Advances in the role of extracellular vesicles in circulating microRNA biomarker discovery for lung cancer

Lung cancer remains a leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and the limited efficacy of current therapeutic approaches. Recent advancements highlight the potential of extracellular vesicles (EVs), particularly those carrying microRNA (miRNA) molecules, as promising non-invasive biomarkers for early detection, prognosis, and therapy monitoring. EVs are nanoscale vesicles secreted by tumour cells, capable of transporting various bioactive molecules including miRNAs while preserving their structural stability in circulation. These miRNAs mirror the molecular state of the tumour and often exhibit distinct expression signatures depending on cancer subtype and stage. Studies have shown that specific EV-associated miRNAs are significantly dysregulated in lung cancer patients and correlate with tumour progression, metastatic potential, and overall survival. Moreover, tracking dynamic changes in EV-miRNA profiles during treatment may provide predictive insights into responsiveness to immunotherapy and targeted therapy. This review emphasizes the diagnostic and prognostic utility of EV-derived miRNAs, highlighting their tumour specificity and stability in bodily fluids. In addition, we summarise key challenges such as the lack of standardisation, EV heterogeneity, and technical variability, while also outlining future directions including single-EV detection, multi-omics integration, AI-driven diagnostics, and therapeutic applications. By integrating these biomarkers into clinical workflows via liquid biopsy, it may become possible to detect lung cancer earlier and adapt therapeutic strategies more effectively ultimately improving patient outcomes and offering new directions in precision oncology.

1 Introduction

Lung cancer is one of the most prevalent malignancies worldwide and remains the leading cause of cancer-related mortality (Tang et al., 2025; Bray et al., 2022). According to the latest data from the International Agency for Research on Cancer (IARC) and its Global Cancer Observatory (GLOBOCAN), lung cancer ranks among the top diagnosed cancers and continues to be the leading cause of cancer-related mortality worldwide. In 2022, nearly 2.48 million new lung cancer cases occurred globally, accompanied by approximately 1.8 million deaths (Zhou et al., 2024). The age-standardised incidence rate (ASIR) was estimated at 23.6 per 100,000 people, and the age-standardised mortality rate (ASMR) was around 16.8 per 100,000 people (Guo et al., 2024). Projections suggest that if current trends persist, by 2050 the burden of lung cancer could rise substantially, potentially reaching ∼4.62 million new cases and ∼3.55 million deaths annually (Zhou et al., 2024).

Due to the typically late manifestation of clear clinical symptoms, lung cancer is frequently diagnosed at advanced stages, thereby reducing the effectiveness of therapeutic interventions and markedly deteriorating patient survival outcomes (Polanco et al., 2021; Vicidomini, 2023). Among the emerging avenues in cancer research is the investigation of tumour-derived circulating microRNAs (miRNAs) and extracellular vesicles (EVs) as non-invasive biomarkers within the concept of liquid biopsy (Zhou et al., 2023). These entities encapsulate tumour-specific molecular signatures, thereby enabling early disease detection and dynamic assessment of treatment response (Ma et al., 2025). EVs are nanoscale, membrane-bound vesicle-like particles released by cells (Belkozhayev et al., 2022; Wen et al., 2024). They carry a diverse cargo of biomolecules, including proteins, lipids, DNA, and various types of RNA particularly miRNAs (Dellar et al., 2022; Babuta and Szabo, 2022; Chen T. et al., 2025). EVs play a critical role in intercellular communication and act as carriers of molecular signals involved in the pathogenesis of various diseases, including cancer (Godakumara et al., 2022). The molecular cargo delivered via EVs serves as a crucial mediator of intercellular signalling, contributing to the regulation of various physiological and pathological processes, including tumorigenesis (Kumar et al., 2024; Kuang et al., 2025). In the context of cancer, tumour-derived EVs can transmit oncogenic signals to surrounding cells within the tumour microenvironment, enhancing their capacity for proliferation, migration, and angiogenesis (Najaflou et al., 2022). Moreover, several miRNAs transported by EVs have been experimentally shown to promote the invasive and metastatic potential of cancer cells (Martellucci et al., 2020). A key biological feature of EVs is their ability to protect nucleic acids particularly miRNAs from enzymatic degradation in the extracellular environment (Buzas, 2023). This protective capacity allows EV-associated miRNAs to remain stable for extended periods in biological fluids such as blood, thereby enabling their direct analysis through non-invasive approaches (Ma et al., 2023; Ferro et al., 2024). The presence of disease-specific expression patterns and the inherent stability of EV-carried miRNAs pave the way for their use as reliable diagnostic and prognostic biomarkers in lung cancer (Bartoszewska et al., 2025). In recent years, there has been a marked increase in interest toward the investigation of circulating EVs as reliable biomarkers for lung cancer (Vasu et al., 2025; Ge et al., 2023). Numerous studies have demonstrated that the EV-associated miRNA expression profiles in the plasma of lung cancer patients differ significantly from those of healthy donors (Li et al., 2024a; Gao et al., 2022). Moreover, the expression levels of certain EV-derived miRNAs have been found to correlate strongly with clinical tumour stage, treatment response, and overall patient survival (Mok et al., 2024; Seyhan, 2023). For instance, diagnostic models based on plasma EV-miRNA signatures have been proposed to distinguish between malignant and benign pulmonary nodules (Liu et al., 2023). One pilot study even indicated that EV-miRNA expression patterns could predict the malignancy of nodules smaller than 1 cm in diameter (Paterson et al., 2022). Collectively, these findings highlight the high diagnostic potential of EV-encapsulated miRNAs for the early detection of lung cancer and for improving clinical prognostication (Paterson et al., 2022; Eckhardt et al., 2023). Previous reviews have mainly focused on the diagnostic potential of EV-miRNAs in liquid biopsy. This review advances the field by integrating updated evidence on EV–miRNA–mediated signaling and tumour progression, while also highlighting unresolved challenges such as heterogeneity and lack of standardisation. Moreover, this review evaluates emerging profiling technologies including single-EV detection, multi-omics approaches, and AI-driven analytics. In addition, it explores the role of EVs and miRNAs in the early diagnosis and prognostication of lung cancer, providing an overview of EV types and mechanisms, a critical evaluation of isolation techniques and miRNA profiling methods, and a synthesis of their biomarker potential with prospective clinical and therapeutic applications.

2 EVs: types, composition, and mechanisms of action

2.1 Types of EVs

EVs are microscopic, vesicle-like structures released by cells into the extracellular environment. They carry a diverse range of biomolecules, including proteins, lipids, and nucleic acids (Di Bella, 2022). EVs serve as essential mediators of intercellular communication within the body, enabling the transfer of biological information from one cell to another (Petroni et al., 2023; Wessler and Meisner-Kober, 2025). Currently, the roles of EVs in both physiological and pathological processes particularly in tumour development and the modulation of immune responses are being extensively investigated (Reale et al., 2022; Gong et al., 2025).

The main types of EVs include exosomes, microvesicles, and apoptotic bodies (Lee et al., 2022). Exosomes represent the smallest EV subpopulation, with a diameter of approximately 30–150 nm, also known as small EVs (SEV) (Zarovni et al., 2025). They are formed through the endosomal pathway as intraluminal vesicles within multivesicular bodies (MVBs). When MVBs fuse with the plasma membrane, these vesicles are released into the extracellular space as exosomes (Xu D. et al., 2022; Kalluri and LeBleu, 2020; Visnovitz et al., 2025). Microvesicles (also known as medium EVs) are EVs ranging from approximately 100–1,000 nm in diameter and are generated by direct outward budding from the plasma membrane (Singh B. et al., 2025). In contrast, apoptotic bodies (also known as large EVs (LEV)) represent the largest type of EVs, released from cells undergoing apoptosis. Their size typically ranges from 1 to 5 μm, and they may contain cellular fragments and nuclear material (Huang et al., 2024; Gregory and Rimmer, 2023).

However, the distinction between these EV subtypes remains challenging, as their size ranges often overlap and many markers are not exclusive to a single population (Verweij et al., 2021; Jeppesen et al., 2019). This lack of clear separation complicates both experimental characterization and clinical translation. In lung cancer research, refining EV classification is critical because different vesicle subtypes show distinct capacities for carrying oncogenic or tumour-suppressive miRNAs, which directly influences their diagnostic and prognostic potential. Recent advances such as single-vesicle imaging, high-resolution flow cytometry, and nanoplasmonic detection are being developed to better distinguish EV subtypes and capture their biological heterogeneity (Kobayashi et al., 2024; von Lersner et al., 2024).

2.2 Composition of EVs

EVs contain a diverse array of biomolecules, including proteins, lipids, nucleic acids (DNA and RNA), and metabolites (Jin et al., 2025). Their membrane consists of a double phospholipid bilayer that protects the internal cargo from the extracellular environment. This membrane features specific proteins derived from the donor cell’s plasma membrane and endosomal system, such as tetraspanins, integrins, and receptors (Hallal et al., 2022; Jankovičová et al., 2020). The EV lumen is enriched with cytosolic proteins, various RNA species, and, in some cases, DNA fragments. This molecular heterogeneity reflects the complex and multifaceted roles of EVs in intercellular communication (Malkin and Bratman, 2020; Huang et al., 2025). Figure 1 illustrates the structural and molecular composition of extracellular vesicles, including exosomes, microvesicles, and apoptotic bodies, and highlights their distinct sizes and cargo profiles.

Figure 1

Figure 1. Structural and molecular composition of EVs including exosomes microvesicles and apoptotic bodies. Created with BioRender, License No. SQ28D9D1PG.

The protein composition of EVs is heterogeneous and includes tetraspanins (CD9, CD63, CD81, CD82), adhesion molecules (integrins, EpCAM, MHC-I/II, ICAM-1), ESCRT proteins (TSG101, ALIX, Rab GTPases), and heat shock proteins (Hsp70, Hsp90) (Stajano et al., 2023; Jankovičová et al., 2024). Although exosomes and microvesicles show differences in proteomic profiles (e.g. CD63/CD81 vs. Annexin A1/CD9), these markers are not absolute (Jeppesen et al., 2023; De Sousa et al., 2023).

Nucleic acids are a key component of EV cargo. EVs contain diverse RNA species, including mRNAs, miRNAs, lncRNAs, and circRNAs (Kwok et al., 2021; Miceli et al., 2024). Notably, miRNAs can constitute up to 40% of total RNA reads in plasma-derived EVs (Mittelbrunn et al., 2011). For instance, tumour-derived EVs carrying miR-9 activate the JAK/STAT signalling cascade in endothelial cells by suppressing SOCS5, thereby promoting angiogenesis. Similarly, EV-miR-23a, part of the miR-23a/27a/24-2 cluster, has been shown to drive postoperative progression and metastasis in early-stage NSCLC by activating Wnt/β-catenin signalling and inducing epigenetic silencing of p16 and CDH13 (Fan et al., 2021). In addition, EV-miR-105 contributes to invasion and vascular remodelling within the tumour microenvironment (Chatterjee et al., 2020). Beyond RNA species, EVs can also carry DNA fragments including genomic, mitochondrial, and extrachromosomal circular DNA (eccDNA) that mirror donor cell mutations and are emerging as promising biomarkers for cancer detection and monitoring (Qian H. et al., 2024).

The lipid composition of EVs defines their structure and function, being rich in cholesterol, sphingomyelin, glycosphingolipids, and ceramide (Zhou et al., 2017). These lipids regulate vesicle budding and stability, and tumour EVs enriched in sphingolipids can modulate immune responses (Pathania et al., 2021). Overall, the molecular composition of EVs mirrors their cellular origin, with miRNA cargo in particular emerging as a critical signature for lung cancer diagnostics and therapeutic targeting (Salomon et al., 2022; Amin et al., 2024).

2.3 Mechanisms of extracellular vesicle release

The biogenesis and secretion of EVs are subtype-specific and occur through tightly regulated intracellular pathways. Exosomes originate from the endosomal system via inward budding of the endosomal membrane, resulting in the formation of intraluminal vesicles (ILVs) within MVBs (Dixson et al., 2023; Kang et al., 2021; Teng and Fussenegger, 2020; Battistelli and Falcieri, 2020; Gurung et al., 2021). When MVBs fuse with the plasma membrane, ILVs are secreted into the extracellular space as exosomes (Krylova and Feng, 2023; Palomar-Alonso et al., 2023) (Figure 2). This process is primarily governed by the endosomal sorting complex required for transport (ESCRT) machinery, although ESCRT-independent mechanisms involving ceramide synthesis and tetraspanin clustering have also been identified (Jin et al., 2022; Liu et al., 2024). Exosome release is facilitated by Rab GTPases and SNARE complexes, which regulate MVB trafficking and membrane fusion events (Ovčar and Kovačič, 2025). Pathological conditions such as hypoxia and oncogenic signalling increase exosome release, enriching them with tumour-derived miRNAs (Kenific et al., 2021; Zubkova et al., 2024). Microvesicles are EVs formed by the direct outward budding of the plasma membrane (Chatterjee et al., 2024).

Figure 2

Figure 2. Biogenesis Pathways of Exosomes and Microvesicles. Created with BioRender, License No. UX28DAB76O. Distinct intracellular mechanisms underlie the formation of exosomes and microvesicles. Exosomes are generated as intraluminal vesicles within MVBs and are released following MVB fusion with the plasma membrane via ESCRT-dependent or ESCRT-independent pathways. Microvesicles originate by direct outward budding of the plasma membrane, regulated by cytoskeletal remodeling, calcium signalling, phospholipid asymmetry loss, and involvement of ARF6, TSG101, and related molecules. Apoptotic bodies arise during programmed cell death (apoptosis) through membrane blebbing and cell fragmentation, and typically contain nuclear fragments, cytoplasmic components, and organ.

Apoptotic bodies (ApoBDs) are LEVs formed during programmed cell death because of cell fragmentation (Kakarla et al., 2020). These vesicles may contain remnants of the nucleus, mitochondria, and other organelles, as well as chromatin DNA. ApoBDs are typically enriched in nuclear DNA and chromatin fragments bound to histones, and they display strong external expression of phosphatidylserine (Qian Y. et al., 2024; Singh M. et al., 2025).

The biogenesis and secretion of EVs are tightly regulated processes that adapt to the physiological state of the cell and external stimuli (Erwin et al., 2023). Factors such as cellular stress, hypoxia, elevated intracellular calcium levels, and oncogenic activity are known to enhance exosome and microvesicle release (Gurunathan et al., 2021). Recent advances have highlighted that EV biogenesis is not solely governed by classical ESCRT pathways but also intersects with major intracellular signaling cascades such as mTOR, p53, NF-κB, and MAPK, which dynamically respond to stress and oncogenic activation (Phan et al., 2024; Yeat and Chen, 2025; Huang et al., 2023).

2.4 Role of EVs in tumour progression and intercellular communication

EVs, including exosomes and microvesicles, are actively utilised as key mediators of communication between cancer cells and their surrounding microenvironment (Kalluri and McAndrews, 2023). These nanoscale structures transport proteins, nucleic acids (miRNA, mRNA, lncRNA), lipids, and metabolites, delivering tumour-specific molecular information to recipient cells (Liu et al., 2022; Wang Y. et al., 2023; Samidurai et al., 2023).

Recent studies have further clarified the multifaceted role of EVs in cancer pathogenesis. For instance, Hánělová et al. (2024) demonstrated that EVs released by tumour cells facilitate molecular communication between cancer cells and their surrounding microenvironment (Hánělová et al., 2024; Hanelova et al., 2023). This, in turn, promotes fibroblast activation, tissue remodelling, immune suppression, angiogenesis, formation of the pre-metastatic niche, and enhanced metastatic progression indicating that EVs actively support key components of tumour-associated homeostasis (Caligiuri and Tuveson, 2023; Patras et al., 2023).

EVs can enhance tumour cell proliferation by transporting cancer-specific signalling molecules (Zhang et al., 2021). For example, a study by Patel et al. (2024) demonstrated that EVs derived from non-small cell lung cancer (NSCLC) cells deliver α-SMA (alpha-smooth muscle actin) to surrounding lung fibroblasts and NSCLC cells, thereby promoting cell proliferation and reducing apoptosis levels (Patel et al., 2024).

Additionally, EVs derived from a human colorectal cancer cell model have been shown to enhance tumour cell proliferation and viability by activating the MAPK/ERK signalling pathway (Long et al., 2024; Rahmati et al., 2024). These findings support the notion that EVs promote tumour growth by delivering mitogenic and survival factors (Lopez et al., 2023).

EVs support tumour progression by promoting cancer-associated angiogenesis, the formation of new blood vessels (Ateeq et al., 2024; Vader et al., 2014). For instance, EVs derived from glioblastoma cells have been found to carry highly angiogenic factors such as VEGF, TGF-β, IL-6, and IL-8 (Yekula et al., 2020; Russo et al., 2023). These proteins activate endothelial cells and enhance the delivery of oxygen and nutrients to the tumour. Moreover, EVs from lung adenocarcinoma cells have been shown to stimulate neovascularisation through the delivery of the sortilin protein, which facilitates the transfer of angiogenic molecules like VEGF and IL-8 to endothelial cells (Yang et al., 2025; Palazzo et al., 2022).

EVs play a pivotal role in enhancing the metastatic potential of cancer cells (Chang et al., 2021). By transporting specific molecules that promote the formation of pre-metastatic niches in distant tissues, EVs facilitate tumour dissemination (Giusti et al., 2023). As demonstrated by Li et al. (2024b), tumour-derived EVs can direct organotropic signalling, influencing metastatic organotropism and even modulating the microbial composition of distant tissues (Li et al., 2024b). These vesicles deliver molecules such as, proliferative cytokines, and immunosuppressive factors, which collectively promote, stromal remodelling, and immune suppression in target organs thus creating a favourable microenvironment for metastasis. In this way, EVs act as active mediators that lay the groundwork for metastatic progression (Chen T. et al., 2025; Wiklander et al., 2019).

