Extracellular Vesicles and Nanoparticles in Regenerative and Personalised Medicine: Diagnostic and Therapeutic Roles—A Narrative Review

Towards artificial intelligence-enabled extracellular vesicle precision drug delivery

The goal is to reverse cancer immune evasion at the level of the sentinel lymph node (SLN). Reduced expansion of CD8+ T cells and other innate immune effector cells in the cancer draining SLN is associated with progression and resistance to checkpoint inhibitors. Cancer-derived extracellular vesicles (EVs) that are PD-L1+ suppress immune recognition at the level of the SLN. The experimental goal is to remodel the SLN to overcome cancer EV-associated immune suppression and induce immune rejection of the tumor. We developed three methodologies for this project: a) Collection of draining lymph fluid to characterize EVs shed by 4T1 syngeneic breast tumors growing in the mammary fat pad. b) Chromatographic separation and characterization of the repertoire of EVs shed by tumors into the tumor microenvironment interstitial space using western blotting, mass spectrometry, and electron microscopy. c) Nanoparticle (NP) delivery of purified populations of EVs to the tumor draining SLN in combination with cytokine chemoattractants for innate immune cells recruitment. We characterized the in vivo interstitial fluid (IF) content of a GFP-4T1 syngeneic murine cancer model to study resident IF EVs transit to the draining lymph node. GFP labeling confirmed the IF EV tumor cell origin. Molecular analysis revealed an abundance of IF EV-associated proteins specifically involved in mitophagy and secretory autophagy. A set of proteins required for sequential steps of fission-induced mitophagy preferentially populated the CD81+/PD-L1+ IF EVs; including PINK1 and ARIH1 E3 ubiquitin ligase (required for Parkin-independent mitophagy), DRP1 and FIS1 (mitochondrial pinching), and VPS35, SEC22b, and Rab33b (vacuolar sorting). SLN immune cell populations could be massively remodeled by introducing hydrogel NPs which have a controlled release of T-cell and dendritic cell chemoattractant to the subcapsular sinus. NPs were successfully used to deliver concentrated packages of EVs subpopulations to the SLN. Introduction of the large CD81-/VEGF+/PD-L1- EV subpopulation (amphisome characteristics) to the SLN augmented tumor growth, angiogenesis, and metastasis, even when cytokine induction was used to remodel the SLN. In marked contrast, introduction of the CD81+/PD-L1+ EV subpopulation (containing mitophagy components) to the SLN in combination with NP release of chemoattractants, induced immune rejection of the syngeneic breast cancer, reducing tumor growth, and blocking metastasis. These findings demonstrate that different populations of EVs have opposite effects on cancer immune evasion at the level of the SLN and that EV-mediated immune suppression can be reversed by SLN remodeling to augment dendritic and CD8+ T cells. Citation Format: Marissa Howard, James Erickson, Amanda Haymond, Alessandra Luchini, Fatah Kashanchi, Lance Liotta. Reversing extracellular vesicle induced tumor immune suppression at the sentinel lymph node: Role of secretory autophagy and mitophagy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3516.

Engineered extracellular vesicles for ischemic stroke treatment

The interest for the detection of extracellular vesicles (EVs) as potential biomarkers in human health and disease is growing exponentially. Their fast and accurate detection and characterization in clinical settings is thus crucial to empower their use in personalized medicine. Because of its ability to discriminate between many EV subsets, flow cytometry (FCM) used in combination with other state of the art techniques, such as cryogenic electron microscopy and dynamic light scattering would be a tool of interest for EV-based diagnostics. However, the small size of EVs hampers the widespread use of standard FCM in the field. The purpose of this study is to enable an efficient and powerful method of quantitative and qualitative assessment of EVs in human plasma by FCM. Using a mixture of latex and silica beads whose size range from 110 to 1300 nm, counting beads, and 405 nm bandpass filter on the violet laser as side scatter detector, we were able to set an EV gate that allows for robust and accurate detection of circulating EVs in human platelet-free plasma (PFP). The EV gate was used to study the two main subsets of EVs retrieved in blood, namely EVs derived from platelets (CD41a+Phosphatidylserine+CD45-) and red blood cells (CD235a+CD45-), in human blood drawn on citrate, EDTA, or heparin, three commonly used anticoagulants. In addition, we used the t-Distributed Stochastic Neighbor Embedding (tSNE) algorithm as a platform in an attempt to instantly detect phenotype changes within the overall population of EVs and their specific subsets. The phenotype of circulating EVs revealed that there are observable differences between anticoagulants, as analysed by tSNE. However, the phenotype of platelet- and red blood cell-derived EVs per se were unaltered by anticoagulants. Overall, our findings provide an innovative framework that can be used for the characterization of EV subtypes by FCM in healthy and diseased individuals.

