Suppr超能文献

以肿瘤相关巨噬细胞为靶点进行癌症治疗。

Targeting tumor-associated macrophages for cancer treatment.

作者信息

Li Mengjun, He Linye, Zhu Jing, Zhang Peng, Liang Shufang

机构信息

State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, No.17, 3rd Section of People's South Road, 610041, Chengdu, China.

Department of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, 610041, China.

出版信息

Cell Biosci. 2022 Jun 7;12(1):85. doi: 10.1186/s13578-022-00823-5.

Abstract

Tumor-associated macrophages (TAMs) are abundant, nearly accounting for 30-50% of stromal cells in the tumor microenvironment. TAMs exhibit an immunosuppressive M2-like phenotype in advanced cancer, which plays a crucial role in tumor growth, invasion and migration, angiogenesis and immunosuppression. Consequently, the TAM-targeting therapies are particularly of significance in anti-cancer strategies. The application of TAMs as anti-cancer targets is expected to break through traditional tumor-associated therapies and achieves favorable clinical effect. However, the heterogeneity of TAMs makes the strategy of targeting TAMs variable and uncertain. Discovering the subset specificity of TAMs might be a future option for targeting TAMs therapy. Herein, the review focuses on highlighting the different modalities to modulate TAM's functions, including promoting the phagocytosis of TAMs, TAMs depletion, blocking TAMs recruitment, TAMs reprogramming and suppressing immunosuppressive tumor microenvironment. We also discuss about several ways to improve the efficacy of TAM-targeting therapy from the perspective of combination therapy and specificity of TAMs subgroups.

摘要

肿瘤相关巨噬细胞(TAM)数量众多,几乎占肿瘤微环境中基质细胞的30%-50%。在晚期癌症中,TAM表现出免疫抑制性的M2样表型,在肿瘤生长、侵袭和迁移、血管生成及免疫抑制中起关键作用。因此,靶向TAM的疗法在抗癌策略中尤为重要。将TAM作为抗癌靶点的应用有望突破传统的肿瘤相关疗法并取得良好的临床效果。然而,TAM的异质性使得靶向TAM的策略多变且不确定。发现TAM的亚群特异性可能是未来靶向TAM治疗的一个选择。在此,本综述着重强调调节TAM功能的不同方式,包括促进TAM的吞噬作用、清除TAM、阻断TAM募集、重编程TAM以及抑制免疫抑制性肿瘤微环境。我们还从联合治疗和TAM亚群特异性的角度讨论了几种提高靶向TAM治疗疗效的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a26/9172100/93a6eacbdbb3/13578_2022_823_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验