Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis

Abstract

Extracellular vesicles (EV) have attracted increasing attention as tumour biomarkers due to their unique biological property. However, conventional methods for EV analysis are mainly based on bulk measurements, which masks the EV‐to‐EV heterogeneity in tumour diagnosis and classification. Herein, a localized fluorescent imaging method (termed Digital Profiling of Proteins on Individual EV, DPPIE) was developed for analysis of multiple proteins on individual EV. In this assay, an anti‐CD9 antibody engineered biochip was used to capture EV from clinical plasma sample. Then the captured EV was specifically recognized by multiple DNA aptamers (CD63/EpCAM/MUC1), followed by rolling circle amplification to generate localized fluorescent signals. By‐analyzing the heterogeneity of individual EV, we found that the high‐dimensional data collected from each individual EV would provide more precise information than bulk measurement (ELISA) and the percent of CD63/EpCAM/MUC1‐triple‐positive EV in breast cancer patients was significantly higher than that of healthy donors, and this method can achieve an overall accuracy of 91%. Moreover, using DPPIE, we are able to distinguish the EV between lung adenocarcinoma and lung squamous carcinoma patients. This individual EV heterogeneity analysis strategy provides a new way for digging more information on EV to achieve multi‐cancer diagnosis and classification.

Multiplexed Profiling of Extracellular Vesicles for Biomarker Development

“…The concept of logic gate, as utilized here, is highly dependent on multiple aptamers being in close proximity. This proximity ligation approach was additionally verified for the sensitive detection of tumour-derived exosomal PD-L1/CD63 [59], and exosomal CD63/EpCAM/ MUC1 using multiple fluorophore coded aptamers [60][61][62].…”

Extracellular Vesicles as Mediators of Therapy Resistance in the Breast Cancer Microenvironment

“…Furthermore, profiling the three tumour-associated protein markers: EGFR, epithelial cell adhesion molecule (EpCAM) and HER2 on circulating EVs in a BC patient cohort, resulted in diagnosing breast tumours with high efficiency (AUC: 0.9845) (area under the receiver operating characteristic curve) and a high sensitivity of 97.37% for distinguishing malignant BC vs. healthy controls, whereas very early, stage I cases were detected with 92.31% sensitivity [ 166 ]. Similarly, in a different study, the percentage of CD63/EpCAM/mucin 1-triple-positive circulating EVs in BC patients was significantly higher than that of healthy controls and this was associated with an overall accuracy of 91% in BC diagnosis [ 167 ]. In a similar study where a microfluidic chip was used for immunocapture and quantification of circulating EVs from patients with BC, a significant increase in the EpCAM-positive EV expression level was detected compared to healthy controls, whereas EV HER2 expression levels were almost consistent with that in tumour tissues assessed by immunohistochemical staining [ 168 ].…”

Protein biomarkers in breast cancer-derived extracellular vesicles for use in liquid biopsies

“…This has advanced our understanding of the molecular heterogeneity of EV sub groups and helped to elucidate the application prospects of these EVs for early disease diagnosis and prognosis. For example, one study reported a localized fluorescentimaging method that enables the detection of multiple proteins on individual EVs using multiple DNA adapters for recognition (28), but the spatial hindrance among different DNA molecules can make analyzing more proteins on each EV surface challenging. In addition, high-resolution flow cytometry has been commercialized, and the standardization of assay protocols is also being established (29,30).…”

“…There was also a study showing that the proportion of CD63/EpCAM/mucin-1 triple-positive vesicle in plasma of patients with BC was significantly higher than that of healthy individuals and that the AUC reached 1.0. The author suggested that analyzing individual EVs can provide more precise information for cancer diagnosis and that using a combination of proteins can improve the detection sensitivity (28). Then, Tian et al (46) found that the weighted sum of eight plasma EV protein markers [including mucin-1, CA-125, carcinoembryonic antigen, HER2, EGFR, prostate-specific membrane antigen (PSMA), EpCAM, and vascular endothelial growth factor (VEGF)] was able to distinguish among metastatic BC, nonmetastatic BC, and healthy donors with an overall accuracy of 91.1%.…”