A Label-Free Platform for Identification of Exosomes from Different Sources

Opto-digital molecular analytics

In contrast to conventional ensemble-average-based methods, opto-digital molecular analytic approaches digitize detection by physically partitioning individual detection events into discrete compartments or directly locating and analyzing the signals from single molecules. The sensitivity can be enhanced by signal amplification reactions, signal enhancement interactions, labelling by strong signal emitters, advanced optics, image processing, and machine learning, while specificity can be improved by designing target-selective probes and profiling molecular dynamics. With the capabilities to attain a limit of detection several orders lower than the conventional methods, reveal intrinsic molecular information, and achieve multiplexed analysis using a small-volume sample, the emerging opto-digital molecular analytics may be revolutionarily instrumental to clinical diagnosis, molecular chemistry and science, drug discovery, and environment monitoring. In this article, we provide a comprehensive review of the recent advances, offer insights into the underlying mechanisms, give comparative discussions on different strategies, and discuss the current challenges and future possibilities.

On the Feasibility of SERS-Based Monitoring of Drug Loading Efficiency in Exosomes for Targeted Delivery

Cancer, a significant cause of mortality, necessitates improved drug delivery strategies. Exosomes, as natural drug carriers, offer a more efficient, targeted, and less toxic drug delivery system compared to direct dispersal methods via ingestion or injection. To be successfully implemented as drug carriers, efficient loading of drugs into exosomes is crucial, and a deeper understanding of the loading mechanism remains to be solved. This study introduces surface-enhanced Raman scattering (SERS) to monitor drug loading efficacy at the single vesicle level. By enhancing the Raman signal, SERS overcomes limitations in Raman spectroscopy. A gold nanopyramids array-based SERS substrate assesses exosome heterogeneity in drug-loading capabilities with the help of single-layer graphene for precise quantification. This research advances targeted drug delivery by presenting a more efficient method of evaluating drug-loading efficiency into individual exosomes through SERS-based monitoring. Furthermore, the study explores leveraging osmotic pressure variations, enhancing the efficiency of drug loading into exosomes.

Surface-Enhanced Raman Scattering (SERS) for exosome detection

BACKGROUND

Exosomes, nanoscale extracellular vesicles secreted by various cells, are abundantly present in biological fluids. They have been identified as carriers of specific molecules, suggesting their potential role in early disease detection. However, their clinical application is hindered by several challenges, including the need for large sample volumes for enrichment, limitations of traditional detection methods, and the complexity involved in phenotype analysis and separation.

OBJECTIVE

This review aims to explore the application of Surface-Enhanced Raman Scattering (SERS) technology in exosome detection. SERS, known for its unique photonic properties and high sensitivity, offers a promising solution for detecting exosomes without the need for large sample volumes or extensive phenotypic analysis. This review focuses on the real-time and non-invasive assessment capabilities of SERS in exosome detection, providing insights into its potential for early disease diagnosis.

CONCLUSION

The review concludes by emphasizing the potential of SERS-based exosome detection in advancing early disease diagnosis. By overcoming existing challenges, SERS technology offers a promising approach for the development of sensitive and specific diagnostic assays, contributing to better patient outcomes and personalized medicine.

Digital SERS immunoassay of Interleukin-6 based on Au@Ag-Au nanotags

Interleukin-6 (IL-6) is a crucial cytokine involved in inflammation and immune regulation. However, the detection of IL-6 with ultrasensitivity and high specificity remains a significant challenge due to the inherent complexity of biofluids. Herein, we present a digital surface enhanced Raman scattering (SERS) immunoassay using core-shell Au@Ag-Au nanotags for IL-6 detection with ultrasensitivity and high reliability. A low-cost silicon chip was functionalized as capture substrates, employing novel SERS nanotags that exhibit strong, robust and reproducible signals at single-nanoparticle resolution as the amplification element. We proposed two analytical methods to validate single-molecule events follow a Poisson distribution and to quantify protein biomarkers over a broad linear dynamic range, respectively. The strong alignment between theoretical and experimental results enhances the method's reliability. Our assay provides two readouts: colorimetric analysis by naked eyes for high concentrations (>1 ng/mL) and digital SERS analysis for low concentrations. Following method optimization, we obtained a linear range from 100 fg/mL to 1 ng/mL (R2 = 0.994) with a limit of detection (LOD) of 12.4 fg/mL, suitable for clinical applications. The method was tested for IL-6 quantification in healthy human serum and saliva, with recoveries from 92.4% to 105.3%. Finally, the immunoassay demonstrated strong consistency with the standard clinical laboratory method when tested with clinical serum samples. Thus, our proposed the digital SERS immunoassay is a promising tool for the precision clinical diagnosis of IL-6-related diseases or other conditions.

Advances in exosome plasmonic sensing: Device integration strategies and AI-aided diagnosis

Exosomes, as next-generation biomarkers, has great potential in tracking cancer progression. They face many detection limitations in cancer diagnosis. Plasmonic biosensors have attracted considerable attention at the forefront of exosome detection, due to their label-free, real-time, and high-sensitivity features. Their advantages in multiplex immunoassays of minimal liquid samples establish the leading position in various diagnostic studies. This review delineates the application principles of plasmonic sensing technologies, highlighting the importance of exosomes-based spectrum and image signals in disease diagnostics. It also introduces advancements in miniaturizing plasmonic biosensing platforms of exosomes, which can facilitate point-of-care testing for future healthcare. Nowadays, inspired by the surge of artificial intelligence (AI) for science and technology, more and more AI algorithms are being adopted to process the exosome spectrum and image data from plasmonic detection. Using representative algorithms of machine learning has become a mainstream trend in plasmonic biosensing research for exosome liquid biopsy. Typically, these algorithms process complex exosome datasets efficiently and establish powerful predictive models for precise diagnosis. This review further discusses critical strategies of AI algorithm selection in exosome-based diagnosis. Particularly, we categorize the AI algorithms into the interpretable and uninterpretable groups for exosome plasmonic detection applications. The interpretable AI enhances the transparency and reliability of diagnosis by elucidating the decision-making process, while the uninterpretable AI provides high diagnostic accuracy with robust data processing by a "black-box" working mode. We believe that AI will continue to promote significant progress of exosome plasmonic detection and mobile healthcare in the near future.

A simple capillary isoelectric focusing method as the novel strategy for the isoelectric point measurement of exosomes and its application in disease diagnosis

A straightforward capillary isoelectric focusing (cIEF) method is established with a isoelectric point (pI) range spanning from 3.5 to 7.0, exhibiting excellent linearity and repeatability, with an R2 value of 0.9937 and migration time RSDs for all standard proteins below 0.3%. Subsequently, this method was applied to model exosomes derived from cell lines and healthy human serum, and the peak attributions of exosomes were identified using DiI labeled exosomes and lysed exosomes. The reproducibility of this method in exosome detection was also validated, as the RSDs of all pI values were less than 1%. Then, we observed a significant increase in the pI of exosomes with higher cholesterol content, irrespective of whether they originated from cell culture medium or mouse plasma. Notably, serum exosomes from healthy volunteers exhibited higher pI values compared to those from hepatocellular carcinoma patients, suggesting a potential diagnostic perspective for cancer. These findings underscore the significance of pI measurement in reflecting modifications in exosomal lipid membrane composition and their implications in biological functions mediated by exosomes.

