Accurate Cancer Diagnosis and Stage Monitoring Enabled by Comprehensive Profiling of Different Types of Exosomal Biomarkers: Surface Proteins and miRNAs

Fluorescence Sensing of Eclampsia Biomarkers via the Immunosorbent Atom Transfer Radical Polymerization Assay

Accurate and quantitative detection of pre-eclampsia markers is crucial in reducing pregnancy mortality rates. This study introduces a novel approach utilizing a fluorescent biosensor by the immunosorbent atom transfer radical polymerization (immuno-ATRP) assay to detect the pre-eclampsia protein marker CD81. The critical step used in this sensor is the novel signal amplification strategy of fluorescein polymerization mediated by ferritin-enhanced controlled radical polymerization, which combines with a traditional enzyme-linked immunosorbent assay (ELISA) to further reduce the detection limit of the CD81 protein concentration. The fluorescence intensity was linear versus logarithmic CD81 protein concentration from 0.1 to 10,000 pg mL-1, and the detection limit was 0.067 pg mL-1. Surprisingly, in 30% normal human serum (NHS), the sensor can also detect target protein over 0.1-10,000 pg mL-1, with 0.083 pg mL-1 for the detection limit. Moreover, the proposed biosensor is designed to be cost-effective, making it accessible, particularly in resource-limited settings where expensive detection techniques may not be available. The affordability of this method enables widespread screening and monitoring of preeclampsia, ultimately benefiting many pregnant women by improving their healthcare outcomes. In short, developing of a low-cost and susceptible direct detection method for preeclampsia protein markers, such as CD81, through the use of the immuno-ATRP assay, has significant implications for reducing pregnancy mortality. This method holds promise for early detection, precise treatment, and improved management of preeclampsia, thereby contributing to better maternal and fetal health.

In Situ Detection of Nucleic Acids in Extracellular Vesicles via Membrane Fusion

Extracellular vesicles (EVs) carry diverse biomolecules (e. g., nucleic acids, proteins) for intercellular communication, serving as important markers for diseases. Analyzing nucleic acids derived from EVs enables non-invasive disease diagnosis and prognosis evaluation. Membrane fusion, a fundamental cellular process wherein two lipid membranes merge, facilitates cell communication and cargo transport. Building on this natural phenomenon, recent years have witnessed the emergence of membrane fusion-based strategies for the detection of nucleic acids within EVs. These strategies entail the encapsulation of detection probes within either artificial or natural vesicles, followed by the induction of membrane fusion with EVs to deliver probes. This innovative approach not only enables in situ detection of nucleic acids within EVs but also ensures the maintenance of structural integrity of EVs, thus preventing nucleic acid degradation and minimizing the interference from free nucleic acids. This concept categorizes approaches into universal and targeted membrane fusion strategies, and discusses their application potential, and challenges and future prospects.

Efficient EVs separation and detection by an alumina-nanochannel-array-membrane integrated microfluidic chip and an antibody barcode biochip

BACKGROUND

Small endosome-derived lipid nanovesicles (30-200 nm) are actively secreted by living cells and serve as pivotal biomarkers for early cancer diagnosis. However, the study of extracellular vesicles (EVs) requires isolation and purification from various body fluids. Although traditional EVs isolation and detection technologies are mature, they usually require large amount of sample, consumes long-time, and have relatively low-throughput. How to efficiently isolate, purify and detect these structurally specific EVs from body fluids with high-throughput remains a great challenge in in vitro diagnostics and clinical research.

RESULTS

Herein, we suggest a nanosized microfluidic device for efficient and economical EVs filtration based on an alumina nanochannel array membrane. We evaluated the filtration device performance of alumina membranes with different diameters and found that an optimized chamber array with a hydrophilic-treated channel diameter of 90 nm could realize a filtration efficiency of up to 82% without any assistance from chemical or physical separation methods. Importantly, by integrating meticulously designed multichannel microfluidic biochips, EVs can be captured in-situ and monitored by antibody barcode biochip. The proposed filtration chip together with the high-throughput detection chip were capable of filtration of a few tens of μL samples and recognition of different phonotypes. The practical filtration and detection of EVs from clinical samples demonstrated the high performance of the device.

SIGNIFICANT

Overall, this work provides a cost-effective, highly efficient and automated EVs filtration chip and detection dual-function integrated chip platform, which can directly separate EVs from serum or cerebrospinal fluid with an efficiency of 82% and conduct in-situ detection. This small fluidic device can provide a powerful tool for highly efficient identifying and analyzing EVs, presenting great application potential in clinical detection.

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.

DNA-Based Nanomaterials for Analysis of Extracellular Vesicles

Extracellular vesicles (EVs) are cell-derived nanovesicles comprising a myriad of molecular cargo such as proteins and nucleic acids, playing essential roles in intercellular communication and physiological and pathological processes. EVs have received substantial attention as noninvasive biomarkers for disease diagnosis and prognosis. Owing to their ability to recognize protein and nucleic acid targets, DNA-based nanomaterials with excellent programmability and modifiability provide a promising tool for the sensitive and accurate detection of molecular cargo carried by EVs. In this perspective, recent advancements in EV analysis using a variety of DNA-based nanomaterials are summarized, which can be broadly classified into three categories: linear DNA probes, DNA nanostructures, and hybrid DNA nanomaterials. The design, construction, advantages, and disadvantages of different types of DNA nanomaterials, as well as their performance for detecting EVs are reviewed. The challenges and opportunities in the field of EV analysis by DNA nanomaterials are also discussed.

Exosomal non-coding RNA: A new frontier in diagnosing and treating pancreatic cancer: A review

Pancreatic cancer is the most fatal malignancy worldwide. Once diagnosed, most patients are already at an advanced stage because of their highly heterogeneous, drug-resistant, and metastatic nature and the lack of effective diagnostic markers. Recently, the study of proliferation, metastasis, and drug resistance mechanisms in pancreatic cancer and the search for useful diagnostic markers have posed significant challenges to the scientific community. Exosomes carry various biomolecules (DNA, non-coding RNAs (ncRNAs), proteins, and lipids) that mediate communication between tumors and other cells. ncRNAs can be transported through exosomes to numerous relevant receptor cells and regulate local epithelial-mesenchymal transition (EMT) in tumor tissue, proliferation, drug resistance, and the establishment of pre-metastatic ecological niches in distant organs. In summary, exosomal ncRNAs promote tumor cell proliferation, invasion, and metastasis through multiple EMT, immunosuppression, angiogenesis, and extracellular matrix remodeling pathways. Moreover, we discuss the significant therapeutic significance of exosomal ncRNAs as PC biomarkers.

