posted on 2024-09-09, 13:03authored byChaewon Park, Soohyun Chung, Hansol Kim, Nayoung Kim, Hye Young Son, Ryunhyung Kim, Sojeong Lee, Geunseon Park, Hyun Wook Rho, Mirae Park, Jueun Han, Yejin Song, Jihee Lee, Sung-Hoon Jun, Yong-Min Huh, Hyoung Hwa Jeong, Eun-Kyung Lim, Eunjung Kim, Seungjoo Haam
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.