Label-Free Exosome Analysis by Surface-Enhanced Raman Scattering Spectroscopy with Laser-Ablated Silver Nanoparticle Substrate

Early diagnostics of breast cancer is crucial to reduce the risk of cancer metastasis and late relapse. Exosome, which contains distinct information of its origin, can be the target object as a liquid biopsy. However, its low sensitivity and inadequate diagnostic tools interfere with the point-of-care testing (POCT) of the exosome. Recently, Surface-enhanced Raman Scattering (SERS) spectroscopy, which amplifies the Raman scattering, has been proved as a promising tool for exosome detection. However, the fabrication process of SERS probe or substrate is still inefficient and far from large-scale production. This study proposes rapid and label-free detection of breast cancer-derived exosomes by statistical analysis of SERS spectra using silver-nanoparticle-based SERS substrate fabricated by selective laser ablation and melting (SLAM). Employing silver nanowires and optimizing laser process parameters enable rapid and low-energy fabrication of SERS substrate. The functionalities including sensitivity, reproducibility, stability, and renewability are evaluated using rhodamine 6G as a probe molecule. Then, the feasibility of POCT is examined by the statistical analysis of SERS spectra of exosomes from malignant breast cancer cells and non-tumorigenic breast epithelial cells. The presented framework is anticipated to be utilized in other biomedical applications, facilitating cost-effective and large-scale production performance.

Electroactivated SERS Nanoplatform for Rapid and Sensitive Detection and Identification of Tumor-Derived Exosome miRNA

Exosomal miRNA expression derived from tumor cells provides a valuable and promising noninvasive modality for the early diagnosis and assessment of the efficacy of cancer treatment. However, accurate detection and identification of miRNA within exosomes have been challenging due to its low abundance and the complexity and tedious extraction with large sample volumes in the separation process. Here, we developed an electrically activated nanoplatform for rapid and sensitive detection and identification of exosome miRNA, through triggering miRNA release by opening exosomes that were captured on the electrode surface using a slightly applied electric field (50 mV), and simultaneously detected them with surface-enhanced Raman spectroscopy (SERS) in situ. The method possessed superior specificity and sensitivity for exosomal miRNA detection, with a low detection concentration of 0.5 nM. The SERS sensor chips also showed a superior sensing performance of exosomal miRNA in complex body fluids such as urine and blood. We found that exosomal miRNA contents derived from tumor cells were significantly higher than those in normal cells, and importantly, the concentrations of exosomes secreted from three different cell lines were distinctly augmented after mild electrical stimulation (ES) treatment. Furthermore, the miRNA expression within exosomes was upregulated after the ES treatment of cells. The developed approach and SERS detection platform for exosomal miRNA are promising for noninvasive and precise screening, classification, and monitoring of cancer.

Plant-Derived Exosome-like Nanoparticles: A Comprehensive Overview of Their Composition, Biogenesis, Isolation, and Biological Applications

Plant-derived exosome-like nanoparticles (PELNs) are a type of membranous vesicle isolated from plant tissues. They contain proteins, lipids, nucleic acids, and other components. PELNs are involved in the defensive response to pathogen attacks by exerting anti-inflammatory, antiviral, antifibrotic, and antitumor effects through the substances they contain. Most PELNs are edible and can be used as carriers for delivering specific drugs without toxicity and side effects, making them a hot topic of research. Sources of PELNs are abundantly, and they can be produced in high yields, with a low risk of developing immunogenicity in vivo. This paper summarizes the formation, isolation, and purification methods; physical properties; and composition of PELNs through a comprehensive literature search. It also analyzes the biomedical applications of PELNs, as well as future research directions. This paper provides new ideas and methods for future research on PELNs.

Label-free single-vesicle based surface enhanced Raman spectroscopy: A robust approach for investigating the biomolecular composition of small extracellular vesicles

Small extracellular vesicles (sEVs) are cell-released vesicles ranging from 30-150nm in size. They have garnered increasing attention because of their potential for both the diagnosis and treatment of disease. The diversity of sEVs derives from their biological composition and cargo content. Currently, the isolation of sEV subpopulations is primarily based on bio-physical and affinity-based approaches. Since a standardized definition for sEV subpopulations is yet to be fully established, it is important to further investigate the correlation between the biomolecular composition of sEVs and their physical properties. In this study, we employed a platform combining single-vesicle surface-enhanced Raman spectroscopy (SERS) and machine learning to examine individual sEVs isolated by size-exclusion chromatography (SEC). The biomolecular composition of each vesicle examined was reflected by its corresponding SERS spectral features (biomolecular "fingerprints"), with their roots in the composition of their collective Raman-active bonds. Origins of the SERS spectral features were validated through a comparative analysis between SERS and mass spectrometry (MS). SERS fingerprinting of individual vesicles was effective in overcoming the challenges posed by EV population averaging, allowing for the possibility of analyzing the variations in biomolecular composition between the vesicles of similar and/or different sizes. Using this approach, we uncovered that each of the size-based fractions of sEVs contained particles with predominantly similar SERS spectral features. Indeed, more than 84% of the vesicles residing within a particular group were clearly distinguishable from that of the other EV sub-populations, despite some spectral variations within each sub-population. Our results suggest the possibility that size-based EV fractionation methods produce samples where similarly eluted sEVs are correlated with their respective biochemical contents, as reflected by their SERS spectra. Our findings therefore highlight the possibility that the biogenesis and respective biological functionalities of the various sEV fractions may be inherently different.

SERS biosensors for liquid biopsy towards cancer diagnosis by detection of various circulating biomarkers: current progress and perspectives

Liquid biopsy has emerged as a promising non-invasive strategy for cancer diagnosis, enabling the detection of various circulating biomarkers, including circulating tumor cells (CTCs), circulating tumor nucleic acids (ctNAs), circulating tumor-derived small extracellular vesicles (sEVs), and circulating proteins. Surface-enhanced Raman scattering (SERS) biosensors have revolutionized liquid biopsy by offering sensitive and specific detection methodologies for these biomarkers. This review comprehensively examines the application of SERS-based biosensors for identification and analysis of various circulating biomarkers including CTCs, ctNAs, sEVs and proteins in liquid biopsy for cancer diagnosis. The discussion encompasses a diverse range of SERS biosensor platforms, including label-free SERS assay, magnetic bead-based SERS assay, microfluidic device-based SERS system, and paper-based SERS assay, each demonstrating unique capabilities in enhancing the sensitivity and specificity for detection of liquid biopsy cancer biomarkers. This review critically assesses the strengths, limitations, and future directions of SERS biosensors in liquid biopsy for cancer diagnosis.

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.

