Exosomal Biomarkers Research Articles

The toxicity of lead on human neuroblastoma cells was alleviated by HUC-MSC-derived exosomes through miR-26a-5p/PTEN pathway

Lead is a ubiquitous environmental chemical with various toxic damage to human body. This investigation aimed to explore the intervention effect of human umbilical cord mesenchymal stem cells derived exosomes (HUC-MSC-exo) on the neurotoxicity of lead and the relevant mechanism. Differential gradient ultracentrifugation was adopted to isolate HUC-MSC-exo. Nanoparticle tracking assay (NTA), Transmission electron microscope (TEM) technology and exosomal specific biomarkers CD9, CD63 and CD81 were adopted for exosomal characterization. Human neuroblastoma cell (SH-SY5Y) was used as the recipient cell. Confocal laser scanning microscope analysis was conducted to confirm the intake of HUC-MSC-exo by SH-SY5Y cells. Cell migration ability, apoptosis, IL-6, IL-1β and TNF-α were analyzed. The role of miR-26a-5p/PTEN axis was assessed. The result showed that the exposure of SH-SY5Y cells to lead activated the miR-26a-5p/PTEN pathway by down-regulating miR-26a-5p and up-regulating PTEN expression, which was related to the significantly decreased cell migration and increased apoptosis, as well as significantly enhanced levels of inflammatory cytokine as compared with the control. While HUC-MSC-exo could significantly alleviate the cytotoxicity, apoptosis and inflammatory effects induced by lead on SH-SY5Y cells via partially restoring miR-26a-5p/PTEN pathway. Herein, we conclude that HUC-MSC-exo can alleviate lead-induced toxic effects on SH-SY5Y cells partially through miR-26a-5p/PTEN pathway.

The concept of the liquid biopsy in the treatment of malignant eye tumours

The liquid biopsy is acutting-edge technique that involves analysing non-solid biological tissues, primarily blood but also ocular fluids, for the presence of cancer cells or fragments of tumour DNA. Unlike traditional biopsies, liquid biopsies are usually minimally invasive and can be performed more frequently, enabling continuous monitoring of disease progression and treatment efficacy. This article (and the associated series of articles) outlines the key developments in liquid biopsy, which include the analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTC) and exosomal RNA and protein biomarkers. Techniques, such as digital droplet PCR and next-generation sequencing (NGS) have made it possible to detect even very low levels of ctDNA, which is crucial for early cancer detection and monitoring minimal residual disease. The detection of rare CTCs is enhanced by techniques, such as microfluidic devices and immunomagnetic separation. Multiomic approaches, whereby exosomal RNA, protein and ctDNA analyses are combined, help to create amore comprehensive picture of tumour biology, including insights into tumour heterogeneity, potentially leading to better diagnostic and prognostic tools and helping to predict treatment response and resistance. The challenges of liquid biopsy application, which will be described in the following article, include (a)standardization, (b)cost and accessibility, (c)validation and clinical utility. However, the liquid biopsy represents apromising frontier in the application of precision ocular oncology, with ongoing research likely to expand its applications and improve its effectiveness in the coming years.

Explainable artificial intelligence-driven prostate cancer screening using exosomal multi-marker based dual-gate FET biosensor

Prostate Imaging Reporting and Data System (PI-RADS) score, a reporting system of prostate MRI cases, has become a standard prostate cancer (PCa) screening method due to exceptional diagnosis performance. However, PI-RADS 3 lesions are an unmet medical need because PI-RADS provides diagnosis accuracy of only 30–40% at most, accompanied by a high false-positive rate. Here, we propose an explainable artificial intelligence (XAI) based PCa screening system integrating a highly sensitive dual-gate field-effect transistor (DGFET) based multi-marker biosensor for ambiguous lesions identification. This system produces interpretable results by analyzing sensing patterns of three urinary exosomal biomarkers, providing a possibility of an evidence-based prediction from clinicians. In our results, XAI-based PCa screening system showed a high accuracy with an AUC of 0.93 using 102 blinded samples with the non-invasive method. Remarkably, the PCa diagnosis accuracy of patients with PI-RADS 3 was more than twice that of conventional PI-RADS scoring. Our system also provided a reasonable explanation of its decision that TMEM256 biomarker is the leading factor for screening those with PI-RADS 3. Our study implies that XAI can facilitate informed decisions, guided by insights into the significance of visualized multi-biomarkers and clinical factors. The XAI-based sensor system can assist healthcare professionals in providing practical and evidence-based PCa diagnoses.

