Profile of matrix-entrapped extracellular vesicles of microenvironmental and infiltrating cell origin in decellularized colorectal cancer and adjacent mucosa.

Cellular elements that infiltrate and surround tumours and pre-metastatic tissues have a prominent role in tumour invasion and growth. The extracellular vesicles specifically entrapped and stored within the extracellular matrix (ECM-EVs) may reflect the different populations of the tumour microenvironment and their change during tumour progression. However, their profile is at present unknown. To elucidate this aspect, we isolated and characterized EVs from decellularized surgical specimens of colorectal cancer and adjacent colon mucosa and analyzed their surface marker profile. ECM-EVs in tumours and surrounding mucosa mainly expressed markers of lymphocytes, natural killer cells, antigen-presenting cells, and platelets, as well as epithelial cells, representing a multicellular microenvironment. No difference in surface marker expression was observed between tumour and mucosa ECM-EVs in stage II-III tumours. At variance, in the colon mucosa adjacent to stage IV carcinomas, ECM-EV profile showed a significantly increased level of immune, epithelial and platelet markers in comparison to the matrix of the corresponding tumour. The increase of EVs from immune cells and platelets was not observed in the mucosa adjacent to low-stage tumours. In addition, CD25, a T-lymphocyte marker, resulted specifically overexpressed by ECM-EVs from stage IV carcinomas, possibly correlated with the pro-tolerogenic environment found in the corresponding tumour tissue. These results outline the tissue microenvironmental profile of EVs in colorectal carcinoma-derived ECM and unveil a profound change in the healthy mucosa adjacent to high-stage tumours.

Comparison of assays measuring extracellular vesicle-tissue factor in plasma samples: Communication from the ISTH SSC Subcommittee on Vascular Biology.

BACKGROUND: Scientific and clinical interest in extracellular vesicles (EVs) is growing. EVs that expose tissue factor (TF) bind factor VII/VIIa and can trigger coagulation. Highly procoagulant TF-exposing EVs are detectable in the circulation in various diseases, such as sepsis, COVID-19 or cancer. Many in-house and commercially available assays have been developed to measure EV-TF activity and antigen but only a few studies have compared some of these assays. The ISTH SSC Subcommittee on Vascular Biology initiated a multicenter study to compare the sensitivity, specificity and reproducibility of these assays. MATERIALS AND METHODS: Platelet-depleted plasma samples were prepared from blood of healthy donors. The plasma samples were spiked either with EVs from human milk, or EVs from TF-positive and TF-negative cell lines. Plasma was also prepared from whole human blood with or without LPS stimulation. Twenty-one laboratories measured EV-TF activity and antigen in the prepared samples using their own assays representing 18 functional and 9 antigenic assays. RESULTS: There was a large variability in the absolute values for the different EV-TF activity and antigen assays. Activity assays had higher specificity and sensitivity compared to antigen assays. In addition, there was a large intra-assay and inter-assay variability. Functional assays that used a blocking anti-TF antibody or immunocapture were the most specific and sensitive. Activity assays that used immunocapture had a lower coefficient of variation compared to assays that isolated EVs by high-speed centrifugation. CONCLUSION: Based on this multicenter study, we recommend measuring EV-TF using a functional assay in the presence of an anti-TF antibody.

Addressing Heterogeneity in Direct Analysis of Extracellular Vesicles and Their Analogs by Membrane Sensing Peptides as Pan-Vesicular Affinity Probes.

