Co‐assembled Manganese‐CpG Nanoliposomes for Enhanced Immunotherapy against Colon Cancer Stem Cells

癌症研究 干细胞 结直肠癌 癌症免疫疗法 免疫疗法 CpG站点 癌症 癌症干细胞 材料科学 医学 化学 生物 内科学 生物化学 细胞生物学 DNA甲基化 基因 基因表达 冶金
作者
Weijian Zhao,Siyu Sun,Xuesong He,Yiran Liu,Jing Meng,Qin Hu,Wang Sheng,Runqing Jia
出处
期刊:Advanced Healthcare Materials [Wiley]
卷期号:14 (20): e2500545-e2500545 被引量:2
标识
DOI:10.1002/adhm.202500545
摘要

Nanovaccines represent a promising strategy for colon cancer immunotherapy, with the potential to elicit potent, tumor-specific immune responses. However, the efficacy of these vaccines is often compromised by the presence of cancer stem cells (CSCs) in the tumor microenvironment (TME). Nanoliposome (NLP) is a widely used delivery system in nucleic acid and drug delivery research. In this study, we enriched MC38-derived CSCs (MCSCs) and developed a manganese-CpG-nanoliposome (Mn@CpG@NLP) nanocomplex using MC38 colon carcinoma tumor lysates as antigens to induce immune responses against MCSCs-derived tumors. Manganese NLPs (Mn@NLP) are initially engineered by incorporating manganese ions to enhance their positive surface charge, thereby optimizing their interaction with cellular membranes and activating the STING signaling pathway to promote bone marrow-derived dendritic cells (BMDCs) maturation. Subsequently, these liposomes are co-assembled with the CpG oligonucleotides (CpG ODNs) 1826 adjuvant, a Toll-like receptor 9 agonist, through electrostatic interactions to form the Mn@CpG@NLP nano-adjuvant complex. The Mn@CpG@NLP complex is efficiently taken up by dendritic cells (DCs), leading to their maturation and activation. This nanocomplex also effectively stimulated cytotoxic T lymphocytes and promoted the secretion of cytokines. In vivo treatment with Mn@CpG@NLP significantly inhibited tumor growth and prolonged survival in a mouse model. This study highlights the potential of nano-adjuvant platforms in immunotherapy targeting cancers driven by colon CSCs.
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
十六发布了新的文献求助10
刚刚
科目三应助科研通管家采纳,获得10
刚刚
自信鹭洋完成签到 ,获得积分10
刚刚
刚刚
和谐元霜发布了新的文献求助10
刚刚
AAAAA完成签到,获得积分0
刚刚
向阳完成签到,获得积分10
1秒前
鱼柒发布了新的文献求助10
1秒前
CodeCraft应助yuyyy采纳,获得10
2秒前
帝青坤灵完成签到,获得积分10
2秒前
今夜有雨发布了新的文献求助10
2秒前
高处无雨发布了新的文献求助10
3秒前
煎饼煎饼发布了新的文献求助10
3秒前
3秒前
科研小白完成签到,获得积分20
3秒前
pcg发布了新的文献求助10
4秒前
4秒前
4秒前
Tickle发布了新的文献求助50
4秒前
上官若男应助陈丽陈丽采纳,获得10
4秒前
ansteel应助可靠的紫雪采纳,获得10
5秒前
wl完成签到,获得积分10
5秒前
5秒前
6秒前
6秒前
6秒前
YY关注了科研通微信公众号
6秒前
dd的mm发布了新的文献求助10
7秒前
l1发布了新的文献求助10
7秒前
Ava应助不吃橘子采纳,获得10
7秒前
8秒前
传奇3应助SZA采纳,获得10
8秒前
8秒前
潮小坤发布了新的文献求助10
9秒前
9秒前
9秒前
9秒前
天天快乐应助鱼柒采纳,获得10
9秒前
Robby完成签到 ,获得积分10
10秒前
一水入秋完成签到,获得积分10
10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
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
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 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 7606681
求助须知:如何正确求助?哪些是违规求助? 9182517
关于积分的说明 19666907
捐赠科研通 7180885
什么是DOI,文献DOI怎么找? 3269632
关于科研通互助平台的介绍 2433550
邀请新用户注册赠送积分活动 2263858