Multicenter, prospective, observational study for urinary exosomal biomarkers of kidney allograft fibrosis

Severity of deceased donor kidney fibrosis impacts graft survival in deceased-donor kidney transplantation. Our aim was to identify potential miRNA biomarkers in urinary exosomes that mirror interstitial fibrosis and tubular atrophy (IFTA) severity. Among 109 urine samples from deceased donors, 34 displayed no IFTA in the zero-day biopsy (No IFTA group), while the remaining 75 deceased donor kidneys exhibited an IFTA score ≥ 1 (IFTA group). After analyzing previous reports and electronic databases, six miRNAs (miR-19, miR-21, miR-29c, miR-150, miR-200b, and miR-205) were selected as potential IFTA biomarker candidates. MiR-21, miR-29c, miR-150, and miR-205 levels were significantly higher, while miR-19 expression was significantly lower in the IFTA group. MiR-21 (AUC = 0.762; P < 0.001) and miR-29c (AUC = 0.795; P < 0.001) showed good predictive accuracy for IFTA. In the No IFTA group, the eGFR level at 1 week after transplantation was significantly higher compared to the IFTA group (41.34 mL/min/1.73m2 vs. 28.65 mL/min/1.73m2, P = 0.012). These findings signify the potential of urinary exosomal miRNAs as valuable biomarker candidates for evaluating the severity of IFTA in deceased donor kidneys before they undergo recovery.

Proteomics of plasma-derived extracellular vesicles reveals S100A8 as a novel biomarker for Alzheimer's disease: A preliminary study

Extracellular vesicles (EVs) act as mediators for intercellular transfer of Aβ and tau proteins, promoting the propagation of these pathological misfolded proteins throughout the brain in Alzheimer's disease (AD). Levels of blood exosomal Aβ42, total Tau (t-Tau) and phosphorylated Tau (p-Tau) had a high correlation with their concentrations in cerebrospinal fluid (CSF), demonstrating that exosomal biomarkers have equal contribution as those in CSF for the diagnosis of AD. We aimed to comprehensively characterize the proteome of plasma-derived EVs to identify differentially expressed proteins (DEPs) and pathways in AD. Tandem mass tag (TMT) labeled quantitative proteomics was applied to analyze plasma-derived EV proteins in 9 AD patients and 9 healthy controls. 335 proteins were quantified, and 12 DEPs were identified including seven upregulated proteins and five down-regulated proteins. Oligomerized Aβ1–42 induced SH-SY5Y cell damage model was built to mimic the pathological changes of AD, and small interfering RNA (siRNA) against S100A8 was used to knock down S100A8 expression. Results displayed S100A8 was down regulated in plasma-derived EVs from AD patients, while enriched in EVs derived from Aβ1–42-induced SH-SY5Y cells. Furthermore, Aβ1–42-induced SH-SY5Y cells treated with S100A8 siRNA showed decreased Aβ levels in cell lysate and EVs, especially in EVs. SignificanceThe investigation aimed to comprehensively characterize the proteome of plasma-derived EVs to identify DEPs and potential biomarker of AD. S100A8 was found down regulated in plasma-derived EVs from AD patients using TMT labeled quantitative proteomics. The diagnostic value of S100A8 was also confirmed using receiver operating characteristic curve (ROC) analysis. Furthermore, Aβ1–42-induced SH-SY5Y cells treated with S100A8 siRNA showed decreased Aβ levels in cell lysate and EVs, especially in EVs. The preliminary findings suggest that suppression of S100A8 expression inhibits Aβ aggregation both in cell lysate and EVs from Aβ1–42-induced SH-SY5Y cells, and S100A8 more likely regulates Aβ aggregation via EVs. Therefore, plasma-derived EV S100A8 might be a potential biomarker of AD. Manipulation of S100A8 expression may be a novel therapeutic strategy in the treatment of AD.

Intermittent lysis on a single paper-based device to extract exosomal nucleic acid biomarkers from biological samples for downstream analysis.