Deep Learning Promotes Profiling of Multiple miRNAs in Single Extracellular Vesicles for Cancer Diagnosis

Extracellular vesicle microRNAs (EV miRNAs) are critical noninvasive biomarkers for early cancer diagnosis. However, accurate cancer diagnosis based on bulk analysis is hindered by the heterogeneity among EVs. Herein, we report an approach for profiling single-EV multi-miRNA signatures by combining total internal reflection fluorescence (TIRF) imaging with a deep learning (DL) algorithm for the first time. This innovative technique allows for the precise characterization of EV miRNAs at the single-vesicle level, overcoming the challenges posed by EV heterogeneity. TIRF with high resolution and a signal-to-noise ratio can simultaneously detect multi-miRNAs in situ in individual EVs. DL algorithm avoids complicated and inaccurate artificial feature extraction, achieving automated high-resolution image analysis. Using this approach, we reveal that the main variation of EVs from 5 cancer cells and normal plasma is the triple-positive EV subpopulation, and the classification accuracy of single triple-positive EVs from 6 sources can reach above 95%. In the clinical cohort, 20 patients (5 lung cancer, 5 breast cancer, 5 cervical cancer, and 5 colon cancer) and 5 healthy controls are predicted with an overall accuracy of 100%. This single-EV strategy provides new opportunities for exploring more specific EV biomarkers to achieve cancer diagnosis and classification.

Acoustic separation and concentration of exosomes for nucleotide detection: ASCENDx

Efficient isolation and analysis of exosomal biomarkers hold transformative potential in biomedical applications. However, current methods are prone to contamination and require costly consumables, expensive equipment, and skilled personnel. Here, we introduce an innovative spaceship-like disc that allows Acoustic Separation and Concentration of Exosomes and Nucleotide Detection: ASCENDx. We created ASCENDx to use acoustically driven disc rotation on a spinning droplet to generate swift separation and concentration of exosomes from patient plasma samples. Integrated plasmonic nanostars on the ASCENDx disc enable label-free detection of enriched exosomes via surface-enhanced Raman scattering. Direct detection of circulating exosomal microRNA biomarkers from patient plasma samples by the ASCENDx platform facilitated a diagnostic assay for colorectal cancer with 95.8% sensitivity and 100% specificity. ASCENDx overcomes existing limitations in exosome-based molecular diagnostics and holds a powerful position for future biomedical research, precision medicine, and point-of-care medical diagnostics.

Diagnostic plasma small extracellular vesicles miRNA signatures for pancreatic cancer using machine learning methods

BACKGROUND

Identifying biomarkers may lead to easier detection and a better understanding of pathogenesis of pancreatic ductal adenocarcinoma (PDAC).

METHODS

Plasma small extracellular vesicles (sEV) from 106 participants, including 20 healthy controls (HC), 12 chronic pancreatitis (CP) patients, 12 benign pancreatic tumour (BPT) patients, and 58 PDAC patients, were profiled for microRNA (miRNA) sequencing. Three machine learning methods were applied to establish and evaluate the diagnostic model.

RESULTS

The plasma sEV miRNA diagnostic signature (d-signature) selected using the three machine learning methods could distinguish PDAC patients from non-PDAC individuals, HC, and benign pancreatic disease (BPD, CP plus BPT) both in training and validation cohort. Combining the d-signature with carbohydrate antigen 19-9 (CA19-9) performed better than with each model alone. Plasma sEV miR-664a-3p was selected by all methods and used to predict PDAC diagnosis with high accuracy combined with CA19-9. Plasma sEV miR-664a-3p was significantly positively associated with the presence of vascular invasion, lower surgery ratio, and poor differentiation. MiR-664a-3p was mainly distributed in the PDAC cancer stroma, including fibers and vessels, and was accompanied by VEGFA expression. Overexpression of miR-664a-3p could promote the epithelial-mesenchymal transition (EMT) and angiogenesis.

CONCLUSION

In conclusion, our study demonstrated the potential utility of the sEV-miRNA d-signature in the diagnosis of PDAC via machine learning methods. A novel sEV biomarker, miR-664a-3p, was identified for the diagnosis of PDAC. It can also potentially promote angiogenesis and metastasis, provide insight into PDAC pathogenesis, and reveal novel regulators of this disease.

A Magnetically Driven Tandem Chip Enables Rapid Isolation and Multiplexed Profiling of Extracellular Vesicles

The protein phenotypes of extracellular vesicles (EVs) have emerged as promising biomarkers for cancer diagnosis and treatment monitoring. However, the technical challenges in rapid isolation and multiplexed molecular detection of EVs have limited their clinical practice. Herein, we developed a magnetically driven tandem chip to achieve streamlined rapid isolation and multiplexed profiling of surface protein biomarkers of EVs. Driven by magnetic force, the magnetic nanomixers not only act as tiny stir bars to promote mass transfer and enhance reaction efficiency of EVs, but also transport on communicating vessels of the tandem chip continuously and expedite the assay workflow. We designed cyclic surface enhancement of Raman scattering (SERS) tags to bind with target EVs and then release them by exonuclease I, eliminating steric hindrance and amplifying the SERS signal of multiple protein biomarkers on EVs. Due to the excellent assay performance, six breast cancer biomarkers were detected simultaneously on EVs using only 10 μL plasma within 1.5 h. The unweighted SUM signature offers great accuracy in discriminating breast cancer patients from healthy donors. Overall, the dynamic magnetic driving tandem chip offers a new avenue to advance the clinical application of EV-based liquid biopsy.

Precision cardiac targeting: empowering curcumin therapy through smart exosome-mediated drug delivery in myocardial infarction

Nanoparticle-mediated drug delivery has emerged as a highly promising and effective therapeutic approach for addressing myocardial infarction. However, clinical translation tends to be a failure due to low cardiac retention as well as liver and spleen entrapment in previous therapies. Herein, we report a two-step exosome delivery system, which precludes internalization by the mononuclear phagocyte system before the delivery of therapeutic cardiac targeting exosomes (ExoCTP). Importantly, curcumin released by ExoCTP diminishes reactive oxygen species over-accumulation in ischemic myocardium, as well as serum levels of lactate dehydrogenase, malonyldialdehyde, superoxide dismutase and glutathione, indicating better antioxidant capacity than free curcumin. Finally, our strategy was proven to greatly potentiate the delivery and therapeutic efficacy of curcumin without systemic toxicity. Taken together, our smart exosome-mediated drug delivery strategy can serve either as therapeutics alone or in combination with other drugs for effective heart targeting and subsequent wound healing.

