Dual size-exclusion chromatography for efficient isolation of extracellular vesicles from bone marrow derived human plasma

Use of extracellular vesicle microRNA profiles in patients with acute myeloid leukemia for the identification of novel biomarkers

OBJECTIVES

This study aimed to establish clinically significant microRNA (miRNA) sets using extracellular vesicles (EVs) from bone marrow (BM) aspirates of patients with acute myelogenous leukemia (AML), and to identify the genes that interact with these EV-derived miRNAs in AML.

MATERIALS AND METHODS

BM aspirates were collected from 32 patients with AML at the time of AML diagnosis. EVs were isolated using size-exclusion chromatography. A total of 965 EV-derived miRNAs were identified in all the samples.

RESULTS

We analyzed the expression levels of these EV-derived miRNAs of the favorable (n = 10) and non-favorable (n = 22) risk groups; we identified 32 differentially expressed EV-derived miRNAs in the non-favorable risk group. The correlation of these miRNAs with risk stratification and patient survival was analyzed using the information of patients with AML from The Cancer Genome Atlas (TCGA) database. Of the miRNAs with downregulated expression in the non-favorable risk group, hsa-miR-181b and hsa-miR-143 were correlated with non-favorable risk and short overall survival. Regarding the miRNAs with upregulated expression in the non-favorable risk group, hsa-miR-188 and hsa-miR-501 were correlated with non-favorable risk and could predict poor survival. Through EV-derived miRNAs-mRNA network analysis using TCGA database, we identified 21 mRNAs that could be potential poor prognosis biomarkers.

CONCLUSIONS

Overall, our findings revealed that EV-derived miRNAs can serve as biomarkers for risk stratification and prognosis in AML. In addition, these EV-derived miRNA-based bioinformatic analyses could help efficiently identify mRNAs with biomarker potential, similar to the previous cell-based approach.

Quality and efficiency assessment of five extracellular vesicle isolation methods using the resistive pulse sensing strategy

Extracellular vesicles (EVs) have attracted great interest due to their great potential in disease diagnosis and therapy. The separation of EVs from complex biofluids with high purity is essential for the accurate analysis of EVs. Despite various methods, there is still no consensus on the best method for high-quality EV isolation and reliable mass production. Therefore, it is important to offer a standardized method for characterizing the properties (size distribution, particle concentration and purity) of EV preparations from different isolation methods. Herein, we employed a NanoCoulter Counter based on the resistive pulse sensing (RPS) strategy that enabled multi-parameter analysis of single EVs to compare the quality and efficiency of different EV isolation techniques including traditional differential ultracentrifugation, ultrafiltration, size exclusion chromatography, membrane affinity binding and polymer precipitation. The data revealed that the NanoCoulter Counter based on the RPS strategy was reliable and effective for the characterization of EVs. The results suggested that although higher particle concentrations were observed in three commercial isolation kits and ultrafiltration, traditional differential ultracentrifugation showed the highest purity. In conclusion, our results from the NanoCoulter Counter provided reliable evidence for the assessment of different EV isolation methods, which contributed to the development of EV-based disease biomarkers and treatments.

Exosomal microRNAs: impact on cancer detection, treatment, and monitoring

Exosomes, measuring between 30 and 150 nm in diameter, are small vesicles enclosed by a lipid bilayer membrane. They are released by various cells in the body and carry a diverse payload of molecules, including proteins, lipids, mRNA, and different RNA species such as long non-coding RNA, circular RNA, and microRNA (miRNA). With lengths of approximately 19-22 nucleotides, miRNAs constitute the predominant cargo in exosomes and serve as crucial regulators of protein biosynthesis. In cancer detection, exosomal miRNAs show promise as non-invasive biomarkers due to their stability and presence in various bodily fluids, aiding in early detection and precise diagnosis with specific miRNA signatures linked to different cancer types. Moreover, exosomal miRNAs influence treatment outcomes by affecting cellular processes like cell growth, cell death, and drug resistance, thereby impacting response to therapy. Additionally, they serve as indicators of disease progression and treatment response, providing insights that can guide treatment decisions and improve patient care. Through longitudinal studies, changes in exosomal miRNA profiles have been observed to correlate with disease progression, metastasis, and response to therapy, highlighting their potential for real-time monitoring of tumor dynamics and treatment efficacy. Understanding the intricate roles of exosomal miRNAs in cancer biology offers opportunities for developing innovative diagnostic tools and therapeutic strategies tailored to individual patients, ultimately advancing precision medicine approaches and improving outcomes for cancer patients. This review aims to provide an understanding of the role of exosomal miRNAs in cancer detection, treatment, and monitoring, shedding light on their potential for revolutionising oncology practices and patient care.