As the role of exosomes in physiological and pathological processes has been properly perceived, harvesting them and their internal components is critical for subsequent applications. This study is a debut of intermittent lysis, which has been integrated into a simple and easy-to-operate procedure on a single paper-based device to extract exosomal nucleic acid biomarkers for downstream analysis. Exosomes from biological samples were captured by anti-CD63-modified papers before being intermittently lysed by high-temperature, short-time treatment with double-distilled water to release their internal components. Exosomal nucleic acids were finally adsorbed by sol-gel silica for downstream analysis. Empirical trials not only revealed that sporadically dropping 95°C ddH2O onto the anti-CD63-modified papers every 5min for 6 times optimized the exosomal nucleic acids extracted by the anti-CD63 paper but also verified that the whole deployed procedure is applicable for point-of-care testing (POCT) in low-resource areas and for both in vitro (culture media) and in vivo (plasma and chronic lesion) samples. Importantly, downstream analysis of exosomal miR-21 extracted by the paper-based procedure integrated with this novel technique discovered that the content of exosomal miR-21 in chronic lesions related to their stages and the levels of exosomal carcinoembryonic antigen originated from colorectal cancer cells correlated to their exosomal miR-21.

Evaluating the Urinary Exosome microRNA Profile of von Hippel Lindau Syndrome Patients with Clear Cell Renal Cell Carcinoma.

Renal cell carcinoma is one of the ten more common malignant tumors worldwide, with a high incidence and mortality rate. Kidney cancer frequently presents at an advanced stage, and it is almost invariably fatal. Much progress has been made in identifying molecular targets for therapy in the hope of improving survival rates, but still, we have no good markers for early detection or progression of the disease. Von Hippel Lindau syndrome (VHL) is an autosomal dominant cancer hereditary syndrome in which affected individuals are at risk of developing bilateral and multifocal renal cell carcinomas (RCC) as well as other tumors. These patients provide an ideal platform to investigate the potential of urinary exosomal miRNA biomarkers in the early development of ccRCC, as these patients are regularly imaged and tumors are actively monitored until the tumor reaches 3 cm before surgical excision. This allows for pre- and post-surgical urine collection and comparison to excised tumor tissues. Studying different biomarkers in urine can provide comprehensive molecular profiling available to patients and physicians and can be a great source of additional tumor genetic information. Pre- and postoperative urine samples were obtained from a cohort of VHL patients undergoing surveillance and surgical excision of ccRCCs, and exosomes were extracted. MicroRNA-Seq analysis was performed on miRNA extracted from both urine-derived exosomes and FFPE material from excised ccRCCs. MicroRNA-Seq analysis highlighted a significant difference in the urinary exosome-derived miRNA expression profiles between VHL patients and normal control individuals. This included decreased expression of the miR-320 family, such as miR-320a, known to be decreased in sporadic ccRCC and suppressed by the HIF1α transcription factor activated by the loss of the VHL gene. MiR-542-5p represented a potential marker of VHL-associated ccRCC that was lowly expressed in normal control urinary exosomes, significantly increased in the preoperative urinary exosomes of tumor-bearing VHL patients, and subsequently reduced to normal levels of expression after tumor excision. In concordance with this, the expression of miR-542-5p was increased in the VHL-associated ccRCC in comparison to the normal kidney. This study shows the potential for miRNA profiling of exosomes from readily available biofluids to both distinguish VHL patient urine from normal control urine microRNAs and to provide biomarkers for the presence of VHL syndrome-associated ccRCC. Further validation studies are necessary to demonstrate the utility of urinary exosome-derived miRNAs as biomarkers in kidney cancer.

Role of vertical circulating exosomes biomarkers in preeclampsia

AbstractPreeclampsia, a hypertensive disorder of pregnancy, poses significant risks to maternal and fetal health. Recent research highlights the potential of vertical circulating exosomes (VCEs) as biomarkers for early detection and monitoring of preeclampsia. Exosomes, small extracellular vesicles involved in intercellular communication, carry bioactive molecules that are messengers of the parental cell status (healthy or undergoing any pathological condition). In preeclampsia, alterations in the cargo of VCEssuch as proteins, lipids, and nucleic acids play the role of biomarkers in pathophysiology complications. These exosomal contents can provide insights into the underlying mechanisms, including endothelial dysfunction, immune response dysregulation, and placental abnormalities. Early identification of specific exosomal biomarkers may facilitate timely therapeutic interventions, improving outcomes for both mother and child. This article explores the emerging role of VCEs in preeclampsia, emphasizing their diagnostic and prognostic potential, and underscores the need for further research to validate these biomarkers and integrate them into clinical practice.