Extracellular vesicles (EVs), crucial mediators of cell-to-cell communication, hold significant diagnostic potential due to their ability to concentrate protein biomarkers in bodily fluids. However, challenges in isolating EVs from biological specimens hinder their widespread use. The preferred strategy involves direct analysis, integrating isolation and analysis solutions, with immunoaffinity methods currently dominating. Yet, the heterogeneous nature of EVs poses challenges, as proposed markers may not be as universally present as thought, raising concerns about biomarker screening reliability. This issue extends to EV-mimics, where conventional methods may lack applicability. Addressing these challenges, the study reports on Membrane Sensing Peptides (MSP) as pan-vesicular affinity ligands for both EVs and their non-canonical analogs, streamlining capture and phenotyping through Single Molecule Array (SiMoA). MSP ligands enable direct analysis of circulating EVs, eliminating the need for prior isolation. Demonstrating clinical translation, MSP technology detects an EV-associated epitope signature in serum and plasma, distinguishing myocardial infarction from stable angina. Additionally, MSP allow analysis of tetraspanin-lacking Red Blood Cell-derived EVs, overcoming limitations associated with antibody-based methods. Overall, the work underlines the value of MSP as complementary tools to antibodies, advancing EV analysis for clinical diagnostics and beyond, and marking the first-ever peptide-based application in SiMoA technology.

Unilateral Primary Aldosteronism: Long-Term Disease Recurrence After Adrenalectomy.

BACKGROUND: Primary aldosteronism (PA) is frequently caused by a unilateral aldosterone-producing adenoma with a PA-driver mutation. Unilateral adrenalectomy has a high probability of short-term biochemical remission, but long-term postsurgical outcomes are relatively undefined. Our objective was to investigate the incidence of long-term recurrence of PA in individuals with postsurgical short-term biochemical remission. METHODS: Adrenalectomized patients for unilateral PA were included from a single referral center. Histopathology and outcomes were assessed according to international histopathology of unilateral primary aldosteronism and PASO (Primary Aldosteronism Surgical Outcome) consensuses. Genotyping was performed using CYP11B2 (aldosterone synthase)-guided sequencing. RESULTS: Classical adrenal histopathology, exemplified by a solitary aldosterone-producing adenoma, was observed in 78% of 90 adrenals, compared with 22% with nonclassical histopathology. The classical group displayed higher aldosterone-to-renin ratios (P=0.013) and lower contralateral ratios (P=0.008). Outcome assessments at both short (12 months [7; 12]) and long (89 months [48; 124]) terms were available for 57 patients. At short-term assessment, 53 (93%) displayed complete biochemical success (43 classical and 10 nonclassical), but long-term assessment demonstrated biochemical PA recurrence in 12 (23%) with an overrepresentation of the nonclassical histopathology (6 [60%] of 10 nonclassical histopathology versus 6 [14%] of 43 classical histopathology; P=0.005). PA-driver mutations were identified in 97% of 64 aldosterone-producing adenomas; there was no association of the aldosterone-producing adenoma genotype with PA recurrence. CONCLUSIONS: A substantial proportion of individuals display postsurgical biochemical recurrence of PA, which is related to the histopathology of the resected adrenal gland. These findings emphasize the role of histopathology and the requirement for continued outcome assessment in the management of surgically treated patients for PA.

A dynamic clamping approach using in silico IK1 current for discrimination of chamber-specific hiPSC-derived cardiomyocytes.

Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CM) constitute a mixed population of ventricular-, atrial-, nodal-like cells, limiting the reliability for studying chamber-specific disease mechanisms. Previous studies characterised CM phenotype based on action potential (AP) morphology, but the classification criteria were still undefined. Our aim was to use in silico models to develop an automated approach for discriminating the electrophysiological differences between hiPSC-CM. We propose the dynamic clamp (DC) technique with the injection of a specific IK1 current as a tool for deriving nine electrical biomarkers and blindly classifying differentiated CM. An unsupervised learning algorithm was applied to discriminate CM phenotypes and principal component analysis was used to visualise cell clustering. Pharmacological validation was performed by specific ion channel blocker and receptor agonist. The proposed approach improves the translational relevance of the hiPSC-CM model for studying mechanisms underlying inherited or acquired atrial arrhythmias in human CM, and for screening anti-arrhythmic agents.

Erratum: Inflammatory extracellular vesicles prompt heart dysfunction via TLR4-dependent NF-κB activation: Erratum.

