Enhancing precision targeting of ovarian cancer tumor cells in vivo through extracellular vesicle engineering

卵巢癌 癌细胞 体内 癌症研究 细胞生物学 离体 微泡 癌症 生物 小RNA 生物化学 生物技术 遗传学 基因
作者
Mona Alharbi,Andrew Lai,Nihar Godbole,Dominic Guanzon,Soumyalekshmi Nair,Felipe Zúñiga,Alexander Quinn,Mengliu Yang,Sherry Y. Wu,Carlos Salomón
出处
期刊:International Journal of Cancer [Wiley]
标识
DOI:10.1002/ijc.35055
摘要

Abstract Extracellular vesicles (EVs) function as natural mediators of intercellular communication, secreted by cells to facilitate cell–cell signaling. Due to their low toxicity, immunogenicity, biodegradability, and potential to encapsulate therapeutic drugs, EVs hold significant therapeutic promise. Nevertheless, their limited targeting ability often diminishes their therapeutic impact. Therefore, enhancing EVs by incorporating targeting units onto their membranes could bolster their targeting capabilities, enabling them to accumulate in specific cells and tissues. In this study, we engineered EVs to fuse ephrin‐B2 with the EV membrane protein LAMP2b. This modification aimed to direct the engineered EVs toward the ephrin‐B4 receptor expressed on the surface of ovarian cancer cells. The engineered EVs retained their inherent properties, including size, expression of EV membrane proteins, and morphology, upon isolation. In vitro experiments using real‐time imaging revealed that EVs engineered with the ephrin‐B2 ligand exhibited substantial internalization and uptake by ovarian cancer cells, in stark contrast to native EVs. In vivo, the engineered EVs carrying the ephrin‐B2 ligand effectively targeted ovarian cancer cells, surpassing the targeting efficiency of control EVs. This innovative approach establishes a novel targeting system, enhancing the uptake of EVs by ovarian cancer cells. Our findings underscore the potential of using EVs to target cancer cells, thereby enhancing the effectiveness of anti‐cancer therapies while minimizing off‐target effects and toxicity in normal cells and organs.
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
周凡淇发布了新的文献求助10
刚刚
song完成签到 ,获得积分10
1秒前
TK发布了新的文献求助10
1秒前
神经完成签到,获得积分20
2秒前
纯真的笑珊完成签到,获得积分10
2秒前
瓜瓜瓜咕发布了新的文献求助30
2秒前
3秒前
3秒前
4秒前
小小发布了新的文献求助10
4秒前
4秒前
5秒前
jing发布了新的文献求助10
5秒前
寒冷天亦发布了新的文献求助10
5秒前
LienAo完成签到 ,获得积分10
5秒前
6秒前
ding应助梦想家健康采纳,获得10
6秒前
Lucas应助注意脚下采纳,获得10
7秒前
YoungLee发布了新的文献求助10
7秒前
8秒前
CE发布了新的文献求助10
9秒前
dfsdf完成签到,获得积分10
9秒前
恩恩发布了新的文献求助10
10秒前
10秒前
NE发布了新的文献求助20
10秒前
11秒前
11秒前
晚晚完成签到 ,获得积分10
11秒前
小小完成签到,获得积分10
11秒前
刮风这天完成签到,获得积分10
13秒前
田様应助asdfqwer采纳,获得10
13秒前
14秒前
14秒前
15秒前
勘大山完成签到,获得积分10
16秒前
Springgg发布了新的文献求助10
16秒前
CodeCraft应助kyrie采纳,获得10
18秒前
共享精神应助寒冷天亦采纳,获得10
18秒前
狗蛋000发布了新的文献求助10
19秒前
20秒前
高分求助中
Continuum thermodynamics and material modelling 3000
Production Logging: Theoretical and Interpretive Elements 2500
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 2000
Applications of Emerging Nanomaterials and Nanotechnology 1111
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Theory of Block Polymer Self-Assembly 750
지식생태학: 생태학, 죽은 지식을 깨우다 700
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3483356
求助须知:如何正确求助?哪些是违规求助? 3072736
关于积分的说明 9127609
捐赠科研通 2764309
什么是DOI,文献DOI怎么找? 1517091
邀请新用户注册赠送积分活动 701898
科研通“疑难数据库(出版商)”最低求助积分说明 700770