The invention discloses a bubble self-stratification digital detection method and
system for miRNA quantification of
extracellular vesicles, and belongs to the technical field of
biomedical engineering and molecular diagnosis. The technical problem to be solved is to provide a simple and sensitive tumor
extracellular vesicle miRNA detection method capable of simultaneously detecting various miRNAs. According to the scheme, a to-be-detected sample and immunocapture bubbles coupled with an anti-EpCAM
antibody are incubated to enrich tumor
extracellular vesicles, a to-be-detected miRNA sample is obtained through in-situ ultrasonic
lysis, then the to-be-detected miRNA sample, a
fluorescence /
DNA double-coding
magnetic bead conjugate and the like are used for constructing an
enzyme digestion system for
enzyme digestion, multifunctional click glass
microbubbles are added to capture unreacted magnetic beads, standing is conducted, self-stratification is conducted, bottom magnetic beads are collected, and the EpCAM
antibody is obtained. After
fluorescence imaging, an image is input into the AI automatic
fluorescence counting and decoding module for counting to obtain a result. The method is used for detecting miR-21 and miR-155 in tumor
extracellular vesicles, and is suitable for noninvasive early diagnosis of tumors.