Noninvasive Diagnosis and Molecular Phenotyping of Breast Cancer through Microbead‐Assisted Flow Cytometry Detection of Tumor‐Derived Extracellular Vesicles

微珠(研究) 流式细胞术 细胞外小泡 癌细胞 乳腺癌 循环肿瘤细胞 癌症研究 病理 医学 癌症 生物 分子生物学 内科学 细胞生物学 转移 生物化学
作者
Wenzhe Li,Bin Shao,Changliang Liu,Huayi Wang,Wangshu Zheng,Weiyao Kong,Xiaoran Liu,Guobin Xu,Chen Wang,Huiping Li,Ling Zhu
出处
期刊:Small methods [Wiley]
卷期号:2 (11) 被引量:19
标识
DOI:10.1002/smtd.201800122
摘要

Abstract Blood‐based detection and molecular phenotyping are highly desired for the early diagnosis and dynamic monitoring of cancer. Extracellular vesicles (EVs) carry molecular information from the cells of origin and are biomarkers of cancer. However, the detection and molecular analysis of EVs has been challenging due to their nanoscaled size. Here, an assessment of the detection and molecular phenotyping of serum EVs based on microbead‐assisted flow cytometry is established. The clinical utility of this method is validated in the diagnosis and human epidermal growth factor receptor 2 (HER2) phenotyping of breast cancer. Good correlation between the status of epithelial cell adhesion molecule (EpCAM) and HER2 expression in EVs and in the cells of origin is found. Both EpCAM+ and HER2+ EVs are demonstrated to be effective diagnostic markers of breast cancer with high sensitivity and specificity. EV‐based HER2 phenotyping is consistent with tissue‐based HER2 phenotyping by immunohistochemistry and can be used as a surrogate for the invasive tissue assessments. The microbead‐assisted flow cytometry assessment of EVs enables rapid and noninvasive detection and molecular phenotyping of cancer and would help to personalized treatment and cancer survival.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
1秒前
寒冷剑愁完成签到,获得积分10
3秒前
4秒前
Bio_yu721完成签到,获得积分10
4秒前
SOLOMON举报真理求助涉嫌违规
4秒前
小二郎应助小坚强采纳,获得10
4秒前
Amy完成签到,获得积分10
5秒前
Bio_yu721发布了新的文献求助10
6秒前
杏梨发布了新的文献求助10
7秒前
bkagyin应助平常的老六采纳,获得10
8秒前
Vivian完成签到,获得积分20
8秒前
9秒前
名丿完成签到,获得积分10
9秒前
香蕉觅云应助含蓄鼠标采纳,获得10
10秒前
10秒前
10秒前
Akim应助科研通管家采纳,获得10
12秒前
脑洞疼应助科研通管家采纳,获得10
12秒前
Hello应助科研通管家采纳,获得10
12秒前
彭于晏应助科研通管家采纳,获得10
12秒前
完美世界应助科研通管家采纳,获得10
12秒前
香蕉觅云应助科研通管家采纳,获得10
12秒前
隐形曼青应助科研通管家采纳,获得10
13秒前
充电宝应助科研通管家采纳,获得10
13秒前
领导范儿应助科研通管家采纳,获得10
13秒前
阿豆阿豆发布了新的文献求助10
14秒前
16秒前
17秒前
小二郎应助杏梨采纳,获得10
18秒前
19秒前
大模型应助关二哥采纳,获得10
19秒前
20秒前
FashionBoy应助清欢采纳,获得10
23秒前
英姑应助阿豆阿豆采纳,获得80
23秒前
24秒前
25秒前
Jacky发布了新的文献求助10
25秒前
Orange应助DODO采纳,获得10
25秒前
高分求助中
Teaching Social and Emotional Learning in Physical Education 900
Gymnastik für die Jugend 600
Chinese-English Translation Lexicon Version 3.0 500
Electronic Structure Calculations and Structure-Property Relationships on Aromatic Nitro Compounds 500
マンネンタケ科植物由来メロテルペノイド類の網羅的全合成/Collective Synthesis of Meroterpenoids Derived from Ganoderma Family 500
[Lambert-Eaton syndrome without calcium channel autoantibodies] 440
Plesiosaur extinction cycles; events that mark the beginning, middle and end of the Cretaceous 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2385659
求助须知:如何正确求助?哪些是违规求助? 2092149
关于积分的说明 5262781
捐赠科研通 1819227
什么是DOI,文献DOI怎么找? 907300
版权声明 559154
科研通“疑难数据库(出版商)”最低求助积分说明 484620