纳米反应器
乳腺癌
小RNA
癌症检测
癌症
纳米技术
计算生物学
材料科学
生物
纳米颗粒
遗传学
基因
作者
Chaewon Park,Soo‐Hyun Chung,H.Y. Kim,Nayoung Kim,Hye Young Son,Ryunhyung Kim,Sojeong Lee,Geunseon Park,Hyun Wook Rho,Mirae Park,Jueun Han,Yejin Song,Ji Hee Lee,Sung‐Hoon Jun,Yong‐Min Huh,Hyoung Hwa Jeong,Eun‐Kyung Lim,Eunjung Kim,Seungjoo Haam
出处
期刊:ACS Nano
[American Chemical Society]
日期:2024-09-09
标识
DOI:10.1021/acsnano.4c08339
摘要
Molecular-profiling-based cancer diagnosis has significant implications for predicting disease prognosis and selecting targeted therapeutic interventions. The analysis of cancer-derived extracellular vesicles (EVs) provides a noninvasive and sequential method to assess the molecular landscape of cancer. Here, we developed an all-in-one fusogenic nanoreactor (FNR) encapsulating DNA-fueled molecular machines (DMMs) for the rapid and direct detection of EV-associated microRNAs (EV miRNAs) in a single step. This platform was strategically designed to interact selectively with EVs and induce membrane fusion under a specific trigger. After fusion, the DMMs recognized the target miRNA and initiated nonenzymatic signal amplification within a well-defined reaction volume, thus producing an amplified fluorescent signal within 30 min. We used the FNRs to analyze the unique expression levels of three EV miRNAs in various biofluids, including cell culture, urine, and plasma, and obtained an accuracy of 86.7% in the classification of three major breast cancer (BC) cell lines and a diagnostic accuracy of 86.4% in the distinction between patients with cancer and healthy donors. Notably, a linear discriminant analysis revealed that increasing the number of miRNAs from one to three improved the accuracy of BC patient discrimination from 78.8 to 95.4%. Therefore, this all-in-one diagnostic platform performs nondestructive EV processing and signal amplification in one step, providing a straightforward, accurate, and effective individual EV miRNA analysis strategy for personalized BC treatment.
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