[ Review ]

JOURNAL OF SENSOR SCIENCE AND TECHNOLOGY - Vol. 34, No. 5, pp.410-422

ISSN: 1225-5475 (Print) 2093-7563 (Online)

Print publication date 30 Sep 2025

Received 16 Jul 2025 Revised 04 Aug 2025 Accepted 05 Aug 2025

DOI: https://doi.org/10.46670/JSST.2025.34.5.410

Exosome-Based Diagnostics: Emerging Tools for Early and Non-Invasive Disease Detection

Yeonwoo Jeong¹ ; Eun-Kyung Lim¹^{, 2}^{, 3}^{, 4}^{, +}

1Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
2Department of Nanobiotechnology, KRIBB School of Biotechnology, UST, Daejeon 34113, Republic of Korea
3School of Pharmacy, Sungkyunkwan University, Suwon 16419, Republic of Korea
4YUHS-KRIBB Medical Convergence Research Institute, Yonsei University, Seoul 03772, Republic of Korea

Correspondence to: ⁺ eklim1112@kribb.re.kr

ⓒ The Korean Sensors Society
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(https://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Exosomes are small extracellular vesicles secreted by parent cells into the extracellular environment. The biomolecules they carry—such as proteins, lipids, and nucleic acids—reflect the molecular profile of their cells of origin. Due to their stability in body fluids and close molecular resemblance to parent cells, exosomes have gained considerable attention as non-invasive biomarkers and diagnostic tools for early and accurate disease detection. This review presents a comprehensive overview of exosome biology, including their biogenesis, molecular composition, and related diagnostic biomarkers. We also summarize current exosome isolation methods and advanced exosome-based diagnostic technologies—such as CRISPR/Cas systems, digital polymerase chain reaction, and surface-enhanced Raman scattering (SERS)—emphasizing their potential for early, sensitive, and non-invasive disease diagnosis.

Keywords:

Exosome, Liquid biopsy, Non-invasive diagnosis, Early diagnosis

1. INTRODUCTION

Accurate and early diagnosis is crucial for the effective treatment and management of diseases [1,2]. However, most current diagnostic methods rely on large, complex equipment—such as magnetic resonance imaging, computed tomography, and positron emission tomography—or require painful and invasive procedures. Detecting cancer at an early stage remains challenging, especially when tumors are too small to be identified [3]. Furthermore, comprehensive assessment of the entire lesion is difficult, as only a limited tissue sample is typically collected for analysis. Molecular evaluations of these samples provide limited insight into intratumoral heterogeneity within a tumor and intermetastatic heterogeneity across metastatic sites [4,5]. As a result, repeated sampling for ongoing monitoring of disease progression or cancer recurrence in treated patients becomes difficult.

Molecular diagnostics using small volumes of liquid biopsy samples—such as saliva, tears, blood, and urine—are emerging as promising, non-invasive in vitro diagnostic tools [6-10]. These biopsies can detect various biomolecules, including circulating tumor cells, tumor-derived nucleic acids, cell-free DNA, and exosomes, all of which have been proposed as potential biomarkers. Among them, exosomes show exceptional promise for non-invasive disease detection due to their structural similarity to parent cells and their lipid bilayer, which stably encapsulates internal biomolecules [11].

Exosomes are typically 30–150 nm in size and are formed through inward budding of the plasma membrane, resulting in their release into the extracellular space [12]. They carry a wide variety of biomolecules, ranging from metabolites such as proteins and lipids to functional molecules like enzymes, antibodies, signaling molecules, and nucleic acids such as messenger RNA (mRNA) (Fig. 1) [11-16]. Once secreted, exosomes circulate through body fluids, transporting proteins, lipids, and signaling molecules that influence cellular differentiation and immune responses, thereby playing a key role in intercellular communication. Their phospholipid membrane protects enclosed biomolecules from enzymatic degradation and immune recognition, enhancing their stability. Due to their high biocompatibility, molecular stability, and ability to transport disease-specific proteins and nucleic acids, exosomes have been extensively studied as biomarkers for the early diagnosis of various diseases.

Fig. 1.

Structure and biogenesis pathway of exosomes. Adapted from Ref. [15].

