Multi-parameter Analysis Of Individual Exosomes And Exploration On Its Tentative Application In Clinical Diagnosis Of Tumor

Exosomes are extracellular vesicles with a diameter of 40-160 nm actively secreted by cells,which are widely distributed in various body fluids and can carry bioinformation(such as proteins,nucleic acids and lipids)from their parental cells.Exosomes secreted by different cells line are heterogeneous in size and content,even by the same cells line.Exosomes secreted by tumor cells are considered as promising biomarkers of liquid biopsy.Therefore,the analysis of biological information carried by exosomes is crucial to diagnosis and prognosis,including cancer and other serious diseases.However,traditional detection methods are mainly bulk measurement,which could only provide the average of all exosomes,and it’s easy to cover up the information of tumor-derived exosomes with a small proportion in the blood.Therefore,development of new methods for individual exosomes analysis suitable for the determination of clinical samples are the research focuses currently.Based on the analysis of surface proteins and internal nucleic acids of individual exosomes,novel methods of multi-parameter analysis of individual exosomes are developed and applied for the detection of plasma samples from clinical tumor patients,which provide new ideas for the development of liquid biopsy strategy of tumor exosomes.The main contents and results are as follows:1.Proceeding from the problem that it is difficult to accurately quantify tumor exosomes in plasma only by a single marker,a method of digital profiling of proteins on individual exosomes(DPPIE)is developed,which successfully realized the localized fluorescent signal amplification detection of CD63/EpCAM/MUC1 triplepositive exosomes in plasma samples of cancer patients.Specifically,exosomes in plasma are captured by biochip modified with anti-CD9 antibody,and the exosomes are scattered on the surface of the biochip.CD63 aptamer is added into the biochip to recognize CD63 protein of exosomes,which eliminate the interference of free protein and ensure that the detection is specific.Characteristic tumor markers of exosomes are identified by EpCAM and MUC1 aptamers.Then,rolling circle amplification reaction is applied to generate localized amplified fluorescent signals on each of exosomes for ultrasensitive digital detection and multi-protein profiling,realizing sensitive detection of CD63/EpCAM/MUC1 triple-positive exosomes.We have achieved a limit of detection(LOD)of 10 vesicles/μL,and the sensitivity is much higher than enzymelinked immunosorbent assay and commercial biosensors based on surface plasmon resonance.Combined with the T-distribution stochastic neighbour embedding,the DPPIE method could accurately distinguish the plasma samples between breast cancer patients and healthy donors.Moreover,DPPIE is able to distinguish the plasma exosomes between lung adenocarcinoma and lung squamous carcinoma patients.We also found CD63/EpCAM/MUC1-triple-positive exosomes do exist in the plasma samples of patients with B-cell acute lymphoblastic leukaemia and T-cell acute lymphoblastic leukaemia,which could be served as potential biomarker for hematologic malignancies diagnosis.Besides,owing to its simplicity and general applicability,DPPIE assay could be widely applied to detect other biomarkers on exosomes by changing aptamers or antibodies.This method may be hopeful for achieving multi-cancer diagnosis and classification.2.To solve the problem that it is difficult to analyze the surface proteins and nucleic acid of individual exosomes simultaneously,a method of localized profiling of tumor-derived individual exosomal PD-L1(LPTIE)is developed based on liposomemediated membrane fusion strategy and signal amplification by exchange reaction(SABER),realizing simultaneous determination of exosome dual-target(surface protein PD-L1 and internal nucleic acid miR-21).Exosomes from plasma are efficiently captured by anti-CD9/anti-CD63/anti-CD81 antibodies engineered biochip,eliminating the interference of free PD-L1 protein.Then,molecular beacon is transfected into exosomes through liposome-mediated membrane fusion strategy,followed by miR-21 inside exosomes are sensitively measured,which successfully discriminate tumor-derived exosomes in plasma and eliminate the interference of normal exosomes.Subsequently,signal amplification by exchange reaction(SABER)is applied to generate amplifying localized fluorescent signals,achieving sensitive profiling of individual tumor-derived exosomal PD-L1 in plasma.Combined with the Sobel-operator machine learning algorithm,the obtained data of exosomal protein and nucleic acid are processed,determining the proportion of tumor-derived exosomal PDL1 subpopulation in the exosomes population.By detecting clinical plasma samples,we found that the proposed method could more accurately distinguish plasma samples of breast cancer patients from healthy donors than enzyme-linked immunosorbent assay and nanoparticle tracking analysis(NTA).On the other hand,it could also distinguish plasma exosomes from breast cancer patients and patients with benign breast tumor.In addition,this method is able to detect various nucleic acids and proteins of exosomes via adding molecular beacon and aptamers,providing a new strategy for achieving more accurate cancer diagnosis and prognostic monitoring of immunotherapy.