A novel algorithm to differentiate between primary lung tumors and distant liver metastasis in lung cancers using an exosome based multi gene biomarker panel

The lack of non-invasive methods for detection of early metastasis is a crucial reason for the poor prognosis of lung cancer (LC) liver metastasis (LM) patients. In this study, the goal was to identify circulating biomarkers based on a biomarker model for the early diagnosis and monitoring of patients with LCLM. An 8-gene panel identified in our previous study was validated in CTC, cfRNA and exosomes isolated from primary lung cancer with & without metastasis. Further multivariate analysis including PCA & ROC was performed to determine the sensitivity and specificity of the biomarker panel. Model validation cohort (n = 79) was used to verify the stability of the constructed predictive model. Further, clinic-pathological factors, survival analysis and immune infiltration correlations were also performed. In comparison to our previous tissue data, exosomes demonstrated a good discriminative value with an AUC of 0.7247, specificity (72.48%) and sensitivity (96.87%) for the 8-gene panel. Further individual gene patterns led us to a 5- gene panel that showed an AUC of 0.9488 (p = < 0.001) and 0.9924 (p = < 0.001) respectively for tissue and exosomes. Additionally, on validating the model in a larger cohort a risk score was obtained (RS > 0.2) for prediction of liver metastasis with an accuracy of 95%. Survival analysis and immune filtration markers suggested that four exosomal markers were independently associated with poor overall survival. We report a novel blood-based exosomal biomarker panel for early diagnosis, monitoring of therapeutic response, and prognostic evaluation of patients with LCLM.

Plasma exosomes contain protein biomarkers valuable for the diagnosis of lung cancer

Accumulating evidence indicates that exosomal proteins are critical in diagnosing malignant tumors. To identify novel exosomal biomarkers for lung cancer diagnosis, we isolated plasma exosomes from 517 lung cancer patients and 168 healthy controls (NLs)—186 lung adenocarcinoma (LUAD) patients (screening (SN): 20, validation (VD): 166), 159 lung squamous carcinoma (LUSC) patients (SN: 20, VD: 139), 172 benign nodules (LUBN) patients (SN: 20, VD: 152) and 168 NLs (SN: 20, VD: 148)—and randomly assigned them to the SN or VD group. Proteomic analysis by LC–MS/MS and PRM were performed on all groups. The candidate humoral markers were evaluated and screened by a machine learning method. All selected biomarkers were identified in the VD groups. For LUAD, a 7-protein panel had AUCs of 97.9% and 87.6% in the training and test sets, respectively, and 89.5% for early LUAD. For LUSC, an 8-protein panel showed AUCs of 99.1% and 87.0% in the training and test sets and 92.3% for early LUSC. For LUAD + LUSC (LC), an 8-protein panel showed AUCs of 85.9% and 80.3% in the training and test sets and 87.1% for early LC diagnosis. The characteristics of the exosomal proteome make exosomes potential diagnostic tools.

Exosomes in the Diagnosis of Neuropsychiatric Diseases: A Review.

Exosomes are 30-150 nm small extracellular vesicles (sEVs) which are highly stable and encapsulated by a phospholipid bilayer. Exosomes contain proteins, lipids, RNAs (mRNAs, microRNAs/miRNAs, long non-coding RNAs/lncRNAs), and DNA of their parent cell. In pathological conditions, the composition of exosomes is altered, making exosomes a potential source of biomarkers for disease diagnosis. Exosomes can cross the blood-brain barrier (BBB), which is an advantage for using exosomes in the diagnosis of central nervous system (CNS) diseases. Neuropsychiatric diseases belong to the CNS diseases, and many potential diagnostic markers have been identified for neuropsychiatric diseases. Here, we review the potential diagnostic markers of exosomes in neuropsychiatric diseases and discuss the potential application of exosomal biomarkers in the early and accurate diagnosis of these diseases. Additionally, we outline the limitations and future directions of exosomes in the diagnosis of neuropsychiatric diseases.

Exosomal Serum Biomarkers as Predictors for Laryngeal Carcinoma.