[This corrects the article DOI: 10.7150/thno.39072.].

Identification of a serum and urine extracellular vesicle signature predicting renal outcome after kidney transplant.

BACKGROUND: A long-standing effort is dedicated towards the identification of biomarkers allowing the prediction of graft outcome after kidney transplant. Extracellular vesicles (EVs) circulating in body fluids represent an attractive candidate, as their cargo mirrors the originating cell and its pathophysiological status. The aim of the study was to investigate EV surface antigens as potential predictors of renal outcome after kidney transplant. METHODS: We characterized 37 surface antigens by flow cytometry, in serum and urine EVs from 58 patients who were evaluated before, and at 10-14 days, 3 months and 1 year after transplant, for a total of 426 analyzed samples. The outcome was defined according to estimated glomerular filtration rate (eGFR) at 1 year. RESULTS: Endothelial cells and platelets markers (CD31, CD41b, CD42a and CD62P) in serum EVs were higher at baseline in patients with persistent kidney dysfunction at 1 year, and progressively decreased after kidney transplant. Conversely, mesenchymal progenitor cell marker (CD1c, CD105, CD133, SSEEA-4) in urine EVs progressively increased after transplant in patients displaying renal recovery at follow-up. These markers correlated with eGFR, creatinine and proteinuria, associated with patient outcome at univariate analysis and were able to predict patient outcome at receiver operating characteristics curves analysis. A specific EV molecular signature obtained by supervised learning correctly classified patients according to 1-year renal outcome. CONCLUSIONS: An EV-based signature, reflecting the cardiovascular profile of the recipient, and the repairing/regenerative features of the graft, could be introduced as a non-invasive tool for a tailored management of follow-up of patients undergoing kidney transplant.

De novo DNA methylation induced by circulating extracellular vesicles from acute coronary syndrome patients.

BACKGROUND AND AIMS: DNA methylation is associated with gene silencing, but its clinical role in cardiovascular diseases (CVDs) remains to be elucidated. We hypothesized that extracellular vesicles (EVs) may carry epigenetic changes, showing themselves as a potentially valuable non-invasive diagnostic liquid biopsy. We isolated and characterized circulating EVs of acute coronary syndrome (ACS) patients and assessed their role on DNA methylation in epigenetic modifications. METHODS: EVs were recovered from plasma of 19 ACS patients and 50 healthy subjects (HS). Flow cytometry, qRT-PCR, and Western blot (WB) were performed to evaluate both intra-vesicular and intra-cellular signals. ShinyGO, PANTHER, and STRING tools were used to perform GO and PPI network analyses. RESULTS: ACS-derived EVs showed increased levels of DNA methyltransferases (DNMTs) (p<0.001) and Ten-eleven translocation (TET) genes reduction. Specifically, de novo methylation transcripts, as DNMT3A and DNMT3B, were significantly increased in plasma ACS-EVs. DNA methylation analysis on PBMCs from healthy donors treated with HS- and ACS-derived EVs showed an important role of DNMTs carried by EVs. PPI network analysis evidenced that ACS-EVs induced changes in PBMC methylome. In the most enriched subnetwork, the hub gene SRC was connected to NOTCH1, FOXO3, CDC42, IKBKG, RXRA, DGKG, BAIAP2 genes that were showed to have many molecular effects on various cell types into onset of several CVDs. Modulation in gene expression after ACS-EVs treatment was confirmed for SRC, NOTCH1, FOXO3, RXRA, DGKG and BAIAP2 (p<0.05). CONCLUSIONS: Our data showed an important role for ACS-derived EVs in gene expression modulation through de novo DNA methylation signals, and modulating signalling pathways in target cells.

Prediction of All-Cause Mortality Following Percutaneous Coronary Intervention in Bifurcation Lesions Using Machine Learning Algorithms.

