ICAM-1-Targeted, Lcn2 siRNA-Encapsulating Liposomes are Potent Anti-angiogenic Agents for Triple Negative Breast Cancer

三阴性乳腺癌 脂质体 药理学 乳腺癌 医学 癌症研究 癌症 化学 内科学 生物化学
作者
Peng Guo,Jiang Yang,Di Jia,Marsha A. Moses,Debra T. Auguste
出处
期刊:Theranostics [Ivyspring International Publisher]
卷期号:6 (1): 1-13 被引量:120
标识
DOI:10.7150/thno.12167
摘要

Lipocalin 2 (Lcn2) is a promising therapeutic target as well as a potential diagnostic biomarker for breast cancer.It has been previously shown to promote breast cancer progression by inducing the epithelial to mesenchymal transition in breast cancer cells as well as by enhancing angiogenesis.Lcn2 levels in urine and tissue samples of breast cancer patients has also been correlated with breast cancer status and poor patient prognosis.In this study, we have engineered a novel liposomal small interfering RNA (siRNA) delivery system to target triple negative breast cancer (TNBC) via a recently identified molecular target, intercellular adhesion molecule-1 (ICAM-1).This ICAM-1-targeted, Lcn2 siRNA-encapsulating liposome (ICAM-Lcn2-LP) binds human TNBC MDA-MB-231cells significantly stronger than non-neoplastic MCF-10A cells.Efficient Lcn2 knockdown by ICAM-Lcn2-LPs led to a significant reduction in the production of vascular endothelial growth factor (VEGF) from MDA-MB-231 cells, which, in turn, led to reduced angiogenesis both in vitro and in vivo.Angiogenesis (neovascularization) is a requirement for solid tumor growth and progression, and its inhibition is an important therapeutic strategy for human cancers.Our results indicate that a tumor-specific strategy such as the TNBC-targeted, anti-angiogenic therapeutic approach developed here, may be clinically useful in inhibiting TNBC progression.
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
刚刚
搜集达人应助文鞅采纳,获得30
刚刚
刚刚
1秒前
2秒前
ni发布了新的文献求助10
2秒前
2秒前
3秒前
科研通AI2S应助Devoted采纳,获得10
3秒前
3秒前
海上发布了新的文献求助10
3秒前
太叔易云发布了新的文献求助10
3秒前
3秒前
qingshiguang完成签到,获得积分10
4秒前
杰杰完成签到,获得积分10
4秒前
冰魂应助叙樊川采纳,获得10
4秒前
小周发布了新的文献求助10
5秒前
小熊发布了新的文献求助10
5秒前
5秒前
zrm发布了新的文献求助60
5秒前
CcC完成签到,获得积分10
6秒前
7秒前
8秒前
zydd发布了新的文献求助10
9秒前
9秒前
赤电鼠鼠发布了新的文献求助10
9秒前
10秒前
gshsj发布了新的文献求助10
10秒前
烟花应助陶醉元枫采纳,获得10
10秒前
hjyylab应助111采纳,获得20
10秒前
10秒前
10秒前
10秒前
10秒前
10秒前
Lei-sir完成签到 ,获得积分10
11秒前
13秒前
慕青应助hm采纳,获得10
13秒前
喵喵发布了新的文献求助10
13秒前
忧郁的风华完成签到,获得积分10
14秒前
高分求助中
Applied Survey Data Analysis (第三版, 2025) 800
Assessing and Diagnosing Young Children with Neurodevelopmental Disorders (2nd Edition) 700
Images that translate 500
Algorithmic Mathematics in Machine Learning 500
Handbook of Innovations in Political Psychology 400
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Nucleophilic substitution in azasydnone-modified dinitroanisoles 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3842039
求助须知:如何正确求助?哪些是违规求助? 3384234
关于积分的说明 10533093
捐赠科研通 3104526
什么是DOI,文献DOI怎么找? 1709663
邀请新用户注册赠送积分活动 823319
科研通“疑难数据库(出版商)”最低求助积分说明 773953