EVs play a crucial role in enabling cancer cells to evade immune surveillance (Yue et al., 2023). Specifically, tumour-derived EVs often exhibit elevated expression of the immune checkpoint molecule PD-L1, which binds to the PD-1 receptor on T lymphocytes and suppresses immune responses. As a result, EVs facilitate immune evasion by tumour cells and may contribute to reduced efficacy of anti-tumour immunotherapies (Ye et al., 2024; Ahmadi et al., 2024). Moreover, recent evidence by Padinharayil et al. (2025) demonstrated that lung cancer–derived small extracellular vesicles (sEVs) profoundly alter T-cell cytokine expression and protein profiles, leading to reduced T-cell viability and dysregulated apoptosis and inflammatory pathways. While some cytotoxic markers remain upregulated, the overall signalling balance suggests impaired T-cell activation. These findings underscore that tumour-derived EVs do not merely suppress immune surveillance through PD-L1 expression but also reprogram T-cell functional states at the transcriptomic and proteomic level, highlighting their dual role in immune evasion and tumour–immune crosstalk (Padinharayil et al., 2025). Beyond their roles in proliferation, angiogenesis, and immune evasion, recent studies reveal that tumour-derived EVs can also drive epigenetic reprogramming through the transfer of non-coding RNAs (Zhang et al., 2025), reshape cellular metabolism by modulating glycolysis and lipid pathways, and even influence the tumour-associated microbiome to favour metastasis. Moreover, EVs have been implicated in resistance to next-generation immunotherapies by carrying additional immune checkpoint ligands such as TIM-3 and LAG-3 (Kumar et al., 2024). Importantly, emerging clinical trials are now testing EV-derived RNA and protein signatures as predictive biomarkers of therapy response in NSCLC patients (Guo et al., 2023), underscoring their translational potential.

Numerous studies have shown that EVs contribute to the development of resistance to chemotherapy and targeted therapies (Zheng et al., 2024; Fu et al., 2023). Notably, tumour-derived EVs may carry drug resistance related proteins such as P-glycoprotein, which, when delivered to recipient cells, enhance the efflux of cytotoxic agents. For example, in melanoma cells with elevated salicylate levels, P-glycoprotein transferred via EVs has been shown to increase chemoresistance (Fu et al., 2023; Kingreen et al., 2024). These findings highlight the role of EVs as “protective carriers” that mediate drug resistance mechanisms and potentially reduce treatment efficacy (Chen Y. et al., 2025). EVs facilitate tumour metastasis by “priming” target tissues prior to metastatic colonisation (Ghoroghi et al., 2021). They influence stromal cells in distant organs, promoting the formation of a low-immunity, pro-tumorigenic microenvironment. For instance, tumour-derived EVs have been shown to activate macrophages in the bone marrow and lungs, thereby creating favourable conditions for the settlement of metastatic cancer cells (Wang Y. et al., 2023; Wang et al., 2024). In this way, EVs play a decisive role in the establishment of pre-metastatic niches, structurally and functionally supporting the metastatic cascade (Izhar and Lesniak, 2025). Table 1 summarises the molecules transported by EVs associated with different cancer types, their effects on target cells, and the resulting biological outcomes. For instance, EVs derived from lung cancer carry the PD-L1 molecule, which suppresses T-lymphocyte activity, while EVs from breast cancer deliver Annexin II, promoting angiogenesis in endothelial cells (Sato and Weaver, 2018; Abdul-Rahman et al., 2024). In summary, tumour-derived EVs function as multifaceted regulators that not only promote proliferation, angiogenesis, metastasis, and immune evasion, but also drive metabolic and epigenetic reprogramming, ultimately positioning them as both key facilitators of cancer progression and promising targets for therapeutic intervention.

Table 1

Table 1. Characteristics of EVs in different cancer types with their molecular cargo, target cells and biological outcomes.

3 Circulating EVs and their role in lung cancer diagnosis

Over the past decade, the high mortality rate associated with lung cancer has driven numerous multicentre studies aimed at enhancing early tumour detection through integrated imaging techniques (X-ray, PET, PET/CT) and blood test correlations (Deng et al., 2025). One such study, the 2004 COSMOS trial (COSMOS, 2025), enrolled over 5,000 asymptomatic smokers, individuals at increased risk for lung cancer. Participants were monitored over 5 years with annual low-dose spiral CT scans, blood tests, and spirometry, alongside assessments of the link between COPD and lung cancer. In addition, large-scale studies have explored circulating biomarkers and radiomic data in healthy individuals. For instance, the CLEARLY study (National Cancer Institute, 2025) launched in 2018, is a multifactorial “bio-radiomic” protocol combining imaging data with blood-based biomarkers to improve early lung cancer detection. Radiomic profiles associated with early-stage disease have been linked to molecular and cellular markers such as miRNAs (miRNAs), proteins, circulating tumour cells (CTCs), and EVs. EVs, which participate in cell proliferation, differentiation, and inflammation, have attracted increasing attention not only as biomarkers but also for their therapeutic potential through intercellular communication (Velpula and Buddolla, 2025).

A single miRNA strand can control numerous genes by inhibiting their translation, making them powerful tools for both diagnostics and therapeutics (Condrat et al., 2020). Recent advances include the engineering of EVs with specific ncRNAs, although identifying distinct miRNA signatures in early-stage tumours remains a challenge. Notably, reliance on single time-point measurements risks oversimplifying the evolving clonal architecture of lung cancer. Longitudinal profiling of EV cargo, particularly miRNAs, could address this limitation by capturing dynamic changes in tumour biology and thereby improving early detection and risk stratification. In support of this, Shimada et al. (2023) demonstrated that reduced levels of EV-miR-30d-5p were significantly associated with lymphovascular invasion in early-stage lung adenocarcinoma, underscoring its potential as a prognostic biomarker for identifying patients at higher risk of recurrence. This finding highlights how EV-miRNA signatures can extend beyond diagnostic applications into prognostic stratification, especially in the context of early-stage disease where treatment decisions are most critical.

Taken together, these developments position EVs as more than passive biomarkers. They represent multifunctional theranostic platforms with the potential to unify diagnostic precision, real-time monitoring, and therapeutic delivery. In this way, EVs could redefine the role of liquid biopsy in lung cancer by bridging molecular and imaging domains, ultimately enabling earlier, more personalised, and potentially more effective interventions. Here, we will review highlights in the diagnostic and therapeutic potential of EVs in lung cancer, particularly their application as components of liquid biopsies and theranostic agents.

3.1 EVs in the circulation

Understanding the origin of EVs offers key insights into the diverse tissue and cellular sources contributing to the circulating EV population. Notably, an analysis of 101 human plasma samples revealed that 99.8% of circulating EVs are derived from hematopoietic cells, with only 0.2% originating from non-hematopoietic tissues (Li Y. et al., 2020). To trace the sources of EVs, an EV-origin method based on extracellular RNA (exLR) profiles was developed (Li Y. et al., 2020; Shaba et al., 2022). This approach involved several steps, including processing RNA-seq data from various tissues and cell types, constructing and refining signature matrices, selecting and validating predictive models, and mapping the EV origin atlas across normal and disease states using a dedicated algorithm.

In the circulatory system, the majority of EVs originate from platelets. As central players in the haemostatic process, platelets are equipped with various granules that, upon activation by specific stimuli often mediated by components of the complement system release their contents and generate microvesicles (MVs) through outward budding of the plasma membrane (Heijnen et al., 1999; Macey et al., 2011). This mechanism not only underscores the critical function of platelets in coagulation but also highlights their emerging role in intercellular communication within the vasculature.

Beyond platelets, several malignancies, including glioblastoma (GBM), gastric (GC), lung (LC), and skin cancers (SC), have been identified as prolific sources of EVs (Chang et al., 2021; Saber et al., 2020). Platelet-derived EVs, due to their rich and diverse molecular cargo, have been shown to interact dynamically with elements of the tumour microenvironment (TME), contributing to cancer progression, remodelling of the TME, and facilitation of metastatic spread (Cho, 2021). The circulating EV pool is further enriched by contributions from various immune and vascular cell types, including monocytes, macrophages, dendritic cells, natural killer (NK) cells, B and T lymphocytes, megakaryocytes, and endothelial cells (Raposo et al., 1996; Ren et al., 2011; Żmigrodzka et al., 2016). In contrast, tissues such as adipose, skeletal muscle, and cardiac tissue release comparatively lower quantities of EVs under physiological conditions (Chaturvedi et al., 2015; Ogawa et al., 2010).

Importantly, cancer cells actively secrete EVs not only into the bloodstream but also into local tissue fluids, enhancing their potential utility as diagnostic biomarkers (Melo et al., 2015). This abundant and specific release of EVs supports their application in non-invasive cancer diagnostics and disease monitoring. Accordingly, ongoing investigations into the tissue-specific origins and molecular heterogeneity of EVs hold great promise for advancing our understanding of cellular diversity and improving the precision of diagnostic strategies (Yáñez-Mó et al., 2015).

EVs have attracted great interest as circulating biomarkers in lung cancer. Lung cancer is often diagnosed late, so there is an intense effort to find non-invasive markers for early detection. EVs are of particular interest because they are more numerous and intrinsically more stable than other liquid biopsy analytes (e.g. cell-free DNA or circulating tumour cells) (Castro-Giner et al., 2018; Caputo et al., 2023). The lipid bilayer protects EV contents (including RNA) from enzymatic degradation in blood. In fact, it has been demonstrated that EV membranes preserve miRNAs under harsh conditions (extreme pH or RNases) far better than free miRNA alone (Russell et al., 2019). For these reasons, EVs are considered ideal vehicles for carrying tumour-derived molecular signals into circulation. Tumour-derived EVs in the blood can thus serve as a “liquid biopsy” of the tumour, carrying on their surface or within their lumen a snapshot of the tumour’s molecular state. Recent reviews note that EV-miRNAs have already been recognised as robust biomarkers in various cancers, assisting in diagnosis and prognosis. In lung cancer specifically, EVs are being actively pursued as diagnostic tools because they can reveal oncogenic mutations and gene expression changes (including miRNAs) non-invasively.

Multiple studies report that cancer patients have elevated levels of circulating EVs relative to healthy individuals, with EV counts often increasing with tumour stage (Caputo et al., 2023). For instance, one study found that EV levels in pulmonary blood correlated strongly with NSCLC clinical stage (Sohal and Kasinski, 2023). Tumour cells can secrete tens of thousands of EVs per day approximately 20,000 vesicles per cell within 48 h a figure corroborated by quantitative studies reporting medulloblastoma cells release between 13,400 and 25,300 EVs per cell during the same period (Choi et al., 2020; Balaj et al., 2011).

Importantly, EVs carry tumour-specific molecules (mutant EGFR, KRAS, PD-L1, oncogenic miRNAs, etc.) that reflect the molecular status of the tumour. Comparative analyses have found distinct profiles of EV cargo in lung cancer patients versus controls, for example, specific EV miRNA signatures differ significantly between NSCLC patients and healthy subjects. Functionally, circulating EVs from lung tumours can reprogram recipient cells: they transfer oncogenic proteins and RNAs that alter the tumour microenvironment (TME) and pre-metastatic niches (Li Y. et al., 2020; Han et al., 2024). Owing to their exceptional stability, tumour-specific miRNA profiles, and ability to transfer oncogenic cargo that reprograms recipient cells, circulating EVs represent heterogeneous yet informative biomarkers that reflect the tumour’s molecular landscape and support both diagnosis and prognosis in lung cancer (Ciferri et al., 2021; Sohal and Kasinski, 2023).

3.2 Functional role of EVs in cancer

Beyond their biomarker value, EVs play active roles in lung cancer biology. Tumour-derived EVs promote angiogenesis, invasion and immune evasion. For example, lung cancer exosomes can carry immune-suppressive signals that inhibit CD8⁺ T cells and natural killer cells, and they can reprogram stromal or bone marrow cells to create a permissive metastatic niche (Abdul Manap et al., 2024; Carreca et al., 2024). Moreover, EVs also shuttle oncogenic proteins and RNAs; for instance, EVs from NSCLC patients were found to carry EGFR mutations and oncogenic ALK–EML4 fusions, potentially enabling detection of driver mutations from blood (Rabinowits et al., 2009; Rolfo et al., 2017; Yanaihara et al., 2006). Thus, EVs mediate cell–cell communication in the tumour microenvironment and beyond. They transfer functional cargo (mRNAs, noncoding RNAs and proteins) that can reprogram recipient cells for example, altering gene expression, promoting proliferation or conferring drug resistance (Sun and Chang, 2024; Prieto-Vila et al., 2021).

All cells including lung cancer cells constitutively secrete EVs (Saviana et al., 2021). Cancer cells may release even more EVs than normal cells due to oncogenic stress. EVs from lung tumours enter the bloodstream through leaky tumour vasculature and drainage from lung parenchyma (Bebelman et al., 2021; Xu D. et al., 2022). Notably, EVs have been detected in bronchoalveolar lavage fluid and pleural effusions of lung cancer patients as well as in peripheral blood. Because EVs mirror the molecular composition of the donor cells, blood EVs can carry tumour-specific signatures (proteins, RNAs) even in early-stage disease (Liam et al., 2020; Tang et al., 2023). In summary, EVs are ubiquitous in circulation and serve as carriers of tumour-derived information.

3.3 EV-mediated transfer of miRNAs

EVs selectively package and shuttle miRNAs as signalling cargo. Packaging is an active, regulated process: specific RNA-binding proteins recognise sequence motifs on miRNAs to sort them into EVs. For example, the RBP hnRNPA2B1 (when sumoylated) binds “EXO-motifs” in certain miRNAs, loading them into exosomes (Li C. et al., 2021). This selectivity means exosomal miRNA profiles often differ markedly from parent cells. Other mechanisms, for example, ceramide-dependent secretion or Ago2-associated loading have also been implicated, reflecting the complex regulation of EV cargo. Once released, EVs can deliver their miRNA payload to diverse recipient cells, modulating cancer and host pathways (Arora and Verma, 2024; Albanese et al., 2021). In lung cancer, key examples include (Figure 3).

Figure 3

Figure 3. EVs released by tumour cells deliver miRNAs to recipient cells, modulating lung cancer progression through multiple pathways. (1) Immune modulation: Tumour-derived EVs carrying miR-21/miR-29a activate NF-κB via TLR7/8 on immune cells, promoting inflammation and tumour growth. (2) Immune evasion: Hypoxic NSCLC-derived EVs enriched in miR-210/miR-23a suppress NK cell cytotoxicity, aiding immune escape. (3) Angiogenesis: EV miR-23a and miR-21 enhance VEGF expression via HIF-1α stabilisation and STAT3 activation, respectively (4) Metastasis and EMT: EV miRNAs (e.g. miR-193a, miR-210) and transcription factors (e.g. SNAI1, ZEB1) promote epithelial–mesenchymal transition and invasiveness through STAT3, Wnt, and TGF-β signalling.

Immune modulation: Tumour-derived EVs containing miR-21 and miR-29a bind Toll-like receptors (TLR7/8) on immune cells, triggering an NF-κB–mediated inflammatory cascade (↑TNFα, IL-6) that promotes tumour growth and metastasis (Fabbri et al., 2012).

Immune evasion: Hypoxic NSCLC cells secrete EVs enriched in miR-210 and miR-23a, which suppress natural killer (NK) cell cytotoxicity (e.g. downregulating CD107a on NK cells) and aid immune escape (Berchem et al., 2016).

Angiogenesis: EV miR-23a (upregulated under hypoxia) targets endothelial prolyl hydroxylases (PHD1/2), stabilising HIF-1α and VEGF to enhance angiogenesis. Similarly, EV miR-21 activates STAT3 signalling in lung epithelial/endothelial cells, upregulating VEGF and promoting blood vessel formation (Hu et al., 2019).

Metastasis/EMT: EV miRNAs can induce epithelial–mesenchymal transition and migration. For example, EVs from cancer-associated fibroblasts carry transcription factors like SNAI1/ZEB1 or miRNAs (e.g. miR-193a, miR-210 from bone marrow cells) that prime lung cells for invasiveness (via STAT3, Wnt, TGF-β pathways) (Zhang et al., 2021; Fan et al., 2020).

Through these and other pathways (NF-κB, STAT3, PI3K/Akt, etc.), EV-delivered miRNAs orchestrate multiple aspects of lung cancer progression, including proliferation, invasion, immune suppression, and metastatic niche formation. Notably, many of these functions have been validated in vitro and in animal models, underscoring the causal role of EV-miRNA transfer in lung cancer pathogenesis and immune modulation (Iranpanah et al., 2023; Yoo et al., 2018).

Other examples of EV-miRNAs in lung cancer include miR-30e-3p, which is downregulated in chemoresistant NSCLC and functions as a predictive biomarker for cisplatin response through regulation of DNA damage repair pathways (Papadaki et al., 2025), and let-7e, a tumour-suppressive exosomal miRNA whose reduced expression correlates with metastasis and poor clinical outcome (Xu et al., 2021); Additional EV-miRNAs such as miR-451a and miR-486-5p serve as diagnostic and prognostic biomarkers distinguishing small-cell from non-small-cell lung cancer (Niu et al., 2025; Ding et al., 2021), while specific EV-miRNA panels have been described for adenocarcinoma and squamous carcinoma subtypes (Abdipourbozorgbaghi et al., 2024). In aggregate, dozens of tumour-derived miRNAs have been detected in blood EVs of lung cancer (Martínez-Espinosa et al., 2024). These miRNAs include oncogenic ones and tumour-suppressors that are dysregulated in cancer (Qian H. et al., 2024; Tulinsky et al., 2022; Ye et al., 2023). Specifically, exosomal miR-21 has been experimentally shown to promote macrophage M2 polarization and tumour progression in NSCLC by targeting IRF1 under hypoxic conditions (Jin and Yu, 2022). Tumour-associated EV-miRNAs in lung cancer are summarised in Table 2, organised by subtype and stage, clinical significance, and mechanistic pathways.

Table 2

Table 2. Tumour-associated EV-miRNAs in lung cancer organised by subtype, stage, clinical significance, and mechanistic pathways.

Most evidence to date derives from in vitro and animal studies, underscoring the causal role of EV-miRNA transfer in lung cancer pathogenesis. Yet, a critical translational gap remains: whether circulating EV-miRNAs act as drivers of disease in humans or represent epiphenomena of tumour activity. Addressing this will require interventional studies targeting EV-miRNA pathways, which could clarify their dual value as biomarkers and therapeutic targets.

Given their dual role as both effectors of tumour progression and stable carriers of molecular cargo, EVs occupy a unique position where the same vesicles that drive oncogenic communication can also be harnessed as non-invasive reporters of tumour presence and behaviour.

3.4 Potential for early detection and non-invasive monitoring

Circulating EVs and their miRNAs show great promise as non-invasive lung cancer biomarkers. Because they circulate at high levels and protect their cargo, EV-based assays can sensitively detect tumour signals. For example, a recent study built a 5-miRNA EV signature from plasma that achieved AUC = 0.920 for distinguishing malignant from benign pulmonary nodules (training cohort) (Zheng et al., 2022). Other large studies report EV miRNA panels with sensitivities ∼75–85% and specificities ∼60–80% for early NSCLC detection. In one cohort of 330 NSCLC patients and 332 controls, combining serum exosomal miR-5684 and miR-125b-5p gave AUC 0.793 (sensitivity 82.7%, specificity 62.1%) (Zhang et al., 2020). Another study showed that adding EV miRNAs (miR-320a, miR-622) to serum CEA and CYFRA21-1 markers could distinguish metastatic vs. non-metastatic NSCLC with AUC ≈ 0.90 (Wang et al., 2020). These results demonstrate that EV-miRNA profiles can rival or complement existing tumour markers.