Stratifying prognosis following coronary bifurcation percutaneous coronary intervention (PCI) is an unmet clinical need that may be fulfilled through the adoption of machine learning (ML) algorithms to refine outcome predictions. We sought to develop an ML-based risk stratification model built on clinical, anatomical, and procedural features to predict all-cause mortality following contemporary bifurcation PCI. Multiple ML models to predict all-cause mortality were tested on a cohort of 2393 patients (training, n = 1795; internal validation, n = 598) undergoing bifurcation PCI with contemporary stents from the real-world RAIN registry. Twenty-five commonly available patient-/lesion-related features were selected to train ML models. The best model was validated in an external cohort of 1701 patients undergoing bifurcation PCI from the DUTCH PEERS and BIO-RESORT trial cohorts. At ROC curves, the AUC for the prediction of 2-year mortality was 0.79 (0.74-0.83) in the overall population, 0.74 (0.62-0.85) at internal validation and 0.71 (0.62-0.79) at external validation. Performance at risk ranking analysis, k-center cross-validation, and continual learning confirmed the generalizability of the models, also available as an online interface. The RAIN-ML prediction model represents the first tool combining clinical, anatomical, and procedural features to predict all-cause mortality among patients undergoing contemporary bifurcation PCI with reliable performance.

Risk stratification of patients with SARS-CoV-2 by tissue factor expression in circulating extracellular vesicles.

Inflammatory response following SARS-CoV-2 infection results in substantial increase of amounts of intravascular pro-coagulant extracellular vesicles (EVs) expressing tissue factor (CD142) on their surface. CD142-EV turned out to be useful as diagnostic biomarker in COVID-19 patients. Here we aimed at studying the prognostic capacity of CD142-EV in SARS-CoV-2 infection. Expression of CD142-EV was evaluated in 261 subjects admitted to hospital for pneumonia and with a positive molecular test for SARS-CoV-2. The study population consisted of a discovery cohort of selected patients (n = 60) and an independent validation cohort including unselected consecutive enrolled patients (n = 201). CD142-EV levels were correlated with post-hospitalization course of the disease and compared to the clinically available 4C Mortality Score as referral. CD142-EV showed a reliable performance to predict patient prognosis in the discovery cohort (AUC = 0.906) with an accuracy of 81.7%, that was confirmed in the validation cohort (AUC = 0.736). Kaplan-Meier curves highlighted a high discrimination power in unselected subjects with CD142-EV being able to stratify the majority of patients according to their prognosis. We obtained a comparable accuracy, being not inferior in terms of prediction of patients' prognosis and risk of mortality, with 4C Mortality Score. The expression of surface vesicular CD142 and its reliability as prognostic marker was technically validated using different immunocapture strategies and assays. The detection of CD142 on EV surface gains considerable interest as risk stratification tool to support clinical decision making in COVID-19.

Supervised and unsupervised learning to define the cardiovascular risk of patients according to an extracellular vesicle molecular signature.

Cardiovascular (CV) disease represents the most common cause of death in developed countries. Risk assessment is highly relevant to intervene at individual level and implement prevention strategies. Circulating extracellular vesicles (EVs) are involved in the development and progression of CV diseases and are considered promising biomarkers. We aimed at identifying an EV signature to improve the stratification of patients according to CV risk and likelihood to develop fatal CV events. EVs were characterized by nanoparticle tracking analysis and flow cytometry for a standardized panel of 37 surface antigens in a cross-sectional multicenter cohort (n = 486). CV profile was defined by presence of different indicators (age, sex, body mass index, hypertension, hyperlipidemia, diabetes, coronary artery disease, cardiac heart failure, chronic kidney disease, smoking habit, organ damage) and according to the 10-year risk of fatal CV events estimated using SCORE charts of European Society of Cardiology. By combining expression levels of EV antigens using unsupervised learning, patients were classified into 3 clusters: Cluster-I (n = 288), Cluster-II (n = 83), Cluster-III (n = 30). A separate analysis was conducted on patients displaying acute CV events (n = 82). Prevalence of hypertension, diabetes, chronic heart failure, and organ damage (defined as left ventricular hypertrophy and/or microalbuminuria) increased progressively from Cluster-I to Cluster-III. Several EV antigens, including markers for platelets (CD41b-CD42a-CD62P), leukocytes (CD1c-CD2-CD3-CD4-CD8-CD14-CD19-CD20-CD25-CD40-CD45-CD69-CD86), and endothelium (CD31-CD105) were independently associated with CV risk indicators and correlated to age, blood pressure, glucometabolic profile, renal function, and SCORE risk. EV profiling, obtained from minimally invasive blood sampling, allows accurate patient stratification according to CV risk profile.