Parasites release extracellular vesicles (EVs) which, in some cases, modulate the host's immune response contributing to the establishment of the infection. In this work we have isolated and characterized the EVs released by trophozoites of the human protozoan parasite Entamoeba histolytica, the causal agent of amoebiasis, when alone or in coculture with human neutrophils, and determined their effect on neutrophil NETs and ROS production. Nanoparticle tracking analysis showed that amoebic EVs are variable in size, ranging from less than 50 nm to nearly 600 nm in diameter (average of 167 nm), whereas neutrophil EVs are more uniform in size, with an average of 136 nm. In cocultures amoeba:neutrophil (1:100) most EVs are 98 nm in size, which is the typical size of exosomes. EVs from amoebae and neutrophils showed almost equal levels of ROS, which were considerably increased in EVs from cocultures. Uptake of amoebic EVs by neutrophils was demonstrated by fluorescence and resulted in a significant reduction in the oxidative burst and NET release triggered by PMA, ionophore A23187, or the amoebae itself used as stimuli. Interestingly, uptake of EVs from cocultures did not affect ROS production, but instead caused a greater delay in the onset of NETs release and in their quantity. A comparative proteomic analysis between the EVs of amoebae and neutrophils separately vs the cocultures showed a similar distribution of protein categories in the GO analysis, but differences in the expression and abundance of proteins such as the N-acetyl-D-galactosamine (GalNAc) inhibitable surface lectin and calreticulin in amoeba EVs, and various antimicrobial molecules in neutrophil EVs, such as lactoferrin and myeloperoxidase. These results highlight the importance of EVs in the immunomodulatory effects exerted by amoeba on human neutrophils.

Bovine besnoitiosis is a re-emerging cattle disease caused by the apicomplexan parasite Besnoitia besnoiti, which severely affects individual animal welfare and profitability in cattle industry. We recently showed that B. besnoiti tachyzoite exposure to bovine polymorphonuclear neutrophils (PMN) effectively triggers neutrophil extracellular trap (NET) formation, leading to parasite immobilization hampering host cell infection. So far, the triggers of this defense mechanism remain unclear. Emerging evidence indicates that extracellular vesicles (EVs) modulate PMN effector functions, such as ROS production or NET formation. Therefore, we tested whether exposure of bovine PMN to EVs from different cellular sources affects classical PMN effector functions and cytokine/chemokine secretion. EVs were isolated from B. besnoiti-infected and non-infected host cells (bovine umbilical vein endothelial cells, BUVEC), from tachyzoite-exposed bovine PMN and from B. besnoiti tachyzoites. EV concentration and size was determined by Nano-Flow cytometry and EV nature was confirmed by both classical EV markers (CD9 and CD81) and transmission electron microscopy (TEM). Overall, PMN stimulation with both BUVEC- and tachyzoite-derived EVs significantly induced extracellular DNA release while EVs from PMN failed to affect NET formation. BUVEC and tachyzoite EV-driven NET formation was confirmed microscopically by the presence of DNA decorated with neutrophil elastase (NE) and histones in typical NET structures. Moreover, confocal microscopy revealed EVs to be internalized by bovine PMN. Referring to PMN activation, EVs from the different cellular sources all failed to affect glycolytic or oxidative responses of bovine PMN as detected by Seahorse®-based analytics and luminol-based chemoluminescence, thereby denying any role of NADPH oxidase (NOX) activity in EV-driven NET formation. Finally, exposure to B. besnoiti-infected BUVEC-derived EVs induced IL-1β and IL-6 release, but failed to drive CXCL8 release of bovine PMN. Hence, we overall demonstrated that EVs of selected cellular origin owned the capacity to trigger NOX-independent NET formation, were incorporated by PMN and selectively fostered IL-1β and IL-6 release.

<h3>Abstract</h3> Novel biological therapies have revolutionised the management of Rheumatoid Arthritis (RA) but no cure currently exists. Mesenchymal stem cells (MSCs) immunomodulate inflammatory responses through paracrine signalling, including via secretion...