EV-based liquid biopsy is being evaluated in clinical settings. For example, a phase 2 trial (ChiCTR1800019877) used EVs from bronchoalveolar lavage fluid (BALF) of NSCLC patients: targeted EV-DNA/RNA analysis (ddPCR, NGS) identified EGFR driver and resistance mutations without tissue biopsy (Tulinsky et al., 2022; Rayamajhi et al., 2024). More broadly, high-throughput platforms (small-RNA NGS of EVs, digital PCR, and emerging microfluidic/nanotech devices) enable multiplexed EV biomarker measurement. Notably, advanced EV-isolation chips (e.g. AC-electrokinetic “Verita” systems) can rapidly enrich exosomes for downstream protein and RNA assays, pointing to scalable diagnostics (Hinestrosa et al., 2022).

Compared to traditional liquid biopsy analytes, EVs offer distinct advantages. Their lipid envelope renders cargo (miRNAs, mRNAs, DNA) more stable than unprotected cell-free nucleic acids. EV assays can capture a broader spectrum of tumour material (RNA and protein in the same vesicle) than ctDNA alone. Moreover, because EVs are continuously shed by tumours, they may detect cancer signals even when ctDNA levels are low (e.g. early-stage disease). However, challenges remain such as EV isolation lacks standardisation and can co-isolate non-tumour vesicles or lipoproteins, potentially reducing specificity. Analytical variability (yield/purity) and the heterogeneous origins of EVs in blood can complicate interpretation (Irmer et al., 2023; Phillips et al., 2021). Nonetheless, EV-based tests enable truly repeatable “liquid biopsies” with minimal patient risk.

In summary, circulating EVs are emerging as a powerful liquid-biopsy source for lung cancer. They can harbour sensitive signatures of tumour miRNAs and proteins, with multiple studies reporting promising diagnostic metrics (high AUC, sensitivity/specificity). Ongoing trials and improved technologies (NGS, ddPCR, nano-capture chips) are advancing EV assays toward clinical use. Compared to tissue biopsy or cfDNA tests, EV-based biomarkers offer non-invasive, multi-dimensional insights into tumour genetics and biology, although further validation and standardisation are needed before routine deployment.

4 Technological approaches for EV isolation and miRNA profiling

4.1 Isolation techniques for EVs: principles, advantages, and limitations

Considering their diverse functions and promising clinical applications, achieving high yields and quality of sEVs is crucial. Numerous isolation methods have been developed, primarily based on the biophysical and biochemical properties of EVs, such as size, density, shape, and surface markers. The choice of isolation technique should be guided by both the intended application whether diagnostic or therapeutic, and the complexity of the biological fluid from which the EVs are derived (Jia et al., 2022).

EVs have attracted significant attention over the past few decades as potential drug delivery vehicles and biomarkers for a wide range of diseases. However, a major challenge in advancing their broader application lies in selecting an optimal, efficient, and reliable isolation strategy. Commonly used techniques include filtration, ultracentrifugation, and affinity-based separation. To obtain well-purified and functionally intact vesicles, it is often necessary to use a carefully selected combination of isolation and purification methods (Akbar et al., 2022). Beyond these approaches, additional strategies have been increasingly employed in recent years. Density gradient centrifugation provides higher purity by separating EVs from lipoproteins and protein aggregates, though it is labour-intensive (Greening et al., 2015). Size-exclusion chromatography (SEC) is considered gentle and reproducible, preserving vesicle integrity but producing diluted fractions (Monguió-Tortajada et al., 2019). Precipitation-based methods, such as PEG-mediated precipitation, are simple and scalable but often co-isolate protein contaminants (Wang P. et al., 2023). Immunoaffinity capture allows enrichment of EV subpopulations using antibodies against markers like CD9, CD63, and CD81, yet yields are typically low and costs high (Fan et al., 2023). More recently, microfluidic-based devices that integrate acoustic, immunoaffinity, and electrophoretic principles have enabled rapid and high-throughput EV isolation from small sample volumes, holding strong potential for clinical translation, though large-scale validation is still required (Hassanzadeh-Barforoushi et al., 2025; Dai et al., 2025).

Numerous techniques have been developed for the isolation of EVs; however, none have yet achieved complete removal of contaminants that may compromise downstream analyses. While innovative and improved methodologies continue to emerge, their broader adoption remains limited due to the need for specialised expertise and the high associated costs (Stam et al., 2021). Table 3 provides a comprehensive overview of both conventional and recently developed methods for the isolation of EVs. Each technique is described by its underlying principle, along with key advantages and limitations relevant to research and clinical applications.

Table 3

Table 3. Comparison of EV isolation methods: Principles, advantages, and limitations.

4.2 Analytical methods for profiling miRNAs in EV

The identification of miRNAs within EVs is critical for elucidating mechanisms of intercellular communication and advancing their application as diagnostic biomarkers (Xu D. et al., 2022). A range of methodologies has been developed for the qualitative and quantitative profiling of miRNAs in EVs, each characterised by distinct principles, strengths, and limitations. Among these, quantitative reverse transcription polymerase chain reaction (RT-qPCR) remains the most widely employed technique due to its high sensitivity and specificity for known miRNA targets. In addition, several other analytical strategies have been established, including molecular beacon in situ hybridisation (MB in situ), surface-enhanced Raman scattering (SERS), microarray analysis, next-generation sequencing (NGS), and isothermal amplification method (Xu M. et al., 2022) (Table 4).

Table 4

Table 4. Summary of advantages and disadvantages of miRNA detection methods.

4.2.1 Quantitative reverse transcription polymerase chain reaction (RT-qPCR)

The gold standard method that is most commonly used for detecting miRNA in EVs. It depends on two stages: first is the synthesis of complementary DNA by reverse transcriptase (RT), followed by using cDNA for PCR amplification. The amplification process is monitored in real time by measuring fluorescence signals emitted either from a double-stranded DNA-binding dye or a sequence-specific fluorescent probe (Xu Y. et al., 2022). In lung cancer research, RT-qPCR has been widely applied to quantify circulating EV-miRNAs such as miR-21, miR-155, and miR-210-3p, which are associated with tumour progression, metastasis, and poor prognosis (Jin and Yu, 2022; Li X. et al., 2021; Hassanin and Ramos, 2024). To solve the challenge of low sensitivity, droplet digital PCR (ddPCR) was designed. ddPCR showed higher accuracy and reproducibility for serum miRNA and can detect low copy numbers of nucleic acids, however, it requires special equipment and is costly (Hindson et al., 2013). In addition, high-throughput RT-qPCR platforms such as Fluidigm BioMark, together with the use of locked nucleic acid (LNA)-modified primers, have enhanced sensitivity and multiplexing capacity, enabling robust detection of low-abundance EV-miRNAs from minimal sample volumes (Takousis, 2018; Jang et al., 2011; He et al., 2021).

4.2.2 Molecular beacon in situ (MB in situ)

The molecular beacon (MB) is a nanoscale, bi-labelled oligonucleotide probe structured as a hairpin loop, featuring a fluorescent reporter dye at one end and a quencher molecule at the opposite end. The resulting fluorescence intensity is directly proportional to the concentration of the MB–miRNA hybrid (Lee et al., 2015). It is a simple process that does not need RNA extraction or amplification, it depends on sample incubation with the beacon. The drawback of this method is the false negative that is caused by low concentration (Lee et al., 2018). To address these limitations, nanomaterial-assisted probes such as graphene oxide and quantum dots have been developed to enhance signal-to-noise ratios and reduce false negatives. Furthermore, microfluidic integration of MB assays has enabled automated, high-throughput detection of EV-miRNAs in clinical samples (Oliveira et al., 2020; Lee et al., 2016). In the context of lung cancer, MB-based approaches have been applied for detecting EV-associated miRNA signatures in patient-derived samples, offering rapid and sensitive monitoring of disease-related molecular changes. This highlights their potential as non-invasive diagnostic and prognostic tools specifically tailored to lung cancer.

4.2.3 Surface-enhanced Raman scattering (SERS)

An increasing number of studies are focusing on the detection of EV-derived miRNAs (miRNAs) using surface-enhanced Raman scattering (SERS) techniques. A recent study demonstrated the use of a modified dual SERS biosensor for the sensitive detection of miRNAs isolated from exosomes. The biosensor incorporates a SERS label consisting of Fe₃O₄@Ag-DNA-Au@Ag@DTNB nanoparticles, functionalised with DNA oligonucleotides complementary to the target miRNA. Upon hybridisation, the target miRNA forms a duplex with the complementary DNA, which is subsequently recognised and cleaved by a duplex-specific nuclease. This cleavage event leads to the release of the SERS-labelled nanoparticles from the substrate, resulting in a measurable quenching of the Raman signal (Pang et al., 2019). More recent SERS platforms allow multiplexed detection of multiple EV-miRNAs simultaneously, and the incorporation of machine learning-assisted spectral analysis has enhanced diagnostic accuracy and sensitivity, supporting their application in clinical liquid biopsy (Neettiyath et al., 2024; Xu et al., 2025).

4.2.4 Microarray

Microarray analysis relies on the use of pre-designed labelled probes that hybridise specifically with complementary cDNA sequences. In this approach, total RNA is first extracted from EVs isolated from the biological sample. Subsequently, a complementary DNA (cDNA) library is synthesised from the extracted RNA. For miRNA detection, the resulting cDNA is incubated with immobilised probes on the microarray chip. Hybridisation occurs between the target cDNA and the corresponding labelled probes, and the relative expression levels of miRNAs are quantified based on the intensity of the resulting hybridisation signals (Sevenler et al., 2018; Li P. et al., 2020). In lung cancer studies, EV-derived miRNA microarray profiling has enabled the identification of diagnostic signatures capable of distinguishing malignant from benign pulmonary nodules, supporting its value in liquid biopsy approaches.

4.2.5 Next-generation sequencing (NGS)

NGS is a high-throughput technology widely used in transcriptome analysis (Miller et al., 2022). It consists of several steps starting from RNA is first extracted and purified, followed by the ligation of universal adaptors to the 5′ and 3′ ends. Reverse transcription and PCR amplification are then performed before sequencing. Compared to microarrays, NGS has superior sensitivity and can overcome the limitations of microarrays, such as the need for large sample quantities and the inability to detect unknown miRNA (Xu D. et al., 2022). When applied to lung cancer, NGS-based EV-miRNA profiling has uncovered novel miRNA biomarkers linked to tumour stage and prognosis, offering higher resolution for early detection and disease monitoring.

4.2.6 Isothermal amplification methods

Isothermal amplification has emerged as a promising alternative to polymerase chain reaction (PCR) for the rapid and efficient amplification of nucleic acids. Unlike PCR, isothermal amplification operates at a constant temperature, enabling nucleic acid amplification under simplified conditions, such as in a water bath. Since its introduction in the early 1990s, a variety of isothermal amplification methods have been developed, offering rapid, sensitive, and straightforward approaches for nucleic acid detection without the need for specialised thermal cycling equipment (Zhao et al., 2015). Isothermal amplification is divided into enzymatic isothermal amplification, that based on exponential or linear amplification kinetics and includes loop-mediated isothermal amplification (LAMP), nuclear acid sequence-based amplification (NASBA), rolling circle amplification (RCA), exponential amplification reaction (EXPAR), and duplex-specific nuclease amplification reaction (DSNAR) and enzyme-free isothermal amplification that relies on competitive hybridisation, including catalytic hairpin assembly (CHA) and hybrid chain reaction (HCR) (Gines et al., 2020).

4.3 Challenges in miRNA profiling from plasma- and serum-derived EVs

The most common human biofluids that have been commonly used for EVs isolation are plasma and serum. The major significant challenge that is associated with these samples is the availability of limited volume, which results in low yield of RNA that could affect the downstream applications, for example, that 2 mL aliquot of serum yields about 200 pg/µL of RNA leading to a reduction in miRNA profiling analyses (Chen et al., 2022). Additionally, the type of isolation method affects the yield of miRNA (Gámez-Valero et al., 2016). Furthermore, heterogeneity of RNA in EVs is considered a problem, as some researchers have suggested that the sEVs lack miRNA enrichment (Chen et al., 2022; Li C. et al., 2021), while others suggest that sEVs carry more tRNA (Chevillet et al., 2014; Hoen et al., 2012). Also, current RNA quality control standards were originally developed for cellular RNA analyses; this method does not represent the RNA cargo that is typically found in sEVs (Valadi et al., 2007; Bellingham et al., 2012; Murillo et al., 2019). Another limitation is the technical variability for effective RNA quantification that requires establishing references and processing controls before downstream computational processing (Tesovnik et al., 2021). Furthermore, the RNA subtypes in EVs are different from cellular small RNA (originally optimised for cellular RNA) may be suboptimal for EV-derived RNA (Chen et al., 2022; Eldh et al., 2012). Moreover, the accuracy of RNA mapping, size distribution profiles and transcript abundance estimation are affected by the selection of sequencing aligners and annotation databases; as a result, analysing EV transcriptomics is more challenging than traditional cellular transcriptomics (Padilla et al., 2023; Everaert et al., 2019).

Collectively, these challenges highlight the urgent need for standardised protocols, EV-specific quality control measures, and tailored analytical approaches to ensure the accuracy, reproducibility, and clinical relevance of EV-derived miRNA profiling.

4.4 Artificial intelligence and next-generation analytical tools

Integration of artificial intelligence (AI) with microfluidic platforms has been shown to enhance EV isolation and analysis. A deep learning–based on-chip system demonstrated automated image identification of tumour exosomes, reducing manual intervention and increasing throughput. Such approaches improve sensitivity, reproducibility, and workflow efficiency, though challenges remain regarding dataset quality, generalisability, and model interpretability (Lu et al., 2025). Beyond isolation, machine learning has also been applied to EV analysis in clinical contexts such as transplant monitoring, where EV-derived molecular features combined with AI enabled earlier and more accurate detection of graft rejection than conventional biomarkers. Although broader validation is needed, this illustrates the potential of AI to extend the diagnostic utility of EVs (Burrello et al., 2025). In oncology, machine learning similarly enhances EV analysis by integrating complex molecular data to improve classification, early detection, and treatment monitoring. Despite these advances, progress is limited by variability in isolation methods, small cohort sizes, and interpretability challenges, underscoring the need for standardised approaches and large-scale validation (Greenberg et al., 2023). Looking ahead, AI also shows promise in advancing EV-based precision drug delivery by optimising isolation, loading, and therapeutic targeting. However, translation into clinical practice will require overcoming constraints related to dataset quality, model transparency, and regulatory approval (Greenberg et al., 2023).

Recent advances have sought to overcome the challenges of EV heterogeneity and limited sensitivity in miRNA-based diagnostics. Deep learning has recently been applied to enhance miRNA profiling within single EVs for cancer diagnosis. By combining fluorescence imaging with AI-based classification, this approach enables multiplexed detection of miRNA signatures at the single-vesicle level, improving sensitivity and revealing EV heterogeneity. Such methods hold promise for more accurate liquid biopsy applications, though further validation and standardisation are required for clinical translation (Zhang et al., 2024). Similarly, a dual-surface-protein orthogonal barcoding strategy has been developed to enable simultaneous tracing of exosome subsets and profiling of their miRNA cargo. By linking surface protein identity with molecular signatures, this approach provides greater resolution of exosome heterogeneity and improves specificity in distinguishing tumour-derived exosomes. Such methods offer valuable insights for cancer diagnostics, though their complexity and need for clinical validation remain important limitations (Lei et al., 2023).

5 EV-mediated miRNA therapeutics: strategies, applications, and clinical translation

EVs are being engineered as biocompatible carriers for miRNA mimics and antimiRs to modulate oncogenic pathways in lung cancer. Preclinical studies demonstrate that EVs can protect miRNA cargo from nuclease degradation, improve cellular uptake, and enable functional delivery to tumour and stromal cells, offering advantages over synthetic nanoparticles. Recent reviews outline multiple lung-relevant targets with roles in proliferation, EMT, angiogenesis, and immune evasion, positioning EVs as promising vectors for these payloads (Munir et al., 2020; Poongodi et al., 2025).

Loading approaches include producer-cell overexpression, electroporation, sonication, saponin permeabilisation, and chemical transfection; each has trade-offs in loading efficiency and vesicle integrity. For tissue targeting, surface display and antibody/aptamer decoration are under active development to increase tumour tropism and reduce off-target exposure (Seyhan, 2023).

Growing experimental evidence supports EV-mediated restoration of tumour-suppressive miRNAs or inhibition of oncogenic miRNAs in thoracic oncology models. For instance, EV-delivered miR-200 family members (miR-200a/b/c, miR-141, and miR-429) suppress EMT and metastatic behaviour in NSCLC by targeting ZEB1/2 and restoring E-cadherin, as confirmed in recent experimental studies (Ling and Yang, 2024). Likewise, EV-miR-126 has demonstrated anti-angiogenic and anti-metastatic effects, while cancer-associated fibroblast–derived EVs were shown to regulate metastatic phenotypes through miR-200 signalling axes. Although most findings remain preclinical, these studies collectively substantiate EVs as modular carriers capable of reprogramming oncogenic circuits in NSCLC (Romanò et al., 2024).

EV cargo can modulate response to immune checkpoint blockade. Beyond PD-L1 transfer, miRNA payloads that down-tune immunosuppressive pathways may synergise with anti-PD-1/PD-L1 by reshaping T-cell states and the cytokine milieu. Lessons from the first-in-human miRNA mimic trial underscore the need for careful dosing, immune monitoring, and delivery-platform selection after immune-related toxicities led to early termination; EVs are being explored as potentially less immunogenic carriers to revisit such tumour-suppressor miRNAs (Brillante et al., 2024).

Clinical deployment requires standardised manufacturing, release testing, and potency assays. Recent consensus and regulatory-facing guidance emphasise identity, purity, reproducibility, and mechanism-of-action–linked potency metrics across the product life cycle. Parallel efforts track early clinical experience with EV-based interventions and map translational hurdles, scalable production, batch-to-batch consistency, and validated bioassays to accelerate oncology applications (Morse et al., 2005; Ng et al., 2022).

EV-based miRNA therapeutics show strong potential to modulate oncogenic pathways in lung cancer, offering stability and specificity over conventional systems. While preclinical results are promising, clinical translation requires overcoming challenges in safety, manufacturing, and standardisation.