Advances of machine learning-assisted small extracellular vesicles detection strategy

Detection of extracellular vesicles (EVs), particularly small EVs (sEVs), is of great significance in exploring their physiological characteristics and clinical applications. The heterogeneity of sEVs plays a crucial role in distinguishing different types of cells and diseases. Machine learning, with its exceptional data processing capabilities, offers a solution to overcome the limitations of conventional detection methods for accurately classifying sEV subtypes and sources. Principal component analysis, linear discriminant analysis, partial least squares discriminant analysis, XGBoost, support vector machine, k-nearest neighbor, and deep learning, along with some combined methods such as principal component-linear discriminant analysis, have been successfully applied in the detection and identification of sEVs. This review focuses on machine learning-assisted detection strategies for cell identification and disease prediction via sEVs, and summarizes the integration of these strategies with surface-enhanced Raman scattering, electrochemistry, inductively coupled plasma mass spectrometry and fluorescence. The performance of different machine learning-based detection strategies is compared, and the advantages and limitations of various machine learning models are also evaluated. Finally, we discuss the merits and limitations of the current approaches and briefly outline the perspective of potential research directions in the field of sEV analysis based on machine learning.

Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously by SERS since the Raman signals of exosomes detected by conventional colloidal nanocrystals or two-dimensional SERS substrates are incomplete and complex. Herein, we develop a novel three-dimensional (3D) surround-enhancing SERS platform, named 3D se-SERS, for the multiplex detection of exosomal proteins. In this 3D se-SERS, proteins and exosomes are covered with "hotspots" generated by the gold nanoparticles, which surround the analytes densely and three-dimensionally, providing sensitive and comprehensive SERS signals. Combining this 3D se-SERS with a deep learning model, we successfully quantitatively profiled seven proteins including CD63, CD81, CD9, CD151, CD171, TSPAN8, and PD-L1 on the surface of plasma exosomes from patients, which can predict the occurrence and advancement of lung cancer. This 3D se-SERS integrating deep learning technique benefits from high sensitivity and significant multiplexing ability for comprehensive analysis of proteins and exosomes, demonstrating the potential of deep learning-driven 3D se-SERS technology for plasma exosome-based early cancer diagnosis.

Exosome Isolation and Detection: From Microfluidic Chips to Nanoplasmonic Biosensor

Exosomes are becoming more widely acknowledged as significant circulating indicators for the prognosis and diagnosis of cancer. Circulating exosomes are essential to the development and spread of cancer, according to a growing body of research. Using existing technology, characterizing exosomes is quite difficult. Therefore, a direct, sensitive, and targeted approach to exosome detection will aid in illness diagnosis and prognosis. The review discusses the new strategies for exosome isolation and detection technologies from microfluidic chips to nanoplasmonic biosensors, analyzing the advantages and limitations of these new technologies. This review serves researchers to better understand exosome isolation and detection methods and to help develop better exosome isolating and detecting devices for clinical applications.

Toward the nanoscale chemical and physical probing of milk-derived extracellular vesicles using Raman and tip-enhanced Raman spectroscopy

Tip-enhanced Raman spectroscopy (TERS) is an advanced technique to perform local chemical analysis of the surface of a sample through the improvement of the sensitivity and the spatial resolution of Raman spectroscopy by plasmonic enhancement of the electromagnetic signal in correspondence with the nanometer-sized tip of an atomic force microscope (AFM). In this work, TERS is demonstrated to represent an innovative and powerful approach for studying extracellular vesicles, in particular bovine milk-derived extracellular vesicles (mEVs), which are nanostructures with considerable potential in drug delivery and therapeutic applications. Raman spectroscopy has been used to analyze mEVs at the micrometric and sub-micrometric scales to obtain a detailed Raman spectrum in order to identify the 'signature' of mEVs in terms of their characteristic molecular vibrations and, therefore, their chemical compositions. With the ability to improve lateral resolution, TERS has been used to study individual mEVs, demonstrating the possibility of investigating a single mEV selected on the surface of the sample and, moreover, analyzing specific locations on the selected mEV with nanometer lateral resolution. TERS potentially allows one to reveal local differences in the composition of mEVs providing new insights into their structure. Also, thanks to the intrinsic properties of TERS to acquire the signal from only the first few nanometers of the surface, chemical investigation of the lipid membrane in correspondence with the various locations of the selected mEV could be performed by analyzing the peaks of the Raman shift in the relevant range of the spectrum (2800-3000 cm-1). Despite being limited to mEVs, this work demonstrates the potential of TERS in the analysis of extracellular vesicles.

Bone Marrow Mesenchymal Stem Cell-Derived Exosomes Promote the Recovery of Spinal Cord Injury and Inhibit Ferroptosis by Inactivating IL-17 Pathway

Mesenchymal stem cell (MSC)-derived exosomes are considered as alternative to cell therapy in various diseases. This study aimed to understand the effect of bone marrow MSC-derived exosomes (BMMSC-exos) on spinal cord injury (SCI) and to unveil its regulatory mechanism on ferroptosis. Exosomes were isolated from BMMSCs and the uptake of BMMSCs-exos by PC12 cells was determined using PKH67 staining. The effect of BMMSC-exos on SCI in rats was studied by evaluating pathological changes of spinal cord tissues, inflammatory cytokines, and ferroptosis-related proteins. Transcriptome sequencing was used to discover the differential expressed genes (DEGs) between SCI rats and BMMSC-exos-treated rats followed by functional enrichment analyses. The effect of BMMSC-exos on ferroptosis and interleukin 17 (IL-17) pathway was evaluated in SCI rats and oxygen-glucose deprivation (OGD)-treated PC12 cells. The results showed that particles extracted from BMMSCs were exosomes that could be taken up by PC12 cells. BMMSC-exos treatment ameliorated injuries of spinal cord, suppressed the accumulation of Fe2+, malondialdehyde (MDA), and reactive oxygen species (ROS), with the elevated glutathione (GSH). Also, BMMSC-exos downregulated the expression of acyl-CoA synthetase long chain family member 4 (ACSL4) and upregulated glutathione peroxidase 4 (GPX4) and cysteine/glutamate antiporter xCT. A total of 110 DEGs were discovered and they were mainly enriched in IL-17 signaling pathway. Further in vitro and in vivo experiments showed that BMMSC-exos inactivated IL-17 pathway. BMMSC-exos promote the recovery of SCI and inhibit ferroptosis by inhibiting the IL-17 pathway, which provides BMMSC-exos as an alternative to the management of SCI.

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

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

Microfluidic Device-Based In Vivo Detection of PD-L1-Positive Small Extracellular Vesicles and Its Application for Tumor Monitoring

Liquid biopsy is of great significance in tumor early diagnosis and treatment stratification. PD-L1-positive small extracellular vesicles (PD-L1+ sEVs) are closely related to tumor growth and immunotherapy response, which are considered valuable liquid biopsy biomarkers. In contrast to conventional in vitro detection, in vivo detection has the ability to improve the detection efficiency and enable continuous or real-time dynamic monitoring. However, in vivo detection of PD-L1+ sEVs has multiple difficulties, such as high cell background, complex blood environments, and lack of a specific and stable detection method. Herein, the in vivo detection of PD-L1+ sEVs method was constructed, which efficiently separated sEVs based on the microfluidic device and quantitatively analyzed PD-L1+ sEVs by aptamer recognition and hybridization chain reaction. The concentration of PD-L1+ sEVs was continuously monitored, and significant differences at different stages of tumor as well as a correlation with tumor volume were found. Diseased and healthy individuals could also be effectively distinguished based on the concentration of PD-L1+ sEVs. The method with good stability, biocompatibility, and detection performance provided a powerful means for in vivo detection of PD-L1+ sEVs, contributing to the clinical diagnosis and treatment of tumor.