A Multicenter Epidemiological Study on Second Malignancy in Non-Syndromic Pheochromocytoma/Paraganglioma Patients in Italy.

No studies have carried out an extensive analysis of the possible association between non-syndromic pheochromocytomas and paragangliomas (PPGLs) and other malignancies. To assess >the risk of additional malignancy in PPGL, we retrospectively evaluated 741 patients with PPGLs followed-up in twelve referral centers in Italy. Incidence of second malignant tumors was compared between this cohort and Italian patients with two subsequent malignancies. Among our patients, 95 (12.8%) developed a second malignant tumor, which were mainly prostate, colorectal and lung/bronchial cancers in males, breast cancer, differentiated thyroid cancer and melanoma in females. The standardized incidence ratio was 9.59 (95% CI 5.46-15.71) in males and 13.21 (95% CI 7.52-21.63) in females. At multivariable analysis, the risk of developing a second malignant tumor increased with age at diagnosis (HR 2.50, 95% CI 1.15-5.44, p = 0.021 for 50-59 vs. <50-year category; HR 3.46, 95% CI 1.67-7.15, p < 0.001 for >60- vs. <50-year). In patients with available genetic evaluation, a positive genetic test was inversely associated with the risk of developing a second tumor (HR 0.25, 95% CI 0.10-0.63, p = 0.003). In conclusion, PPGLs patients have higher incidence of additional malignant tumors compared to the general population who had a first malignancy, which could have an impact on the surveillance strategy.

Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension.

[Figure: see text].

Extracellular Vesicle Surface Markers as a Diagnostic Tool in Transient Ischemic Attacks.

Background and Purpose: Extracellular vesicles (EVs) are promising biomarkers for cerebral ischemic diseases, but not systematically tested in patients with transient ischemic attacks (TIAs). We aimed at (1) investigating the profile of EV-surface antigens in patients with symptoms suspicious for TIA; (2) developing and validating a predictive model for TIA diagnosis based on a specific EV-surface antigen profile. Methods: We analyzed 40 subjects with symptoms suspicious for TIA and 20 healthy controls from a training cohort. An independent cohort of 28 subjects served as external validation. Patients were stratified according to likelihood of having a real ischemic event using the Precise Diagnostic Score, defined as: unlikely (score 0­1), possible-probable (score 2­3), or very likely (score 4­8). Serum vesicles were quantified by nanoparticle tracking analysis and EV-surface antigen profile characterized by multiplex flow cytometry. Results: EV concentration increased in patients with very likely or possible-probable TIA (P<0.05) compared with controls. Nanoparticle concentration was directly correlated with the Precise Diagnostic score (R=0.712; P<0.001). After EV immuno-capturing, CD8, CD2, CD62P, melanoma-associated chondroitin sulfate proteoglycan, CD42a, CD44, CD326, CD142, CD31, and CD14 were identified as discriminants between groups. Receiver operating characteristic curve analysis confirmed a reliable diagnostic performance for each of these markers taken individually and for a compound marker derived from their linear combinations (area under the curve, 0.851). Finally, a random forest model combining the expression levels of selected markers achieved an accuracy of 96% and 78.9% for discriminating patients with a very likely TIA, in the training and external validation cohort, respectively. Conclusions: The EV-surface antigen profile appears to be different in patients with transient symptoms adjudicated to be very likely caused by brain ischemia compared with patients whose symptoms were less likely to due to brain ischemia. We propose an algorithm based on an EV-surface-antigen specific signature that might aid in the recognition of TIA.