6 Conclusion and future prospects

EVs and their cargo of miRNA molecules represent a rapidly advancing frontier in the non-invasive diagnosis and management of lung cancer. The exceptional stability of EV-carried miRNAs in the circulatory system, along with their cancer-specific expression signatures, make them highly attractive candidates as liquid biopsy biomarkers. Their detection from easily obtainable biological fluids such as blood, saliva, or bronchoalveolar lavage offers practical advantages in terms of patient comfort, cost-effectiveness, and clinical applicability. EV-associated miRNAs have demonstrated significant potential not only in the early detection of NSCLC, but also in the prediction of disease progression, monitoring of therapeutic response, and even in stratifying patients based on likely prognosis. Importantly, these miRNAs may provide real-time insights into tumour evolution and resistance mechanisms, enabling clinicians to dynamically adjust treatment regimens. Despite the promising outlook, several challenges remain. There is a critical need for standardization of EV isolation and miRNA profiling protocols, as well as robust validation across large, multi-centre cohorts to ensure reproducibility and clinical reliability. Furthermore, deciphering the molecular mechanisms through which EV-derived miRNAs regulate tumour initiation, angiogenesis, metastasis, and immune evasion will be essential for their integration into precision oncology. Looking ahead, EVs also offer exciting possibilities as therapeutic vectors, capable of delivering miRNAs or gene-silencing agents directly to tumour cells with high specificity. This opens the door to a new generation of miRNA-based therapeutics, potentially overcoming limitations of conventional treatments by targeting cancer at the epigenetic and post-transcriptional level. Unlike previous reviews that primarily emphasized the diagnostic value of EV-miRNAs, this review provides a broader and updated synthesis by integrating recent insights into EV–miRNA–mediated signaling, unresolved challenges such as heterogeneity and standardisation, and forward-looking perspectives including single-EV detection, multi-omics integration, AI-driven analytics, and therapeutic applications. In conclusion, EV-associated miRNAs stand at the crossroads of diagnostics and therapeutics, offering a unique dual role as both biomarkers and biological modulators. Continued interdisciplinary research combining molecular biology, bioinformatics, and clinical oncology will be essential to translate these insights into tangible benefits for patients with lung cancer. Future prospects include the integration of EV-miRNA profiling with multi-omics approaches (genomics, proteomics, metabolomics) to create more comprehensive biomarker panels for precision medicine. Advances in microfluidics and single-vesicle sequencing may allow high-resolution analysis of miRNA heterogeneity, thereby improving diagnostic specificity. Moreover, the convergence of AI with EV research holds promise for automating biomarker discovery, predicting therapeutic responses, and personalising treatment regimens. Clinically, EV-based delivery systems for engineered miRNAs or gene-silencing tools may emerge as a new generation of targeted therapeutics, though their safety, scalability, and regulatory approval remain key challenges. Ultimately, collaborative efforts across basic science, clinical research, and bioengineering will be required to move EV-miRNAs from bench to bedside and establish them as mainstream tools in lung cancer management.

Author contributions

AB: Writing – original draft, Investigation, Writing – review and editing, Supervision. MA-Y: Writing – review and editing, Writing – original draft. YA: Writing – review and editing. KnS: Writing – review and editing. AA: Writing – review and editing. AY: Writing – review and editing. NJ: Writing – review and editing. KmS: Writing – review and editing. CW: Writing – original draft, Writing – review and editing, Supervision, Conceptualization.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR27195585).

Acknowledgements

The authors gratefully acknowledge BioRender.com for providing the intuitive platform used to create scientific illustrations that significantly enhanced the visual quality of this manuscript.

Conflict of interest

Author CW was employed by Novel Global Community Educational Foundation.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbreviations

ApoBD, Apoptotic Body; ddPCR, Droplet Digital PCR; ESCRT, Endosomal Sorting Complex Required for Transport; EVs, Extracellular Vesicles; LEV, Large Extracellular Vesicles; miRNAs, microRNAs; MVBs, Multivesicular Bodies; NGS, Next-Generation Sequencing; PS, Phosphatidylserine; RT-qPCR, Reverse Transcription quantitative Polymerase Chain Reaction; SERS, Surface-Enhanced Raman Scattering; SEV, Small Extracellular Vesicles.

References

Abdipourbozorgbaghi, M., Vancura, A., Radpour, R., and Haefliger, S. (2024). Circulating miRNA panels as a novel non-invasive diagnostic, prognostic, and potential predictive biomarkers in non-small cell lung cancer (NSCLC). Br. J. Cancer 131, 1350–1362. doi:10.1038/s41416-024-02831-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Abdul Manap, A. S., Ngwenya, F. M., Kalai Selvan, M., Arni, S., Hassan, F. H., Mohd Rudy, A. D., et al. (2024). Lung cancer cell-derived exosomes: progress on pivotal role and its application in diagnostic and therapeutic potential. Front. Oncol. 14, 1459178. doi:10.3389/fonc.2024.1459178

PubMed Abstract | CrossRef Full Text | Google Scholar

Abdul-Rahman, T., Roy, P., Herrera-Calderón, R. E., Khidri, F. F., Omotesho, Q. A., Rumide, T. S., et al. (2024). Extracellular vesicle-mediated drug delivery in breast cancer theranostics. Discov. Oncol. 15 (1), 181. doi:10.1007/s12672-024-01007-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Ahmadi, M., Abbasi, R., and Rezaie, J. (2024). Tumor immune escape: extracellular vesicles roles and therapeutics application. Cell Commun. Signal 22 (1), 9. doi:10.1186/s12964-023-01370-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Akbar, A., Malekian, F., Baghban, N., Kodam, S. P., and Ullah, M. (2022). Methodologies to isolate and purify clinical grade extracellular vesicles for medical applications. Cells 11 (2), 186. doi:10.3390/cells11020186

PubMed Abstract | CrossRef Full Text | Google Scholar

Albanese, M., Chen, Y. A., Hüls, C., Gärtner, K., Tagawa, T., Mejias-Perez, E., et al. (2021). MicroRNAs are minor constituents of extracellular vesicles that are rarely delivered to target cells. PLoS Genet. 17 (12), e1009951. doi:10.1371/journal.pgen.1009951

PubMed Abstract | CrossRef Full Text | Google Scholar

Amin, S., Massoumi, H., Tewari, D., Roy, A., Chaudhuri, M., Jazayerli, C., et al. (2024). Cell type-specific extracellular vesicles and their impact on health and disease. Int. J. Mol. Sci. 25, 2730. doi:10.3390/ijms25052730

PubMed Abstract | CrossRef Full Text | Google Scholar

Arora, S., and Verma, N. (2024). Exosomal microRNAs as potential biomarkers and therapeutic targets in corneal diseases. Mol. Vis. 30, 92–106.

PubMed Abstract | Google Scholar

Ateeq, M., Broadwin, M., Sellke, F. W., and Abid, M. R. (2024). Extracellular vesicles’ role in angiogenesis and altering angiogenic signaling. Med. Sci. (Basel) 12 (1), 4. doi:10.3390/medsci12010004

PubMed Abstract | CrossRef Full Text | Google Scholar

Babuta, M., and Szabo, G. (2022). Extracellular vesicles in inflammation: focus on the microRNA cargo of EVs in modulation of liver diseases. J. Leukoc. Biol. 111 (1), 75–92. doi:10.1002/JLB.3MIR0321-156R

PubMed Abstract | CrossRef Full Text | Google Scholar

Bae, J. H., Lee, C. H., Jung, D., Yea, K., Song, B. J., Lee, H., et al. (2024). Extracellular vesicle isolation and counting system (EVics) based on simultaneous tandem tangential flow filtration and large field-of-view light scattering. J. Extracell. Vesicles 13 (7), e12479. doi:10.1002/jev2.12479

PubMed Abstract | CrossRef Full Text | Google Scholar

Balaj, L., Lessard, R., Dai, L., Cho, Y.-J., Pomeroy, S., Breakefield, X. O., et al. (2011). Tumour microvesicles contain retrotransposon elements and amplified oncogene sequences. Nat. Commun. 2 (1), 180. doi:10.1038/ncomms1180

PubMed Abstract | CrossRef Full Text | Google Scholar

Baranyai, T., Herczeg, K., Onódi, Z., Voszka, I., Módos, K., Marton, N., et al. (2015). Isolation of exosomes from blood plasma: qualitative and quantitative comparison of ultracentrifugation and size exclusion chromatography methods. PloS One 10 (12), e0145686. doi:10.1371/journal.pone.0145686

PubMed Abstract | CrossRef Full Text | Google Scholar

Bartoszewska, E., Misiąg, P., Czapla, M., Rakoczy, K., Tomecka, P., Filipski, M., et al. (2025). The role of microRNAs in lung cancer: mechanisms, diagnostics and therapeutic potential. Int. J. Mol. Sci. 26 (8), 3736. doi:10.3390/ijms26083736

PubMed Abstract | CrossRef Full Text | Google Scholar

Battistelli, M., and Falcieri, E. (2020). Apoptotic bodies: particular extracellular vesicles involved in intercellular communication. Biol. (Basel). 9 (1), 21. doi:10.3390/biology9010021

PubMed Abstract | CrossRef Full Text | Google Scholar

Bebelman, M. P., Janssen, E., Pegtel, D. M., and Crudden, C. (2021). The forces driving cancer extracellular vesicle secretion. Neoplasia 23 (1), 149–157. doi:10.1016/j.neo.2020.11.011

PubMed Abstract | CrossRef Full Text | Google Scholar

Belkozhayev, A. M., Al-Yozbaki, M., George, A., Ye, N. R., Sharipov, K. O., Byrne, L. J., et al. (2022). Extracellular vesicles, stem cells and the role of miRNAs in neurodegeneration. Curr. Neuropharmacol. 20 (8), 1450–1478. doi:10.2174/1570159X19666210817150141

PubMed Abstract | CrossRef Full Text | Google Scholar

Bellingham, S. A., Coleman, B. M., and Hill, A. F. (2012). Small RNA deep sequencing reveals a distinct miRNA signature released in exosomes from prion-infected neuronal cells. Nucleic Acids Res. 40 (21), 10937–10949. doi:10.1093/nar/gks832

PubMed Abstract | CrossRef Full Text | Google Scholar

Berchem, G., Noman, M. Z., Bosseler, M., Paggetti, J., Baconnais, S., Le Cam, E., et al. (2016). Hypoxic tumor-derived microvesicles negatively regulate NK cell function by a mechanism involving TGF-β and miR23a transfer. Oncoimmunology 5, e1062968. doi:10.1080/2162402X.2015.1062968

PubMed Abstract | CrossRef Full Text | Google Scholar

Böing, A. N., Van Der Pol, E., Grootemaat, A. E., Coumans, F. A., Sturk, A., and Nieuwland, R. (2014). Single-step isolation of extracellular vesicles by size-exclusion chromatography. J. Extracell. Vesicles 3 (1), 23430. doi:10.3402/jev.v3.23430

PubMed Abstract | CrossRef Full Text | Google Scholar

Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., et al. (2022). Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 74 (3), 229–263. doi:10.3322/caac.21834

PubMed Abstract | CrossRef Full Text | Google Scholar

Brillante, S., Volpe, M., and Indrieri, A. (2024). Advances in microRNA therapeutics: from preclinical to clinical studies. Hum. Gene Ther. 35 (17–18), 628–648. doi:10.1089/hum.2024.113

PubMed Abstract | CrossRef Full Text | Google Scholar

Burrello, J., Panella, S., Barison, I., Castellani, C., Burrello, A., Airale, L., et al. (2025). Machine learning-assisted assessment of extracellular vesicles can monitor cellular rejection after heart transplant. Commun. Med. 5 (1), 288. doi:10.1038/s43856-025-00999-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Buzas, E. I. (2023). The roles of extracellular vesicles in the immune system. Nat. Rev. Immunol. 23 (4), 236–250. doi:10.1038/s41577-022-00763-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Caligiuri, G., and Tuveson, D. A. (2023). Activated fibroblasts in cancer: perspectives and challenges. Cancer Cell 41 (3), 434–449. doi:10.1016/j.ccell.2023.02.015

PubMed Abstract | CrossRef Full Text | Google Scholar

Cao, W., Zeng, Z., He, Z., and Lei, S. (2021). Hypoxic pancreatic stellate cell-derived exosomal mirnas promote proliferation and invasion of pancreatic cancer through the PTEN/AKT pathway. Aging (Albany NY) 13 (5), 7120–7132. doi:10.18632/aging.202569

PubMed Abstract | CrossRef Full Text | Google Scholar

Caputo, S., Grioni, M., Brambillasca, C. S., Monno, A., Brevi, A., Freschi, M., et al. (2020). Galectin-3 in prostate cancer stem-like cells is immunosuppressive and drives early metastasis. Front. Immunol. 11, 1820. doi:10.3389/fimmu.2020.01820

PubMed Abstract | CrossRef Full Text | Google Scholar

Caputo, V., Ciardiello, F., Corte, C. M. D., Martini, G., Troiani, T., and Napolitano, S. (2023). Diagnostic value of liquid biopsy in the era of precision medicine: 10 years of clinical evidence in cancer. Explor. Target Antitumor Ther. 4 (1), 102–138. doi:10.37349/etat.2023.00125

PubMed Abstract | CrossRef Full Text | Google Scholar

Carreca, A. P., Tinnirello, R., Miceli, V., Galvano, A., Gristina, V., Incorvaia, L., et al. (2024). Extracellular vesicles in lung cancer: implementation in diagnosis and therapeutic perspectives. Cancers 16, 1967. doi:10.3390/cancers16111967

PubMed Abstract | CrossRef Full Text | Google Scholar

Castillo-Sanchez, R., Churruca-Schuind, A., Martinez-Ival, M., and Salazar, E. P. (2022). Cancer-associated fibroblasts communicate with breast tumor cells through extracellular vesicles in tumor development. Technol. Cancer Res. Treat. 21, 15330338221131647. doi:10.1177/15330338221131647

PubMed Abstract | CrossRef Full Text | Google Scholar

Castro-Giner, F., Gkountela, S., Donato, C., Alborelli, I., Quagliata, L., Ng, C. K. Y., et al. (2018). Cancer diagnosis using a liquid biopsy: challenges and expectations. Diagn. (Basel) 8 (2), 31. doi:10.3390/diagnostics8020031

PubMed Abstract | CrossRef Full Text | Google Scholar

Chang, W. H., Cerione, R. A., and Antonyak, M. A. (2021). Extracellular vesicles and their roles in cancer progression. Methods Mol. Biol. 2174, 143–170. doi:10.1007/978-1-0716-0759-6_10

PubMed Abstract | CrossRef Full Text | Google Scholar

Chatterjee, V., Yang, X., Ma, Y., Wu, M. H., and Yuan, S. Y. (2020). Extracellular vesicles: new players in regulating vascular barrier function. Am. J. Physiol. Heart Circ. Physiol. 319 (6), H1181–H1196. doi:10.1152/ajpheart.00579.2020

PubMed Abstract | CrossRef Full Text | Google Scholar

Chatterjee, S., Kordbacheh, R., and Sin, J. (2024). Extracellular vesicles: a novel mode of viral propagation exploited by enveloped and non-enveloped viruses. Microorganisms 12 (2), 274. doi:10.3390/microorganisms12020274

PubMed Abstract | CrossRef Full Text | Google Scholar

Chaturvedi, P., Kalani, A., Medina, I., Familtseva, A., and Tyagi, S. C. (2015). Cardiosome mediated regulation of MMP9 in diabetic heart: role of mir29b and mir455 in exercise. J. Cell. Mol. Med. 19, 2153–2161. doi:10.1111/jcmm.12589

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, Y. S., Ma, Y. D., Chen, C., Shiesh, S. C., and Lee, G. B. (2019). An integrated microfluidic system for on-chip enrichment and quantification of circulating extracellular vesicles from whole blood. Lab. Chip 19, 3305–3315. doi:10.1039/c9lc00624a

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, T. Y., Gonzalez-Kozlova, E., Soleymani, T., La Salvia, S., Kyprianou, N., Sahoo, S., et al. (2022). Extracellular vesicles carry distinct proteo-transcriptomic signatures that are different from their cancer cell of origin. Iscience 25 (6), 104414. doi:10.1016/j.isci.2022.104414

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, Y., Kleeff, J., and Sunami, Y. (2024). Pancreatic cancer cell- and cancer-associated fibroblast-derived exosomes in disease progression, metastasis, and therapy. Discov. Oncol. 15 (1), 253. doi:10.1007/s12672-024-01111-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, T., Chen, D., Su, W., Liang, J., Liu, X., and Cai, M. (2025a). Extracellular vesicles as vital players in drug delivery: a focus on clinical disease treatment. Front. Bioeng. Biotechnol. 13, 1600227. doi:10.3389/fbioe.2025.1600227

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, Y., Douanne, N., Wu, T., Kaur, I., Tsering, T., Erzingatzian, A., et al. (2025b). Leveraging nature’s nanocarriers: translating insights from extracellular vesicles to biomimetic synthetic vesicles for biomedical applications. Sci. Adv. 11 (9), eads5249. doi:10.1126/sciadv.ads5249

PubMed Abstract | CrossRef Full Text | Google Scholar

Chevillet, J. R., Kang, Q., Ruf, I. K., Briggs, H. A., Vojtech, L. N., Hughes, S. M., et al. (2014). Quantitative and stoichiometric analysis of the microRNA content of exosomes. Proc. Natl. Acad. Sci. 111 (41), 14888–14893. doi:10.1073/pnas.1408301111

PubMed Abstract | CrossRef Full Text | Google Scholar

Cho, W. C. S. (2021). Extracellular vesicles: biology and potentials in cancer therapeutics. Int. J. Mol. Sci. 22, 9586. doi:10.3390/ijms22179586

PubMed Abstract | CrossRef Full Text | Google Scholar

Choi, B. H., Quan, Y. H., Rho, J., Hong, S., Park, Y., Choi, Y., et al. (2020). Levels of extracellular vesicles in pulmonary and peripheral blood correlate with stages of lung cancer patients. World J. Surg. 44, 3522–3529. doi:10.1007/s00268-020-05630-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Ciferri, M. C., Quarto, R., and Tasso, R. (2021). Extracellular vesicles as biomarkers and therapeutic tools: from pre-clinical to clinical applications. Biol. (Basel) 10 (5), 359. doi:10.3390/biology10050359

PubMed Abstract | CrossRef Full Text | Google Scholar

Condrat, C. E., Thompson, D. C., Barbu, M. G., Bugnar, O. L., Boboc, A., Cretoiu, D., et al. (2020). miRNAs as biomarkers in disease: latest findings regarding their role in diagnosis and prognosis. Cells 9 (2), 276. doi:10.3390/cells9020276

PubMed Abstract | CrossRef Full Text | Google Scholar

Contado, C. (2017). Field flow fractionation techniques to explore the “nano-world”. Anal. Bioanal. Chem. 409 (10), 2501–2518. doi:10.1007/s00216-017-0180-6

PubMed Abstract | CrossRef Full Text | Google Scholar

COSMOS (2025). Continuous observation of smoking subject. Available online at: https://www.clinicaltrials.gov/study/NCT01248806 (Accessed July 20, 2025).