In this review, we provide a brief overview of recent research trends in exosome-based molecular diagnostic techniques.

2. EXOSOME BIOLOGY

Exosomes are a subtype of extracellular vesicles (EVs), which are broadly classified based on their size and biogenesis [12]. For instance, apoptotic bodies (also called apoptosomes) form during programmed cell death (apoptosis) and range from 100 to 5000 nm in size. Ectosomes are produced via direct outward budding from the plasma membrane, while exosomes originate through the endosomal pathway—formed by inward budding of the endosomal membrane and released into the extracellular space upon fusion of multivesicular bodies with the plasma membrane. Exosomes typically range from 30 to 150 nm in diameter. Other EV subtypes, such as exosomes and exophores, have also been distinguished based on differences in their biogenetic pathways and physical characteristics.

The exosomal membrane contains a variety of biomolecular markers, including glycoproteins, cholesterol, and transmembrane proteins [13]. These surface molecules reflect the molecular profile of the parent cells, enhancing their utility in cell-specific identification. Among these, the cluster of differentiation (CD) family proteins are widely used as exosomal surface markers. For example, CD44 is overexpressed in gastric cancer, while HER2 is commonly overexpressed in breast cancer; both serve as critical diagnostic proteomic biomarkers [17].

In addition to proteins, exosomes also encapsulate nucleic acids—referred to as exosomal nucleic acids (exoNAs)—including mRNA, miRNAs, and other regulatory RNAs. These exoNAs closely mirror the genetic profile of their cell of origin and serve as valuable genomic biomarkers for early and non-invasive disease detection. For instance, exoNAs hold promise for both early cancer detection and molecular characterization of tumor subtypes. The following sections highlight disease-specific exosomal biomarkers and their diagnostic potential [18,19].

3. EXOSOMAL BIOMARKERS

Exosomes carry a wide range of biomolecules—proteins, lipids, and nucleic acids—that originate from parent cells. Because these molecular contents reflect the physiological and pathological states of the source cells, exosomes have emerged as promising biomarkers and non-invasive diagnostic tools. This section briefly reviews representative exosomal biomarkers that have been extensively explored in recent studies.

3.1 Protein markers

Exosomal proteins, in particular, have been shown to influence tumor cell proliferation, metastasis, and the tumor microenvironment [20-22]. For example, synaptotagmin 7 promotes angiogenesis, supplying tumors with nutrients and oxygen, thereby supporting tumor growth. As such, exosomal proteins represent valuable targets for disease diagnosis.

Recent studies have demonstrated methods for capturing and analyzing specific exosomes. Yang et al. employed antibody-functionalized magnetic nanoparticles (MNPs) to isolate targeted exosomes [23]. After lysis, internal proteins were extracted and identified via fluorescence labeling. Similarly, Zhang et al. developed a method using anti-CD63 aptamers conjugated to MNPs, enabling selective exosome detection and offering a promising alternative to antibody-based approaches [24].

Clinically, HER2 has been identified as a key exosomal protein biomarker for HER2-positive breast cancer [25,26]. In neurodegenerative diseases, tau protein and α-synuclein have been detected in exosomes from patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD), respectively [27-29]. Additionally, transactive response DNA-binding protein 43 (TDP-43) and its phosphorylated form (pTDP-43), identified in cerebrospinal fluid–derived exosomes, are associated with amyotrophic lateral sclerosis (ALS) [30].

3.2 Lipid and membrane-associated markers

Lipids also serve as valuable biomarkers for disease diagnosis. One of the most commonly identified lipid markers associated with inflammatory responses is phosphatidylserine [31,32]. Alterations in ceramide and sphingomyelin, key components of the exosomal lipid profile, have been demonstrated as potential biomarkers for the early detection of hepatic cancer [33]. Similarly, lysophosphatidic acid is recognized as a tumor biomarker, while elevated levels of triglycerides are known to contribute to tumor growth [34]. Prostate-specific molecules found in urinary exosomes, such as prostatic acid phosphatase and prostate transglutaminase, have been investigated for their association with prostate cancer [35]. Consequently, compositional changes in cholesterol, sphingolipids, and phosphoinositides have also been reported as disease-related indicators.