Localized Imaging of Programmed Death-Ligand 1 on Individual Tumor-Derived Extracellular Vesicles for Prediction of Immunotherapy Response

Programmed death-ligand 1 (PD-L1) on tumor-derived small extracellular vesicles (EVs) is a biomarker for prediction of the immunotherapy response. However, conventional bulk measurement can hardly analyze the expression of PD-L1 on individual tumor-derived EVs. Herein, a method for localized imaging of tumor-derived individual EVs PD-L1 (LITIE) is developed. In this assay, EVs in plasma were directly captured on a biochip. Then the liposome-mediated membrane fusion strategy was used to image miR-21 in EVs to discriminate miR-21-positive EVs from the whole EVs populations. Subsequently, the primer exchange reaction (PER) is applied to generate localized and amplified fluorescent signals for imaging PD-L1 on identified tumor-derived EVs. When applied in clinical sample tests, the LITIE assay could effectively distinguish breast cancer patients from healthy donors or patients with benign tumors. Interestingly, in a mice melanoma model, the LITIE assay showed the ability to predict immunotherapy response even before drug treatment. Thus, we think the strategy of measuring individual tumor-derived EVs PD-L1 could serve as an alternative way for screening clinical responders suitable for immunotherapy.

Asymmetrically split DNAzyme-based colorimetric and electrochemical dual-modal biosensor for detection of breast cancer exosomal surface proteins

Exosomal surface proteins are potentially useful for breast cancer diagnosis and awareness of risk. However, some detection techniques involving complex operations and expensive instrumentation are limited to advance to clinical applications. To solve this problem, we develop a dual-modal sensor combining naked-eye detection and electrochemical assay of exosomal surface proteins from breast cancer. Most of existing sensors rely on aptamers recognizing exosomes and generating amplified signals at the same time, which require well-designed aptamer probes to avoid difficulties in identifying exosomes. In our work, aptamers not bound by the exosomes can serve as complete templates to induce formation of G quadruplexes. The peroxidase activity of the G-quadruplex/hemin DNAzyme catalyze substrates can generate both color and electrochemical signals. The developed dual-modal sensor offers a remarkable capability to differentiate nonmetastatic, metastatic breast cancer patients, and healthy individuals through the analysis of exosomal surface proteins. The sensor's distinctive features, including its universality, simplicity, and cost-effectiveness, position it as a promising diagnostic tool in breast cancer research and clinical practice.

Recent progress in quantitative technologies for the analysis of cancer-related exosome proteins

Exosomes are a kind of extracellular vesicles, which play a significant role in intercellular communication and molecular exchange. Cancer-derived exosomes are potential and ideal biomarkers for the early diagnosis and treatment monitoring of cancers because of their abundant biological information and contribution to the interaction between cancer cells and the tumor microenvironment. However, there are a number of drawbacks, such as low sensitivity and tedious steps, in conventional detection techniques. Furthermore, exosome quantification is not enough to accurately distinguish cancer patients from healthy individuals. Therefore, developing efficient, accurate, and inexpensive exosome surface protein analysis techniques is necessary and critical. In recent years, a considerable number of researchers have presented novel detection strategies in this field. This review summarizes the recent progress in quantitative technologies for the analysis of cancer-related exosome proteins, mainly including the detection methods based on aptamers, nanomaterials, and antibodies, discusses a roadmap for future developments, and aims to offer an innovative perspective of exosome research.

Accurate and Convenient Lung Cancer Diagnosis through Detection of Extracellular Vesicle Membrane Proteins via Förster Resonance Energy Transfer

Tumor-derived extracellular vesicles (EVs) are promising to monitor early stage cancer. Unfortunately, isolating and analyzing EVs from a patient's liquid biopsy are challenging. For this, we devised an EV membrane proteins detection system (EV-MPDS) based on Förster resonance energy transfer (FRET) signals between aptamer quantum dots and AIEgen dye, which eliminated the EV extraction and purification to conveniently diagnose lung cancer. In a cohort of 80 clinical samples, this system showed enhanced accuracy (100% versus 65%) and sensitivity (100% versus 55%) in cancer diagnosis as compared to the ELISA detection method. Improved accuracy of early screening (from 96.4% to 100%) was achieved by comprehensively profiling five biomarkers using a machine learning analysis system. FRET-based tumor EV-MPDS is thus an isolation-free, low-volume (1 μL), and highly accurate approach, providing the potential to aid lung cancer diagnosis and early screening.

Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential

Major depressive disorder (MDD) is a chronic, generally episodic and debilitating disease that affects an estimated 300 million people worldwide, but its pathogenesis is poorly understood. The heritability estimate of MDD is 30-40%, suggesting that genetics alone do not account for most of the risk of major depression. Another factor known to associate with MDD involves environmental stressors such as childhood adversity and recent life stress. Recent studies have emerged to show that the biological impact of environmental factors in MDD and other stress-related disorders is mediated by a variety of epigenetic modifications. These epigenetic modification alterations contribute to abnormal neuroendocrine responses, neuroplasticity impairment, neurotransmission and neuroglia dysfunction, which are involved in the pathophysiology of MDD. Furthermore, epigenetic marks have been associated with the diagnosis and treatment of MDD. The evaluation of epigenetic modifications holds promise for further understanding of the heterogeneous etiology and complex phenotypes of MDD, and may identify new therapeutic targets. Here, we review preclinical and clinical epigenetic findings, including DNA methylation, histone modification, noncoding RNA, RNA modification, and chromatin remodeling factor in MDD. In addition, we elaborate on the contribution of these epigenetic mechanisms to the pathological trait variability in depression and discuss how such mechanisms can be exploited for therapeutic purposes.

Four differentially expressed exosomal miRNAs as prognostic biomarkers and therapy targets in endometrial cancer: Bioinformatic analysis

Endometrial cancer (EC) is one of the most common gynecological malignancies worldwide. Accumulated evidence has demonstrated exosomes of cancer cells carry microRNAs (miRNAs) to nonmalignant cells to induce metastasis. Our study aimed to find possible biomarkers of EC. Data for miRNA expression related with exosome from EC patients were downloaded from The Cancer Genome Atlas database, and the miRNA expression profiles associated with exosomes of EC were downloaded from the National Center for Biotechnology Information. We used different algorithms to analyze the differential miRNA expression, infer the relative proportion of immune infiltrating cells, predict chemotherapy sensitivity, and comprehensively score each gene set to evaluate the potential biological function changes of different samples. The gene ontology analysis and Kyoto encyclopedia of genome genomics pathway analysis were performed for specific genes. A total of 13 differential miRNAs were identified, of which 4 were up-regulated. The 4 miRNAs, that is hsa-miR-17-3p, hsa-miR-99b-3p, hsa-miR-193a-5p, and hsa-miR-320d, were the hub exosomal miRNAs that were all closely related to the clinic phenotypes and prognosis of patients. This study preliminarily indicates that the 4 hub exosomal miRNAs (hsa-miR-17-3p, hsa-miR-99b-3p, hsa-miR-193a-5p, and hsa-miR-320d) could be used as prognostic biomarkers or therapy targets in EC. Further studies are required to make sure of their real feasibility and values in the EC clinic and the relative research.

