药品
药理学
癌症
马普替林
医学
癌症研究
内科学
抗抑郁药
海马体
作者
Sai Tian,Mengting Xu,Xiangxin Geng,Jiansong Fang,Hanchen Xu,Xinying Xue,Hongmei Hu,Qing Zhang,Dianping Yu,Mengmeng Guo,Hongwei Zhang,Jinyuan Lu,Chuanbin Guo,Qun Wang,Sanhong Liu,Weidong Zhang
标识
DOI:10.1002/advs.202410285
摘要
Abstract Immune checkpoint inhibitors (ICIs) are drugs that inhibit immune checkpoint (ICP) molecules to restore the antitumor activity of immune cells and eliminate tumor cells. Due to the limitations and certain side effects of current ICIs, such as programmed death protein‐1, programmed cell death‐ligand 1, and cytotoxic T lymphocyte‐associated antigen 4 (CTLA4) antibodies, there is an urgent need to find new drugs with ICP inhibitory effects. In this study, a network‐based computational framework called m ulti‐ net work algorithm‐driven d rug r epositioning targeting I CP ( Mnet‐DRI ) is developed to accurately repurpose novel ICIs from ≈3000 Food and Drug Administration‐approved or investigational drugs. By applying Mnet‐DRI to PD‐L1, maprotiline (MAP), an antidepressant drug is repurposed, as a potential PD‐L1 modifier for colorectal and lung cancers. Experimental validation revealed that MAP reduced PD‐L1 expression by targeting E3 ubiquitin ligase speckle‐type zinc finger structural protein (SPOP), and the combination of MAP and anti‐CTLA4 in vivo significantly enhanced the antitumor effect, providing a new alternative for the clinical treatment of colorectal and lung cancer.
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