Google Scholar

Dai, Y., Cui, Y., Li, J., Li, P., and Huang, X. (2025). Integrated microfluidic platforms for extracellular vesicles: separation, detection, and clinical translation. Apl. Bioeng. 9 (3), 031502. doi:10.1063/5.0273892

PubMed Abstract | CrossRef Full Text | Google Scholar

De Sousa, K. P., Rossi, I., Abdullahi, M., Ramirez, M. I., Stratton, D., and Inal, J. M. (2023). Isolation and characterization of extracellular vesicles and future directions in diagnosis and therapy. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 15 (1), e1835. doi:10.1002/wnan.1835

PubMed Abstract | CrossRef Full Text | Google Scholar

Dellar, E. R., Hill, C., Melling, G. E., Carter, D. R. F., and Baena-Lopez, L. A. (2022). Unpacking extracellular vesicles: RNA cargo loading and function. J. Extracell. Biol. 1 (5), e40. doi:10.1002/jex2.40

PubMed Abstract | CrossRef Full Text | Google Scholar

Deng, R., Zhang, K., and Li, J. (2017). Isothermal amplification for microRNA detection: from the test tube to the cell. Accounts Chem. Res. 50 (4), 1059–1068. doi:10.1021/acs.accounts.7b00040

PubMed Abstract | CrossRef Full Text | Google Scholar

Deng, Z., Ma, X., Zou, S., Tan, L., and Miao, T. (2025). Innovative technologies and their clinical prospects for early lung cancer screening. Clin. Exp. Med. 25 (1), 212. doi:10.1007/s10238-025-01752-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Di Bella, M. A. (2022). Overview and update on extracellular vesicles: considerations on exosomes and their application in modern medicine. Biol. (Basel) 11 (6), 804. doi:10.3390/biology11060804

PubMed Abstract | CrossRef Full Text | Google Scholar

Ding, L., Tian, W., Zhang, H., Li, W., Ji, C., Wang, Y., et al. (2021). MicroRNA-486-5p suppresses lung cancer via downregulating mTOR signaling in vitro and in vivo. Front. Oncol. 11, 655236. doi:10.3389/fonc.2021.655236

PubMed Abstract | CrossRef Full Text | Google Scholar

Dixson, A. C., Dawson, T. R., Di, V. D., and Weaver, A. M. (2023). Context-specific regulation of extracellular vesicle biogenesis and cargo selection. Nat. Rev. Mol. Cell Biol. 24 (7), 454–476. doi:10.1038/s41580-023-00576-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Eckhardt, C. M., Gambazza, S., Bloomquist, T. R., De, H. P., Vuppala, A., Vokonas, P. S., et al. (2023). Extracellular vesicle-encapsulated microRNAs as novel biomarkers of lung health. Am. J. Respir. Crit. Care Med. 207 (1), 50–59. doi:10.1164/rccm.202109-2208OC

PubMed Abstract | CrossRef Full Text | Google Scholar

Eldh, M., Lötvall, J., Malmhäll, C., and Ekström, K. (2012). Importance of RNA isolation methods for analysis of exosomal RNA: evaluation of different methods. Mol. Immunol. 50 (4), 278–286. doi:10.1016/j.molimm.2012.02.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Erwin, N., Serafim, M. F., and He, M. (2023). Enhancing the cellular production of extracellular vesicles for developing therapeutic applications. Pharm. Res. 40 (4), 833–853. doi:10.1007/s11095-022-03420-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Everaert, C., Helsmoortel, H., Decock, A., Hulstaert, E., Van Paemel, R., Verniers, K., et al. (2019). Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles. Sci. Rep. 9 (1), 17574. doi:10.1038/s41598-019-53892-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Fabbri, M., Paone, A., Calore, F., Galli, R., Gaudio, E., Santhanam, R., et al. (2012). MicroRNAs bind to toll-like receptors to induce prometastatic inflammatory response. Proc. Natl. Acad. Sci. U.S.A. 109, E2110–E2116. doi:10.1073/pnas.1209414109

PubMed Abstract | CrossRef Full Text | Google Scholar

Fan, J., Xu, G., Chang, Z., Zhu, L., and Yao, J. (2020). miR-210 transferred by lung cancer cell-derived exosomes may act as proangiogenic factor in cancer-associated fibroblasts by modulating JAK2/STAT3 pathway. Clin. Sci. Lond. Engl. 1979 134, 807–825. doi:10.1042/CS20200039

PubMed Abstract | CrossRef Full Text | Google Scholar

Fan, X., Tao, S., Li, Q., Deng, B., Tan, Q. Y., and Jin, H. (2021). The miR-23a/27a/24-2 cluster promotes postoperative progression of early-stage non-small cell lung cancer. Mol. Ther. – Oncolytics 24, 205–217. doi:10.1016/j.omto.2021.12.014

PubMed Abstract | CrossRef Full Text | Google Scholar

Fan, Y., Pionneau, C., Cocozza, F., Boëlle, P. Y., Chardonnet, S., Charrin, S., et al. (2023). Differential proteomics argues against a general role for CD9, CD81 or CD63 in the sorting of proteins into extracellular vesicles. J. Extracell. Vesicles 12 (8), e12352. doi:10.1002/jev2.12352

PubMed Abstract | CrossRef Full Text | Google Scholar

Ferro, A., Saccu, G., Mattivi, S., Gaido, A., Herrera Sanchez, M. B., Haque, S., et al. (2024). Extracellular vesicles as delivery vehicles for non-coding RNAs: potential biomarkers for chronic liver diseases. Biomolecules 14, 277. doi:10.3390/biom14030277

PubMed Abstract | CrossRef Full Text | Google Scholar

Fu, X., Song, J., Yan, W., Downs, B. M., Wang, W., and Li, J. (2023). The biological function of tumor-derived extracellular vesicles on metabolism. Cell Commun. Signal 21 (1), 150. doi:10.1186/s12964-023-01111-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Gámez-Valero, A., Monguió-Tortajada, M., Carreras-Planella, L., Franquesa, M. L., Beyer, K., and Borràs, F. E. (2016). Size-exclusion Chromatography-based isolation minimally alters extracellular vesicles’ characteristics compared to precipitating agents. Sci. Rep. 6 (1), 33641. doi:10.1038/srep33641

PubMed Abstract | CrossRef Full Text | Google Scholar

Gao, S., Guo, W., Liu, T., Liang, N., Ma, Q., Gao, Y., et al. (2022). Plasma extracellular vesicle microRNA profiling and the identification of a diagnostic signature for stage I lung adenocarcinoma. Cancer Sci. 113 (2), 648–659. doi:10.1111/cas.15222

PubMed Abstract | CrossRef Full Text | Google Scholar

Ge, Y., Ye, T., Fu, S., Jiang, X., Song, H., Liu, B., et al. (2023). Research progress of extracellular vesicles as biomarkers in immunotherapy for non-small cell lung cancer. Front. Immunol. 14, 1114041. doi:10.3389/fimmu.2023.1114041

PubMed Abstract | CrossRef Full Text | Google Scholar

Ghoroghi, S., Mary, B., Asokan, N., Goetz, J. G., and Hyenne, V. (2021). Tumor extracellular vesicles drive metastasis (it’s a long way from home). FASEB Bioadv. 3 (11), 930–943. doi:10.1096/fba.2021-00079

PubMed Abstract | CrossRef Full Text | Google Scholar

Ghosh, A., Davey, M., Chute, I. C., Griffiths, S. G., Lewis, S., Chacko, S., et al. (2014). Rapid isolation of extracellular vesicles from cell culture and biological fluids using a synthetic peptide with specific affinity for heat shock proteins. PloS One 9 (10), e110443. doi:10.1371/journal.pone.0110443

PubMed Abstract | CrossRef Full Text | Google Scholar

Gines, G., Menezes, R., Xiao, W., Rondelez, Y., and Taly, V. (2020). Emerging isothermal amplification technologies for microRNA biosensing: applications to liquid biopsies. Mol. Aspects Med. 72, 100832. doi:10.1016/j.mam.2019.11.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Giusti, I., Poppa, G., Di, F. G., D'Ascenzo, S., and Dolo, V. (2023). Metastatic dissemination: role of tumor-derived extracellular vesicles and their use as clinical biomarkers. Int. J. Mol. Sci. 24 (11), 9590. doi:10.3390/ijms24119590

PubMed Abstract | CrossRef Full Text | Google Scholar

Godakumara, K., Dissanayake, K., Hasan, M. M., Kodithuwakku, S. P., and Fazeli, A. (2022). Role of extracellular vesicles in intercellular communication during reproduction. Reprod. Domest. Anim. 57, 14–21. doi:10.1111/rda.14205

PubMed Abstract | CrossRef Full Text | Google Scholar

Gong, Z., Cheng, C., Sun, C., and Cheng, X. (2025). Harnessing engineered extracellular vesicles for enhanced therapeutic efficacy: advancements in cancer immunotherapy. J. Exp. Clin. Cancer Res. 44 (1), 138. doi:10.1186/s13046-025-03403-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Greenberg, Z. F., Graim, K. S., and He, M. (2023). Towards artificial intelligence-enabled extracellular vesicle precision drug delivery. Adv. Drug Deliv. Rev. 199, 114974. doi:10.1016/j.addr.2023.114974

PubMed Abstract | CrossRef Full Text | Google Scholar

Greening, D. W., Xu, R., Ji, H., Tauro, B. J., and Simpson, R. J. (2015). A protocol for exosome isolation and characterization: evaluation of ultracentrifugation, density-gradient separation, and immunoaffinity capture methods. Methods Mol. Biol. 1295, 179–209. doi:10.1007/978-1-4939-2550-6_15

PubMed Abstract | CrossRef Full Text | Google Scholar

Gregory, C. D., and Rimmer, M. P. (2023). Extracellular vesicles arising from apoptosis: forms, functions, and applications. J. Pathol. 260 (5), 592–608. doi:10.1002/path.6138

PubMed Abstract | CrossRef Full Text | Google Scholar

Guo, W., Zhou, B., Zhao, L., Huai, Q., Tan, F., Xue, Q., et al. (2023). Plasma extracellular vesicle long RNAs predict response to neoadjuvant immunotherapy and survival in patients with non-small cell lung cancer. Pharmacol. Res. 196, 106921. doi:10.1016/j.phrs.2023.106921

PubMed Abstract | CrossRef Full Text | Google Scholar

Guo, L., Zhu, C., Cai, L., Zhang, X., Fang, Y., Chen, H., et al. (2024). Global burden of lung cancer in 2022 and projected burden in 2050. Chin. Med. J. 137 (21), 2577–2582. doi:10.1097/CM9.0000000000003268

PubMed Abstract | CrossRef Full Text | Google Scholar

Gurunathan, S., Kang, M.-H., and Kim, J.-H. (2021). A comprehensive review on factors influences biogenesis, functions, therapeutic and clinical implications of exosomes. Int. J. Nanomedicine 16, 1281–1312. doi:10.2147/IJN.S291956

PubMed Abstract | CrossRef Full Text | Google Scholar

Gurung, S., Perocheau, D., Touramanidou, L., and Baruteau, J. (2021). The exosome journey: from biogenesis to uptake and intracellular signalling. Cell Commun. Signal 19 (1), 47. doi:10.1186/s12964-021-00730-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Hallal, S., Tűzesi, T., Grau, G. E., Buckland, M. E., and Alexander, K. L. (2022). Understanding the extracellular vesicle surface for clinical molecular biology. J. Extracell. Vesicles 11 (10), e12260. doi:10.1002/jev2.12260

PubMed Abstract | CrossRef Full Text | Google Scholar

Han, T., Hao, Q., Chao, T., Sun, Q., Chen, Y., Gao, B., et al. (2024). Extracellular vesicles in cancer: golden goose or trojan horse. J. Mol. Cell Biol. 16 (5), mjae025. doi:10.1093/jmcb/mjae025

PubMed Abstract | CrossRef Full Text | Google Scholar

Hanelova, K., Raudenska, M., Kratochvilova, M., Navratil, J., Vicar, T., Bugajova, M., et al. (2023). Autophagy modulators influence the content of important signalling molecules in PS-positive extracellular vesicles. Cell Commun. Signal 21 (1), 120. doi:10.1186/s12964-023-01126-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Hánělová, K., Raudenská, M., Masařík, M., and Balvan, J. (2024). Protein cargo in extracellular vesicles as the key mediator in the progression of cancer. Cell Commun. Signal 22 (1), 25. doi:10.1186/s12964-023-01408-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Hassanin, A. A. I., and Ramos, K. S. (2024). Circulating exosomal miRNA profiles in non-small cell lung cancers. Cells 13, 1562. doi:10.3390/cells13181562

PubMed Abstract | CrossRef Full Text | Google Scholar

Hassanzadeh-Barforoushi, A., Sango, X., Johnston, E. L., Haylock, D., and Wang, Y. (2025). Microfluidic devices for manufacture of therapeutic extracellular vesicles: advances and opportunities. J. Extracell. Vesicles 14 (7), e70132. doi:10.1002/jev2.70132

PubMed Abstract | CrossRef Full Text | Google Scholar

He, X., Park, S., Chen, Y., and Lee, H. (2021). Extracellular vesicle-associated miRNAs as a biomarker for lung cancer in liquid biopsy. Front. Mol. Biosci. 8, 630718. doi:10.3389/fmolb.2021.630718

PubMed Abstract | CrossRef Full Text | Google Scholar

Heijnen, H. F., Schiel, A. E., Fijnheer, R., Geuze, H. J., and Sixma, J. J. (1999). Activated platelets release two types of membrane vesicles: microvesicles by surface shedding and exosomes derived from exocytosis of multivesicular bodies and alpha-granules. Blood 94, 3791–3799. doi:10.1182/blood.v94.11.3791.423a22_3791_3799

PubMed Abstract | CrossRef Full Text | Google Scholar

Heinemann, M. L., Ilmer, M., Silva, L. P., Hawke, D. H., Recio, A., Vorontsova, M. A., et al. (2014). Benchtop isolation and characterization of functional exosomes by sequential filtration. J. Chromatogr. A 1371, 125–135. doi:10.1016/j.chroma.2014.10.026

PubMed Abstract | CrossRef Full Text | Google Scholar

Hindson, C. M., Chevillet, J. R., Briggs, H. A., Gallichotte, E. N., Ruf, I. K., Hindson, B. J., et al. (2013). Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat. methods 10 (10), 1003–1005. doi:10.1038/nmeth.2633

PubMed Abstract | CrossRef Full Text | Google Scholar

Hinestrosa, J. P., Kurzrock, R., Lewis, J. M., Schork, N. J., Schroeder, G., Kamat, A. M., et al. (2022). Early-stage multi-cancer detection using an extracellular vesicle protein-based blood test. Commun. Med. 2, 29. doi:10.1038/s43856-022-00088-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Hoen, E. N., Buermans, H. P., Waasdorp, M., Stoorvogel, W., Wauben, M. H., and 't Hoen, P. A. C. (2012). Deep sequencing of RNA from immune cell-derived vesicles uncovers the selective incorporation of small non-coding RNA biotypes with potential regulatory functions. Nucleic acids Res. 40 (18), 9272–9285. doi:10.1093/nar/gks658

PubMed Abstract | CrossRef Full Text | Google Scholar

Hu, H.-Y., Yu, C.-H., Zhang, H.-H., Zhang, S. Z., Yu, W. Y., Yang, Y., et al. (2019). Exosomal miR-1229 derived from colorectal cancer cells promotes angiogenesis by targeting HIPK2. Int. J. Biol. Macromol. 132, 470–477. doi:10.1016/j.ijbiomac.2019.03.221

PubMed Abstract | CrossRef Full Text | Google Scholar

Huang, Y., Hertzel, A. V., Fish, S. R., Halley, C. L., Bohm, E. K., Martinez, H. M., et al. (2023). TP53/p53 facilitates stress-induced exosome and protein secretion by adipocytes. Diabetes 72 (11), 1560–1573. doi:10.2337/db22-1027

PubMed Abstract | CrossRef Full Text | Google Scholar

Huang, Z., Zhuang, Y., Li, W., Ma, M., Lei, F., Qu, Y., et al. (2024). Apoptotic vesicles are required to repair DNA damage and suppress premature cellular senescence. J. Extracell. Vesicles 13 (4), e12428. doi:10.1002/jev2.12428

PubMed Abstract | CrossRef Full Text | Google Scholar

Huang, K., Yang, C., Xu, Y., and Wang, Y. (2025). Unraveling the multifaceted roles of extracellular vesicles in bladder cancer: diagnostic insights and therapeutic opportunities. Front. Oncol. 15, 1554819. doi:10.3389/fonc.2025.1554819

PubMed Abstract | CrossRef Full Text | Google Scholar

Iranpanah, A., Kooshki, L., Moradi, S. Z., Saso, L., Fakhri, S., and Khan, H. (2023). The exosome-mediated PI3K/Akt/mTOR signaling pathway in neurological diseases. Pharmaceutics 15 (3), 1006. doi:10.3390/pharmaceutics15031006

PubMed Abstract | CrossRef Full Text | Google Scholar

Irmer, B., Chandrabalan, S., Maas, L., Bleckmann, A., and Menck, K. (2023). Extracellular vesicles in liquid biopsies as biomarkers for solid tumors. Cancers 15, 1307. doi:10.3390/cancers15041307

PubMed Abstract | CrossRef Full Text | Google Scholar

Izhar, M., and Lesniak, M. S. (2025). Role of extracellular vesicles in the pathogenesis of brain metastasis. J. Extracell. Biol. 4 (5), e70051. doi:10.1002/jex2.70051

PubMed Abstract | CrossRef Full Text | Google Scholar

Jang, J. S., Simon, V. A., Feddersen, R. M., Rakhshan, F., Schultz, D. A., Zschunke, M. A., et al. (2011). Quantitative miRNA expression analysis using Fluidigm microfluidics dynamic arrays. BMC Genomics 12, 144. doi:10.1186/1471-2164-12-144

PubMed Abstract | CrossRef Full Text | Google Scholar

Jankovičová, J., Sečová, P., Michalková, K., and Antalíková, J. (2020). Tetraspanins, more than markers of extracellular vesicles in reproduction. Int. J. Mol. Sci. 21 (20), 7568. doi:10.3390/ijms21207568

