Optimized dose selective HDAC inhibitor tucidinostat overcomes anti-PD-L1 antibody resistance in experimental solid tumors

doi:10.1186/s12916-022-02598-5

	Optimized dose selective HDAC inhibitor tucidinostat overcomes anti-PD-L1 antibody resistance in experimental solid tumors
	Zhang,Pei 1,2; Du,Yang2,3 ; Bai,Hua 1; Wang,Zhijie 1; Duan,Jianchun 1; Wang,Xin 1; Zhong,Jia 1; Wan,Rui 1; Xu,Jiachen 1; He,Xiran 4; Wang,Di 1; Fei,Kailun 1; Yu,Ruofei 1; Tian,Jie 2,5,6; Wang,Jie1
发表期刊	BMC Medicine
	2022-11-09
卷号	20 期号:1
通讯作者	Tian,Jie(jie.tian@ia.ac.cn) ; Wang,Jie(zlhuxi@163.com)
摘要	AbstractBackgroundAlthough immune checkpoint inhibitors (ICIs) have influenced the treatment paradigm for multiple solid tumors, increasing evidence suggests that primary and adaptive resistance may limit the long-term efficacy of ICIs. New therapeutic strategies with other drug combinations are hence warranted to enhance the antitumor efficacy of ICIs. As a novel tumor suppressor, histone deacetylase (HDAC) inhibitor tucidinostat has been successfully confirmed to act against hematological malignancies. However, the underlying mechanisms of action for tucidinostat and whether it can manipulate the tumor microenvironment (TME) in solid tumors remain unclear.MethodsThree murine tumor models (4T1, LLC, and CT26) were developed to define the significant role of different doses of tucidinostat in TME. The immunotherapeutic effect of tucidinostat combined with anti-programmed cell death ligand 1 antibody (aPD-L1) was demonstrated. Furthermore, the effect of tucidinostat on phenotypic characteristics of peripheral blood mononuclear cells (PBMCs) from lung cancer patients was investigated.ResultsWith an optimized dose, tucidinostat could alter TME and promote the migration and infiltration of CD8+ T cells into tumors, partially by increasing the activity of C-C motif chemokine ligand 5 (CCL5) via NF-κB signaling. Moreover, tucidinostat significantly promoted M1 polarization of macrophages and increased the in vivo antitumor efficacy of aPD-L1. Tucidinostat also enhanced the expression of the costimulatory molecules on human monocytes, suggesting a novel and improved antigen-presenting function.ConclusionsA combination regimen of tucidinostat and aPD-L1 may work synergistically to reduce tumor burden in patients with cancer by enhancing the immune function and provided a promising treatment strategy to overcome ICI treatment resistance.
关键词	Tucidinostat Tumor microenvironment PD-L1 CCL5 Solid tumor
DOI	10.1186/s12916-022-02598-5
语种	英语
WOS记录号	BMC:10.1186/s12916-022-02598-5
出版者	BioMed Central
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50476
专题	中国科学院分子影像重点实验室
通讯作者	Tian,Jie; Wang,Jie
作者单位	1.National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Medical Oncology 2.CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 3.The University of Chinese Academy of Sciences 4.Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute; Department of Medical Oncology 5.Beihang University; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine 6.Xidian University; School of Life Science and Technology
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhang,Pei,Du,Yang,Bai,Hua,et al. Optimized dose selective HDAC inhibitor tucidinostat overcomes anti-PD-L1 antibody resistance in experimental solid tumors[J]. BMC Medicine,2022,20(1).
APA	Zhang,Pei.,Du,Yang.,Bai,Hua.,Wang,Zhijie.,Duan,Jianchun.,...&Wang,Jie.(2022).Optimized dose selective HDAC inhibitor tucidinostat overcomes anti-PD-L1 antibody resistance in experimental solid tumors.BMC Medicine,20(1).
MLA	Zhang,Pei,et al."Optimized dose selective HDAC inhibitor tucidinostat overcomes anti-PD-L1 antibody resistance in experimental solid tumors".BMC Medicine 20.1(2022).