CRISPR/Cas13a-Based MicroRNA Detection in Tumor-Derived Extracellular Vesicles

MicroRNAs (miRNAs) in extracellular vesicles (EVs) play essential roles in cancer initiation and progression. Quantitative measurements of EV miRNAs are critical for cancer diagnosis and longitudinal monitoring. Traditional PCR-based methods, however, require multi-step procedures and remain as bulk analysis. Here, the authors introduce an amplification-free and extraction-free EV miRNA detection method using a CRISPR/Cas13a sensing system. CRISPR/Cas13a sensing components are encapsulated in liposomes and delivered them into EVs through liposome-EV fusion. This allows for accurately quantify specific miRNA-positive EV counts using 1 × 108  EVs. The authors show that miR-21-5p-positive EV counts are in the range of 2%-10% in ovarian cancer EVs, which is significantly higher than the positive EV counts from the benign cells (<0.65%). The result show an excellent correlation between bulk analysis with the gold-standard method, RT-qPCR. The authors also demonstrate multiplexed protein-miRNA analysis in tumor-derived EVs by capturing EpCAM-positive EVs and quantifying miR-21-5p-positive ones in the subpopulation, which show significantly higher counts in the plasma of cancer patients than healthy controls. The developed EV miRNA sensing system provides the specific miRNA detection method in intact EVs without RNA extraction and opens up the possibility of multiplexed single EV analysis for protein and RNA markers.

Rapid exosome isolation and in situ multiplexed detection of exosomal surface proteins and microRNAs on microfluidic platform

Exosomes are considered as promising biomarkers for early cancer diagnosis and prognosis. However, the majority of the research studies focused on a single type of exosomal biomarkers, which cannot comprehensively reflect the state of cancer for accurate diagnosis. To address this problem, we presented a ship-shaped microfluidic device containing a microcolumn array for simultaneous in situ detection of exosomal surface proteins and miRNAs. Exosomes were first captured in the microchannels modified with CD63 protein aptamer. Exosomal surface proteins and miRNAs were simultaneously detected in four parallel channels to avoid the interference of fluorescent signals using specific aptamers labeled by Cy5 and catalytic hairpin assembly (CHA) based signal amplification strategy. The limit of detection for multiplexed markers in exosomes was 83 exosomes per μL, which is comparable to previously reported methods. Through quantitative analysis of two disease-specific surface proteins and miRNAs derived from different cancer cells and clinical serum samples, different cancer subtypes as well as cancer patients and healthy people could be significantly distinguished. These results suggest that this simple, highly sensitive, and more accurate analytical strategy by simultaneous in situ profiling of different types of exosomal biomarkers has potential applications in cancer diagnosis and stage monitoring.

Exosomal miRNAs in the microenvironment of pancreatic cancer

Pancreatic cancer (PC) is highly aggressive having an extremely poor prognosis. The tumor microenvironment (TME) of PC is complex and heterogeneous. Various cellular components in the microenvironment are capable of secreting different active substances that are involved in promoting tumor development. Their release may occur via exosomes, the most abundant extracellular vesicles (EVs), that can carry numerous factors as well as act as a mean of intercellular communication. Emerging evidence suggests that miRNAs are involved in the regulation and control of many pathological and physiological processes. They can also be transported by exosomes from donor cells to recipient cells, thereby regulating the TME. Exosomal miRNAs show promise for use as future targets for PC diagnosis and prognosis, which may reveal new treatment strategies for PC. In this paper, we review the important role of exosomal miRNAs in mediating cellular communication in the TME of PC as well as their potential use in clinical applications.

miRNAs as Predictors of Barrier Integrity

The human body has several barriers that protect its integrity and shield it from mechanical, chemical, and microbial harm. The various barriers include the skin, intestinal and respiratory epithelia, blood-brain barrier (BBB), and immune system. In the present review, the focus is on the physical barriers that are formed by cell layers. The barrier function is influenced by the molecular microenvironment of the cells forming the barriers. The integrity of the barrier cell layers is maintained by the intricate balance of protein expression that is partly regulated by microRNAs (miRNAs) both in the intracellular space and the extracellular microenvironment. The detection of changes in miRNA patterns has become a major focus of diagnostic, prognostic, and disease progression, as well as therapy-response, markers using a great variety of detection systems in recent years. In the present review, we highlight the importance of liquid biopsies in assessing barrier integrity and challenges in differential miRNA detection.

Combined Ultrasensitive Detection of Renal Cancer Proteins and Cells Using an Optical Microfiber Functionalized with Ti3C2 MXene and Gold Nanorod-Nanosensitized Interfaces

The ultrasensitive and quantitative detection of renal cancer protein biomarkers present at ultralow concentrations for early-stage cancer diagnosis requires a biosensing probe possessing ultrahigh detection sensitivity and remarkable biosensing selectivity. Here, we report an optical microfiber integrated with Ti₃C₂-supported gold nanorod hybrid nanointerfaces for implementation in ultrasensitive sensing of the carbonic anhydrase IX (CAIX) protein and renal cancer cells. Because the evanescent field of the fiber is strongly coupled with nanointerfaces in the near-infrared region, the proposed optical microfiber biosensor achieves ultrahigh-sensitivity detection of the CAIX protein biomarker with ultralow limits of detection (LODs) of 13.8 zM in pure buffer solution and 0.19 aM in 30% serum solution. In addition, the proposed sensor also successfully and specifically recognizes living renal cancer cells in cell culture media with a LOD of 180 cells/mL. This strategy may serves as a powerful biosensing platform that combines the quantification of protein biomarkers and cancer cells, resulting in a higher accuracy of early-stage renal cancer diagnosis and screenings.

A review of sensors for classification and subtype discrimination of cancer: Insights into circulating tumor cells and tumor-derived extracellular vesicles

Liquid biopsy can reflect the state of tumors in vivo non-invasively, thus providing a strong basis for the early diagnosis, individualized treatment monitoring and prognosis of tumors. Circulating tumor cells (CTCs) and tumor-derived extracellular vesicles (tdEVs) contain information-rich components, such as nucleic acids and proteins, and they are essential markers for liquid biopsies. Their capture and analysis are of great importance for the study of disease occurrence and development and, consequently, have been the subject of many reviews. However, both CTCs and tdEVs carry the biological characteristics of their original tissue, and few reviews have focused on their function in the staging and classification of cancer. In this review, we focus on state-of-the-art sensors based on the simultaneous detection of multiple biomarkers within CTCs and tdEVs, with clinical applications centered on cancer classification and subtyping. We also provide a thorough discussion of the current challenges and prospects for novel sensors with the ultimate goal of cancer classification and staging. It is hoped that these most advanced technologies will bring new insights into the clinical practice of cancer screening and diagnosis.