PubMed Abstract | CrossRef Full Text | Google Scholar

Jankovičová, J., Michalková, K., Sečová, P., Horovská, Ľ., and Antalíková, J. (2024). The extracellular vesicle tetraspanin CD63 journey from the testis through the epididymis to mature bull sperm. Sci. Rep. 14, 29449. doi:10.1038/s41598-024-81021-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Jeppesen, D. K., Fenix, A. M., Franklin, J. L., Higginbotham, J. N., Zhang, Q., Zimmerman, L. J., et al. (2019). Reassessment of exosome composition. Cell 177 (2), 428–445.e18. doi:10.1016/j.cell.2019.02.029

PubMed Abstract | CrossRef Full Text | Google Scholar

Jeppesen, D. K., Zhang, Q., Franklin, J. L., and Coffey, R. J. (2023). Extracellular vesicles and nanoparticles: emerging complexities. Trends Cell Biol. 33 (8), 667–681. doi:10.1016/j.tcb.2023.01.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Jia, Y., Yu, L., Ma, T., Xu, W., Qian, H., Sun, Y., et al. (2022). Small extracellular vesicles isolation and separation: current techniques, pending questions and clinical applications. Theranostics 12 (15), 6548–6575. doi:10.7150/thno.74305

PubMed Abstract | CrossRef Full Text | Google Scholar

Jiang, C., Zhang, N., Hu, X., and Wang, H. (2021a). Tumor-associated exosomes promote lung cancer metastasis through multiple mechanisms. Mol. Cancer 20 (1), 117. doi:10.1186/s12943-021-01411-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Jiang, X., Li, J., Zhang, B., Hu, J., Ma, J., Cui, L., et al. (2021b). Differential expression profile of plasma exosomal microRNAs in women with polycystic ovary syndrome. Fertil. Steril. 115 (3), 782–792. doi:10.1016/j.fertnstert.2020.08.019

PubMed Abstract | CrossRef Full Text | Google Scholar

Jin, J., and Yu, G. (2022). Hypoxic lung cancer cell-derived exosomal miR-21 mediates macrophage M2 polarization and promotes cancer cell proliferation through targeting IRF1. World J. Surg. Oncol. 20, 241. doi:10.1186/s12957-022-02706-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Jin, Y., Ma, L., Zhang, W., Yang, W., Feng, Q., and Wang, H. (2022). Extracellular signals regulate the biogenesis of extracellular vesicles. Biol. Res. 55 (1), 35. doi:10.1186/s40659-022-00405-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Jin, Y., Xu, C., Zhu, Y., and Gu, Z. (2025). Extracellular vesicle as a next-generation drug delivery platform for rheumatoid arthritis therapy. J. Control Release 381, 113610. doi:10.1016/j.jconrel.2025.113610

PubMed Abstract | CrossRef Full Text | Google Scholar

Kakarla, R., Hur, J., Kim, Y. J., and Chwae, Y. J. (2020). Apoptotic cell-derived exosomes: messages from dying cells. Exp. Mol. Med. 52, 1–6. doi:10.1038/s12276-019-0362-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Kalluri, R., and LeBleu, V. S. (2020). The biology, function, and biomedical applications of exosomes. Science 367 (6478), eaau6977. doi:10.1126/science.aau6977

PubMed Abstract | CrossRef Full Text | Google Scholar

Kalluri, R., and McAndrews, K. M. (2023). The role of extracellular vesicles in cancer. Cell 186 (8), 1610–1626. doi:10.1016/j.cell.2023.03.010

PubMed Abstract | CrossRef Full Text | Google Scholar

Kang, T., Atukorala, I., and Mathivanan, S. (2021). Biogenesis of extracellular vesicles. Subcell. Biochem. 97, 19–43. doi:10.1007/978-3-030-67171-6_2

PubMed Abstract | CrossRef Full Text | Google Scholar

Kenific, C. M., Zhang, H., and Lyden, D. (2021). An exosome pathway without an ESCRT. Cell Res. 31 (2), 105–106. doi:10.1038/s41422-020-00418-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Khanicheragh, P., Abbasi-Malati, Z., Saghebasl, S., Hassanpour, P., Milani, S. Z., Rahbarghazi, R., et al. (2024). Exosomes and breast cancer angiogenesis; highlights in intercellular communication. Cancer Cell Int. 24 (1), 402. doi:10.1186/s12935-024-03606-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Kingreen, T., Kewitz-Hempel, S., Rohde, C., Hause, G., Sunderkötter, C., and Gerloff, D. (2024). Extracellular vesicles from highly invasive melanoma subpopulations increase the invasive capacity of less invasive melanoma cells through mir-1246-mediated inhibition of CCNG2. Cell Commun. Signal 22 (1), 442. doi:10.1186/s12964-024-01820-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Kobayashi, H., Shiba, T., Yoshida, T., Bolidong, D., Kato, K., Sato, Y., et al. (2024). Precise analysis of single small extracellular vesicles using flow cytometry. Sci. Rep. 14, 7465. doi:10.1038/s41598-024-57974-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Konoshenko, M. Y., Lekchnov, E. A., Vlassov, A. V., and Laktionov, P. P. (2018). Isolation of extracellular vesicles: general methodologies and latest trends. BioMed Res. Int. 2018 (1), 8545347. doi:10.1155/2018/8545347

PubMed Abstract | CrossRef Full Text | Google Scholar

Kowal, J., Arras, G., Colombo, M., Jouve, M., Morath, J. P., Primdal-Bengtson, B., et al. (2016). Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes. Proc. Natl. Acad. Sci. U. S. A. 113 (8), E968–E977. doi:10.1073/pnas.1521230113

PubMed Abstract | CrossRef Full Text | Google Scholar

Krylova, S. V., and Feng, D. (2023). The machinery of exosomes: biogenesis, release, and uptake. Int. J. Mol. Sci. 24 (2), 1337. doi:10.3390/ijms24021337

PubMed Abstract | CrossRef Full Text | Google Scholar

Kuang, L., Wu, L., and Li, Y. (2025). Extracellular vesicles in tumor immunity: mechanisms and novel insights. Mol. Cancer 24 (1), 45. doi:10.1186/s12943-025-02233-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Kumar, M. A., Baba, S. K., Sadida, H. Q., Marzooqi, S. A., Jerobin, J., Altemani, F. H., et al. (2024). Extracellular vesicles as tools and targets in therapy for diseases. Signal Transduct. Target Ther. 9 (1), 27. doi:10.1038/s41392-024-01735-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Kwok, Z. H., Ni, K., and Jin, Y. (2021). Extracellular vesicle associated non-coding RNAs in lung infections and injury. Cells 10 (05), 965. doi:10.3390/cells10050965

PubMed Abstract | CrossRef Full Text | Google Scholar

Lee, J. H., Kim, J. A., Kwon, M. H., Kang, J. Y., and Rhee, W. J. (2015). In situ single step detection of exosome microRNA using molecular beacon. Biomaterials 54, 116–125. doi:10.1016/j.biomaterials.2015.03.014

PubMed Abstract | CrossRef Full Text | Google Scholar

Lee, J. H., Kim, J. A., Jeong, S., and Rhee, W. J. (2016). Simultaneous and multiplexed detection of exosome microRNAs using molecular beacons. Biosens. Bioelectron. 86, 202–210. doi:10.1016/j.bios.2016.06.058

PubMed Abstract | CrossRef Full Text | Google Scholar

Lee, J., Kwon, M. H., Kim, J. A., and Rhee, W. J. (2018). Detection of exosome miRNAs using molecular beacons for diagnosing prostate cancer. Artif. Cells, Nanomedicine, Biotechnol. 46 (Suppl. 3), 52–63. doi:10.1080/21691401.2018.1489263

PubMed Abstract | CrossRef Full Text | Google Scholar

Lee, C., Han, J., and Jung, Y. (2022). Pathological contribution of extracellular vesicles and their MicroRNAs to progression of chronic liver disease. Biol. (Basel) 11 (5), 637. doi:10.3390/biology11050637

PubMed Abstract | CrossRef Full Text | Google Scholar

Lei, Y., Fei, X., Ding, Y., Zhang, J., Zhang, G., Dong, L., et al. (2023). Simultaneous subset tracing and miRNA profiling of tumor-derived exosomes via dual-surface-protein orthogonal barcoding. Sci. Adv. 9 (40), eadi1556. doi:10.1126/sciadv.adi1556

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, Y., and Liu, F. (2023). The extracellular vesicles targeting tumor microenvironment: a promising therapeutic strategy for melanoma. Front. Immunol. 14, 1200249. doi:10.3389/fimmu.2023.1200249

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, P., Luo, X., Xie, Y., Li, P., Hu, F., Chu, J., et al. (2020a). GC-derived EVs enriched with microRNA-675-3p contribute to the MAPK/PD-L1-mediated tumor immune escape by targeting CXXC4. Mol. Ther. Nucleic Acids 22, 615–626. doi:10.1016/j.omtn.2020.08.020

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, Y., He, X., Li, Q., Lai, H., Zhang, H., Hu, Z., et al. (2020b). EV-origin: enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile. Comput. Struct. Biotechnol. J. 18, 2851–2859. doi:10.1016/j.csbj.2020.10.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, C., Qin, F., Wang, W., Ni, Y., Gao, M., Guo, M., et al. (2021a). hnRNPA2B1-Mediated extracellular vesicles sorting of miR-122-5p potentially promotes lung cancer progression. Int. J. Mol. Sci. 22, 12866. doi:10.3390/ijms222312866

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, X., Chen, Z., Ni, Y., Bian, C., and Huang, J. (2021b). Tumor-associated macrophages secret exosomal miR-155 and miR-196a-5p to promote metastasis of non-small-cell lung cancer. Transl. Lung Cancer Res. 10 (3), 1338–1354. doi:10.21037/tlcr-20-1255

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, Y., Sui, S., and Goel, A. (2024a). Extracellular vesicles associated microRNAs: their biology and clinical significance as biomarkers in gastrointestinal cancers. Semin. Cancer Biol. 99, 5–23. doi:10.1016/j.semcancer.2024.02.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, Y., Zheng, Y., Tan, X., Du, Y., Wei, Y., and Liu, S. (2024b). Extracellular vesicle-mediated pre-metastatic niche formation via altering host microenvironments. Front. Immunol. 15, 1367373. doi:10.3389/fimmu.2024.1367373

PubMed Abstract | CrossRef Full Text | Google Scholar

Liam, C. K., Liam, Y. S., and Wong, C. K. (2020). Extracellular vesicle-based EGFR genotyping in bronchoalveolar lavage fluid. Transl. Lung Cancer Res. 9 (2), 168–171. doi:10.21037/tlcr.2020.03.06

PubMed Abstract | CrossRef Full Text | Google Scholar

Liga, A., Vliegenthart, A. D. B., Oosthuyzen, W., Dear, J. W., and Kersaudy-Kerhoas, M. (2015). Exosome isolation: a microfluidic road-map. Lab a Chip 15 (11), 2388–2394. doi:10.1039/c5lc00240k

PubMed Abstract | CrossRef Full Text | Google Scholar

Ling, Z., and Yang, L. (2024). Diagnostic value of miR-200 family in non-small cell lung cancer: a meta-analysis. Biomarkers Med. 18 (8), 419–431. doi:10.2217/bmm-2024-0087

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, J., Yao, Y., Huang, J., Sun, H., Pu, Y., Tian, M., et al. (2022). Comprehensive analysis of lncRNA-miRNA-mRNA networks during osteogenic differentiation of bone marrow mesenchymal stem cells. BMC Genomics 23 (1), 425. doi:10.1186/s12864-022-08646-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, L., Wang, F., Nan, Y., Zou, X., Jiang, D., and Wang, Z. (2023). Diagnostic value of circulating miRNA in the benign and malignant lung nodules: a systematic review and meta-analysis. Med. Baltim. 102 (46), e35857. doi:10.1097/MD.0000000000035857

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, M., Wen, Z., Zhang, T., Zhang, L., Liu, X., and Wang, M. (2024). The role of exosomal molecular cargo in exosome biogenesis and disease diagnosis. Front. Immunol. 15, 1417758. doi:10.3389/fimmu.2024.1417758

PubMed Abstract | CrossRef Full Text | Google Scholar

Livshits, M. A., Khomyakova, E., Evtushenko, E. G., Lazarev, V. N., Kulemin, N. A., Semina, S. E., et al. (2015). Isolation of exosomes by differential centrifugation: theoretical analysis of a commonly used protocol. Sci. Rep. 5 (1), 17319. doi:10.1038/srep17319

PubMed Abstract | CrossRef Full Text | Google Scholar

Long, Y., Dan, Y., Jiang, Y., Ma, J., Zhou, T., Fang, L., et al. (2024). Colorectal cancer cell-derived extracellular vesicles promote angiogenesis through JAK/STAT3/VEGFA signaling. Biology 13, 873. doi:10.3390/biology13110873

PubMed Abstract | CrossRef Full Text | Google Scholar

Lopez, K., Lai, S. W. T., Lopez, G. E. J., Dávila, R. G., and Shuck, S. C. (2023). Extracellular vesicles: a dive into their role in the tumor microenvironment and cancer progression. Front. Cell Dev. Biol. 11, 1154576. doi:10.3389/fcell.2023.1154576

PubMed Abstract | CrossRef Full Text | Google Scholar

Lu, Y., Wang, H., Zeng, Z., Hui, J., Ji, J., Mao, H., et al. (2025). A deep learning-based integrated analytical system for tumor exosome on-chip isolation and automated image identification. Talanta Open 11, 100398. doi:10.1016/j.talo.2025.100398

CrossRef Full Text | Google Scholar

Ma, C., Ding, R., Hao, K., Du, W., Xu, L., Gao, Q., et al. (2023). Storage stability of blood samples for miRNAs in glycosylated extracellular vesicles. Molecules 29 (1), 103. doi:10.3390/molecules29010103

PubMed Abstract | CrossRef Full Text | Google Scholar

Ma, L., Liu, Y. H., Liu, C., Wang, S. Q., Ma, J., Li, X. Q., et al. (2025). lncRNA, miRNA, and mRNA of plasma and tumor-derived exosomes of cardiac myxoma-related ischaemic stroke. Sci. Data 12, 91. doi:10.1038/s41597-025-04410-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Macey, M. G., Enniks, N., and Bevan, S. (2011). Flow cytometric analysis of microparticle phenotype and their role in thrombin generation. Cytom. B Clin.Cytom. 80, 57–63. doi:10.1002/cyto.b.20551

PubMed Abstract | CrossRef Full Text | Google Scholar

Malkin, E. Z., and Bratman, S. V. (2020). Bioactive DNA from extracellular vesicles and particles. Cell Death Dis. 11 (7), 584. doi:10.1038/s41419-020-02803-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Martellucci, S., Orefice, N. S., Angelucci, A., Luce, A., Caraglia, M., and Zappavigna, S. (2020). Extracellular vesicles: new endogenous shuttles for miRNAs in cancer diagnosis and therapy? Int. J. Mol. Sci. 21 (18), 6486. doi:10.3390/ijms21186486

PubMed Abstract | CrossRef Full Text | Google Scholar

Martínez-Espinosa, I., Serrato, J. A., Cabello-Gutiérrez, C., Carlos-Reyes, C., and Ortiz-Quintero, B. (2024). Exosome-derived miRNAs in liquid biopsy for lung cancer. Life Basel Switz. 14, 1608. doi:10.3390/life14121608

PubMed Abstract | CrossRef Full Text | Google Scholar

Melo, S. A., Luecke, L. B., Kahlert, C., Fernandez, A. F., Gammon, S. T., Kaye, J., et al. (2015). Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature 523, 177–182. doi:10.1038/nature14581

PubMed Abstract | CrossRef Full Text | Google Scholar

Miceli, R. T., Chen, T. Y., Nose, Y., Tichkule, S., Brown, B., Fullard, J. F., et al. (2024). Extracellular vesicles, RNA sequencing, and bioinformatic analyses: challenges, solutions, and recommendations. J. Extracell. Vesicles 13 (12), e70005. doi:10.1002/jev2.70005

PubMed Abstract | CrossRef Full Text | Google Scholar

Miller, A. M., Szalontay, L., Bouvier, N., Hill, K., Ahmad, H., Rafailov, J., et al. (2022). Next-generation sequencing of cerebrospinal fluid for clinical molecular diagnostics in pediatric, adolescent and young adult brain tumor patients. Neuro-oncology 24 (10), 1763–1772. doi:10.1093/neuonc/noac035

PubMed Abstract | CrossRef Full Text | Google Scholar

Mittelbrunn, M., Gutiérrez-Vázquez, C., Villarroya-Beltri, C., González, S., Sánchez-Cabo, F., González, M. Á., et al. (2011). Unidirectional transfer of microRNA-loaded exosomes from T cells to antigen-presenting cells. Nat. Commun. 2, 282. doi:10.1038/ncomms1285

PubMed Abstract | CrossRef Full Text | Google Scholar

Mok, E. T. Y., Chitty, J. L., and Cox, T. R. (2024). miRNAs in pancreatic cancer progression and metastasis. Clin. Exp. Metastasis 41 (3), 163–186. doi:10.1007/s10585-023-10256-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Monguió-Tortajada, M., Gálvez-Montón, C., Bayes-Genis, A., Roura, S., and Borràs, F. E. (2019). Extracellular vesicle isolation methods: rising impact of size-exclusion chromatography. Cell. Mol. Life Sci. 76 (12), 2369–2382. doi:10.1007/s00018-019-03071-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Morse, M. A., Garst, J., Osada, T., Khan, S., Hobeika, A., Clay, T. M., et al. (2005). A phase I study of dexosome immunotherapy in patients with advanced non-small cell lung cancer. J. Transl. Med. 3, 9. doi:10.1186/1479-5876-3-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Munir, J., Yoon, J. K., and Ryu, S. (2020). Therapeutic miRNA-enriched extracellular vesicles: current approaches and future prospects. Cells 9 (10), 2271. doi:10.3390/cells9102271

PubMed Abstract | CrossRef Full Text | Google Scholar

Murillo, O. D., Thistlethwaite, W., Rozowsky, J., Subramanian, S. L., Lucero, R., Shah, N., et al. (2019). exRNA atlas analysis reveals distinct extracellular RNA cargo types and their carriers present across human biofluids. Cell 177 (2), 463–477.e15. doi:10.1016/j.cell.2019.02.018

PubMed Abstract | CrossRef Full Text | Google Scholar

Najaflou, M., Shahgolzari, M., Khosroushahi, A. Y., and Fiering, S. (2022). Tumor-derived extracellular vesicles in cancer immunoediting and their potential as oncoimmunotherapeutics. Cancers (Basel) 15 (1), 82. doi:10.3390/cancers15010082

PubMed Abstract | CrossRef Full Text | Google Scholar

Nakamaru, K., Tomiyama, T., Kobayashi, S., Ikemune, M., Tsukuda, S., Ito, T., et al. (2020). Extracellular vesicles microRNA analysis in type 1 autoimmune pancreatitis: increased expression of microRNA-21. Pancreatology 20 (3), 318–324. doi:10.1016/j.pan.2020.02.012

PubMed Abstract | CrossRef Full Text | Google Scholar

National Cancer Institute (2025). Validation of multiparametric models and circulating and imaging biomarkers to improve lung cancer EARLY detection (CLEARLY). Available online at: https://www.clinicaltrials.gov/study/NCT04323579 (Accessed July 20, 2025).