Osteoarthritis (OA) is a chronic degenerative disease of the joint, involving cartilage degradation, synovial inflammation, and subchondral bone remodeling. Extracellular vesicles (EVs)—membrane-bound particles released by cells and have emerged as key mediators of intercellular communication in joint homeostasis and OA pathogenesis. EVs facilitate crosstalk between chondrocytes, synovial fibroblasts, and mesenchymal stem cells (MSCs), influencing joint health and disease progression. In OA, EV cargo: including proteins, miRNAs, and lipids, undergoes pathological changes that promote inflammation, matrix degradation, senescence, and calcification. Recent studies demonstrate that OA-derived EVs can induce catabolic and pro-inflammatory responses in recipient cells, while EVs from therapeutic sources such as MSCs, exhibit chondroprotective and anti-inflammatory effects in preclinical models. Additionally, EV surface markers and cargo profiles correlate with OA severity and pain, supporting their utility as minimally invasive biomarkers for early diagnosis and patient stratification. Cross-species comparisons suggest that EV signatures may be conserved, highlighting their translational potential in both human and veterinary medicine. However, the field is limited by variability in EV isolation and characterization methods, which hampers reproducibility and clinical application. To advance the clinical translation of EVs, standardized workflows and a deeper mechanistic understanding of EV function in the joint are essential. Identifying disease-specific EV biomarkers could enable earlier OA diagnosis and personalized treatment strategies, while optimizing therapeutic EVs could support regenerative approaches to slow or reverse joint degeneration and improve outcomes for human patients.

Background: Cardiomyocyte (CM) cell death plays a significant role in left ventricular (LV) remodeling and cardiac dysfunction following myocardial infarction (MI). While extracellular vesicles (EVs) secreted by cardiosphere-derived cells (CDCs) have shown efficacy in promoting cardiac repair in large animal models of MI, their translational potential is limited by their biodistribution. To improve cardiac uptake, we previously engineered CDC-derived EVs to express a CM-specific binding peptide (CMP) on their surface. CMP-EVs demonstrated improved cardiac retention in vivo and decreased CM apoptosis in vitro when compared with non-targeted EVs. We hypothesized that targeting therapeutic EVs to CMs would result in further reduction of CM cell death in vivo and improvement in cardiac function post-MI. Methods: EVs were isolated from serum-free media as previously described and characterized by established protocols for size, morphology, and protein expression. To determine if CMP-EVs could enhance cardioprotection in vivo , we induced acute MI in adult C57BL/6 mice and randomized them to receive 1) EVs, 2) CMP-EVs or 3) vehicle control by IV and intramyocardial delivery according to approved institutional protocols. LVEF was assessed by echo at 1- and 28-days post-MI and tissue samples processed for assessment of EV biodistribution and histological endpoints. Results: CMP-EVs demonstrated superior cardiac targeting (IV route) and retention (intramyocardial route) when compared with control EVs 24 hours post MI (fold change of 1.8 ± 0.23 and 4.8 ± 2.3 respectively; n=8-10 mice/group, mean ± SEM, p&lt;0.05, t-test). Intramyocardial administered CDC-derived EVs improved LVEF compared with vehicle control treated animals 4 weeks post-MI (55 ± 2% vs 44 ± 2%). Mice treated with CMP-EVs demonstrated a statistically significant improvement in LVEF (64 ± 5%) compared with non-targeted EVs (n=6-8 mice/group, mean ± SEM, p&lt;0.05, one-way ANOVA). Conclusions: Targeting CMP-EVs to CMs post-MI improved cardiac function compared with control EVs, highlighting the potential importance of CMs as a target cell for CDC-derived EV therapy and demonstrating a strategy to further optimize therapeutic EV delivery to increase efficacy and decease off-target effects.