Liposome fusogenic enzyme-free circuit enables high-fidelity determination of single exosomal RNA

Accurate determination of single exosomal inclusions in situ presents a significant challenge due to their extremely low abundance as well sub-100 nm vesicle dimensions. Here, we created a Liposome Fusogenic Enzyme-free circuit (LIFE) approach for the high-fidelity identification of exosome-encapsulated cargoes without destroying the vesicle integrity. The probe-loaded cationic fusogenic liposome could capture and fuse with a single target exosome, enabling probes delivery and target biomolecule-initiated cascaded signal amplification in situ. Then the DNAzyme probe encountered conformal change upon exosomal microRNA activation, and generated a convex DNAzyme structure to cleave the RNA site of substrate probe. After that, the target microRNA could be released to introduce a cleavage cycle to yield amplified fluorescence readout. Therefore, trace cargoes in a single exosome could be accurately determined by elaborately controlling the ratio of introduced LIFE probe, paving the way toward the exploration of a universal sensing platform for the assessment of exosomal cargoes to facilitate early disease diagnosis and personalized treatment.

Highly Effective Detection of Exosomal miRNAs in Plasma Using Liposome-Mediated Transfection CRISPR/Cas13a

Exosomal miRNAs play a critical role in cancer biology and could be potential biomarkers for cancer diagnosis. However, due to the low abundance of miRNAs in the exosomes, recognizing and detecting disease-associated exosomal miRNAs in an easy-to-operate way remain a challenge. Herein, we used a liposome-mediated membrane fusion strategy (MFS) to transfect CRISPR/Cas13a into exosomes, termed MFS-CRISPR, directly measuring exosomal miRNAs in plasma. Using the MFS-CRISPR platform for detection of the exosomal miR-21, we achieve a linear range spanning four orders of magnitude (10⁴-10⁸ particles/mL) and the method is able to detect the exosomal miR-21 in as low as 1.2 × 10³ particles/mL. The liposome-mediated MFS could confine fluorescent signals in fused vesicles, which can be used for exosome heterogeneity analysis. Moreover, MFS-CRISPR assay was evaluated by measuring clinical samples, and the difference of miR-21 expression of breast cancer patients and healthy donors was significant. Because of high sensitivity and simplicity, the proposed method could have promising clinical potential for cancer diagnosis and treatment monitoring.

The EPH/Ephrin System in Pancreatic Ductal Adenocarcinoma (PDAC): From Pathogenesis to Treatment

Pancreatic ductal adenocarcinoma (PDAC) is a major concern for health care systems worldwide, since its mortality remains unaltered despite the surge in cutting-edge science. The EPH/ephrin signaling system was first investigated in the 1980s. EPH/ephrins have been shown to exert bidirectional signaling and cell-to-cell communication, influencing cellular morphology, adhesion, migration and invasion. Recent studies have highlighted the critical role of the EPH/ephrin system in various physiologic processes, including cellular proliferation, survival, synaptic plasticity and angiogenesis. Thus, it has become evident that the EPH/ephrin signaling system may have compelling effects on cell homeostasis that contribute to carcinogenesis. In particular, the EPH/ephrins have an impact on pancreatic morphogenesis and development, whereas several EPHs and ephrins are altered in PDAC. Several clinical and preclinical studies have attempted to elucidate the effects of the EPH/ephrin pathway, with multilayered effects on PDAC development. These studies have highlighted its highly promising role in the diagnosis, prognosis and therapeutic management of PDAC. The aim of this review is to explore the obscure aspects of the EPH/ephrin system concerning the development, physiology and homeostasis of the pancreas.

Dual Imaging Single Vesicle Surface Protein Profiling and Early Cancer Detection

Single vesicle molecular profiling has the potential to transform cancer detection and monitoring by precisely probing cancer-associated extracellular vesicles (EVs) in the presence of normal EVs in body fluids, but it is challenging due to the small EV size, low abundance of antigens on individual vesicles, and a complex biological matrix. Here, we report a facile dual imaging single vesicle technology (DISVT) for surface protein profiling of individual EVs and quantification of target-specific EV subtypes based on direct molecular capture of EVs from diluted biofluids, dual EV-protein fluorescence-light scattering imaging, and fast image analysis using Bash scripts, Python, and ImageJ. Plasmonic gold nanoparticles (AuNPs) were used to label and detect targeted surface protein markers on individual EVs with dark-field light scattering imaging at the single particle level. Monte Carlo calculations estimated that the AuNPs could detect EVs down to 40 nm in diameter. Using the DISVT, we profiled surface protein markers of interest across individual EVs derived from several breast cancer cell lines, which reflected the parental cells. Studies with plasma EVs from healthy donors and breast cancer patients revealed that the DISVT, but not the traditional bulk enzyme-linked immunosorbent assay, detected human epidermal growth factor receptor 2 (HER2)-positive breast cancer at an early stage. The DISVT also precisely differentiated HER2-positive breast cancer from HER2-negative breast cancer. We additionally showed that the amount of tumor-associated EVs was tripled in locally advanced patients compared to that in early-stage patients. These studies suggest that single EV surface protein profiling with DISVT can provide a facile and high-sensitivity method for early cancer detection and quantitative monitoring.

Aptamer-Assisted Traceless Isolation of PD-L1-Positive Small Extracellular Vesicles for Dissecting Their Subpopulation Signature and Function

Small extracellular vesicles (sEVs) are heterogeneous membrane-bound vesicles that carry numerous bioactive molecules. Studies have reported that sEVs carrying PD-L1 on the surface could contribute to immunosuppression; however, the precise mechanisms are unclear. To fully dissect their mode of action, it requires qualified methods to specifically isolate natural PD-L1-positive sEVs from heterogeneous sEVs. This study reported an aptamer-assisted capture-and-release strategy for traceless isolation of PD-L1-positive sEVs. The PD-L1 aptamer-anchored magnetic microspheres enable the specific capture of PD-L1-positive sEVs. The traceless release of captured PD-L1-positive sEVs was triggered by competition of complementary oligonucleotides, endowing the obtained label-free PD-L1-positive sEVs with natural properties. Benefited from this traceless isolation strategy, the distinct molecule profiles in adhesion and immuno-regulation between PD-L1-positive and PD-L1-negative sEVs were revealed. Compared to PD-L1-negative sEVs, PD-L1-positive sEVs were much more concentrated in cadherin binding, accompanied by increased adhesion to lymphatic endothelial cells and T cells but decreased adhesion to the extracellular matrix. Moreover, PD-L1-positive sEVs could transfer their enriched immunosuppressive "synapse"-related proteins to antigen-presenting cells, thereby inducing a tolerogenic-like phenotype. In summary, the present work dissects the subpopulation signature and action mode of PD-L1-positive sEVs for the first time and provides a general approach to the traceless isolation of sEV subpopulations.