3.3 Nucleic acid markers

Genomic markers provide insights into health conditions and can indicate pathological changes at the molecular level [16]. In particular, microRNAs (miRNAs)—key post-transcriptional regulators of gene expression—reflect disease states through aberrant expression patterns. Exosome-encapsulated miRNAs (exo-miRNAs) circulate throughout the body and can function as non-invasive biomarkers for accurate disease diagnosis and therapeutic monitoring [8,9]. For instance, exosomal miR-21 and miR-205 are upregulated during tumorigenesis, while miR-145 is downregulated in breast cancer [36,37]. Similarly, miR-125b-3p, miR-122-5p, and miR-205-5p have been identified as potential exosomal biomarkers for pancreatic cancer [38]. miR-29 has been linked to colorectal cancer, and miR-135b and miR-21 have been associated with gastric cancer [39-42]. In neurodegenerative diseases, exosomal miR-574-5p has been associated with Alzheimer’s disease (AD), while miR-19, miR-24, and miR-195 have been identified as potential biomarkers for Parkinson’s disease (PD) [27,43]. Additionally, downregulation of exosomal miR-27a-3p has been reported in patients with ALS [30].

The polymerase chain reaction (PCR) remains the most widely used method for detecting exoNAs [44]. Rolling circle amplification (RCA) is another effective technique, offering benefits such as high sensitivity, low error rates, and compatibility with low-volume or crude samples [45,46]. Furthermore, recent advancements in high-sensitivity analytical technologies—such as next-generation sequencing (NGS) and digital PCR—have enabled the detection of trace levels of target biomarkers [10,47]. In addition, simplified and efficient approaches, including isothermal amplification and nonenzymatic signal amplification using molecular beacons and nanoprobes, are being actively explored for exoNA-based diagnostics.

4. EXOSOME ISOLATION

Accurate disease diagnosis using exosomes requires high-purity enrichment, selective isolation, and highly sensitive detection techniques. Although exosomes are abundant in plasma—typically exceeding 10⁹ particles per milliliter—the concentration of disease-specific exosomal biomarkers is relatively low [48,49]. For instance, HER2-positive exosomes may occur at levels lower than 1,000 particles/mL in patients with HER2-overexpressing cancers.

Currently available methods for exosome isolation include ultracentrifugation, size exclusion chromatography, immunoaffinity capture, polymer-based precipitation, and microfluidics-based techniques [50,51].

4.1 Ultracentrifugation

Ultracentrifugation is the most widely used method for exosome isolation. It involves the sequential separation of particles based on their size and density [50,52-54]. In a typical protocol, large cells and debris are first removed at low centrifugal speeds (300–2,000 × g), followed by the elimination of microvesicles at intermediate speeds (approximately 10,000 × g). Finally, high-speed ultracentrifugation (approximately 100,000 × g) is used to pellet the exosomes from biofluids. Although regarded as the gold standard, ultracentrifugation is associated with low exosome yield and potential protein contamination, often necessitating additional purification steps.

4.2 Size-exclusion chromatography

Size-exclusion chromatography (SEC) is a widely used technique for exosome isolation, separating particles based on their size [55,56]. Unlike ultracentrifugation, SEC enables the recovery of intact and biologically functional exosomes with minimal physical stress or shear force. However, its application is limited by co-isolation of similarly sized impurities—such as lipoprotein particles—which necessitates additional purification steps [57]. To address this, a recent bidirectional flow-controlled filtration system using nanoporous membranes (50–200 nm) has demonstrated improved performance, achieving higher purity and throughput compared to conventional methods [58].

4.3 Precipitation

Precipitation is another commonly used approach for concentrating exosomes [59]. It relies on polymers that induce exosome aggregation, enabling their subsequent precipitation and purification. For instance, polyethylene glycol is often used to precipitate and isolate exosomes from various sample types, including serum, plasma, and cell culture medium [60,61]. Similarly, poly-L-lysine has been employed to aggregate exosomes from plasma, followed by recovery using an elution buffer [62]. This method has shown greater efficiency compared to ultracentrifugation.

