Surface Engineering of Natural Killer Cells with CD44‐targeting Ligands for Augmented Cancer Immunotherapy

CD44细胞 癌症研究 免疫疗法 癌细胞 癌症免疫疗法 免疫系统 转移 化学 癌症 细胞生物学 材料科学 细胞 生物 免疫学 生物化学 遗传学
作者
Sungjun Kim,Shujin Li,Ashok Kumar Jangid,Hee Won Park,Dong‐Joon Lee,Han‐Sung Jung,Kyobum Kim
出处
期刊:Small [Wiley]
卷期号:20 (24): e2306738-e2306738 被引量:40
标识
DOI:10.1002/smll.202306738
摘要

Adoptive immunotherapy utilizing natural killer (NK) cells has demonstrated remarkable efficacy in treating hematologic malignancies. However, its clinical intervention for solid tumors is hindered by the limited expression of tumor-specific antigens. Herein, lipid-PEG conjugated hyaluronic acid (HA) materials (HA-PEG-Lipid) for the simple ex-vivo surface coating of NK cells is developed for 1) lipid-mediated cellular membrane anchoring via hydrophobic interaction and thereby 2) sufficient presentation of the CD44 ligand (i.e., HA) onto NK cells for cancer targeting, without the need for genetic manipulation. Membrane-engineered NK cells can selectively recognize CD44-overexpressing cancer cells through HA-CD44 affinity and subsequently induce in situ activation of NK cells for cancer elimination. Therefore, the surface-engineered NK cells using HA-PEG-Lipid (HANK cells) establish an immune synapse with CD44-overexpressing MIA PaCa-2 pancreatic cancer cells, triggering the "recognition-activation" mechanism, and ultimately eliminating cancer cells. Moreover, in mouse xenograft tumor models, administrated HANK cells demonstrate significant infiltration into solid tumors, resulting in tumor apoptosis/necrosis and effective suppression of tumor progression and metastasis, as compared to NK cells and gemcitabine. Taken together, the HA-PEG-Lipid biomaterials expedite the treatment of solid tumors by facilitating a sequential recognition-activation mechanism of surface-engineered HANK cells, suggesting a promising approach for NK cell-mediated immunotherapy.
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
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
zang发布了新的文献求助10
刚刚
刚刚
10发布了新的文献求助10
1秒前
chifan完成签到 ,获得积分10
2秒前
蓝莓发布了新的文献求助10
2秒前
辛勤的鼠标完成签到,获得积分10
2秒前
2秒前
aa发布了新的文献求助30
3秒前
一心扑在搞学术完成签到,获得积分10
3秒前
4秒前
搜集达人应助cheng采纳,获得30
4秒前
5秒前
大模型应助xiaoqin采纳,获得10
6秒前
霓霓完成签到,获得积分10
7秒前
7秒前
7秒前
7秒前
8秒前
Lucas应助平淡的鹤采纳,获得10
9秒前
骡马市的阿强应助Simoni采纳,获得10
10秒前
Few_Li发布了新的文献求助10
10秒前
兑奖券发布了新的文献求助10
11秒前
传奇3应助精明怜南采纳,获得30
11秒前
Pami发布了新的文献求助10
12秒前
彭于晏应助Pami采纳,获得10
12秒前
13秒前
13秒前
科研通AI6.4应助长系青采纳,获得10
13秒前
潇潇雨歇完成签到,获得积分10
14秒前
蓝莓完成签到,获得积分10
14秒前
yordeabese完成签到,获得积分10
17秒前
18秒前
dxdxxd应助pcg采纳,获得10
19秒前
19秒前
19秒前
21秒前
大华完成签到,获得积分10
21秒前
23秒前
xing_xing应助luo采纳,获得20
24秒前
鲲鹏完成签到 ,获得积分10
25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
Römisch-Germanische Forschungen 1000
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7611155
求助须知:如何正确求助?哪些是违规求助? 9186848
关于积分的说明 19681107
捐赠科研通 7185022
什么是DOI,文献DOI怎么找? 3270491
关于科研通互助平台的介绍 2434107
邀请新用户注册赠送积分活动 2265235