In situ detection of exosomal RNAs for cancer diagnosis

Exosomes are considered as biomarkers reflecting the physiological state of the human body. Studies have revealed that the expression levels of specific exosomal RNAs are closely associated with certain cancers. Thus, detection of exosomal RNA offers a new avenue for liquid biopsy of cancers. Many exosomal RNA detection methods based on various principles have been developed, and most of the methods detect the extracted RNAs after lysing exosomes. Besides complex and time-consuming extraction steps, a major drawback of this approach is the degradation of the extracted RNAs in the absence of plasma membrane and cytosol. In addition, there is considerable loss of RNAs during their extraction. In situ detection of exosomal RNAs can avoid these drawbacks, thus allowing higher diagnostic reliability. In this paper, in situ detection of exosomal RNAs was systematically reviewed from the perspectives of detection methods, transport methods of the probe systems, probe structures, signal amplification strategies, and involved functional materials. Furthermore, the limitations and possible improvements of the current in situ detection methods for exosomal RNAs towards the clinical diagnostic application are discussed. This review aims to provide a valuable reference for the development of in situ exosomal RNA detection strategies for non-invasive diagnosis of cancers. STATEMENT OF SIGNIFICANCE: Certain RNAs have been identified as valuable biomarkers for some cancers, and sensitive detection of cancer-related RNAs is expected to achieve better diagnostic efficacy. Currently, the detection of exosomal RNAs is receiving increasing attention due to their high stability and significant concentration differences between patients and healthy individuals. In situ detection of exosomal RNAs has greater diagnostic reliability due to the avoidance of RNA degradation and loss. However, this mode is still limited by some factors such as detection methods, transport methods of the probe systems, probe structures, signal amplification strategies, etc. This review focuses on the progress of in situ detection of exosomal RNAs and aims to promote the development of this field.

Monocrystalline Labeling Enables Stable Plasmonic Enhancement for Isolation-Free Extracellular Vesicle Analysis

Sensitive detection of extracellular vesicles (EVs) as emerging biomarkers has shown great promises for disease diagnosis. Plasmonic metal nanostructures conjugated with molecules that bind specific biomarker targets are widely used for EVs sensing but involve tradeoffs between particle-size-dependent signal intensity and conjugation efficiency. One solution to this problem would be to induce nucleation on nanoparticles that have successfully bound a target biomarker to permit in situ nanoparticle growth for signal amplification, but approaches that are evaluated to date require harsh conditions or lack nucleation specificity, prohibiting their effective use with most biological specimens. This study describes a one-step in situ strategy to induce monocrystalline copper shell growth on gold nanorod probes without decreasing signal by disrupting probe-target interactions or lipid bilayer integrity to enable EV biomarker detections. This approach increases the detected nanoparticle signal about two orders of magnitude after a 10 min copper nanoshell growth reaction. This has significant implications for improved disease detection, as indicated by the ability of a novel immunoassay using this approach to detect low abundance EVs carrying a pathogen-derived biomarker, after their direct capture from serum, to facilitate the diagnosis of tuberculosis cases in a diagnostically challenging pediatric cohort.

Microfluidic Strategies for Extracellular Vesicle Isolation: Towards Clinical Applications

Extracellular vesicles (EVs) are double-layered lipid membrane vesicles released by cells. Currently, EVs are attracting a lot of attention in the biological and medical fields due to their role as natural carriers of proteins, lipids, and nucleic acids. Thus, they can transport useful genomic information from their parental cell through body fluids, promoting cell-to-cell communication even between different organs. Due to their functionality as cargo carriers and their protein expression, they can play an important role as possible diagnostic and prognostic biomarkers in various types of diseases, e.g., cancers, neurodegenerative, and autoimmune diseases. Today, given the invaluable importance of EVs, there are some pivotal challenges to overcome in terms of their isolation. Conventional methods have some limitations: they are influenced by the starting sample, might present low throughput and low purity, and sometimes a lack of reproducibility, being operator dependent. During the past few years, several microfluidic approaches have been proposed to address these issues. In this review, we summarize the most important microfluidic-based devices for EV isolation, highlighting their advantages and disadvantages compared to existing technology, as well as the current state of the art from the perspective of the use of these devices in clinical applications.

Early Diagnosis of Brain Diseases Using Artificial Intelligence and EV Molecular Data: A Proposed Noninvasive Repeated Diagnosis Approach

Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invasive and enable repeatable measurements based on body fluids. However, EVs from various cells and organs are mixed in the blood, acting as potential obstacles for brain diagnostic systems using BDEVs. Therefore, it is important to screen appropriate brain EV markers to isolate BDEVs in blood. Here, we established a strategy for screening potential BDEV biomarkers. To collect various molecular data from the BDEVs, we propose that the sensitivity and specificity of the diagnostic system could be enhanced using machine learning and AI analysis. This BDEV-based diagnostic strategy could be used to diagnose various brain diseases and will help prevent disease through early diagnosis and early treatment.

Interplay of four types of RNA modification writers revealed distinct tumor microenvironment and biological characteristics in pancreatic cancer

Background

Pancreatic cancer (PC) is one of the most lethal malignancies and carries a dismal mortality and morbidity. Four types of RNA modification (namely m6A, m1A, APA and A-to-I) could be catalyzed by distinct enzymatic compounds ("writers"), mediating numerous epigenetic events in carcinogenesis and immunomodulation. We aim to investigate the interplay mechanism of these writers in immunogenomic features and molecular biological characteristics in PC.

Methods

We first accessed the specific expression pattern and transcriptional variation of 26 RNA modification writers in The Cancer Genome Atlas (TCGA) dataset. Unsupervised consensus clustering was performed to divide patients into two RNA modification clusters. Then, based on the differentially expressed genes (DEGs) among two clusters, RNA modification score (WM_Score) model was established to determine RNA modification-based subtypes and was validated in International Cancer Genome Consortium (ICGC) dataset. What's more, we manifested the unique status of WM_Score in transcriptional and post-transcriptional regulation, molecular biological characteristics, targeted therapies and immunogenomic patterns.

Results

We documented the tight-knit correlations between transcriptional expression and variation of RNA modification writers. We classified patients into two distinct RNA modification patterns (WM_Score_high and _low), The WM_Score_high subgroup was correlated with worse prognosis, Th2/Th17 cell polarization and oncogenic pathways (e.g. EMT, TGF-β, and mTORC1 signaling pathways), whereas the WM_Score_low subgroup associated with favorable survival rate and Th1 cell trend. WM_Score model also proved robust predictive power in interpreting transcriptional and post-transcriptional events. Additionally, the potential targeted compounds with related pathways for the WM_Score model were further identified.