Urease-Powered Micromotors with Spatially Selective Distribution of Enzymes for Capturing and Sensing Exosomes

Enzyme-catalyzed micro/nanomotors (MNMs) exhibit tremendous potential for biological isolation and sensing, because of their biocompatibility, versatility, and ready access to biofuel. However, flow field generated by enzyme-catalyzed reactions might significantly hinder performance of surface-linked functional moieties, e.g., the binding interaction between MNMs and target cargos. Herein, we develop enzymatic micromotors with spatially selective distribution of urease to enable the independent operation of various modules and facilitate the capture and sensing of exosomes. When urease is modified into the motors' cavity, the flow field from enzyme catalysis has little effect on the exterior surface of the motors. The active motion and encapsulating urease internally result in enhancement of ∼35% and 18% in binding efficiency of target cargos, e.g., exosomes as an example here, compared to their static counterparts and moving micromotors with urease modified externally, respectively. Once exosomes are trapped, they can be transferred to a clean environment by the motors for Raman signal detection and/or identification using the surface Raman enhancement scattering (SERS) effect of coated gold nanoshell. The biocatalytic micromotors, achieving spatial separation between driving module and function module, offer considerable promise for future design of multifunctional MNMs in biomedicine and diagnostics.

Controlling the Nucleation and Growth of Salt from Bodily Fluid for Enhanced Biosensing Applications

Surface-enhanced Raman spectroscopy (SERS) represents a transformative tool in medical diagnostics, particularly for the early detection of key biomarkers such as small extracellular vesicles (sEVs). Its unparalleled sensitivity and compatibility with intricate biological samples make it an ideal candidate for revolutionizing noninvasive diagnostic methods. However, a significant challenge that mars its efficacy is the throughput limitation, primarily anchored in the prerequisite of hotspot and sEV colocalization within a minuscule range. This paper delves deep into this issue, introducing a never-attempted-before approach which harnesses the principles of crystallization-nucleation and growth. By synergistically coupling lasers with plasmonic resonances, we navigate the challenges associated with the analyte droplet drying method and the notorious coffee ring effect. Our method, rooted in a profound understanding of crystallization's materials science, exhibits the potential to significantly increase the areal density of accessible plasmonic hotspots and efficiently guide exosomes to defined regions. In doing so, we not only overcome the throughput challenge but also promise a paradigm shift in the arena of minimally invasive biosensing, ushering in advanced diagnostic capabilities for life-threatening diseases.

Plasma versus serum for extracellular vesicle (EV) isolation: A duel for reproducibility and accuracy for CNS-originating EVs biomarker analysis

Blood-derived extracellular vesicles (EVs) are a popular source of biomarkers for central nervous system (CNS) diseases, but inconsistencies in isolation and analysis hinder their clinical translation. This review summarizes recent studies that investigate the impact of different anticoagulated plasma and serum on the yield, purity, and molecular content of EVs. Specifically, the studies compare ethylenediaminetetraacetic acid (EDTA), citrate, heparin plasma, and serum and highlight the risk of contamination from platelet-derived EVs. Here, I offer practical guidelines for standardizing EV isolation and analysis, recommending the use of plasma anticoagulated with acid-citrate-dextrose (ACD) or citrate followed by EDTA and heparin, subgroup analyses for samples from different biobank repositories, and avoiding serum and plasma-to-serum transformation. Other factors like illness, age, gender, meal timing, exercise, circadian timing, and arm pressure during blood draw can alter EV signatures. Yet, how these variables interact with different anticoagulated plasma or serum samples is unclear, necessitating further research. Furthermore, whether the changes are dependent on the isolation or quantification methodology remains an area of investigation. Importantly, the perspective emphasizes the need for consistency in experimental methodologies to improve the reproducibility and clinical applicability of CNS-originating EV biomarker studies. The proposed guidelines, along with ongoing efforts to standardize blood sample handling and collection, may facilitate the development of more reliable and informative CNS-originating EV biomarkers for diagnosis, prognosis, and treatment monitoring of CNS diseases.

Self-Functionalized Superlattice Nanosensor Enables Glioblastoma Diagnosis Using Liquid Biopsy

Glioblastoma (GBM), the most aggressive and lethal brain cancer, is detected only in the advanced stage, resulting in a median survival rate of 15 months. Therefore, there is an urgent need to establish GBM diagnosis tools to identify the tumor accurately. The clinical relevance of the current liquid biopsy techniques for GBM diagnosis remains mostly undetermined, owing to the challenges posed by the blood-brain barrier (BBB) that restricts biomarkers entering the circulation, resulting in the unavailability of clinically validated circulating GBM markers. GBM-specific liquid biopsy for diagnosis and prognosis of GBM has not yet been developed. Here, we introduce extracellular vesicles of GBM cancer stem cells (GBM CSC-EVs) as a previously unattempted, stand-alone GBM diagnosis modality. As GBM CSCs are fundamental building blocks of tumor initiation and recurrence, it is desirable to investigate these reliable signals of malignancy in circulation for accurate GBM diagnosis. So far, there are no clinically validated circulating biomarkers available for GBM. Therefore, a marker-free approach was essential since conventional liquid biopsy relying on isolation methodology was not viable. Additionally, a mechanism capable of trace-level detection was crucial to detecting the rare GBM CSC-EVs from the complex environment in circulation. To break these barriers, we applied an ultrasensitive superlattice sensor, self-functionalized for surface-enhanced Raman scattering (SERS), to obtain holistic molecular profiling of GBM CSC-EVs with a marker-free approach. The superlattice sensor exhibited substantial SERS enhancement and ultralow limit of detection (LOD of attomolar 10-18 M concentration) essential for trace-level detection of invisible GBM CSC-EVs directly from patient serum (without isolation). We detected as low as 5 EVs in 5 μL of solution, achieving the lowest LOD compared to existing SERS-based studies. We have experimentally demonstrated the crucial role of the signals of GBM CSC-EVs in the precise detection of glioblastoma. This was evident from the unique molecular profiles of GBM CSC-EVs demonstrating significant variation compared to noncancer EVs and EVs of GBM cancer cells, thus adding more clarity to the current understanding of GBM CSC-EVs. Preliminary validation of our approach was undertaken with a small amount of peripheral blood (5 μL) derived from GBM patients with 100% sensitivity and 97% specificity. Identification of the signals of GBM CSC-EV in clinical sera specimens demonstrated that our technology could be used for accurate GBM detection. Our technology has the potential to improve GBM liquid biopsy, including real-time surveillance of GBM evolution in patients upon clinical validation. This demonstration of liquid biopsy with GBM CSC-EV provides an opportunity to introduce a paradigm potentially impacting the current landscape of GBM diagnosis.