A Robust and Efficient Method to Purify DNA-Scaffolded Nanostructures by Gravity-Driven Size Exclusion Chromatography

In recent decades, nucleic acid self-assemblies have emerged as popular nanomaterials due to their programmable and robust assembly, prescribed geometry, and versatile functionality. However, it remains a challenge to purify large quantities of DNA nanostructures or DNA-templated nanocomplexes for various applications. Commonly used purification methods are either limited by a small scale or incompatible with functionalized structures. To address this unmet need, we present a robust and scalable method of purifying DNA nanostructures by Sepharose resin-based size exclusion. The resin column can be manually packed in-house with reusability. The separation is driven by a low-pressure gravity flow in which large DNA nanostructures are eluted first followed by smaller impurities of ssDNA and proteins. We demonstrated the efficiency of the method for purifying DNA origami assemblies and protein-immobilized DNA nanostructures. Compared to routine agarose gel electrophoresis that yields 1 μg or less of purified products, this method can purify ∼100-1000 μg of DNA nanostructures in less than 30 min, with the overall collection yield of 50-70% of crude preparation mixture. The purified nanocomplexes showed more precise activity in evaluating enzyme functions and antibody-triggered activation of complement protein reactions.

Charge-Based Isolation of Extracellular Vesicles from Human Plasma

Extracellular vesicles (EVs) have garnered significant attention due to their potential applications in disease diagnostics and management. However, the process of isolating EVs, primarily from blood samples, is still suboptimal. This is mainly attributed to the abundant nature of soluble proteins and lipoproteins, which are often separated together with EVs in the end products of conventional isolation methods. As such, we devise a single-step charge-based EV isolation method by utilizing positively charged beads to selectively remove negatively charged major impurities from human plasma via electrostatic interaction. By carefully controlling the buffer pH, we successfully collected EVs from undesired plasma components with superior purity and yield compared to conventional EV collection methods. Moreover, the developed process is rapid, taking only about 20 min for overall EV isolation. The charge-based isolation can ultimately benefit the EV-based liquid biopsy field for the early diagnosis of various diseases.

Breast cancer derived exosomes: Theragnostic perspectives and implications

Breast cancer (BC) is the most prevalent malignancy affecting women worldwide. Although conventional treatments such as chemotherapy, surgery, hormone therapy, radiation therapy, and biological therapy are commonly used, they often entail significant side effects. Therefore, there is a critical need to investigate more cost-effective and efficient treatment modalities in BC. Extracellular vesicles (EVs), including exosomes, microvesicles, and apoptotic bodies, play a crucial role in modulating recipient cell behaviour and driving cancer progression. Among the EVs, exosomes provide valuable insights into cellular dynamics under both healthy and diseased conditions. In cancer, exosomes play a critical role in driving tumor progression and facilitating the development of drug resistance. BC-derived exosomes (BCex) dynamically influence BC progression by regulating cell proliferation, immunosuppression, angiogenesis, metastasis, and the development of treatment resistance. Additionally, BCex serve as promising diagnostic markers in BC which are detectable in bodily fluids such as urine and saliva. Targeted manipulation of BCex holds significant therapeutic potential. This review explores the therapeutic and diagnostic implications of exosomes in BC, underscoring their relevance to the disease. Furthermore, it discusses future directions for exosome-based research in BC, emphasizing the necessity for further exploration in this area.

Nanoplasmonic Detection of EGFR Mutations Based on Extracellular Vesicle-Derived EGFR-Drug Interaction