4.4 Immune affinity capture

The immunoaffinity-based method offers a highly selective and specific strategy for exosome isolation [63]. It utilizes antibodies targeting specific surface protein markers to capture exosomes. CD63—a member of the tetraspanin family of four-pass transmembrane proteins and commonly present on the exosome surface [64]—has been extensively used as a capture target due to its abundant and consistent expression. For example, Chen et al. functionalized an anti-CD63 antibody on a microfluidic chip to successfully extract exosomes from serum samples [65]. Similarly, Kanwar et al. employed a 12-channel microfluidic device using CD63-based immunoaffinity to isolate exosomes [66]. The captured exosomes were labeled with a carbocyanine dye and quantified using a plate reader. Their study reported a 2.34-fold higher capture efficiency in serum samples from patients with pancreatic cancer compared to healthy controls, underscoring the diagnostic potential of immunoaffinity-based exosome isolation techniques.

4.5 Microfluidic system

Microfluidic systems for exosome isolation offer numerous advantages, including rapid processing, minimal sample volume requirements, high throughput, cost-effectiveness, and compatibility with multiplexing and automation [67]. Additionally, these platforms can be integrated with other established isolation techniques to enhance overall performance.

For example, Haam et al. assembled anti-HER2 antibody-functionalized silica nanoparticles into a herringbone structure within a microfluidic chip (Fig. 2 (b)) [68]. This configuration enhanced fluid mixing and increased the interaction between exosomes and surface-immobilized antibodies, enabling efficient capture of HER2-positive exosomes from the urine of a breast cancer mouse model—thus allowing for sensitive, non-invasive diagnosis. They also reported that antibody-functionalized MNPs are effective for isolating and enriching high-purity exosomes [69]. When combined with a microfluidic system, MNPs conjugated with anti-HER2 and anti-CD63 antibodies were used to successfully isolate HER2- and CD63-overexpressing exosomes from urine via magnetic separation. Alternatively, microfluidic chips integrated with electrodes and functionalized with antibodies can capture exosomes based on immune affinity [70]. The application of an electrical potential selectively releases the bound and concentrated target exosomes.

Fig. 2.

Schematic of microfluidic-based exosome diagnostics. Adapted from (a) Ref. [74] and (b) Ref. [68].

Furthermore, a fully automated microfluidic platform has been developed to isolate tumor-derived exosomes and analyze their physical characteristics, such as size, concentration, and zeta potential. Integration with deep learning algorithms has enabled real-time, point-of-care analysis, highlighting its potential for advanced lab-on-a-chip diagnostics [71].

5. EXOSOME-BASED DIAGNOSTICS

Equally important is the analysis of exosomal cargo—such as signaling molecules like proteins, mRNA, and miRNAs—to determine their relevance to disease [13,72,73]. Traditionally, techniques like western blotting and enzyme-linked immunosorbent assay (ELISA) have been used to detect exosomal proteins. More recently, a variety of advanced analytical methods have been developed, including nanoparticle tracking analysis, dynamic light scattering, flow cytometry, NGS, digital PCR, isothermal amplification, and surface-enhanced Raman scattering (SERS). This section introduces several state-of-the-art technologies used for exosome characterization and cargo analysis.

5.1 Microfluidic platforms

Microfluidic platforms show strong potential for exosome-based diagnostic applications when integrated with analytical techniques. Li et al. developed a detection platform targeting SORL1 and CD9 proteins—biomarkers associated with colorectal cancer (CRC)—using a three-dimensional (3D) porous microfluidic chip [75]. The system achieved over 90% capture efficiency for CRC-related exosomes. A quantum-dot-based fluorescence probe was then used to label and visualize SORL1, achieving an area under the curve (AUC) of 0.99, demonstrating excellent specificity, sensitivity, and early diagnostic potential.

Lim et al. developed a microfluidic device integrated with a signal-amplifiable 3D nanostructured hydrogel to detect breast-cancer-derived exoNAs in blood samples [74]. The detection probe featured a hairpin structure containing a fluorophore (FAM) and a black hole quencher (BHQ). In its native state, fluorescence was quenched via fluorescence resonance energy transfer (FRET). Upon target recognition, a catalytic hairpin assembly (CHA) reaction was triggered, restoring the fluorescence signal. Kim et al. also employed this strategy, using immunoaffinity magnetophoresis to isolate HER2-positive exosomes and analyze encapsulated mRNA in real time via CHA (Fig. 2 (a)) [74].