Characterization of Circulating Extracellular Vesicle Surface Antigens in Patients With Primary Aldosteronism.

[Figure: see text].

Assessment of Anti-Hypertensive Drug Adherence by Serial Aldosterone-To-Renin Ratio Measurement.

Reduced or absent compliance to anti-hypertensive treatment is a major obstacle to the achievement of blood pressure target in patients with arterial hypertension. Current available methods for therapeutic adherence assessment display low accuracy, limited applicability in clinical practice and/or high costs. We designed a prospective study to evaluate the accuracy of serial measurement of ARR to assess the therapeutic compliance to RAAS inhibitors. We prospectively enrolled 80 subjects: 40 patients with arterial hypertension and 40 normotensive controls. The ARR was evaluated at baseline and 2 and 8 week after initiation of a RAAS inhibitor in patients with hypertension, and at baseline and 2 weeks for the control group. Adherence to the prescribed therapy was confirmed by therapeutic drug monitoring. We observed a significant increase of renin levels and reduction of aldosterone levels after RAAS inhibitors initiation, with consequent reduction of ARR. Delta ARR (ΔARR), defined as relative change in ARR before and after treatment initiation, provided high accuracy for determination of therapeutic compliance, with an AUC of 0.900 at 2 weeks and 0.886 at 8 weeks. A cut-off of -48% of ΔARR provided 90% sensitivity and 75% specificity, at 2 and 8 weeks. In conclusion, the measurement of ΔARR is a powerful test, cheap and widely available to accurately identify the non-adherence to RAAS inhibitors treatment. Herein we propose the implementation of ΔARR in clinical practice through a multi-step flow-chart for the management of patients with uncontrolled blood pressure, with identification of those suspected of non-adherence, reserving therapeutic drug monitoring for non-adherence confirmation.

Circulating extracellular vesicles are endowed with enhanced procoagulant activity in SARS-CoV-2 infection.

BACKGROUND: Coronavirus-2 (SARS-CoV-2) infection causes an acute respiratory syndrome accompanied by multi-organ damage that implicates a prothrombotic state leading to widespread microvascular clots. The causes of such coagulation abnormalities are unknown. The receptor tissue factor, also known as CD142, is often associated with cell-released extracellular vesicles (EV). In this study, we aimed to characterize surface antigens profile of circulating EV in COVID-19 patients and their potential implication as procoagulant agents. METHODS: We analyzed serum-derived EV from 67 participants who underwent nasopharyngeal swabs molecular test for suspected SARS-CoV-2 infection (34 positives and 33 negatives) and from 16 healthy controls (HC), as referral. A sub-analysis was performed on subjects who developed pneumonia (n = 28). Serum-derived EV were characterized for their surface antigen profile and tested for their procoagulant activity. A validation experiment was performed pre-treating EV with anti-CD142 antibody or with recombinant FVIIa. Serum TNF-α levels were measured by ELISA. FINDINGS: Profiling of EV antigens revealed a surface marker signature that defines circulating EV in COVID-19. A combination of seven surface molecules (CD49e, CD209, CD86, CD133/1, CD69, CD142, and CD20) clustered COVID (+) versus COVID (-) patients and HC. CD142 showed the highest discriminating performance at both multivariate models and ROC curve analysis. Noteworthy, we found that CD142 exposed onto surface of EV was biologically active. CD142 activity was higher in COVID (+) patients and correlated with TNF-α serum levels. INTERPRETATION: In SARS-CoV-2 infection the systemic inflammatory response results in cell-release of substantial amounts of procoagulant EV that may act as clotting initiation agents, contributing to disease severity. FUNDING: Cardiocentro Ticino Institute, Ente ospedaliero Cantonale, Lugano-Switzerland.