Analysis of membrane proteins from extracellular vesicles (EVs) has emerged as an important strategy for molecular cancer diagnosis. The epidermal growth factor receptor (EGFR) is one of the most well-known oncogenic membrane proteins, particularly in non-small cell lung cancer (NSCLC), where targeted therapies using tyrosine kinase inhibitors (TKIs) are often addressed based on EGFR mutation status. Consequently, several studies aimed at analyzing oncogenic membrane proteins have been proposed for cancer diagnosis. However, conventional protein analysis still faces limitations due to the requirement for large sample quantities and extensive post-labeling processes. Here, we develop a nanoplasmonic detection method for EGFR mutations in the diagnosis of NSCLC based on interactions between EGFR loaded in EVs and TKI. Gefitinib is selected as a model TKI due to its strong signals in the surface-enhanced Raman spectroscopy (SERS) and mutation-dependent binding affinity to EGFR. We demonstrate an SERS signal attributed to gefitinib at a higher value in the EGFR exon 19 deletion, both in cells and EVs, compared to wild-type and exon 19 deletion/T790M variants. Furthermore, we observe a significantly higher gefitinib SERS signal in EGFR obtained from exon 19 deletion NSCLC patient plasma-derived EVs compared with those from wild-type and exon 19 deletion/T790M EVs. Since our approach utilizes an analysis of the SERS signal generated by the interaction between oncogenic membrane proteins within EVs and targeted drugs, its diagnostic applicability could potentially extend to other liquid biopsy methods based on EVs.

Advances in mesenchymal stem/stromal cell-based therapy and their extracellular vesicles for skin wound healing

Wound healing is a dynamic and complicated process containing overlapping phases. Presently, definitive therapy is not available, and the investigation into optimal wound care is influenced by the efficacy and cost-effectiveness of developing therapies. Accumulating evidence demonstrated the potential role of mesenchymal stem/stromal cell (MSC) therapy in several tissue injuries and diseases due to their high proliferation and differentiation abilities along with an easy collection procedure, low tumorigenesis, and immuno-privileged status. MSCs have also accelerated wound repair in all phases through their advantageous properties, such as accelerating wound closure, improving re-epithelialization, elevating angiogenesis, suppressing inflammation, and modulating extracellular matrix (ECM) remodeling. In addition, the beneficial therapeutic impacts of MSCs are largely associated with their paracrine functions, including extracellular vesicles (EVs). Exosomes and microvesicles are the two main subgroups of EVs. These vesicles are heterogeneous bilayer membrane structures that contain several proteins, lipids, and nucleic acids. EVs have emerged as a promising alternative to stem cell-based therapies because of their lower immunogenicity, tumorigenicity, and ease of management. MSCs from various sources have been widely investigated in skin wound healing and regeneration. Considering these features, in this review, we highlighted recent studies that the investigated therapeutic potential of various MSCs and MSC-EVs in skin damages and wounds.

Updated Methods of Extracellular Vesicles Isolation

Extracellular vesicles (EVs) are considered as cargo and mediate intercellular communication. As natural biological nanoparticles, EVs can be secreted by almost all kinds of cells and exist in biofluids such as milk, urine, blood, etc. In the past decades, several methods have been utilized to isolate EVs from cell culture medium, biofluids, and tissues. Here in this chapter, we summarized conventional and novel methods and fundamental procedures of EVs extraction and purification from different biofluids (plasma, urine, milk, and saliva) and tissues (brain, intestinal tissue, muscles, and heart). The present section also discusses how to choose appropriate methods to extract EVs from tissues based on downstream analysis. This chapter will expand the horizons of EVs isolation and purification from different mediums.

Integrated Pipeline of Rapid Isolation and Analysis of Human Plasma Exosomes for Cancer Discrimination Based on Deep Learning of MALDI-TOF MS Fingerprints

Plasma exosomes have shown great potential for liquid biopsy in clinical cancer diagnosis. Herein, we present an integrated strategy for isolating and analyzing exosomes from human plasma rapidly and then discriminating different cancers excellently based on deep learning fingerprints of plasma exosomes. Sequential size-exclusion chromatography (SSEC) was developed efficiently for separating exosomes from human plasma. SSEC isolated plasma exosomes, taking as less as 2 h for a single sample with high purity such that the discard rates of high-density lipoproteins and low/very low-density lipoproteins were 93 and 85%, respectively. Benefitting from the rapid and high-purity isolation, the contents encapsulated in exosomes, covered by plasma proteins, were well profiled by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS). We further analyzed 220 clinical samples, including 79 breast cancer patients, 57 pancreatic cancer patients, and 84 healthy controls. After MS data pre-processing and feature selection, the extracted MS feature peaks were utilized as inputs for constructing a multi-classifier artificial neural network (denoted as Exo-ANN) model. The optimized model avoided overfitting and performed well in both training cohorts and test cohorts. For the samples in the independent test cohort, it realized a diagnosed accuracy of 80.0% with an area under the curve of 0.91 for the whole group. These results suggest that our integrated pipeline may become a generic tool for liquid biopsy based on the analysis of plasma exosomes in clinics.