Acoustofluidic lysis of cancer cells and Raman spectrum profiling

The lysis of cancer cells inside a sessile droplet was performed using traveling surface acoustic waves (SAWs) without any chemical reagents. Raman spectrum profiling was then carried out to explore detailed cell-derived data. The Rayleigh waves formed by an interdigital transducer were made to propagate along the surface of an LiNbO3 substrate. Polystyrene microparticles (PSMPs) were used to establish mechanical cell lysis effectively, and gold nanoparticles (AuNPs) were added to enhance the Raman signals from the lysed cells by SAWs. The lysis efficiency was evaluated according to the size and concentration of the PSMPs in experiments where the frequency was varied. Lysis occurred mainly by mechanical collision using PSMPs in a high-frequency domain, and the lysis efficiency was improved by increasing the application time and the energy density of the SAWs. Raman signals from the lysed cells were greatly enhanced by nanogaps formed by the AuNPs, which were evenly distributed irrespective of the SAWs through the frequency-independent behavior of the AuNPs. Finally, detailed Raman spectra of MDA-MB-231, malignant breast cancer cells, were acquired, and various organic matter-derived peaks were observed. The 95% confidence region for cells subjected to lysis was more widely distributed than that of cells not subjected to lysis. The proposed SAW platform is expected to facilitate the detection of small quantities and to be applied in biomedical applications.

Engineered extracellular vesicles-like biomimetic nanoparticles as an emerging platform for targeted cancer therapy

Nanotechnology offers the possibility of revolutionizing cancer theranostics in the new era of precision oncology. Extracellular vesicles (EVs)-like biomimetic nanoparticles (EBPs) have recently emerged as a promising platform for targeted cancer drug delivery. Compared with conventional synthetic vehicles, EBPs have several advantages, such as lower immunogenicity, longer circulation time, and better targeting capability. Studies on EBPs as cancer therapeutics are rapidly progressing from in vitro experiments to in vivo animal models and early-stage clinical trials. Here, we describe engineering strategies to further improve EBPs as effective anticancer drug carriers, including genetic manipulation of original cells, fusion with synthetic nanomaterials, and direct modification of EVs. These engineering approaches can improve the anticancer performance of EBPs, especially in terms of tumor targeting effectiveness, stealth property, drug loading capacity, and integration with other therapeutic modalities. Finally, the current obstacles and future perspectives of engineered EBPs as the next-generation delivery platform for anticancer drugs are discussed.

Exosomal delivery of cannabinoids against cancer

Exosomes are extracellular vesicles (EVs) originating from endosomes that play a role in cellular communication. These vesicles which mimic the parental cells that release them are promising candidates for targeted drug delivery and therapeutic applications against cancer because of their favorable biocompatibility, specific targeting, low toxicity, and immunogenicity. Currently, Delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD) and other cannabinoids (e.g., CBG, THCV, CBC), are being explored for their anticancer and anti-proliferative properties. Several mechanisms, including cell cycle arrest, proliferation inhibition, activation of autophagy and apoptosis, inhibition of adhesion, metastasis, and angiogenesis have been proposed for their anticancer activity. EVs could be engineered as cannabinoid delivery systems for tumor-specificity leading to superior anticancer effects. This review discusses current techniques for EV isolation from various sources, characterization and strategies to load them with cannabinoids. More extensively, we culminate information available on different sources of EVs that have anticancer activity, mechanism of action of cannabinoids against various wild type and resistant tumors and role of CBD in histone modifications and cancer epigenetics. We have also enumerated the role of EVs containing cannabinoids against various tumors and in chemotherapy induced neuropathic pain.

Recent Progress in Extracellular Vesicle-Based Carriers for Targeted Drug Delivery in Cancer Therapy

Extracellular vesicles (EVs) are small, membrane-based vesicles released by cells that play a critical role in various physiological and pathological processes. They act as vehicles for transporting a variety of endogenous cargo molecules, enabling intercellular communication. Due to their natural properties, EVs have emerged as a promising "cell-free therapy" strategy for treating various diseases, including cancer. They serve as excellent carriers for different therapeutics, including nucleic acids, proteins, small molecules, and other nanomaterials. Modifying or engineering EVs can improve the efficacy, targeting, specificity, and biocompatibility of EV-based therapeutics for cancer therapy. In this review, we comprehensively outline the biogenesis, isolation, and methodologies of EVs, as well as their biological functions. We then focus on specific applications of EVs as drug carriers in cancer therapy by citing prominent recent studies. Additionally, we discuss the opportunities and challenges for using EVs as pharmaceutical drug delivery vehicles. Ultimately, we aim to provide theoretical and technical support for the development of EV-based carriers for cancer treatment.

Regenerative Potential of Injured Spinal Cord in the Light of Epigenetic Regulation and Modulation

A spinal cord injury is a form of physical harm imposed on the spinal cord that causes disability and, in many cases, leads to permanent mammalian paralysis, which causes a disastrous global issue. Because of its non-regenerative aspect, restoring the spinal cord's role remains one of the most daunting tasks. By comparison, the remarkable regenerative ability of some regeneration-competent species, such as some Urodeles (Axolotl), Xenopus, and some teleost fishes, enables maximum functional recovery, even after complete spinal cord transection. During the last two decades of intensive research, significant progress has been made in understanding both regenerative cells' origins and the molecular signaling mechanisms underlying the regeneration and reconstruction of damaged spinal cords in regenerating organisms and mammals, respectively. Epigenetic control has gradually moved into the center stage of this research field, which has been helped by comprehensive work demonstrating that DNA methylation, histone modifications, and microRNAs are important for the regeneration of the spinal cord. In this review, we concentrate primarily on providing a comparison of the epigenetic mechanisms in spinal cord injuries between non-regenerating and regenerating species. In addition, we further discuss the epigenetic mediators that underlie the development of a regeneration-permissive environment following injury in regeneration-competent animals and how such mediators may be implicated in optimizing treatment outcomes for spinal cord injurie in higher-order mammals. Finally, we briefly discuss the role of extracellular vesicles (EVs) in the context of spinal cord injury and their potential as targets for therapeutic intervention.

A New Detection Method of Oral and Oropharyngeal Squamous Cell Carcinoma Based on Multivariate Analysis of Surface Enhanced Raman Spectra of Salivary Exosomes

Raman spectroscopy recently proved a tremendous capacity to identify disease-specific markers in various (bio)samples being a non-invasive, rapid, and reliable method for cancer detection. In this study, we first aimed to record vibrational spectra of salivary exosomes isolated from oral and oropharyngeal squamous cell carcinoma patients and healthy controls using surface enhancement Raman spectroscopy (SERS). Then, we assessed this method's capacity to discriminate between malignant and non-malignant samples by means of principal component-linear discriminant analysis (PC-LDA) and we used area under the receiver operating characteristics with illustration as the area under the curve to measure the power of salivary exosomes SERS spectra analysis to identify cancer presence. The vibrational spectra were collected on a solid plasmonic substrate developed in our group, synthesized using tangential flow filtered and concentrated silver nanoparticles, capable of generating very reproducible spectra for a whole range of bioanalytes. SERS examination identified interesting variations in the vibrational bands assigned to thiocyanate, proteins, and nucleic acids between the saliva of cancer and control groups. Chemometric analysis indicated discrimination sensitivity between the two groups up to 79.3%. The sensitivity is influenced by the spectral interval used for the multivariate analysis, being lower (75.9%) when the full-range spectra were used.