5.2 Droplet digital PCR (ddPCR)

Droplet digital PCR (ddPCR), which operates using nanoliter-sized droplets, provides high sensitivity, precision, and reproducibility—even with minimal input samples. As such, it has been widely adopted for the detection of diagnostic biomarkers in exosomes [10]. For instance, miR-29a has been successfully detected in urinary exosomes using ddPCR, showing greater sensitivity compared to conventional PCR [79]. Shen et al. isolated EpCAM-positive exosomes using MNPs and quantified long non-coding RNAs RP11-77G23.5 and PHEX-AS1 via ddPCR for lung cancer diagnosis [80]. Similarly, Zhang et al. introduced a photothermally assisted ddPCR method for analyzing prostate cancer–derived exosomes [81]. They confirmed the upregulated expression of miR-21-5p, miR-375-3p, and miR-574-3p in cancer cells. This approach enables enhanced sensitivity and rapid detection due to the synergistic effect of localized photothermal heating.

5.3 CRISPR/Cas-based detection

Recently, clustered regularly interspaced short palindromic repeats (CRISPR) and associated protein (Cas)-based technologies have emerged as advanced molecular diagnostic tools [82,83]. CRISPR/Cas systems have also been applied to the identification of exosomal biomarkers. For instance, Song et al. developed a CRISPR/Cas9-mediated light-up aptamer transcription assay to detect tumor-derived DNA in urine (Fig. 3 (a)) [77]. DNA extracted from exosomes was captured using a positively charged polymer, followed by specific cleavage via the CRISPR/Cas9 system. This triggered the transcription of a light-up aptamer under the control of the T7 promoter, enabling fluorescence-based signal detection.

Fig. 3.

Schematic of CRISPR/Cas-based exosome diagnostics. Adapted from (a) Ref. [77] and (b) Ref. [78].

Moon et al. introduced a ligation-free RNA detection strategy using CRISPR/Cas12a-mediated signal amplification (Fig. 3 (b)) [78]. After target RNA recognition, ligation-free DNA amplification produced amplicons that activated the trans-cleavage activity of Cas12a. The activated enzyme cleaved FAM- and BHQ2-labeled single-stranded DNA (ssDNA), generating amplified fluorescence signals. This method enabled the sensitive detection of cancer-related genes such as ERBB2 and GRB7 (Fig. 4 (a)) [93].

Fig. 4.

Schematic of fluorescence-based exosome diagnostics. Adapted from (a) Ref. [93], (b) Ref. [89], (c) Ref. [88], and (d) Ref. [87].

Peng et al. employed a CD63 aptamer-based approach to isolate exosomes from serum using CD63-conjugated magnetic beads [84]. The captured exosomes were released via bubble mixing and analyzed using the CRISPR/Cas13a system for exoNA detection. Jiang et al. developed a smartphone-enabled colorimetric assay for tumor-derived exosome detection using a nanozyme-based platform with dual-aptamer recognition targeting EpCAM and CD63 [85]. Upon exosome binding, triggering DNA was released, activating the Cas12a trans-cleavage activity. The activated Cas12a cleaved ssDNA linked to multifunctional nanozymes, initiating catalytic activity for visual signal generation. This platform enabled ultrasensitive and specific detection of lung cancer-derived exosomes with smartphone-based readout integration.

5.4 Alternative nucleic acid-based detection

In addition to the above approaches, several other nucleic acid-based diagnostic strategies have been reported to detect exoNAs with high sensitivity. For instance, isothermal amplification methods have gained considerable attention for their simplicity and compatibility with point-of-care platforms. Seo et al. used rolling-circle amplification (RCA) to amplify exoNAs and detected gastric cancer-derived exosomes via a lateral flow assay (LFA) [45,86]. A nucleic acid amplification circuit-based hydrogel system was also developed to detect miR-21 and miR-99a, two well-known gastric cancer markers. In this platform, target miRNAs hybridize with circular DNA probes embedded within a hydrogel, triggering RCA and producing fluorescence signals comparable to those of PCR [86].