The lack of screening methods for LSCC is a critical issue, as treatment options and the treatment outcome greatly depend on the stage of LSCC at initial diagnosis. Therefore, the objective of this study was to identify potential exosomal serum biomarkers that can diagnose LSCC and distinguish between early- and late-stage disease. A multiplexed proteomic array was used to identify differentially expressed proteins in exosomes isolated from the serum samples of LSCC patients compared to the control group (septorhinoplasty, SRP). The most promising proteins for diagnosis and differentiation were calculated using biostatistical methods and were validated by immunohistochemistry (IHC), Western blots (WB), and ELISA. Exosomal insulin-like growth factor binding protein 7 (IGFBP7) and Annexin A1 (ANXA1) were the most promising exosomal biomarkers for distinguishing between control and LSCC patients and also between different stages of LSCC (fold change up to 15.9, p < 0.001 for all). The identified proteins represent potentially novel non-invasive biomarkers. However, these results need to be validated in larger cohorts with a long-term follow-up. Exosomal biomarkers show a superior signal-to-noise ratio compared to whole serum and may therefore be an important tool for non-invasive biomarker profiling for laryngeal carcinoma in the future.

Potential Exosome Biomarkers for Parkinson's Disease Diagnosis: A Systematic Review and Meta-Analysis.

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. Given its prevalence, reliable biomarkers for early diagnosis are required. Exosomal proteins within extracellular nanovesicles are promising candidates for diagnostic, screening, prognostic, and disease monitoring purposes in neurological diseases such as PD. This review aims to evaluate the potential of extracellular vesicle proteins or miRNAs as biomarkers for PD. A comprehensive literature search until January 2024 was conducted across multiple databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, to identify relevant studies reporting exosome biomarkers in blood samples from PD patients. Out of 417 articles screened, 47 studies were selected for analysis. Among exosomal protein biomarkers, α-synuclein, tau, Amyloid β 1-42, and C-X-C motif chemokine ligand 12 (CXCL12) were identified as significant markers for PD. Concerning miRNA biomarkers, miRNA-24, miR-23b-3p, miR-195-3p, miR-29c, and mir-331-5p are promising across studies. α-synuclein exhibited increased levels in PD patients compared to control groups in twenty-one studies, while a decrease was observed in three studies. Our meta-analysis revealed a significant difference in total exosomal α-synuclein levels between PD patients and healthy controls (standardized mean difference [SMD] = 1.369, 95% confidence interval [CI] = 0.893 to 1.846, p < 0.001), although these results are limited by data availability. Furthermore, α-synuclein levels significantly differ between PD patients and healthy controls (SMD = 1.471, 95% CI = 0.941 to 2.002, p < 0.001). In conclusion, certain exosomal proteins and multiple miRNAs could serve as potential biomarkers for diagnosis, prognosis prediction, and assessment of disease progression in PD.

APPROACH: Sensitive Detection of Exosomal Biomarkers by Aptamer-Mediated Proximity Ligation Assay and Time-Resolved Förster Resonance Energy Transfer.

Exosomal biomarker detection holds great importance in the field of in vitro diagnostics, offering a non-invasive and highly sensitive approach for early disease detection and personalized treatment. Here, we proposed an "APPROACH" strategy, combining aptamer-mediated proximity ligation assay (PLA) with rolling circle amplification (RCA) and time-resolved Förster resonance energy transfer (TR-FRET) for the sensitive and semi-homogenous detection of exosomal biomarkers. PLA probes consisted of a cholesterol-conjugated oligonucleotide, which anchored to the membrane of an exosome, and a specific aptamer oligonucleotide that recognized a target protein of the exosome; the proximal binding of pairs of PLA probes to the same exosome positioned the oligonucleotides in the vicinity of each other, guiding the hybridization and ligation of two subsequently added backbone and connector oligonucleotides to form a circular DNA molecule. Circular DNA formed from PLA underwent rolling circle amplification (RCA) for signal amplification, and the resulting RCA products were subsequently quantified by TR-FRET. The limits of detection provided by APPROACH for the exosomal biomarkers CD63, PD-L1, and HER2 were 0.46 ng∙μL-1, 0.77 ng∙μL-1, and 1.1 ng∙μL-1, respectively, demonstrating excellent analytical performance with high sensitivity and quantification accuracy. Furthermore, the strategy afforded sensitive detection of exosomal CD63 with a LOD of 1.56 ng∙μL-1 in complex biological matrices, which underscored its anti-interference capability and potential for in vitro detection. The proposed strategy demonstrates wide-ranging applicability in quantifying diverse exosomal biomarkers while exhibiting robust analytical characteristics, including high sensitivity and accuracy.

Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers

Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer. However, some patients develop resistance to this therapy; therefore, monitoring its efficacy is essential. Here, we describe a deep learning-assisted monitoring of trastuzumab efficacy based on a surface-enhanced Raman spectroscopy (SERS) immunoassay against HER2-overexpressing mouse urinary exosomes. Individual Raman reporters bearing the desired SERS tag and exosome capture substrate were prepared for the SERS immunoassay; SERS tag signals were collected to prepare deep learning training data. Using this deep learning algorithm, various complicated mixtures of SERS tags were successfully quantified and classified. Exosomal antigen levels of five types of cell-derived exosomes were determined using SERS-deep learning analysis and compared with those obtained via quantitative reverse transcription polymerase chain reaction and western blot analysis. Finally, drug efficacy was monitored via SERS-deep learning analysis using urinary exosomes from trastuzumab-treated mice. Use of this monitoring system should allow proactive responses to any treatment-resistant issues.

Transferrin-conjugated magnetic nanoparticles for the isolation of brain-derived blood exosomal MicroRNAs: A novel approach for Parkinson's disease diagnosis

BackgroundBrain-derived exosomes circulate in the bloodstream and other bodily fluids, serving as potential indicators of neurological disease progression. These exosomes present a promising avenue for the early and precise diagnosis of neurodegenerative conditions. Notably, miRNAs found in plasma extracellular vesicles (EVs) offer distinct diagnostic benefits due to their stability, abundance, and resistance to breakdown. ResultsIn this study, we introduce a method using transferrin conjugated magnetic nanoparticles (TMNs) to isolate these exosomes from the plasma of patients with neurological disorders. This TMNs technique is both quick (<35 min) and cost-effective, requiring no high-priced ingredients or elaborate equipment for EV extraction. Our method successfully isolated EVs from 33 human plasma samples, including those from patients with Parkinson's disease (PD), Multiple Sclerosis (MS), and Dementia. Using quantitative polymerase chain reaction (PCR) analysis, we evaluated the potential of 8 exosomal miRNA profiles as biomarker candidates. Six exosomal miRNA biomarkers (miR-195-5p, miR-495-3p, miR-23b-3P, miR-30c-2-3p, miR-323a-3p, and miR-27a-3p) were consistently linked with all stages of PD. SignificanceThe TMNs method provides a practical, cost-efficient way to isolate EVs from biological samples, paving the way for non-invasive neurological diagnoses. Furthermore, the identified miRNA biomarkers in these exosomes may emerge as innovative tools for precise diagnosis in neurological disorders including PD.

Exosomes for neurodegenerative diseases: diagnosis and targeted therapy.

Neurodegenerative diseases are still challenging clinical issues, with no curative interventions available and early, accurate diagnosis remaining difficult. Finding solutions to them is of great importance. In this review, we discuss possible exosomal diagnostic biomarkers and explore current explorations in exosome-targeted therapy for some common neurodegenerative diseases, offering insights into the clinical transformation of exosomes in this field. The burgeoning research on exosomes has shed light on their potential applications in disease diagnosis and treatment. As a type of extracellular vesicles, exosomes are capable of crossing the blood - brain barrier and exist in various body fluids, whose components can reflect pathophysiological changes in the brain. In addition, they can deliver specific drugs to brain tissue, and even possess certain therapeutic effects themselves. And the recent advancements in engineering modification technology have further enabled exosomes to selectively target specific sites, facilitating the possibility of targeted therapy for neurodegenerative diseases. The unique properties of exosomes give them great potential in the diagnosis and treatment of neurodegenerative diseases, and provide novel ideas for dealing with such diseases.

Sensitive detection of multiple blood biomarkers via immunomagnetic exosomal PCR for the diagnosis of Alzheimer's disease.