Biomarkers for parkinsonian disorders in CNS-originating EVs: promise and challenges

Extracellular vesicles (EVs), including exosomes, microvesicles, and oncosomes, are nano-sized particles enclosed by a lipid bilayer. EVs are released by virtually all eukaryotic cells and have been shown to contribute to intercellular communication by transporting proteins, lipids, and nucleic acids. In the context of neurodegenerative diseases, EVs may carry toxic, misfolded forms of amyloidogenic proteins and facilitate their spread to recipient cells in the central nervous system (CNS). CNS-originating EVs can cross the blood-brain barrier into the bloodstream and may be found in other body fluids, including saliva, tears, and urine. EVs originating in the CNS represent an attractive source of biomarkers for neurodegenerative diseases, because they contain cell- and cell state-specific biological materials. In recent years, multiple papers have reported the use of this strategy for identification and quantitation of biomarkers for neurodegenerative diseases, including Parkinson's disease and atypical parkinsonian disorders. However, certain technical issues have yet to be standardized, such as the best surface markers for isolation of cell type-specific EVs and validating the cellular origin of the EVs. Here, we review recent research using CNS-originating EVs for biomarker studies, primarily in parkinsonian disorders, highlight technical challenges, and propose strategies for overcoming them.

Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers

Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy of simultaneous detection of 6 types of early-stage cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles of exosomes using artificial intelligence in a retrospective study design. It includes classification models that recognize signal patterns of plasma exosomes to identify both their presence and tissues of origin. Using 520 test samples, our system identified cancer presence with an area under the curve value of 0.970. Moreover, the system classified the tumor organ type of 278 early-stage cancer patients with a mean area under the curve of 0.945. The final integrated decision model showed a sensitivity of 90.2% at a specificity of 94.4% while predicting the tumor organ of 72% of positive patients. Since our method utilizes a non-specific analysis of Raman signatures, its diagnostic scope could potentially be expanded to include other diseases.

The Potential Use of Exosomes in Anti-Cancer Effect Induced by Polarized Macrophages

The rapid development of aberrant cells outgrowing their normal bounds, which can subsequently infect other body parts and spread to other organs-a process known as metastasis-is one of the significant characteristics of cancer. The main reason why cancer patients die is because of widespread metastases. This abnormal cell proliferation varies in cancers of over a hundred types, and their response to treatment can vary substantially. Several anti-cancer drugs have been discovered to treat various tumors, yet they still have harmful side-effects. Finding novel, highly efficient targeted therapies based on modifications in the molecular biology of tumor cells is essential to reduce the indiscriminate destruction of healthy cells. Exosomes, an extracellular vesicle, are promising as a drug carrier for cancer therapy due to their good tolerance in the body. In addition, the tumor microenvironment is a potential target to regulate in cancer treatment. Therefore, macrophages are polarized toward M1 and M2 phenotypes, which are involved in cancer proliferation and are malignant. It is evident from recent studies that controlled macrophage polarization might contribute to cancer treatment, by the direct way of using miRNA. This review provides an insight into the potential use of exosomes to develop an 'indirect', more natural, and harmless cancer treatment through regulating macrophage polarization.

Label-Free Identification of Exosomes using Raman Spectroscopy and Machine Learning

Exosomes, nano-sized extracellular vesicles (EVs) secreted from cells, carry various cargo molecules reflecting their cells of origin. As EV content, structure, and size are highly heterogeneous, their classification via cargo molecules by determining their origin is challenging. Here, a method is presented combining surface-enhanced Raman spectroscopy (SERS) with machine learning algorithms to employ the classification of EVs derived from five different cell lines to reveal their cellular origins. Using an artificial neural network algorithm, it is shown that the label-free Raman spectroscopy method's prediction ratio correlates with the ratio of HT-1080 exosomes in the mixture. This machine learning-assisted SERS method enables a new direction through label-free investigation of EV preparations by differentiating cancer cell-derived exosomes from those of healthy. This approach will potentially open up new avenues of research for early detection and monitoring of various diseases, including cancer.

From Conventional to Microfluidic: Progress in Extracellular Vesicle Separation and Individual Characterization

Extracellular vesicles (EVs) are nanoscale membrane vesicles, which contain a wide variety of cargo such as proteins, miRNAs, and lipids. A growing body of evidence suggests that EVs are promising biomarkers for disease diagnosis and therapeutic strategies. Although the excellent clinical value, their use in personalized healthcare practice is not yet feasible due to their highly heterogeneous nature. Taking the difficulty of isolation and the small size of EVs into account, the characterization of EVs at a single-particle level is both imperative and challenging. In a bid to address this critical point, more research has been directed into a microfluidic platform because of its inherent advantages in sensitivity, specificity, and throughput. This review discusses the biogenesis and heterogeneity of EVs and takes a broad view of state-of-the-art advances in microfluidics-based EV research, including not only EV separation, but also the single EV characterization of biophysical detection and biochemical analysis. To highlight the advantages of microfluidic techniques, conventional technologies are included for comparison. The current status of artificial intelligence (AI) for single EV characterization is then presented. Furthermore, the challenges and prospects of microfluidics and its combination with AI applications in single EV characterization are also discussed. In the foreseeable future, recent breakthroughs in microfluidic platforms are expected to pave the way for single EV analysis and improve applications for precision medicine.

Shape-Preserving Transformation of Electrodeposited Macroporous Microparticles for Single-Particle SERS Applications

Microparticles composed of bicontinuous and ordered macropores are important in many applications. However, rational integration of ordered macropores into a single crystalline microparticle remains a challenge. Here, we report a method to prepare three-dimensionally ordered macroporous (3DOM) Ag₇O₈NO₃ micropyramids via selectively cementing the colloidal crystal templates via an electrochemical method and their shape-preserving transformation into 3DOM Ag micropryamids formed by Ag nanoparticles via a chemical reduction process. The interconnected macropores facilitated the transportation and enrichment of the analyte molecules into the 3DOM Ag micropyramids. The dense Ag nanoparticles on the skeletons of the 3DOM Ag micropyramids provided strong electromagnetic fields. Taken together, a 3DOM Ag micropyramid as a kind of single-particle surface-enhanced Raman scattering (SERS) sensing substrate demonstrated high SERS sensitivity and outstanding SERS signal reproducibility. We explored the application of 3DOM Ag micropyramids in SERS detection of biomolecules (e.g., adenosine, adenine, hemoglobin bovine, and lysozyme) and proved their potentials in distinguishing exosomes from tumor and non-tumor cells. The method can be extended to prepared 3DOM structures of other materials with promising applications in sensing, separation, and catalytic fields.

Analyzing bronchoalveolar fluid derived small extracellular vesicles using single-vesicle SERS for non-small cell lung cancer detection

An emerging body of research by biologists and clinicians has demonstrated the clinical application of small extracellular vesicles (sEVs, also commonly referred to as exosomes) as biomarkers for cancer detections. sEVs isolated from various body fluids such as blood, saliva, urine, and cerebrospinal fluid have been used for biomarker discoveries with highly encouraging outcomes. Among the biomarkers discovered are those responsible for multiple cancer types and immune responses. These biomarkers are recapitulated from the tumor microenvironments. Yet, despite numerous discussions of sEVs in scientific literature, sEV-based biomarkers have so far played only a minor role for cancer diagnostics in the clinical setting, notably less so than other techniques such as imaging and biopsy. In this paper, we report the results of a pilot study (n = 10 from each of the patient and the control group) using bronchoalveolar lavage fluid to determine the presence of sEVs related to non-small cell lung cancer in twenty clinical samples examined using surface enhanced Raman spectroscopy (SERS).

