survival. This case highlights the potential of personalized therapy in treating pancreatic cancer, particularly in patients with distinctive features of the TiME that may predict favorable responses to immunotherapy. Personalized strategies that consider the spatial structure and composition of the TiME may offer a promising avenue for achieving long-term progression-free survival in patients with pancreatic cancer. Show less
📄 PDF DOI: 10.3389/fimmu.2025.1547388
FGFR1