Blood exosomes are emerging as potential biomarkers for diagnosing brain diseases such as Alzheimer's disease (AD). There is currently a lack of an ultrasensitive technology for identifying core AD biomarkers in blood exosomes to optimize the utility of biomarkers in clinical practice. Here, an immunomagnetic exosomal polymerase chain reaction (iMEP) platform was developed using DNA-conjugated antibodies for the rapid detection of amyloid-β (Aβ1-40 and Aβ1-42) and phosphorylated tau (p-tau396,404 and p-tau181) in clinical blood exosomes. The toehold shift-mediated DNA affinity pulldown eliminates the high detection background, which allows the detection of biomarkers at concentrations down to 10 femtograms per milliliter. With the iMEP assay, exosomal Aβ1-42 was more accurate in differentiating patients with AD from healthy individuals compared with exosomal p-tau181 and p-tau396,404, with a sensitivity of 95.0% and a specificity of 95.0%. The iMEP technique is also adept at quantifying the levels of different exosomal biomarkers associated with disease pathogenesis.

Identification of Plasma Exosomes hsa_circ_0001360 and hsa_circ_0000038 as Key Biomarkers of Coronary Heart Disease.

Coronary heart disease (CHD) is the leading cause of death and disability worldwide. Accumulating evidence reveals that atherosclerosis (AS), characterized by systemic, chronic, and multifocal disease, and is the primary pathological basis of cardiovascular diseases, including CHD. However, the molecular underpinnings of CHD are still far from well understood. Our study attempted to identify aberrant plasma exosome-derived circRNAs and key exosomal circRNA biomarkers for CHD. The expression profiles of mRNAs, circRNAs, and lncRNAs in the blood exosomes of CHD patients and healthy controls were obtained from the exoRBase database. The corresponding miRNAs of the differentially expressed mRNAs, circRNAs, and lncRNAs were predicted via ENCORI and the miRcode database. LncRNAs/circRNAs and mRNAs with the cotargeted miRNAs were selected to construct an interaction network. Multiple machine learning algorithms have been used to explore potential biomarkers, followed by verification in patients with CHD using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Based on the cutoff criterion of P < 0.05, we identified 85 differentially expressed circRNAs (4 upregulated and 81 downregulated), 43 differentially expressed lncRNAs (24 upregulated and 19 downregulated), and 312 differentially expressed mRNAs (55 upregulated and 257 downregulated). Functional enrichment analysis revealed that the differentially expressed mRNAs were involved mainly in neutrophil extracellular trap (NET) formation and the nucleotide-binding oligomerization domain- (NOD-) like receptor signaling pathway. Further analysis revealed that the DEGs in the circRNA/lncRNA-miRNA-mRNA interaction network were closely related to lipid and atherosclerotic signaling pathways. Hsa_circ_0001360 and hsa_circ_0000038 were identified as potential biomarkers for CHD based on three machine learning algorithms. The relative expression levels of hsa_circ_0001360 and hsa_circ_0000038 were significantly altered in plasma exosomes from patients with CHD. ROC curve analysis revealed that the areas under the curve (AUCs) were 0.860, 0.870, and 0.940 for hsa_circ_0001360, hsa_circ_0000038, and the two-gene combination, respectively. The circRNA/lncRNA-miRNA-mRNA interaction network might help to elucidate the pathogenesis of CHD. Hsa_circ_0001360 combined with hsa_circ_0000038 might be an important diagnostic biomarker.

Utilizing Magnetic Levitation to Detect Lung Cancer-Associated Exosomes.

Extracellular vesicles, especially exosomes, have attracted attention in the last few decades as novel cancer biomarkers. Exosomal membrane proteins provide easy-to-reach targets and can be utilized as information sources of their parent cells. In this study, a MagLev-based, highly sensitive, and versatile biosensor platform for detecting minor differences in the density of suspended objects is proposed for exosome detection. The developed platform utilizes antibody-functionalized microspheres to capture exosomal membrane proteins (ExoMPs) EpCAM, CD81, and CD151 as markers for cancerous exosomes, exosomes, and non-small cell lung cancer (NSCLC)-derived exosomes, respectively. Initially, the platform was utilized for protein detection and quantification by targeting solubilized ExoMPs, and a dynamic range of 1-100 nM, with LoD values of 1.324, 0.638, and 0.722 nM for EpCAM, CD81, and CD151, were observed, respectively. Then, the sensor platform was tested using exosome isolates derived from NSCLC cell line A549 and MRC5 healthy lung fibroblast cell line. It was shown that the sensor platform is able to detect and differentiate exosomal biomarkers derived from cancerous and non-cancerous cell lines. Overall, this innovative, simple, and rapid method shows great potential for the early diagnosis of lung cancer through exosomal biomarker detection.