Google Scholar

Neettiyath, A., Chung, K., Liu, W., and Lee, L. P. (2024). Nanoplasmonic sensors for extracellular vesicles and bacterial membrane vesicles. Nano Converg. 11 (1), 23. doi:10.1186/s40580-024-00431-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Ng, C. Y., Kee, L. T., Al-Masawa, M. E., Lee, Q. H., Subramaniam, T., Kok, D., et al. (2022). Scalable production of extracellular vesicles and its therapeutic values: a review. Int. J. Mol. Sci. 23 (14), 7986. doi:10.3390/ijms23147986

PubMed Abstract | CrossRef Full Text | Google Scholar

Niu, Y., Fu, G., Xia, S., Li, M., Qiu, L., Wang, J., et al. (2025). Three circulating miRNAs related to non-small-cell lung cancer progression: an integrative analysis of their biological roles. Biology 14 (4), 399. doi:10.3390/biology14040399

PubMed Abstract | CrossRef Full Text | Google Scholar

Ogawa, R., Tanaka, C., Sato, M., Nagasaki, H., Sugimura, K., Okumura, K., et al. (2010). Adipocyte-derived microvesicles contain RNA that is transported into macrophages and might be secreted into blood circulation. Biochem. Biophys. Res. Commun. 398, 723–729. doi:10.1016/j.bbrc.2010.07.008

PubMed Abstract | CrossRef Full Text | Google Scholar

Oliveira, G. P., Zigon, E., Rogers, G., Davodian, D., Lu, S., Jovanovic-Talisman, T., et al. (2020). Detection of extracellular vesicle RNA using molecular beacons. iScience 23 (1), 100782. doi:10.1016/j.isci.2019.100782

PubMed Abstract | CrossRef Full Text | Google Scholar

Ovčar, A., and Kovačič, B. (2025). Biogenesis of extracellular vesicles (EVs) and the potential use of embryo-derived EVs in medically assisted reproduction. Int. J. Mol. Sci. 26, 42. doi:10.3390/ijms26010042

PubMed Abstract | CrossRef Full Text | Google Scholar

Padilla, J. C. A., Barutcu, S., Malet, L., Deschamps-Francoeur, G., Calderon, V., Kwon, E., et al. (2023). Profiling the polyadenylated transcriptome of extracellular vesicles with long-read nanopore sequencing. BMC genomics 24 (1), 564. doi:10.1186/s12864-023-09552-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Padinharayil, H., Varghese, J., Varghese, P. R., Wilson, C. M., and George, A. (2025). Small extracellular vesicle (sEV) uptake from lung adenocarcinoma and squamous cell carcinoma alters T-Cell cytokine expression and modulates protein profiles in sEV biogenesis. Proteomes 13, 15. doi:10.3390/proteomes13020015

PubMed Abstract | CrossRef Full Text | Google Scholar

Palazzo, C., D'Alessio, A., and Tamagnone, L. (2022). Message in a bottle: endothelial cell regulation by extracellular vesicles. Cancers (Basel) 14 (8), 1969. doi:10.3390/cancers14081969

PubMed Abstract | CrossRef Full Text | Google Scholar

Palomar-Alonso, N., Lee, M., and Kim, M. (2023). Exosomes: membrane-associated proteins, challenges and perspectives. Biochem. Biophys. Rep. 37, 101599. doi:10.1016/j.bbrep.2023.101599

PubMed Abstract | CrossRef Full Text | Google Scholar

Pang, Y., Wang, C., Lu, L., Wang, C., Sun, Z., and Xiao, R. (2019). Dual-SERS biosensor for one-step detection of microRNAs in exosome and residual plasma of blood samples for diagnosing pancreatic cancer. Biosens. Bioelectron. 130, 204–213. doi:10.1016/j.bios.2019.01.039

PubMed Abstract | CrossRef Full Text | Google Scholar

Papadaki, C., Mortoglou, M., Boukouris, A. E., Gourlia, K., Markaki, M., Lagoudaki, E., et al. (2025). MicroRNA expression analysis and biological pathways in chemoresistant non-small cell lung cancer. Cancers 17 (15), 2504. doi:10.3390/cancers17152504

PubMed Abstract | CrossRef Full Text | Google Scholar

Patel, B., Gaikwad, S., and Prasad, S. (2024). Exploring the significance of extracellular vesicles: key players in advancing cancer and possible theranostic tools. Cancer Pathog. Ther. 3 (2), 109–119. doi:10.1016/j.cpt.2024.04.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Paterson, E., Blenkiron, C., Danielson, K., and Henry, C. (2022). Recommendations for extracellular vesicle miRNA biomarker research in the endometrial cancer context. Transl. Oncol. 23, 101478. doi:10.1016/j.tranon.2022.101478

PubMed Abstract | CrossRef Full Text | Google Scholar

Pathania, A. S., Prathipati, P., and Challagundla, K. B. (2021). New insights into exosome mediated tumor-immune escape: clinical perspectives and therapeutic strategies. Biochim. Biophys. Acta Rev. Cancer 1876 (2), 188624. doi:10.1016/j.bbcan.2021.188624

PubMed Abstract | CrossRef Full Text | Google Scholar

Patras, L., Paul, D., and Matei, I. R. (2023). Weaving the nest: extracellular matrix roles in pre-metastatic niche formation. Front. Oncol. 13, 1163786. doi:10.3389/fonc.2023.1163786

PubMed Abstract | CrossRef Full Text | Google Scholar

Petroni, D., Fabbri, C., Babboni, S., Menichetti, L., Basta, G., and Del, T. S. (2023). Extracellular vesicles and intercellular communication: challenges for in vivo molecular imaging and tracking. Pharmaceutics 15 (6), 1639. doi:10.3390/pharmaceutics15061639

PubMed Abstract | CrossRef Full Text | Google Scholar

Phan, H. D., Squires, W. R. B., Mayne, K. E., Kelly, G. R., Jafardoust, R., and Christian, S. L. (2024). CD24 regulates extracellular vesicle release via an aSMase/PI3K/mTORC2/ROCK/actin pathway in B lymphocytes. bioRxiv.

Google Scholar

Phillips, W., Willms, E., and Hill, A. F. (2021). Understanding extracellular vesicle and nanoparticle heterogeneity: novel methods and considerations. Proteomics 21, e2000118. doi:10.1002/pmic.202000118

PubMed Abstract | CrossRef Full Text | Google Scholar

Polanco, D., Pinilla, L., Gracia-Lavedan, E., Mas, A., Bertran, S., Fierro, G., et al. (2021). Prognostic value of symptoms at lung cancer diagnosis: a three-year observational study. J. Thorac. Dis. 13 (3), 1485–1494. doi:10.21037/jtd-20-3075

PubMed Abstract | CrossRef Full Text | Google Scholar

Poongodi, R., Hsu, Y. W., Yang, T. H., Huang, Y. H., Yang, K. D., Lin, H. C., et al. (2025). Stem cell-derived extracellular vesicle-mediated therapeutic signaling in spinal cord injury. Int. J. Mol. Sci. 26 (2), 723. doi:10.3390/ijms26020723

PubMed Abstract | CrossRef Full Text | Google Scholar

Prieto-Vila, M., Yoshioka, Y., and Ochiya, T. (2021). Biological functions driven by mRNAs carried by extracellular vesicles in cancer. Front. Cell Dev. Biol. 9, 620498. doi:10.3389/fcell.2021.620498

PubMed Abstract | CrossRef Full Text | Google Scholar

Qian, H., Maghsoudloo, M., Kaboli, P. J., Babaeizad, A., Cui, Y., Fu, J., et al. (2024a). Decoding the promise and challenges of miRNA-Based cancer therapies: an essential update on miR-21, miR-34, and miR-155. Int. J. Med. Sci. 21, 2781–2798. doi:10.7150/ijms.102123

PubMed Abstract | CrossRef Full Text | Google Scholar

Qian, Y., Hong, X., Yu, Y., Du, C., Li, J., Yu, J., et al. (2024b). Characterization and functional analysis of extrachromosomal circular DNA discovered from circulating extracellular vesicles in liver failure. Clin. Transl. Med. 14 (10), e70059. doi:10.1002/ctm2.70059

PubMed Abstract | CrossRef Full Text | Google Scholar

Rabinowits, G., Gerçel-Taylor, C., Day, J. M., Taylor, D. D., and Kloecker, G. H. (2009). Exosomal microRNA: a diagnostic marker for lung cancer. Clin. Lung Cancer 10, 42–46. doi:10.3816/CLC.2009.n.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Rahmati, S., Moeinafshar, A., and Rezaei, N. (2024). The multifaceted role of extracellular vesicles (EVs) in colorectal cancer: metastasis, immune suppression, therapy resistance, and autophagy crosstalk. J. Transl. Med. 22, 452. doi:10.1186/s12967-024-05267-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Raposo, G., Nijman, H. W., Stoorvogel, W., Liejendekker, R., Harding, C. V., Melief, C. J., et al. (1996). B lymphocytes secrete antigen-presenting vesicles. J. Exp.Med. 183, 1161–1172. doi:10.1084/jem.183.3.1161

PubMed Abstract | CrossRef Full Text | Google Scholar

Rayamajhi, S., Sipes, J., Tetlow, A. L., Saha, S., Bansal, A., and Godwin, A. K. (2024). Extracellular vesicles as liquid biopsy biomarkers across the cancer journey: from early detection to recurrence. Clin. Chem. 70 (1), 206–219. doi:10.1093/clinchem/hvad176

PubMed Abstract | CrossRef Full Text | Google Scholar

Reale, A., Khong, T., and Spencer, A. (2022). Extracellular vesicles and their roles in the tumor immune microenvironment. J. Clin. Med. 11 (23), 6892. doi:10.3390/jcm11236892

PubMed Abstract | CrossRef Full Text | Google Scholar

Ren, Y., Yang, J., Xie, R., Gao, L., Yang, Y., Fan, H., et al. (2011). Exosomal-like vesicles with immune-modulatory features are present in human plasma and can induce CD4+ T-cell apoptosis in vitro. Transfus. (Paris) 51, 1002–1011. doi:10.1111/j.1537-2995.2010.02909.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Rider, M. A., Hurwitz, S. N., and Meckes, D. G. (2016). ExtraPEG: a polyethylene glycol-based method for enrichment of extracellular vesicles. Sci. Rep. 6 (1), 23978. doi:10.1038/srep23978

PubMed Abstract | CrossRef Full Text | Google Scholar

Rolfo, C., Laes, J. F., Reclusa, P., Valentino, A., Lienard, M., Gil-Bazo, I., et al. (2017). P2.01-093 Exo-ALK proof of concept: exosomal analysis of ALK alterations in advanced NSCLC patients. J. Thorac. Oncol. 12, S844–S845. doi:10.1016/j.jtho.2016.11.1145

CrossRef Full Text | Google Scholar

Romanò, S., Nele, V., Campani, V., De Rosa, G., and Cinti, S. (2024). A comprehensive guide to extract information from extracellular vesicles: a tutorial review towards novel analytical developments. Anal. Chim. Acta 1302, 342473. doi:10.1016/j.aca.2024.342473

PubMed Abstract | CrossRef Full Text | Google Scholar

Rufo, J., Zhang, P., Wang, Z., Gu, Y., Yang, K., Rich, J., et al. (2024). High-yield and rapid isolation of extracellular vesicles by flocculation via orbital acoustic trapping: FLOAT. Microsystems Nanoeng. 10 (1), 23. doi:10.1038/s41378-023-00648-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Russell, A. E., Sneider, A., Witwer, K. W., Bergese, P., Bhattacharyya, S. N., Cocks, A., et al. (2019). Biological membranes in EV biogenesis, stability, uptake, and cargo transfer: an ISEV position paper arising from the ISEV membranes and EVs workshop. J. Extracell. Vesicles 8 (1), 1684862. doi:10.1080/20013078.2019.1684862

PubMed Abstract | CrossRef Full Text | Google Scholar

Russo, M. N., Whaley, L. A., Norton, E. S., Zarco, N., and Guerrero-Cázares, H. (2023). Extracellular vesicles in the glioblastoma microenvironment: a diagnostic and therapeutic perspective. Mol. Asp. Med. 91, 101167. doi:10.1016/j.mam.2022.101167

PubMed Abstract | CrossRef Full Text | Google Scholar

Saber, S. H., Ali, H. E. A., Gaballa, R., Gaballah, M., Ali, H. I., Zerfaoui, M., et al. (2020). Exosomes are the driving force in preparing the soil for the metastatic seeds: lessons from the prostate cancer. Cells 9, 564. doi:10.3390/cells9030564

PubMed Abstract | CrossRef Full Text | Google Scholar

Salomon, C., Das, S., Erdbrügger, U., Kalluri, R., Lim, S. K., Olefsky, J. M., et al. (2022). Extracellular vesicles and their emerging roles as cellular messengers in endocrinology: an endocrine society scientific statement. Endocr. Rev. 43 (03), 441–468. doi:10.1210/endrev/bnac009

PubMed Abstract | CrossRef Full Text | Google Scholar

Samidurai, A., Olex, A. L., Ockaili, R., Kraskauskas, D., Roh, S. K., Kukreja, R. C., et al. (2023). Integrated analysis of lncRNA-miRNA-mRNA regulatory network in rapamycin-induced cardioprotection against ischemia/reperfusion injury in diabetic rabbits. Cells 12 (24), 2820. doi:10.3390/cells12242820

PubMed Abstract | CrossRef Full Text | Google Scholar

Sato, S., and Weaver, A. M. (2018). Extracellular vesicles: important collaborators in cancer progression. Essays Biochem. 62 (2), 149–163. doi:10.1042/EBC20170080

PubMed Abstract | CrossRef Full Text | Google Scholar

Saviana, M., Romano, G., Le, P., Acunzo, M., and Nana-Sinkam, P. (2021). Extracellular vesicles in lung cancer metastasis and their clinical applications. Cancers (Basel) 13 (22), 5633. doi:10.3390/cancers13225633

PubMed Abstract | CrossRef Full Text | Google Scholar

Selmaj, I., Cichalewska, M., Namiecinska, M., Galazka, G., Horzelski, W., Selmaj, K. W., et al. (2017). Global exosome transcriptome profiling reveals biomarkers for multiple sclerosis. Ann. Neurology 81 (5), 703–717. doi:10.1002/ana.24931

PubMed Abstract | CrossRef Full Text | Google Scholar

Sevenler, D., Daaboul, G. G., Ekiz Kanik, F., Unlu, N. L., and Unlu, M. S. (2018). Digital microarrays: single-molecule readout with interferometric detection of plasmonic nanorod labels. ACS Nano 12 (6), 5880–5887. doi:10.1021/acsnano.8b02036

PubMed Abstract | CrossRef Full Text | Google Scholar

Seyhan, A. A. (2023). Circulating microRNAs as potential biomarkers in pancreatic cancer—advances and challenges. Int. J. Mol. Sci. 24, 13340. doi:10.3390/ijms241713340

PubMed Abstract | CrossRef Full Text | Google Scholar

Shaba, E., Vantaggiato, L., Governini, L., Haxhiu, A., Sebastiani, G., Fignani, D., et al. (2022). Multi-omics integrative approach of extracellular vesicles: a future challenging milestone. Proteomes 10 (2), 12. doi:10.3390/proteomes10020012

PubMed Abstract | CrossRef Full Text | Google Scholar

Shimada, Y., Yoshioka, Y., Kudo, Y., Mimae, T., Miyata, Y., Adachi, H., et al. (2023). Extracellular vesicle-associated microRNA signatures related to lymphovascular invasion in early-stage lung adenocarcinoma. Sci. Rep. 13, 4823. doi:10.1038/s41598-023-32041-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Singh, B., Fredriksson, S. M., Muthukrishnan, U., Natarajan, B., Stransky, S., Görgens, A., et al. (2025a). Extracellular histones as exosome membrane proteins regulated by cell stress. J. Extracell. Vesicles 14 (2), e70042. doi:10.1002/jev2.70042

PubMed Abstract | CrossRef Full Text | Google Scholar

Singh, M., Tiwari, P. K., Kashyap, V., and Kumar, S. (2025b). Proteomics of extracellular vesicles: recent updates, challenges and limitations. Proteomes 13 (1), 12. doi:10.3390/proteomes13010012

PubMed Abstract | CrossRef Full Text | Google Scholar

Sohal, I. S., and Kasinski, A. L. (2023). Emerging diversity in extracellular vesicles and their roles in cancer. Front. Oncol. 13, 1167717. doi:10.3389/fonc.2023.1167717

PubMed Abstract | CrossRef Full Text | Google Scholar

Stajano, D., Lombino, F. L., Schweizer, M., Glatzel, M., Saftig, P., Gromova, K. V., et al. (2023). Tetraspanin 15 depletion impairs extracellular vesicle docking at target neurons. J. Extracell. Biol. 2 (9), e113. doi:10.1002/jex2.113

PubMed Abstract | CrossRef Full Text | Google Scholar

Stam, J., Bartel, S., Bischoff, R., and Wolters, J. C. (2021). Isolation of extracellular vesicles with combined enrichment methods. J. Chromatogr. B 1169, 122604. doi:10.1016/j.jchromb.2021.122604

PubMed Abstract | CrossRef Full Text | Google Scholar

Stefańska, K., Józkowiak, M., Angelova, V. A., Shibli, J. A., Golkar-Narenji, A., Antosik, P., et al. (2023). The role of exosomes in human carcinogenesis and cancer therapy-recent findings from molecular and clinical research. Cells 12 (3), 356. doi:10.3390/cells12030356

PubMed Abstract | CrossRef Full Text | Google Scholar

Sun, D. S., and Chang, H. H. (2024). Extracellular vesicles: function, resilience, biomarker, bioengineering, and clinical implications. Tzu Chi Med. J. 36 (3), 251–259. doi:10.4103/tcmj.tcmj_28_24

