Flexible Three-Dimensional Net for Intravascular Fishing of Circulating Tumor Cells

循环肿瘤细胞 化学 网(多面体) 转移 肿瘤细胞 癌症研究 癌症 内科学 生物 医学 几何学 数学
作者
Shi‐Bo Cheng,Ming Wang,Chi Zhang,Miaomiao Chen,Yi‐Ke Wang,Shan Tian,Na Zhan,Weiguo Dong,Min Xie,Wei‐Hua Huang
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:92 (7): 5447-5455 被引量:17
标识
DOI:10.1021/acs.analchem.0c00203
摘要

Current strategies for in vitro isolation of circulating tumor cells (CTCs) fail to detect extremely rare CTCs heterogeneously distributed in blood. It is possible to devise methods for in vivo capture of CTCs based on processing almost all of the blood in the human body to improve detection sensitivity, but the complicated manipulation, biosafety concerns, and limited capture efficiency of conventional detection strategies prohibit their implementation in the clinic. Herein, we present a flexible three-dimensional (3-D) CTC-Net probe for intravascular collection of CTCs. The CTC-Net, consisting of a 3-D elastic scaffold with an interconnected, spatially distributed network accommodates a large quantity of immobilized antibodies and provides an enhanced substrate-cell contact frequency, which results in an enhanced capture efficiency and effective detection of heterogeneous CTCs. The as-prepared CTC-Net can be readily compressed and injected into blood vessels and fully unfolded to form a 3-D "fishing-net" structure for capture of the CTCs, and then retracted for imaging and downstream gene analysis of the captured CTCs. Significant advantages for the CTC-Net over currently available in vitro and in vivo procedures are demonstrated for detection of extremely rare CTCs from wild-type rats and successful capture of CTCs and CTC clusters before metastasis in the case of tumor-bearing rats. Our research demonstrates for the first time the use of a 3-D scaffold CTC-Net probe for in vivo capture of CTCs. The method shows exceptional performance for cell capture, which is readily implemented and holds great potential in the clinic for early diagnosis of cancer.

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
1秒前
YWD发布了新的文献求助10
1秒前
Gins完成签到,获得积分10
2秒前
5秒前
5秒前
moriaty完成签到,获得积分10
6秒前
可爱的函函应助史一采纳,获得10
7秒前
7秒前
7秒前
dyan完成签到,获得积分10
7秒前
8秒前
9秒前
彩色的书翠完成签到,获得积分10
10秒前
科研通AI6.1应助南晚采纳,获得10
11秒前
天真的棉花糖完成签到 ,获得积分10
11秒前
moriaty发布了新的文献求助100
12秒前
12秒前
12秒前
苦哈哈发布了新的文献求助10
13秒前
13秒前
万事胜意发布了新的文献求助10
16秒前
DaLu发布了新的文献求助10
16秒前
Werner完成签到 ,获得积分10
17秒前
18秒前
mable完成签到,获得积分20
18秒前
19秒前
19秒前
20秒前
mable发布了新的文献求助10
22秒前
LaTeXer应助虚幻的莞采纳,获得30
23秒前
23秒前
lalala发布了新的文献求助10
23秒前
24秒前
郎谋完成签到,获得积分10
24秒前
25秒前
纯情的芷烟关注了科研通微信公众号
25秒前
ikun发布了新的文献求助10
25秒前
28秒前
健壮的绿凝完成签到,获得积分10
29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
Kinesiophobia : a new view of chronic pain behavior 2000
Psychology and Work Today 1000
Research for Social Workers 1000
Mastering New Drug Applications: A Step-by-Step Guide (Mastering the FDA Approval Process Book 1) 800
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5902786
求助须知:如何正确求助?哪些是违规求助? 6762285
关于积分的说明 15753414
捐赠科研通 5026446
什么是DOI,文献DOI怎么找? 2706615
邀请新用户注册赠送积分活动 1654853
关于科研通互助平台的介绍 1601143