Synthetic and naturally occurring particles, such as nanoparticles (NPs) and exosomes; a type of extracellular vesicles (EVs), have garnered widespread attention across various fields, including biomaterials, oncology, and delivery systems for drugs and vaccines. Traditional methods for identifying NPs and EVs, such as transmission electron microscopy, are often prohibitively expensive and labor-intensive. As an alternative, the assessment of electrokinetic attributes such as zeta potential or electrophoretic mobility, conductance, and mean count rate, offers a more cost-effective, rapid, and reliable means of characterizing these particles. In this context, we introduce the first application of a quantum machine learning (QML)-based electrokinetic mining for the identification of green-synthesized iron- and cobalt-based NPs, as well as exosomes derived from human embryonic stem cells (hESC), human lung cancer (A549) cells, and colorectal cancer (CRC) cells, based solely on their electrokinetic attributes. Comparative analyses involving cross-validation, train-test splits, confusion matrices, and Receiver Operating Characteristic (ROC) curves revealed that classical ML techniques could accurately identify the types of NPs and EVs. Notably, QML demonstrated proficiency in differentiating between various NPs and EVs, including the distinction of EVs in the plasma of CRC patients versus those of healthy individuals. Furthermore, QML's application has been extended to the identification of NPs along with EVs in the plasma of CRC patients and experimental mice, achieving higher prediction performance even with a minimal training dataset, demonstrating that QML based electrokinetic mining could identify NPs or EVs with minimal training data, thereby facilitating novel clinical development in the realm of liquid biopsies.

Background and Objectives: Extracellular vesicles (EVs) derived from mesenchymal stem cells have gained much attention as potential therapeutic agents in many diseases, including hearing disorders such as sensorineural hearing loss (SNHL). EVs inherit similar therapeutic effects, including the stimulation of tissue regeneration from the parental cells. The aim of our study was to isolate EVs produced by MSCs and use them to treat inner ear cells in culture to evaluate their protective potential against the damaging effect of an ototoxic drug. Materials and Methods: We isolated MSC-derived EVs by precipitation and characterized them by number, size, and morphology using nanoparticle tracking analysis and TEM, evaluated the protein concentration by BCA assay and the presence of EV markers CD9, CD63, and CD81 by the Dot Blot immunoblotting method. HEI-OC1 inner ear cell line was treated with EVs either alone or followed by Cisplatin. We assessed the uptake of EVs in HEI-OC1 cells by fluorescence microscopy after PKH26 labeling, ROS production by the DCFDA (dichlorfluorescein diacetate) assay, cellular viability by Alamar Blue assay, and apoptosis with the Annexin V/Propidium Iodide method. Results: The isolated EVs had mean dimensions of 184.4 nms and the concentration of the EV suspension was 180 × 106 particles/mL. TEM analysis showed intact vesicular structures with lipid-bilayer membranes having similar sizes with those measured by NTA. The PKH26-labeled EVs were observed in the HEI-OC1 cells after 24 h incubation, the amount increasing with the concentration. EVs reduced ROS production and increased the number of viable cells both alone and as pretreatment before Cisplatin, dose-dependently. Cells in early apoptosis were inhibited by EVs, while those in late apoptosis were enhanced, both with and without Cisplatin. Conclusions: EVs secreted by MSC protected HEI-OC1 cells against Cisplatin toxicity, reduced ROS production, and stimulated cell viability and the elimination of damaged cells by apoptosis, protecting the HEI-OC1 cells against Cisplatin-induced damage.

Background: Mammography is the current diagnostic standard for breast cancer screening and monitoring. However, accessibility challenges, accuracy issues and patient discomfort all contribute to reduced patient compliance and utilization, resulting in a need for more effective diagnostic tools. An artificial intelligence (AI)-based lipidomic blood test may add significant value to early breast cancer detection rate and improve outcomes for patients. We have previously reported a series of lipidomic studies (n=793) and derived a lipid signature from plasma-enriched extracellular vesicles (EVs) that effectively distinguished people with localized breast cancer from cancer-free controls. Here we report the development of a breast cancer detection AI model from lipidomic data assessed directly using plasma samples. Methods: Lipids in both EVs and plasma collected from fasted breast cancer and control blood samples (n=256) were extracted and analysed by liquid chromatography-high resolution mass spectrometry (LC-HRAM-MS). Over 400 manually curated lipids were quantified. A bootstrapped analysis using Boruta, a robust and statistically rigorous feature selection algorithm based on random forest feature importance, was employed to identify cancer discriminatory lipid signatures in EV and plasma lipidomes consistently selected across 2000 bootstrap samples. The resulting lipid signature was then used to train an ensemble of 18 distinct machine learning models for cancer status prediction using a majority vote to aggregate the individual predictions. Model performance and variability were assessed over 2000 iterations of leave-group-out cross-validation (LGOCV) using an 80/20 train-test split. Average patient-level predictions across LGOCV iterations were recorded for both EV-and plasma-derived models and the two modalities were compared using an exact paired samples test (McNemar’s test). Results: Both the EV- and plasma-derived lipid signatures performed well in distinguishing breast cancer samples from controls. The development of a bioinformatics AI pipeline enabled the creation of a robust ensemble model achieving an F1 score of 0.89 in plasma with LGOCV. The final plasma ensemble predictive performance of 86.1% (±4.5%) in accuracy, 91.4% (±5.4%) in sensitivity, and 78.7% (±8.6%) specificity was achieved, which is comparable to that of EV (accuracy: 86.1±4.4%, sensitivity: 90.4±5.3%, specificity: 80.2±8.7%). Paired samples analysis using McNemar’s test indicated no significant differences between models trained on EV- and plasma-derived lipid signatures in either the sensitivity (p=0.65), specificity (p=0.49), or accuracy (p=0.42). Conclusion: The initial study demonstrated the high performance of a plasma-enriched extracellular vesicle-derived lipid biomarker signature for early breast cancer detection. Direct assessment of the lipidomic signature from plasma showed promise in simplifying the test. Assessing plasma directly offered advantages in terms of scalability, higher throughput, and ease of implementation. Further verification of the lipid signature in an upcoming study involving 500 plasma samples is planned. Ongoing studies will further optimize the plasma lipidomic signature and strengthen our AI pipeline. These findings support the potential clinical application of AI-based lipidomic profiling as a blood-based screening tool for breast cancer detection. Citation Format: Ameline Lim, Cheka Kehelpannala, Fatemeh Vafaee, Forrest Koch, Dana Pascovici, Desmond Li, Kerry Heffernan, Gillian Lamoury, Amani Batarseh, Bruce Mann. Development of an Artificial Intelligence-based breast cancer detection model using Plasma Lipidomic Signature [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-07-02.