Lim et al. introduced a Janus hydrogel-based, fuel-simulated powered amplification strategy for in vivo detection of gastric cancer exoNAs (Fig. 4 (d)) [87]. This platform enabled the simultaneous, enzyme-free detection of miR-135b and miR-21. The same group later reported a CHA-based hydrogel sensor for enzyme-free detection of miR-574-5p, derived from an AD in vivo model, achieving a detection limit of 1.29 pM with high sensitivity and selectivity (Fig. 4 (c)) [88].

Beyond amplification-based techniques, membrane fusion systems have also been explored for exoNA detection [89-91]. For example, Lei et al. developed a platform based on membrane fusion between liposomes containing fluorescent probes and target exosomes [90]. Fusion-induced fluorescence changes enabled label-free, high-throughput detection at the single-exosome level. Similarly, Park et al. employed a membrane-fusion strategy using a fusogenic nanoreactor (Fig. 4 (b)) [89]. A FRET reaction was initiated upon fusion with cancer-derived exosomes using encapsulated DNA fuel, enabling detection of breast cancer exosomes within 30 minutes.

Although not based on nucleic acids, a colorimetric detection system for HER2-overexpressing exosomes has also been reported [92]. In this method, polydiacetylene thin films were combined with hydrophilic magnetic nanoparticles (MNPs) and anti-HER2 antibodies, enabling visual detection of exosomes at concentrations as low as 8.5 × 10⁸ particles/mL in a breast cancer mouse model.

5.5 Electrochemical-based detection

Electrochemical sensing has emerged as a versatile strategy for detecting exosomes due to its high sensitivity, simplicity, and compatibility with miniaturized platforms. In a typical electrochemical setup, aptamer-functionalized electrodes are used to capture exosomes, where the binding event induces a measurable signal change [94]. For instance, the release of redox-active molecules, such as methylene blue, from the electrode surface upon exosome binding can lead to signal attenuation. Zhang et al. developed a signal amplification strategy that employs CD63 aptamers for exosome capture, followed by a hybridization chain reaction (HCR) initiated by an EpCAM aptamer and an initiator strand (Fig. 5 (a)) [95]. The resulting HCR amplicons were subsequently conjugated to horseradish peroxidase (HRP) for electrochemical signal generation. Jiang et al. simplified this approach by designing a system based on tetrahedral DNA nanostructures anchored to gold microelectrodes and coated with polydopamine (pDA) (Fig. 5 (b)) [96]. These nanostructures contained CD63 aptamers for exosome capture. Upon binding, HRP catalyzed the polymerization of pDA, producing measurable electrochemical signals. Liu et al. developed a dual-mode biosensor to detect programmed death-ligand 1-positive (PD-L1⁺) exosomes associated with cancer progression [97]. They utilized silver-coated magnetic nanoparticles functionalized with mucin1 (MUC1) aptamers for magnetic capture, and the system exhibited intrinsic peroxidase-like activity for colorimetric detection. Simultaneously, anti-PD-L1 antibodies immobilized on an electrochemical electrode were used to generate a signal via an electrochemical readout, enabling dual-modal detection (colorimetric and electrochemical) of cancer-derived exosomes.

Fig. 5.

Schematic of electrochemically and SERS-based exosome diagnostics. Adapted from (a) Ref. [95], (b) Ref. [96], and (c) Ref. [98].

5.6 Surface-enhanced Raman scattering (SERS)-based detection

Surface-enhanced Raman scattering (SERS) is a powerful optical technique that significantly amplifies the Raman signals of molecular fingerprints, thus enabling label-free and ultrasensitive detection at the single-molecule level [99,100]. Yang et al. developed an SERS-based optical platform by functionalizing gold nanostructures with receptor probes to detect prostate cancer cell-derived exoNAs [101]. This system achieved a detection limit as low as 100 aM. Similarly, Wang et al. integrated a microfluidic chip for detecting prostate cancer exosomes using CD63 as a surface marker [102]. Anti-CD63 antibody-enriched exosomes were captured within the microchannel, and signal readouts were obtained using EpCAM-functionalized Raman beads.