Conclusions

Our research unfolds a novel horizon on the interplay network of four RNA modifications in PC. This WM_Score model demonstrated powerful predictive capacity in epigenetic, immunological and biological landscape, providing a theoretical basis for future clinical judgments of PC.

Recent Advances in Exosomal miRNA Biosensing for Liquid Biopsy

As a noninvasive detection technique, liquid biopsy plays a valuable role in cancer diagnosis, disease monitoring, and prognostic assessment. In liquid biopsies, exosomes are considered among the potential biomarkers because they are important bioinformation carriers for intercellular communication. Exosomes transport miRNAs and, thus, play an important role in the regulation of cell growth and function; therefore, detection of cancer cell-derived exosomal miRNAs (exo-miRNAs) gives effective information in liquid biopsy. The development of sensitive, convenient, and reliable exo-miRNA assays will provide new perspectives for medical diagnosis. This review presents different designs and detection strategies of recent exo-miRNA assays in terms of signal transduction and amplification, as well as signal detection. In addition, this review outlines the current attempts at bioassay methods in liquid biopsies. Lastly, the challenges and prospects of exosome bioassays are also considered.

Plant extracellular vesicles: A novel bioactive nanoparticle for tumor therapy

Extracellular vesicles are tiny lipid bilayer-enclosed membrane particles, including apoptotic bodies, micro vesicles, and exosomes. Organisms of all life forms can secrete extracellular vesicles into their surrounding environment, which serve as important communication tools between cells and between cells and the environment, and participate in a variety of physiological processes. According to new evidence, plant extracellular vesicles play an important role in the regulation of transboundary molecules with interacting organisms. In addition to carrying signaling molecules (nucleic acids, proteins, metabolic wastes, etc.) to mediate cellular communication, plant cells External vesicles themselves can also function as functional molecules in the cellular microenvironment across cell boundaries. This review introduces the source and extraction of plant extracellular vesicles, and attempts to clarify its anti-tumor mechanism by summarizing the current research on plant extracellular vesicles for disease treatment. We speculate that the continued development of plant extracellular vesicle-based therapeutic and drug delivery platforms will benefit their clinical applications.

Recent advances in integrated microfluidics for liquid biopsies and future directions

Liquid biopsies have piqued the interest of researchers as a new tumor diagnosis technique due to their unique benefits of non-invasiveness, sensitivity, and convenience. Recent advances in microfluidic technology have integrated separation, purification, and detection, allowing for high-throughput, high-sensitivity, and high-controllability detection of specific biomarkers in liquid biopsies. With the increasing demand for tumor detection and individualized treatment, new challenges are emerging for the ever-improving microfluidic technology. The state-of-the-art microfluidic design and fabrications have been reviewed in this manuscript, and how this technology can be applied to liquid biopsies from the point of view of the detection process. The primary discussion objectives are circulating tumor cells (CTCs), exosomes, and circulating nucleic acid (ctDNA). Furthermore, the challenges and future direction of microfluidic technology in detecting liquid biomarkers have been discussed.

Simultaneous detection of cancerous exosomal miRNA-21 and PD-L1 with a sensitive dual-cycling nanoprobe

Simultaneous detection of specific exosomal surface proteins and inner microRNAs are hampered by their heterogeneity, low abundance and spatial segregation in nanovesicles. Here, we design a dual-cycling nanoprobe (DCNP) to enable single-step simultaneous quantitation of cancerous exosomal surface programmed death-ligand 1 (PD-L1) (ExoPD-L1) and miRNA-21 (ExomiR-21) directly in exosome lysates, without resorting to either RNA extraction or time-consuming transmembrane penetration. In this design, DNA molecular machine-based dual-recognition probes co-assemble onto gold nanoparticle surface for engineering 'silent' DCNPs, which enable signal-amplified synchronous response to dual-targets as activated by ExomiR-21 and ExoPD-L1 within 20 min. Benefiting from cycling amplification of the molecular machine, DCNPs sensor achieves detection limits of tumor exosomes, ExoPD-L1 and ExomiR-21 down to 10 particles/μL, 0.17 pg/mL and 66 fM, respectively. Such a sensitive dual-response strategy allows simultaneous tracking the dynamic changes of ExoPD-L1 and ExomiR-21 expression regulated by signaling molecules or therapeutics. This approach further detects circulating ExoPD-L1 and ExomiR-21 in human plasma to differentiate breast cancer patients from healthy individuals with high accuracy, showing great potential of DCNPs for simultaneous profiling exosomal surface and inside biomarkers, and for clinical precision diagnosis.

Fluorescence Analysis of Circulating Exosomes for Breast Cancer Diagnosis Using a Sensor Array and Deep Learning

Emerging liquid biopsy methods for investigating biomarkers in bodily fluids such as blood, saliva, or urine can be used to perform noninvasive cancer detection. However, the complexity and heterogeneity of exosomes require improved methods to achieve the desired sensitivity and accuracy. Herein, we report our study on developing a breast cancer liquid biopsy system, including a fluorescence sensor array and deep learning (DL) tool AggMapNet. In particular, we used a 12-unit sensor array composed of conjugated polyelectrolytes, fluorophore-labeled peptides, and monosaccharides or glycans to collect fluorescence signals from cells and exosomes. Linear discriminant analysis (LDA) processed the fluorescence spectral data of cells and cell-derived exosomes, demonstrating successful discrimination between normal and different cancerous cells and 100% accurate classification of different BC cells. For heterogeneous plasma-derived exosome analysis, CNN-based DL tool AggMapNet was applied to transform the unordered fluorescence spectra into feature maps (Fmaps), which gave a straightforward visual demonstration of the difference between healthy donors and BC patients with 100% prediction accuracy. Our work indicates that our fluorescent sensor array and DL model can be used as a promising noninvasive method for BC diagnosis.

Extracellular vesicle biomarkers for pancreatic cancer diagnosis: a systematic review and meta-analysis

BACKGROUND

Extracellular vesicle (EV) biomarkers have promising diagnosis and screening capacity for several cancers, but the diagnostic value for pancreatic cancer (PC) is controversial. The aim of our study was to review the diagnostic performance of EV biomarkers for PC.

METHODS

We performed a systematic review of PubMed, Medline, and Web Of Science databases from inception to 18 Feb 2022. We identified studies reporting the diagnostic performance of EV biomarkers for PC and summarized the information of sensitivity, specificity, area under the curve (AUC), or receiver operator characteristic (ROC) curve) in according to a pre-designed data collection form. Pooled sensitivity and specificity was calculated using a random-effect model.