Small extracellular vesicles from senescent stem cells trigger adaptive mechanisms in young stem cells by increasing antioxidant enzyme expression

Over the past decades, the medical exploitation of nanotechnology has been largely increasing and finding its way into translational research and clinical applications. Despite their biomedical potential, uncertainties persist regarding the intricate role that nanomaterials may play on altering physiology in healthy and diseased tissues. Extracellular vesicles (EVs) are recognized as an important pathway for intercellular communication and known to be mediators of cellular stress. EVs are currently explored for targeted delivery of therapeutic agents, including nanoformulations, to treat and diagnose cancer or other diseases. Here, we aimed to investigate whether nanomaterials could have a possible impact on EV functionality, their safety, and whether EVs can play a role in nanomaterial toxicity profiles. To evaluate this, the impact of inorganic nanomaterial administration on EVs derived from murine melanoma and human breast cancer cells was tested. Cells were incubated with subtoxic concentrations of 4 different biomedically relevant inorganic nanoparticles (NPs): gold, silver, silicon dioxide, or iron oxide. The results displayed a clear NP and cell-type-dependent effect on increasing or decreasing EV secretion. Furthermore, the expression pattern of several EV-derived miRNAs was significantly changed upon NP exposure, compared to nontreated cells. Detailed pathway analysis and additional studies confirmed that EVs obtained from NP-exposed cells could influence immunological responses and cellular physiology. Together, these data reveal that NPs can have wide-ranging effects which can result in toxicity concerns or enhanced therapeutic potential as a secondary enhanced effect mediated and enhanced by EVs.

Context: Extracellular vesicles (EVs) are related to the dissemination of the pathogen and to the regulation of the host immune system in infectious diseases. However, the role of EVs in Ocular toxoplasmosis remains unclear. Aims: The goal of this study was to identify and characterize the concentration and size of EVs in the aqueous humor (AH) and plasma of patients with ocular toxoplasmosis (OT) compared to other types of uveitis (OTU) and cataract. Settings and Design: AH and plasma were collected from six patients with active OT, six patients with OTU, and six patients with cataract. All patients were also assessed clinically. Subjects and Methods: EVs were isolated using the membrane affinity column method. Nanoparticle Tracking Analysis (NTA) was performed to determine the size and concentration of EVs. Statistical Analysis Used: The ANOVA test was used to determine statistical difference. P < 0.05 was considered statistically significant. Results: EV was present in the AH of different types of uveitis as well as in patients with cataract. The concentration of EV in AH was significantly lower in OT and OTU compared to cataract (P = 0.03). However, in the plasma, all groups presented a similar concentration of EV. The size of EV was the same in the AH and plasma among the three groups. Conclusion: This initial study successfully identified and characterized EVs in the AH and plasma from patients with OT as well as OTU and cataract. Further studies are necessary to better understand the role of EVs in different ocular pathologies.