PubMed Abstract | CrossRef Full Text | Google Scholar

Takousis, P. (2018). Analysis of micro-RNA expression by qPCR on a microfluidics platform for Alzheimer's disease biomarker discovery. Methods Mol. Biol. 1750, 283–292. doi:10.1007/978-1-4939-7704-8_19

PubMed Abstract | CrossRef Full Text | Google Scholar

Tan, L., Zhao, M., Wu, H., Zhang, Y., Tong, X., Gao, L., et al. (2021). Downregulated serum exosomal miR-451a expression correlates with renal damage and its intercellular communication role in systemic lupus erythematosus. Front. Immunol. 12, 630112. doi:10.3389/fimmu.2021.630112

PubMed Abstract | CrossRef Full Text | Google Scholar

Tang, H., Zhou, X., Zhao, X., Luo, X., Luo, T., Chen, Y., et al. (2022). HSP90/IKK-rich small extracellular vesicles activate pro-angiogenic melanoma-associated fibroblasts via the NF-κB/CXCL1 axis. Cancer Sci. 113 (4), 1168–1181. doi:10.1111/cas.15271

PubMed Abstract | CrossRef Full Text | Google Scholar

Tang, Y., Liu, X., Sun, M., Xiong, S., Xiao, N., Li, J., et al. (2023). Recent progress in extracellular vesicle-based carriers for targeted drug delivery in cancer therapy. Pharmaceutics 15 (7), 1902. doi:10.3390/pharmaceutics15071902

PubMed Abstract | CrossRef Full Text | Google Scholar

Tang, F. H., Wong, H. Y. T., Tsang, P. S. W., Yau, M., Tam, S. Y., Law, L., et al. (2025). Recent advancements in lung cancer research: a narrative review. Transl. Lung Cancer Res. 14 (3), 975–990. doi:10.21037/tlcr-24-979

PubMed Abstract | CrossRef Full Text | Google Scholar

Tauro, B. J., Greening, D. W., Mathias, R. A., Ji, H., Mathivanan, S., Scott, A. M., et al. (2012). Comparison of ultracentrifugation, density gradient separation, and immunoaffinity capture methods for isolating human colon cancer cell line LIM1863-derived exosomes. Methods 56 (2), 293–304. doi:10.1016/j.ymeth.2012.01.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Teng, F., and Fussenegger, M. (2020). Shedding light on extracellular vesicle biogenesis and bioengineering. Adv. Sci. (Weinh) 8 (1), 2003505. doi:10.1002/advs.202003505

PubMed Abstract | CrossRef Full Text | Google Scholar

Tesovnik, T., Jenko Bizjan, B., Šket, R., Debeljak, M., Battelino, T., and Kovač, J. (2021). Technological approaches in the analysis of extracellular vesicle nucleotide sequences. Front. Bioeng. Biotechnol. 9, 787551. doi:10.3389/fbioe.2021.787551

PubMed Abstract | CrossRef Full Text | Google Scholar

Théry, C., Amigorena, S., Raposo, G., and Clayton, A. (2006). Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Curr. Protoc. Cell Biol. 30 (1), Unit 3.22–22. doi:10.1002/0471143030.cb0322s30

PubMed Abstract | CrossRef Full Text | Google Scholar

Tulinsky, L., Dzian, A., Matakova, T., and Ihnat, P. (2022). Overexpression of the miR-143/145 and reduced expression of the let-7 and miR-126 for early lung cancer diagnosis. J. Appl. Biomed. 20, 1–6. doi:10.32725/jab.2022.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Vader, P., Breakefield, X. O., and Wood, M. J. (2014). Extracellular vesicles: emerging targets for cancer therapy. Trends Mol. Med. 20 (7), 385–393. doi:10.1016/j.molmed.2014.03.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Valadi, H., Ekström, K., Bossios, A., Sjöstrand, M., Lee, J. J., and Lötvall, J. O. (2007). Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol. 9 (6), 654–659. doi:10.1038/ncb1596

PubMed Abstract | CrossRef Full Text | Google Scholar

Vasu, S., Johnson, V., M, A., Reddy, K. A., and Sukumar, U. K. (2025). Circulating extracellular vesicles as promising biomarkers for precession diagnostics: a perspective on lung cancer. ACS Biomater. Sci. Eng. 11 (1), 95–134. doi:10.1021/acsbiomaterials.4c01323

PubMed Abstract | CrossRef Full Text | Google Scholar

Velpula, T., and Buddolla, V. (2025). Enhancing detection and monitoring of circulating tumor cells: integrative approaches in liquid biopsy advances. J. Liq. Biopsy. 8, 100297. doi:10.1016/j.jlb.2025.100297

PubMed Abstract | CrossRef Full Text | Google Scholar

Verweij, F. J., Balaj, L., Boulanger, C. M., Carter, D. R. F., Compeer, E. B., D’Angelo, G., et al. (2021). The power of imaging to understand extracellular vesicle biology in vivo. Nat. Methods 18 (9), 1013–1026. doi:10.1038/s41592-021-01206-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Vicidomini, G. (2023). Current challenges and future advances in lung cancer: Genetics, instrumental diagnosis and treatment. Cancers (Basel) 15 (14), 3710. doi:10.3390/cancers15143710

PubMed Abstract | CrossRef Full Text | Google Scholar

Visnovitz, T., Lenzinger, D., Koncz, A., Vizi, P. M., Bárkai, T., Vukman, K. V., et al. (2025). A 'torn bag mechanism' of small extracellular vesicle release via limiting membrane rupture of en bloc released amphisomes (amphiectosomes). Elife 13, RP95828. doi:10.7554/eLife.95828

PubMed Abstract | CrossRef Full Text | Google Scholar

von Lersner, A. K., Fernandes, F., Ozawa, P. M. M., Jackson, M., Masureel, M., Ho, H., et al. (2024). Multiparametric single-vesicle flow cytometry resolves extracellular vesicle heterogeneity and reveals selective regulation of biogenesis and cargo distribution. ACS Nano 18 (15), 10464–10484. doi:10.1021/acsnano.3c11561

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, N., Guo, W., Song, X., Liu, L., and Niu, L. (2020). Tumor-associated exosomal miRNA biomarkers to differentiate metastatic vs. nonmetastatic non-small cell lung cancer. Clin. Chem. Lab. Med. 58, 1535–1545. doi:10.1515/cclm-2019-1329

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, P., Arntz, O. J., Husch, J. F. A., Kraan, P. M. V., Beucken, J. J., and van de Loo, F. A. J. (2023a). Molecular and clinical characterization of ICOS expression in breast cancer through large-scale transcriptome data. PLoS One 18, e0293469. doi:10.1371/journal.pone.0293469

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, Y., Xiao, T., Zhao, C., and Li, G. (2023b). The regulation of exosome generation and function in physiological and pathological processes. Int. J. Mol. Sci. 25 (1), 255. doi:10.3390/ijms25010255

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, L., Wang, W., Hu, D., Liang, Y., Liu, Z., Zhong, T., et al. (2024). Tumor-derived extracellular vesicles regulate macrophage polarization: role and therapeutic perspectives. Front. Immunol. 15, 1346587. doi:10.3389/fimmu.2024.1346587

PubMed Abstract | CrossRef Full Text | Google Scholar

Wen, X., Hao, Z., Yin, H., Min, J., Wang, X., Sun, S., et al. (2024). Engineered extracellular vesicles as a new class of nanomedicine. Chem. Bio. Eng. 2 (1), 3–22. doi:10.1021/cbe.4c00122

PubMed Abstract | CrossRef Full Text | Google Scholar

Wessler, S., and Meisner-Kober, N. (2025). On the road: extracellular vesicles in intercellular communication. Cell Commun. Signal 23 (1), 95. doi:10.1186/s12964-024-01999-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Wiklander, O. P. B., Brennan, M., Lötvall, J., Breakefield, X. O., and El, A. S. (2019). Advances in therapeutic applications of extracellular vesicles. Sci. Transl. Med. 11 (492), eaav8521. doi:10.1126/scitranslmed.aav8521

PubMed Abstract | CrossRef Full Text | Google Scholar

Wu, Q., Qi, B., Duan, X., Ming, X., Yan, F., He, Y., et al. (2021). MicroRNA-126 enhances the biological function of endothelial progenitor cells under oxidative stress via PI3K/Akt/GSK3β and ERK1/2 signaling pathways. Bosnian J. Basic Med. Sci. 21 (1), 71–80. doi:10.17305/bjbms.2019.4493

PubMed Abstract | CrossRef Full Text | Google Scholar

Wu, Y., Zhang, J., Li, G., Wang, L., Zhao, Y., Zheng, B., et al. (2024). Exosomal miR-320d promotes angiogenesis and colorectal cancer metastasis via targeting GNAI1 to affect the JAK2/STAT3 signaling pathway. Cell Death Dis. 15 (12), 913. doi:10.1038/s41419-024-07297-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Xu, S., Zheng, L., Kang, L., Xu, H., and Gao, L. (2021). microRNA-let-7e in serum-derived exosomes inhibits the metastasis of non-small-cell lung cancer in a SUV39H2/LSD1/CDH1-dependent manner. Cancer Gene Ther. 28 (3–4), 250–264. doi:10.1038/s41417-020-00216-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Xu, D., Di, K., Fan, B., Wu, J., Gu, X., Sun, Y., et al. (2022a). MicroRNAs in extracellular vesicles: sorting mechanisms, diagnostic value, isolation, and detection technology. Front. Bioeng. Biotechnol. 10, 948959. doi:10.3389/fbioe.2022.948959

PubMed Abstract | CrossRef Full Text | Google Scholar

Xu, M., Ji, J., Jin, D., Wu, Y., Wu, T., Lin, R., et al. (2022b). The biogenesis and secretion of exosomes and multivesicular bodies (MVBs): intercellular shuttles and implications in human diseases. Genes Dis. 10 (5), 1894–1907. doi:10.1016/j.gendis.2022.03.021

PubMed Abstract | CrossRef Full Text | Google Scholar

Xu, Y., Feng, K., Zhao, H., Di, L., Wang, L., and Wang, R. (2022c). Tumor-derived extracellular vesicles as messengers of natural products in cancer treatment. Theranostics 12 (4), 1683–1714. doi:10.7150/thno.67775

PubMed Abstract | CrossRef Full Text | Google Scholar

Xu, G., Jin, J., Fu, Z., Wang, G., Lei, X., Xu, J., et al. (2025). Extracellular vesicle-based drug overview: research landscape, quality control and nonclinical evaluation strategies. Signal Transduct. Target. Ther. 10, 255. doi:10.1038/s41392-025-02312-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., et al. (2006). Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9, 189–198. doi:10.1016/j.ccr.2006.01.025

PubMed Abstract | CrossRef Full Text | Google Scholar

Yáñez-Mó, M., Siljander, P.R.-M., Andreu, Z., Zavec, A. B., Borràs, F. E., Buzas, E. I., et al. (2015). Biological properties of extracellular vesicles and their physiological functions. J. Extracell. Vesicles 4, 27066. doi:10.3402/jev.v4.27066

PubMed Abstract | CrossRef Full Text | Google Scholar

Yang, F., Yan, Y., Yang, Y., Hong, X., Wang, M., Yang, Z., et al. (2020). MiR-210 in exosomes derived from CAFs promotes non-small cell lung cancer migration and invasion through PTEN/PI3K/AKT pathway. Cell Signal. 73, 109675. doi:10.1016/j.cellsig.2020.109675

PubMed Abstract | CrossRef Full Text | Google Scholar

Yang, G., Wang, Y. D., Mo, F., Xu, Z., Lu, B., Fan, P., et al. (2024). PEDOT-Citrate/SIKVAV modified bioaffinity microelectrode arrays for detecting theta rhythm cells in the retrosplenial cortex of rats under sensory conflict. Sens. Actuat. B-Chem. 399, 134802. doi:10.1016/j.snb.2023.134802

CrossRef Full Text | Google Scholar

Yang, S., Fang, Y., Ma, Y., Wang, F., Wang, Y., Jia, J., et al. (2025). Angiogenesis and targeted therapy in the tumour microenvironment: from basic to clinical practice. Clin. Transl. Med. 15 (4), e70313. doi:10.1002/ctm2.70313

PubMed Abstract | CrossRef Full Text | Google Scholar

Ye, Q., Raese, R., Luo, D., Cao, S., Wan, Y.-W., Qian, Y., et al. (2023). MicroRNA, mRNA, and proteomics biomarkers and therapeutic targets for improving lung cancer treatment outcomes. Cancers 15, 2294. doi:10.3390/cancers15082294

PubMed Abstract | CrossRef Full Text | Google Scholar

Ye, Z., Li, G., and Lei, J. (2024). Influencing immunity: role of extracellular vesicles in tumor immune checkpoint dynamics. Exp. Mol. Med. 56 (11), 2365–2381. doi:10.1038/s12276-024-01340-w

PubMed Abstract | CrossRef Full Text | Google Scholar

Yeat, N. Y., and Chen, R. H. (2025). Extracellular vesicles: biogenesis mechanism and impacts on tumor immune microenvironment. J. Biomed. Sci. 32 (1), 85. doi:10.1186/s12929-025-01182-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Yekula, A., Yekula, A., Muralidharan, K., Kang, K., Carter, B. S., and Balaj, L. (2020). Extracellular vesicles in glioblastoma tumor microenvironment. Front. Immunol. 10, 3137. doi:10.3389/fimmu.2019.03137

PubMed Abstract | CrossRef Full Text | Google Scholar

Yin, L., Liu, X., Shao, X., Feng, T., Xu, J., Wang, Q., et al. (2021). The role of exosomes in lung cancer metastasis and clinical applications: an updated review. J. Transl. Med. 19 (1), 312. doi:10.1186/s12967-021-02985-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Yoo, K. W., Li, N., Makani, V., Singh, R. N., Atala, A., and Lu, B. (2018). Large-scale preparation of extracellular vesicles enriched with specific microRNA. Tissue Eng. Part C Methods 24 (11), 637–644. doi:10.1089/ten.TEC.2018.0249

PubMed Abstract | CrossRef Full Text | Google Scholar

Yue, M., Hu, S., Sun, H., Tuo, B., Jia, B., Chen, C., et al. (2023). Extracellular vesicles remodel tumor environment for cancer immunotherapy. Mol. Cancer 22 (1), 203. doi:10.1186/s12943-023-01898-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Zarovni, N., Mladenović, D., Brambilla, D., Panico, F., and Chiari, M. (2025). Stoichiometric constraints for detection of EV-borne biomarkers in blood. J. Extracell. Vesicles 14 (2), e70034. doi:10.1002/jev2.70034

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, X., Li, Y., Shen, S., Lee, S., and Dou, H. (2018). Field-flow fractionation: a gentle separation and characterization technique in biomedicine. TrAC Trends Anal. Chem. 108, 231–238. doi:10.1016/j.trac.2018.09.005

CrossRef Full Text | Google Scholar

Zhang, Z., Tang, Y., Song, X., Xie, L., and Zhao, S. (2020). Tumor-derived exosomal miRNAs as diagnostic biomarkers in non-small cell lung cancer. Front. Oncol. 10, 560025. doi:10.3389/fonc.2020.560025

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, X., Liu, D., Gao, Y., Lin, C., An, Q., Feng, Y., et al. (2021). The biology and function of extracellular vesicles in cancer development. Front. Cell Dev. Biol. 9, 777441. doi:10.3389/fcell.2021.777441

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, X. W., Qi, G. X., Liu, M. X., Yang, Y. F., Wang, J. H., Yu, Y. L., et al. (2024). Deep learning promotes profiling of multiple miRNAs in single extracellular vesicles for cancer diagnosis. ACS Sensors 9 (3), 1555–1564. doi:10.1021/acssensors.3c02789

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, Z., Luo, Z., Liu, Y., Sahoo, S. S., Dembele, V., Wu, M. J., et al. (2025). Proteomic tracking extracellular vesicle RNA interactors in recipient immune cells through orthogonal labelings. J. Am. Chem. Soc. 147 (32), 28577–28582. doi:10.1021/jacs.5c07631

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhao, Y., Chen, F., Li, Q., Wang, L., and Fan, C. (2015). Isothermal amplification of nucleic acids. Chem. Rev. 115 (22), 12491–12545. doi:10.1021/acs.chemrev.5b00428

PubMed Abstract | CrossRef Full Text | Google Scholar

Zheng, D., Zhu, Y., Zhang, J., Zhang, W., Wang, H., Chen, H., et al. (2022). Identification and evaluation of circulating small extracellular vesicle microRNAs as diagnostic biomarkers for patients with indeterminate pulmonary nodules. J. Nanobiotechnology 20, 172. doi:10.1186/s12951-022-01366-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Zheng, L., Chang, R., Liang, B., Wang, Y., Zhu, Y., Jia, Z., et al. (2024). Overcoming drug resistance through extracellular vesicle-based drug delivery system in cancer treatment. Cancer Drug Resist. 7, 50. doi:10.20517/cdr.2024.107

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, W., Fong, M. Y., Min, Y., Somlo, G., Liu, L., Palomares, M. R., et al. (2014). Cancer-secreted miR-105 destroys vascular endothelial barriers to promote metastasis. Cancer Cell 25, 501–515. doi:10.1016/j.ccr.2014.03.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, L., McInnes, J., Wierda, K., Holt, M., Herrmann, A., Jackson, R., et al. (2017). Tau association with synaptic vesicles causes presynaptic dysfunction. Nat. Commun. 8, 15295. doi:10.1038/ncomms15295

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, X., Liu, M., Sun, L., Cao, Y., Tan, S., Luo, G., et al. (2023). Circulating small extracellular vesicles microRNAs plus CA-125 for treatment stratification in advanced ovarian cancer. J. Transl. Med. 21, 927. doi:10.1186/s12967-023-04774-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, J., Xu, Y., Liu, J., Feng, L., Yu, J., and Chen, D. (2024). Global burden of lung cancer in 2022 and projections to 2050: incidence and mortality estimates from GLOBOCAN. Cancer Epidemiol. 93, 102693. doi:10.1016/j.canep.2024.102693

PubMed Abstract | CrossRef Full Text | Google Scholar

Żmigrodzka, M., Guzera, M., Miśkiewicz, A., Jagielski, D., and Winnicka, A. (2016). The biology of extracellular vesicles with focus on platelet microparticles and their role in cancer development and progression. Tumour Biol. 37, 14391–14401. doi:10.1007/s13277-016-5358-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Zubkova, E., Kalinin, A., Bolotskaya, A., Beloglazova, I., and Menshikov, M. (2024). Autophagy-dependent secretion: crosstalk between autophagy and exosome biogenesis. Curr. Issues Mol. Biol. 46 (3), 2209–2235. doi:10.3390/cimb46030142

PubMed Abstract | CrossRef Full Text | Google Scholar