Therapeutic targeting of trained immunity

免疫 医学 计算生物学 药理学 免疫学 生物 免疫系统
作者
Willem J. M. Mulder,Jordi Ochando,Leo A. B. Joosten,Zahi A. Fayad,Mihai G. Netea
出处
期刊:Nature Reviews Drug Discovery [Nature Portfolio]
卷期号:18 (7): 553-566 被引量:376
标识
DOI:10.1038/s41573-019-0025-4
摘要

Immunotherapy is revolutionizing the treatment of diseases in which dysregulated immune responses have an important role. However, most of the immunotherapy strategies currently being developed engage the adaptive immune system. In the past decade, both myeloid (monocytes, macrophages and dendritic cells) and lymphoid (natural killer cells and innate lymphoid cells) cell populations of the innate immune system have been shown to display long-term changes in their functional programme through metabolic and epigenetic programming. Such reprogramming causes these cells to be either hyperresponsive or hyporesponsive, resulting in a changed immune response to secondary stimuli. This de facto innate immune memory, which has been termed ‘trained immunity’, provides a powerful ‘targeting framework’ to regulate the delicate balance of immune homeostasis, priming, training and tolerance. In this Opinion article, we set out our vision of how to target innate immune cells and regulate trained immunity to achieve long-term therapeutic benefits in a range of immune-related diseases. These include conditions characterized by excessive trained immunity, such as inflammatory and autoimmune disorders, allergies and cardiovascular disease and conditions driven by defective trained immunity, such as cancer and certain infections. Cells in the innate immune system can display adaptive characteristics that lead to increased responsiveness to secondary stimulation by pathogens. This innate immune memory has been termed ‘trained immunity’. Here, Mulder and colleagues describe the mechanisms responsible for the induction of trained immunity and propose strategies to regulate it as a potential treatment of immune-related diseases.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
cdd完成签到,获得积分10
刚刚
Microbiota完成签到,获得积分10
1秒前
胡杨树2006完成签到,获得积分10
1秒前
甜甜友容完成签到,获得积分10
1秒前
张靖完成签到 ,获得积分10
4秒前
leeheeseung发布了新的文献求助20
5秒前
易槐完成签到 ,获得积分10
5秒前
Nereus完成签到 ,获得积分10
8秒前
可耐的问柳完成签到 ,获得积分10
10秒前
量子星尘发布了新的文献求助150
10秒前
彳亍宣完成签到 ,获得积分10
11秒前
meng完成签到,获得积分10
12秒前
儒雅的如松完成签到 ,获得积分10
13秒前
ok123完成签到 ,获得积分10
14秒前
15秒前
从前慢完成签到 ,获得积分10
16秒前
小白天钓鱼完成签到 ,获得积分10
17秒前
persi完成签到 ,获得积分10
18秒前
科研通AI6应助科研通管家采纳,获得150
24秒前
科研通AI6应助科研通管家采纳,获得10
24秒前
科研通AI5应助科研通管家采纳,获得10
24秒前
科研通AI5应助科研通管家采纳,获得10
24秒前
量子星尘发布了新的文献求助10
30秒前
共享精神应助xingsixs采纳,获得10
32秒前
沁雪完成签到 ,获得积分10
33秒前
nav完成签到 ,获得积分10
35秒前
羽冰酒完成签到 ,获得积分10
35秒前
carl完成签到 ,获得积分10
36秒前
LIUJIE完成签到,获得积分10
37秒前
38秒前
量子星尘发布了新的文献求助10
40秒前
老白完成签到,获得积分10
40秒前
东桑末榆发布了新的文献求助10
41秒前
42秒前
嘎哈完成签到 ,获得积分10
46秒前
8D完成签到,获得积分10
48秒前
49秒前
leeheeseung完成签到,获得积分20
49秒前
shuoliu完成签到 ,获得积分10
51秒前
53秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Acute Mountain Sickness 2000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
Thomas Hobbes' Mechanical Conception of Nature 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5093339
求助须知:如何正确求助?哪些是违规求助? 4306976
关于积分的说明 13417433
捐赠科研通 4133171
什么是DOI,文献DOI怎么找? 2264356
邀请新用户注册赠送积分活动 1268004
关于科研通互助平台的介绍 1203813