P-262 Staining plasma with lipophilic dye followed by size-exclusion chromatography, immune-capturing and on-bead flow cytometry is a highly sensitive approach to quantifying colorectal cancer derived extracellular nanovesicles

Abstract

Development of new and effective methods for screening and early diagnosis of colon cancer is an important scientific and technological issue. There is a tendency to move from invasive methods to liquid biopsy. Extracellular nanovesicles (ENVs) secreted by colon cancer cells may serve as a marker of disease. Standard approaches to analyze cancer-derived ENVs in plasma suppose consequent steps of ENV isolation followed by immune-based labeling and quantification. However, at the early stage of cancer development, the amount of ENVs derived from cancer cells is supposedly not sufficient to be detected by available methods. Low sensitivity of currently available methods and low concentration of colon cancer-derived ENVs (cc-ENVs) compromise overall ENV- based approach for early cancer diagnosis. To solve this issue, we explored ‘inverse’ technology of cc-ENV quantification. This approach supposes three consequent steps: firstly, the labelling of all membranous components of plasma with lipophilic dye (CM-Dil); secondly, the isolation of population of ENVs formed by endosomal route (exosomes) by size-exclusion chromatography; thirdly, the quantification of tumor-specific fraction of these vesicles by flow cytometry with immune-beads. To prove the concept of this approach, we isolated ENVs from colon cancer cells (COLO 320) by ultracentrifugation according to the official rules of MISEV2018. EV concentrations were estimated by the NTA (NanoSight NS300). 20*1010, 10*1010 and 1*1010 EVs were added to the same amount ml of healthy donor blood plasma. The mixtures were colored and purified using the developed method. To isolate and quantify ccENVs, we first defined markers present in surface of ENVs secreted by COLO320 cells (GPA33 and RegIV) and created immune-bead decorated with antibodies specific to these markers. EVs were analyzed by flow cytometry (CytoFLEX) for the above markers with immune beads. GPA33(+) and RegIV (+) ENVs were isolated from mixture of CM-Dil-labeled ENVs and assayed by flow cytometry. The analysis of PE-positive events was carried out by FlowJo 10.7.1 software. The amount of GPA33(+) and RegIV (+) ENVs derived from colon cancer cells and estimated by developed method had obvious dose-dependency. The 20*1010, 10*1010 and 1*1010 cc-ENVs diluted in 2 mL of healthy donor’s plasma (which had a background signal without cc-ENVs) were quantified as 272, 177, 119 (CV, %) and 346, 179, 83 (CV, %), respectively. Since the portion of artificially mixed cc-ENVs could be estimated in a range of 0,1 – 1% of the total amount of plasma ENVs, proposed methods provide exceptional sensitivity for cc-ENV detection and might by applied for cancer screening. The proposed technique allowed for the quantification of minimal numbers of specific colon cancer-derived ENVs in plasma and can be applied in the frame of ENV-based methods of colon cancer diagnosis. The new technology may also be used to improve sensitivity of ENV-based diagnostic methods of other cancer types.