Recently, advanced plasmonic sensing techniques, such as surface plasmon resonance and SERS, have been combined with artificial intelligence (AI) to enhance diagnostic accuracy [103]. For instance, Carmichael et al. developed a label-free SERS method to distinguish between normal and cancerous cells using machine learning algorithms for early pancreatic cancer diagnosis [104]. Similarly, Kim et al. applied deep learning to SERS data to monitor therapeutic responses to trastuzumab, an HER2-targeted monoclonal antibody (Fig. 5 (c)) [98]. Distinct Raman reporters were conjugated to exosomal surface markers, such as GRB7, CD63, GAPDH, and HER2, to monitor treatment resistance. The resulting SERS spectra were analyzed using deep learning algorithms, enabling precise monitoring of treatment efficacy and resistance development.

5.7 Artificial intelligence (AI)-integrated technologies

AI innovations are also transforming exosome diagnostics across ddPCR, CRISPR/Cas, and SERS platforms [98,103,104]. Liu et al. integrated a 4-plex ddPCR platform with machine learning to simultaneously detect exoNAs for breast cancer diagnosis [105]. This approach significantly improved diagnostic accuracy over conventional ddPCR, representing a powerful strategy for early and precise cancer detection. Similarly, Zhang et al. developed a CRISPR/Cas13a-based detection platform for identifying colorectal cancer (CRC) from fecal exoNAs, achieving 97.4% diagnostic accuracy—surpassing traditional methods [106]. Yang et al. applied Raman spectroscopy to detect hepatocellular carcinoma, and Lee et al. utilized atomic force microscopy (AFM) for non-small cell lung cancer detection [107,108]. These advancements underscore the promise of AI-integrated exosome diagnostic technologies for non-invasive, accurate, and early disease detection.

6. CONCLUSIONS

Exosome-based diagnostics are emerging as powerful tools for the early detection of diseases such as cancer, neurodegenerative disorders, and metabolic conditions. Future advancements involving highly sensitive, high-throughput platforms integrated with AI-driven data interpretation will further enhance their clinical utility. Exosomes are precise diagnostic tools because their molecular content reflects the disease state and genetic profile of their parent cells. Moreover, exosome analysis enables monitoring of tumor heterogeneity and treatment responses, positioning it as a critical technology in personalized medicine. The development of single-exosome profiling techniques to analyze nucleic acids, proteins, and lipids at the individual exosome level allows for the identification of rare exosome subpopulations and subtle intercellular differences, thereby significantly improving diagnostic accuracy.

Acknowledgments

This research was supported by IITP and NRF grants funded by Korea government (MSIT) (RS-2024-00459749, and RS-2025-00554718), the Ministry of Education (RS-2023-00275869), Technology Development Program for Biological Hazards Management in Indoor Air through Korea Environment Industry & Technology Institute (KEITI) funded by Korea government (ME) (2021003370003), Korea Evaluation Institute of Industrial Technology (KEIT) grant funded by Korea government (MOTIE) (RS-2024-00403563 and RS-2022-00154853), KHIDI grant funded by Korea government (MOHW) (RS-2025-02213315), and KRIBB Research Initiative Program (KGM1322511, KGM1032511).

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Yeonwoo Jeong is a postdoctoral researcher at the Bionanotechnology Research Center of the Korea Research Institute of Bioscience and Biotechnology (KRIBB). He received his B.S. degree in Marine Biomaterials and Aquaculture from Pukyoung National University (PKNU), Korea, in 2016, and his Ph.D. from the Department of Chemistry at Chungbuk National University (CBNU), Korea, in 2021. His research interests include polymer synthesis, surface modifications, and molecular diagnostics.

Eun-Kyung Lim is the principal researcher at the Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Department of Nanobiotechnology, KRIBB School of Biotechnology, University of Science and Technology (UST). She serves in adjunct positions at the School of Pharmacy, Sungkyunkwan University, and the YUHS-KRIBB Medical Convergence Research Institute at Yonsei University. She received her B.S. degree from the Department of Chemical and Engineering, Yonsei University, Korea, in 2007 and her Ph.D. from the Department of Chemical and Biomolecular Engineering, Yonsei University, Korea, in 2011. She then moved to the Department of Radiology, College of Medicine, Yonsei University as a postdoctoral researcher and research assistant. Her research interests include nanomaterial processing, nano-biological fusion, bio-nano particles, nano-carriers, and biomaterial technologies.