Exosomes in pathogenesis, diagnosis, and therapy of ischemic stroke

Ischemic stroke is one of the major contributors to death and disability worldwide. Thus, there is an urgent need to develop early brain tissue perfusion therapies following acute stroke and to enhance functional recovery in stroke survivors. The morbidity, therapy, and recovery processes are highly orchestrated interactions involving the brain with other tissues. Exosomes are natural and ideal mediators of intercellular information transfer and recognized as biomarkers for disease diagnosis and prognosis. Changes in exosome contents express throughout the physiological process. Accumulating evidence demonstrates the use of exosomes in exploring unknown cellular and molecular mechanisms of intercellular communication and organ homeostasis and indicates their potential role in ischemic stroke. Inspired by the unique properties of exosomes, this review focuses on the communication, diagnosis, and therapeutic role of various derived exosomes, and their development and challenges for the treatment of cerebral ischemic stroke.

Nanomaterials assisted exosomes isolation and analysis towards liquid biopsy

Exosomes has attracted tremendous research interests as they are emerging as a new paradigm of liquid biopsy. Although the concentration of exosomes in blood is relatively abundant, there still exists various vesicle-like nanoparticles, such as microvesicles, apoptotic bodies. It's an urgent need to isolate and enrich exosomes from the complex contaminants in biofluid samples. Moreover, the expressing level of exosomal biomarkers varies a lot, which make the sensitive molecular detection of exosomes in high demand. Unfortunately, the efficient isolation and sensitive molecular quantification of exosomes is still a major obstacle hindering the further development and clinical application of exosome-based liquid biopsy. Nanomaterials, with unique physiochemical properties, have been widely used in biosensing and analysis aspects, thus they are thought as powerful tools for effective purification and molecular analysis of exosomes. In this review, we summarized the most recent progresses in nanomaterials assisted exosome isolation and analysis towards liquid biopsy. On the one hand, nanomaterials can be used as capture substrates to afford large binding area and specific affinity to exosomes. Meanwhile, nanomaterials can also be served as promising signal transducers and amplifiers for molecular detection of exosomes. Furthermore, we also pointed out several potential and promising research directions in nanomaterials assisted exosome analysis. It's envisioned that this review will give the audience a complete outline of nanomaterials in exosome study, and further promote the intersection of nanotechnology and bio-analysis.

Recent progress in surface-enhanced Raman spectroscopy-based biosensors for the detection of extracellular vesicles

Extracellular vesicles (EVs) are a type of mediator that enables intercellular communication. Moreover, EVs carry critical molecular information from parental cells, making them ideal biomarkers for clinical screening and diagnosis. Currently, several sensing technologies have been established to sensitively detect EVs. Among them, surface-enhanced Raman spectroscopy (SERS) has become a powerful analytical tool with high sensitivity and low detection limits. In this review, we first cover the biological characteristics of EVs and the principle of SERS amplification. Then, we describe the recent progress in SERS technology applied to detect EVs, including direct label-free methods and indirect labeling strategies, in which substrate fabrication and nanoprobe assembly were emphasized. Furthermore, SERS technology could also be used to characterize or monitor the behavior of programmable EVs. Finally, we discuss the prospects and issues to be addressed for the development of SERS technology for EV analysis.

Emerging SERS biosensors for the analysis of cells and extracellular vesicles

Cells and their derived extracellular vesicles (EVs) or exosomes contain unique molecular signatures that could be used as biomarkers for the detection of severe diseases such as cancer, as well as monitoring the treatment response. Revealing these molecular signatures requires developing non-invasive ultrasensitive tools to enable single molecule/cell-level detection using a small volume of sample with low signal-to-noise ratio background and multiplex capability. Surface-enhanced Raman scattering (SERS) can address the current limitations in studying cells and EVs through two main mechanisms: plasmon-enhanced electric field (the so-called electromagnetic mechanism (EM)), and chemical mechanism (CM). In this review, we first highlight these two SERS mechanisms and then discuss the nanomaterials that have been used to develop SERS biosensors based on each of the aforementioned mechanisms as well as the combination of these two mechanisms in order to take advantage of the synergic effect between electromagnetic enhancement and chemical enhancement. Then, we review the recent advances in designing label-aided and label-free SERS biosensors in both colloidal and planar systems to investigate the surface biomarkers on cancer cells and their derived EVs. Finally, we discuss perspectives of emerging SERS biosensors in future biomedical applications. We believe this review article will thus appeal to researchers in the field of nanobiotechnology including material sciences, biosensors, and biomedical fields.

Salivary Exosomal MicroRNA-486-5p and MicroRNA-10b-5p in Oral and Oropharyngeal Squamous Cell Carcinoma

Background and Objectives: The research aimed at evaluating the capacity of salivary exosomal miR-10b-5p and miR-486-5p for oral and oropharyngeal cancer detection. Materials and Methods: The saliva samples were harvested from histopathological diagnosed oral and oropharyngeal squamous cell carcinoma patients and healthy volunteer subjects. The exosomes were isolated by differential ultracentrifugation and quantified by Nano Track Analysis. The microRNAs were extracted and quantified from salivary exosomes by quantitative Real-Time Polymerase Chain Reaction. Results: This research comprised fifty participants. When compared to healthy controls, salivary exosomal miR-486-5p was elevated and miR-10b-5p was reduced in oral and oropharyngeal squamous cell carcinoma. Moreover, miR-486-5p had a high expression level in stage II of cancer in comparison to the other cancer stages. The cancer samples presented an increased exosome dimension compared to the control samples. Conclusions: Salivary exosomal miR-10b-5p and miR-486-5p have an altered expression in oral and oropharyngeal cancer.

The Signaling Pathways Induced by Exosomes in Promoting Diabetic Wound Healing: A Mini-Review

Impaired healing of diabetic wounds harms patients' quality of life and even leads to disability and death, which is an urgent issue to be solved clinically. Despite the great progress that has been achieved, it remains a worldwide challenge to develop effective therapeutic treatments for diabetic wounds. Recently, exosomes have attracted special attention because they can be involved in immune response, antigen presentation, cell migration, cell differentiation, tumor invasion and other processes. Meanwhile, exosomes have been proven to hold great potential in the treatment of diabetic wounds. Mechanistic studies of exosomes based on signaling pathways could not only help to uncover the mechanisms by which exosomes promote diabetic wound healing but could also provide a theoretical basis for the clinical application of exosomes. Herein, our mini-review aims to summarize the progress of research on the use of various exosomes derived from different cell types to promote diabetic wound healing, with a focus on the classical signaling pathways, including PI3K/Akt, Wnt, NF-κB, MAPK, Notch, Nrf2, HIF-1α/VEGF and TGF-β/Smad. The results show that exosomes could regulate these signaling pathways to down-regulate inflammation, reduce oxidative stress, increase angiogenesis, promote fibroblast proliferation, induce re-epithelization and inhibit scar formation, making exosomes attractive candidates for the treatment of diabetic wounds.

