细胞外小泡
肺
表型
胞外囊泡
仿形(计算机编程)
免疫荧光
微泡
细胞生物学
计算生物学
肺癌
蛋白质亚细胞定位预测
生物
细胞外
蛋白质组学
蛋白质组
癌症研究
化学
纳米粒子跟踪分析
工作流程
病理
基因表达谱
小泡
绿色荧光蛋白
多路复用
细胞外液
生物信息学
腺癌
定量蛋白质组学
医学
临床表型
作者
Mi Hyeon Cho,Yein Chung,Yoonjeong Choi,Baekdong Cha,Jayeon Song,Nuri Oh,Ala Jo,Thomas S.C. Ng,Hyunho Kim,Hyun‐Kyung Woo,Chang Hyun Kim,Cesar M. Castro,Miles A. Miller,Hakho Lee
摘要
Lung cancer is frequently diagnosed after curative treatment windows have narrowed, creating a need for minimally invasive biomarkers that report tumor development at earlier stages. Extracellular vesicles (EVs) are promising analytical targets because they carry molecular cargo from their originating cells, but tumor-associated EV signals can be rare in blood and obscured in bulk measurements. Here, we present Cygnus (Cyclic-imaging gateway to nanovesicles underlying signature), an end-to-end workflow that integrates cyclic immunofluorescence imaging with multiscale analysis of individual EVs. Cygnus preserves vesicle-level measurements, quantifies marker co-expression, resolves EV subpopulations, and summarizes single-vesicle phenotypes into sample-level profiles. In a genetically engineered mouse model of lung adenocarcinoma, Cygnus revealed dynamic changes in EV protein composition and identified an EpCAM- and/or CTSH-positive EV subpopulation before tumors were detectable by radiography. In a pilot clinical cohort (n = 35), plasma EV profiling showed lung cancer-associated marker patterns compared with non-cancer controls and nominated a CTSH/PDL1/MET marker combination for future validation. These findings support multiplexed individual-EV profiling as a strategy for defining candidate lung cancer-associated EV signatures and position Cygnus as an integrated workflow for translating vesicle-level heterogeneity into sample-level EV profiles.
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