RESULTS

We identified 39 studies, including 2037 PC patients and 1632 noncancerous, seven of which were conducted independent validation tests. Seventeen studies emphasized on EV RNAs, sixteen on EV proteins, and sixteen on biomarker panels. MiR-10b, miR-21, and GPC1 were the most frequently reported RNA and protein for PC diagnosis. For individual RNAs and proteins, the pooled sensitivity and specificity were 79% (95% CI: 77-81%) and 87% (95% CI: 85-89%), 72% (95% CI: 69-74%) and 77% (95% CI: 74-80%), respectively. the pooled sensitivity and specificity of EV RNA combined with protein panels were 84% (95% CI: 81-86%) and 89% (95% CI: 86-91%), respectively. Surprisingly, for early stage (stage I and II) PC EV biomarkers showed excellent diagnostic performance with the sensitivity of 90% (95% CI: 87-93%) and the specificity of 94% (95% CI: 92-95%). Both in sensitivity and subgroup analyses, we did not observe notable difference in pooled sensitivity and specificity. Studies might be limited by the isolation and detection techniques of EVs to a certain extent.

CONCLUSIONS

EV biomarkers showed appealing diagnostic preference for PC, especially for early stage PC. Solving the deficiency of technologies of isolation and detection EVs has important implications for application these novel noninvasive biomarkers in clinical practice.

Extracellular Vesicle (EV) Dot Blotting for Multiplexed EV Protein Detection in Complex Biofluids

Extracellular vesicles (EVs) are nanoscale vesicles secreted from cells, carrying biomolecular cargos similar to their cells of origin. Measuring the protein content of EVs in biofluids can offer a crucial insight into human health and disease. For example, detecting tumor-derived EVs' protein markers can aid in early diagnosis of cancer, which is life-saving. In order to use these EV proteins for diagnosis, sensitive and multiplexed methods are required. The current methods for EV protein detection typically require large sample consumption due to challenges with sensitivity and often need an EV isolation step for complex biofluid samples such as blood plasma. In this work, we have developed a simple and sensitive method for multiplexed detection of protein markers on EV membrane surfaces, which we call "EV dot blotting", inspired by conventional dot blotting techniques. After optimization of multiple factors such as antibody concentration, blocking reagent, type of 3D membranes, and use of gold nanoparticles for signal enhancement, cancer-cell-derived EVs were spiked in pooled normal human plasma for conducting a multiplexed assay in a microarray format. Without the need of isolating EVs from blood plasma, a limit of detection of 3.1 × 10⁵ EVs/mL or 1863 EVs/sample was achieved for CD9 protein, 4.7 × 10⁴ EVs/mL or 281 EVs/sample for CD24, and 9.0 × 10⁴ EVs/mL or 538 EVs/sample for EpCAM, up to 4 orders of magnitude lower than those of conventional ELISA. This platform offers sensitive, multiplexed, simple, and low-cost EV protein detection directly from complex biofluids with minimal sample consumption, providing a useful tool for multiplexed EV protein quantification for a variety of applications.

Research Progress in the Application of Exosomes in Immunotherapy

Exosomes are nanoscale extracellular vesicles (EVs), which are present in all body fluids tested. They are secreted by a variety of cells including macrophages, dendritic cells, mast cells, granulocytes, lymphocytes, and tumor cells. Exosomes secreted by different cells have different biological components and functional characteristics and play an important role in many pathophysiological activities. Recent studies have revealed that exosomes can regulate the occurrence and development of inflammatory immune diseases and tumors by transmitting their unique proteins, lipids, and nucleic acids as signaling molecules to other cells. Exosomes serve as a novel class of diagnostic biomarkers and drug delivery systems with promising applications in immunotherapy, particularly because breakthroughs in nanotechnology have led to the development and exploration of engineered exosomes for immunotargeted therapies. Therefore, here we review the progress being made on the application of exosomes in immunotherapy and its multiple regulatory mechanisms and explore the potential application of exosomes in immunotherapy in the future.

Utilizing Exosomal-EPHs/Ephrins as Biomarkers and as a Potential Platform for Targeted Delivery of Therapeutic Exosomes

Exosomes are cell-secreted nanoparticles containing various molecules including small vesicles, microRNAs (miRNAs), messenger RNAs or bioactive proteins which are thought to be of paramount importance for intercellular communication. The unique effects of exosomes in terms of cell penetration capacity, decreased immunogenicity and inherent stability, along with their key role in mediating information exchange among tumor cells and their surrounding tumor microenvironment (TME), render them a promising platform for drug targeted delivery. Compared to synthetic drugs, exosomes boast a plethora of advantages, including higher biocompatibility, lower toxicity and increased ability of tissue infiltration. Nevertheless, the use of artificial exosomes can be limited in practice, partly due to their poor targeting ability and partly due to their limited efficacy. Therefore, efforts have been made to engineer stem cell-derived exosomes in order to increase selectiveness and effectivity, which can then become loaded with various active substances depending on the therapeutic approach followed. Erythropoietin-producing human hepatocellular receptors (EPHs), along with their ligands, the EPH family receptor interacting proteins (ephrins), have been extensively investigated for their key roles in both physiology and cancer pathogenesis. EPHs/ephrins exhibit both tumorigenic and tumor suppressing properties, with their targeting representing a promising, novel therapeutic approach in cancer patients’ management. In our review, the use of ephrin-loaded exosomes as a potential therapeutic targeted delivery system in cancer will be discussed.

Stimuli-Mediated Specific Isolation of Exosomes from Blood Plasma for High-Throughput Profiling of Cancer Biomarkers

Exosomes, ranging from 30-150 nm in diameter, have emerged as promising non-invasive biomarkers for the diagnosis and prognosis of numerous diseases. However, current research on exosomes is largely restricted by the lack of an efficient method to isolate exosomes from real samples. Herein, the first stimuli-mediated enrichment and purification system to selectively and efficiently extract exosomes from clinical plasma for high-throughput profiling of exosomal mRNAs as cancer biomarkers is presented. This novel isolation system relies on specific installation of the stimuli-responsive copolymers onto exosomal phospholipid bilayers, by which the enrichment and purification are exclusively achieved for exosomes rather than the non-vesicle counterparts co-existing in real samples. The stimuli-mediated isolation system outperforms conventional methods such as ultracentrifugation and polyethylene glycol-based precipitation in terms of isolation yield, purity, and retained bioactivity. The high performance of the isolation system is demonstrated by enriching exosomes from 77 blood plasma samples and validated the clinical potentials in profiling exosomal mRNAs for cancer diagnosis and discrimination with high accuracy. This simple isolation system can boost the development of extracellular vesicle research, not limited to exosomes, in both basic and clinical settings.