Artificial Intelligent Label-Free SERS Profiling of Serum Exosomes for Breast Cancer Diagnosis and Postoperative Assessment

Breast cancer subtypes have important implications of treatment responses and clinical outcomes. Exosomes have been considered as promising biomarkers for liquid biopsies, but the utility of exosomes for accurate diagnosis of distinct breast cancer subtypes is a grand challenge due to the difficulty in uncovering the subtle compositional difference in complex clinical settings. Herein, we report an artificial intelligent surface-enhanced Raman spectroscopy (SERS) strategy for label-free spectroscopic analysis of serum exosomes, allowing for accurate diagnosis of breast cancer and assessment of surgical outcomes. Our deep learning algorithm trained with SERS spectra of cancer cell-derived exosomes is demonstrated with a 100% prediction accuracy for human patients with different breast cancer subtypes who do not undergo surgery using SERS spectra of serum exosomes. Furthermore, when combined with similarity analysis by principal component analysis, our approach is able to evaluate the surgical outcomes of breast cancer of distinct molecular subtypes.

Small Extracellular Vesicles Secreted by Nigrostriatal Astrocytes Rescue Cell Death and Preserve Mitochondrial Function in Parkinson's Disease

Extracellular vesicles (EVs) are emerging as powerful players in cell-to-cell communication both in healthy and diseased brain. In Parkinson's disease (PD)-characterized by selective dopaminergic neuron death in ventral midbrain (VMB) and degeneration of their terminals in striatum (STR)-astrocytes exert dual harmful/protective functions, with mechanisms not fully elucidated. Here, this study shows that astrocytes from the VMB-, STR-, and VMB/STR-depleted brains release a population of small EVs  in a region-specific manner. Interestingly, VMB-astrocytes secreted the highest rate of EVs, which is further exclusively increased in response to CCL3, a chemokine that promotes robust dopaminergic neuroprotection in different PD models. The neuroprotective potential of nigrostriatal astrocyte-EVs is investigated in differentiated versus undifferentiated SH-SY5Y cells exposed to oxidative stress and mitochondrial toxicity. EVs from both VMB- and STR-astrocytes counteract H2 O2 -induced caspase-3 activation specifically in differentiated cells, with EVs from CCL3-treated astrocytes showing a higher protective effect. High resolution respirometry further reveals that nigrostriatal astrocyte-EVs rescue neuronal mitochondrial complex I function impaired by the neurotoxin MPP+ . Notably, only EVs from VMB-astrocyte fully restore ATP production, again specifically in differentiated SH-SY5Y. These results highlight a regional diversity in the nigrostriatal system for the secretion and activities of astrocyte-EVs, with neuroprotective implications for PD.

Gold Nanopyramid Arrays for Non-Invasive Surface-Enhanced Raman Spectroscopy-Based Gastric Cancer Detection via sEVs

Gastric cancer (GC) is one of the most common and lethal types of cancer affecting over one million people, leading to 768,793 deaths globally in 2020 alone. The key for improving the survival rate lies in reliable screening and early diagnosis. Existing techniques including barium-meal gastric photofluorography and upper endoscopy can be costly and time-consuming and are thus impractical for population screening. We look instead for small extracellular vesicles (sEVs, currently also referred as exosomes) sized ⌀ 30-150 nm as a candidate. sEVs have attracted a significantly higher level of attention during the past decade or two because of their potentials in disease diagnoses and therapeutics. Here, we report that the composition information of the collective Raman-active bonds inside sEVs of human donors obtained by surface-enhanced Raman spectroscopy (SERS) holds the potential for non-invasive GC detection. SERS was triggered by the substrate of gold nanopyramid arrays we developed previously. A machine learning-based spectral feature analysis algorithm was developed for objectively distinguishing the cancer-derived sEVs from those of the non-cancer sub-population. sEVs from the tissue, blood, and saliva of GC patients and non-GC participants were collected (n = 15 each) and analyzed. The algorithm prediction accuracies were reportedly 90, 85, and 72%. "Leave-a-pair-of-samples out" validation was further performed to test the clinical potential. The area under the curve of each receiver operating characteristic curve was 0.96, 0.91, and 0.65 in tissue, blood, and saliva, respectively. In addition, by comparing the SERS fingerprints of individual vesicles, we provided a possible way of tracing the biogenesis pathways of patient-specific sEVs from tissue to blood to saliva. The methodology involved in this study is expected to be amenable for non-invasive detection of diseases other than GC.

Quantification of Serum Exosome Biomarkers Using 3D Nanoporous Gold and Spectrophotometry

Tumor-derived exosomes may provide biomarkers for cancer treatment. Using sputtering technology, an affinity-based device to capture exosomes was developed using nanoporous substrate (NPG)-coated silicon microscopy. Immunology-based techniques detect and purify exosomes using gold coating with a specific antigen. Inverted fluorescent microscopy was used to detect target exosomes quantitatively utilizing fluorescent nanospheres as the label. We quantified the expression of CD63 surface protein markers on exosomes from conditioned culture media of breast cancer cells. The exosomes that targeted specific proteins with controls were statistically analyzed and compared to those that targeted non-specific proteins. Results from SEM showed that the exosomes were circular, between 30 and 150 nanometers in size. The porous gold substrates captured more exosomes than the nonporous substrates. Nitric acid treatments at different times resulted in a variety of pore sizes. Despite the increase in the size of the pores, the number of exosomes found in the porous gold substrate treated for 10 min nearly doubled compared to the one treated for 5 min. In this work, a fluorescence biosensor was developed to detect breast cancer exosomes using nanoporous gold substrates (NPG). Assay and model exosomes of specific breast cancer cells showed that exosomes exhibit diagnostic surface protein markers, reflecting the protein profile of their parent cells. Furthermore, the specific binding between the exosome surface antibodies and the targets identified the CD63 biomarkers on the exosome, suggesting these markers' diagnostic potential. This study can accelerate exosome research in determining tumor-related exosomes and develop novel cancer diagnostic methods.

Phase 2 of extracellular RNA communication consortium charts next-generation approaches for extracellular RNA research

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

Immune-Cell-Derived Exosomes for Cancer Therapy

Exosomes are a type of extracellular vesicles secreted by cells in normal or pathological conditions for cell-cell communication. With immunomodulatory characteristics and potential therapeutic properties, immune-cell-derived exosomes play an important role in cancer therapy. They express various antigens on their surface, which can be employed for antigen presentation, immunological activation, and metabolic regulation, leading to the killing of cancerous cells. In addition, immune-cell-derived exosomes have received extensive attention as a drug delivery platform in effective antitumor therapy due to their excellent biocompatibility, low immunogenicity, and high loading capacity. In this review, the biological and therapeutic characteristics of immune-cell-derived exosomes are comprehensively outlined. The antitumor mechanism of exosomes secreted by immune cells, including macrophages, dendritic cells, T cells, B cells, and natural killer cells, are systematically summarized. Moreover, the applications of immune-cell-derived exosomes as nanocarriers to transport antitumor agents (chemotherapeutic drugs, genes, proteins, etc.) are discussed. More importantly, the existing challenges of immune-cell-derived exosomes are pointed out, and their antitumor potentials are also discussed.