Addressing Heterogeneity in direct analysis of Extracellular Vesicles and analogues using Membrane-Sensing Peptides as Pan-Affinity Probes DOI Creative Commons
Alessandro Gori, Roberto Frigerio, Paola Gagni

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 20, 2023

Abstract Extracellular vesicles (EVs), crucial mediators of cell-to-cell communication, hold immense potential for diagnostic applications due to their ability enrich protein biomarkers in body fluids. However, challenges isolating EVs from complex biological specimens hinder widespread use. In this frame, integrated isolation-and-analysis workflows are the go-to strategy, most which see prevalence immunoaffinity methods. Yet, high heterogeneity poses challenges, as proposed ubiquitous markers less homogenously prevalent than believed, raising concerns about reliability downstream biomarker discovery programs. This issue extends burgeoning field engineered EV-mimetics and bio-nanoparticles, where conventional immune-affinity methods may lack applicability. Addressing these we introduce use Membrane Sensing Peptides (MSP) “universal” affinity ligands both EV-analogues. Employing a streamlined process integrating on-bead capture vesicle phenotyping through Single Molecule Array (SiMoA) technology, showcase application MSP analysis circulating blood derivatives, eliminating need prior EV isolation. Demonstrating possible clinical translation directly detect an EV-associated epitope signature serum plasma samples, demonstrating its distinguishing patients with myocardial infarction versus stable angina. At last, notably, exhibits unique capability enable tetraspanin-lacking Red Blood Cell derived (RBC-EVs). Overall, unlike traditional antibody-based methods, probes work agnostically, overcoming limitations associated surface abundance or scarcity. highlights advancing diagnostics beyond. Of note, represents also first-ever peptide-based SiMoA technology.

Language: Английский

Thermophoretic glycan profiling of extracellular vesicles for triple-negative breast cancer management DOI Creative Commons
Yike Li, Shaohua Zhang, Chao Liu

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 14, 2024

Abstract Triple-negative breast cancer (TNBC) is a highly metastatic and heterogeneous type of with poor outcomes. Precise, non-invasive methods for diagnosis, monitoring prognosis TNBC are particularly challenging due to paucity biomarkers. Glycans on extracellular vesicles (EVs) hold the promise as valuable biomarkers, but conventional glycan analysis not feasible in clinical practice. Here, we report that lectin-based thermophoretic assay (EVLET) streamlines vibrating membrane filtration (VMF) amplification, allowing rapid, sensitive, selective cost-effective EV profiling plasma. A pilot cohort study shows signature reaches 91% accuracy detection 96% longitudinal therapeutic response. Moreover, demonstrate potential predicting progression. Our EVLET system lays foundation management by glycans.

Language: Английский

Citations

26
Revolutionary Point‐of‐Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies DOI Creative Commons
Fatemeh Haghayegh,

Alireza Norouziazad,

Elnaz Haghani

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: unknown

Published: July 3, 2024

Early-stage disease detection, particularly in Point-Of-Care (POC) wearable formats, assumes pivotal role advancing healthcare services and precision-medicine. Public benefits of early detection extend beyond cost-effectively promoting outcomes, to also include reducing the risk comorbid diseases. Technological advancements enabling POC biomarker recognition empower discovery new markers for various health conditions. Integration wearables with intelligent frameworks represents ground-breaking innovations automation operations, conducting advanced large-scale data analysis, generating predictive models, facilitating remote guided clinical decision-making. These substantially alleviate socioeconomic burdens, creating a paradigm shift diagnostics, revolutionizing medical assessments technology development. This review explores critical topics recent progress development 1) systems solutions physiological monitoring, as well 2) discussing current trends adoption smart technologies within settings developing biological assays, ultimately 3) exploring utilities platforms discovery. Additionally, translation from research labs broader applications. It addresses associated risks, biases, challenges widespread Artificial Intelligence (AI) integration diagnostics systems, while systematically outlining potential prospects, challenges, opportunities.

Language: Английский

Citations

24
An electrochemical biosensor designed with entropy-driven autocatalytic DNA circuits for sensitive detection of ovarian cancer-derived exosomes DOI
Ying Deng,

Tianci Zhou,

Kai Hu

et al.

Biosensors and Bioelectronics, Journal Year: 2024, Volume and Issue: 250, P. 116060 - 116060

Published: Jan. 23, 2024

Language: Английский

Citations

18
Ovarian Cancer Screening: Where Do We Stand Now ? DOI Creative Commons
Ikuo Konishi,

Kaoru Abiko,

Takuma Hayashi

et al.

Academia oncology., Journal Year: 2025, Volume and Issue: 2(1)

Published: Jan. 13, 2025

Language: Английский

Citations

1
Inaugurating High‐Throughput Profiling of Extracellular Vesicles for Earlier Ovarian Cancer Detection DOI Creative Commons
Ala Jo, Allen Green, Jamie E. Medina

et al.

Advanced Science, Journal Year: 2023, Volume and Issue: 10(27)

Published: July 23, 2023

Detecting early cancer through liquid biopsy is challenging due to the lack of specific biomarkers for lesions and potentially low levels these markers. The current study systematically develops an extracellular-vesicle (EV)-based test detection, specifically focusing on high-grade serous ovarian carcinoma (HGSOC). marker selection based emerging insights into HGSOC pathogenesis, notably that it arises from precursor within fallopian tube. This work thus establishes murine tube (mFT) cells with oncogenic mutations performs proteomic analyses mFT-derived EVs. identified markers are then evaluated orthotopic animal model. In serially-drawn blood tumor-bearing mice, mFT-EV increase tumor initiation, supporting their potential use in detection. A pilot clinical (n = 51) further narrows EV five candidates, EpCAM, CD24, VCAN, HE4, TNC. combined expression distinguishes non-cancer 89% sensitivity 93% specificity. same also effective classifying three groups (non-cancer, early-stage HGSOC, late-stage HGSOC). developed approach, first time inaugurated tube-derived EVs, could be a minimally invasive tool monitor women at high risk timely intervention.

Language: Английский

Citations

21
Proteomic analysis of ascitic extracellular vesicles describes tumour microenvironment and predicts patient survival in ovarian cancer DOI Creative Commons
Anna Kotrbová, Kristína Gömöryová,

Antónia Mikulová

et al.

Journal of Extracellular Vesicles, Journal Year: 2024, Volume and Issue: 13(3)

Published: March 1, 2024

High-grade serous carcinoma of the ovary, fallopian tube and peritoneum (HGSC), most common type ovarian cancer, ranks among deadliest malignancies. Many HGSC patients have excess fluid in called ascites. Ascites is a tumour microenvironment (TME) containing various cells, proteins extracellular vesicles (EVs). We isolated EVs from patients' ascites by orthogonal methods analyzed them mass spectrometry. identified not only set 'core ascitic EV-associated proteins' but also defined their subset unique to Using single-cell RNA sequencing data, we mapped origin HGSC-specific different types cells present Surprisingly, did come predominantly non-malignant cell such as macrophages fibroblasts. Flow cytometry combination with analysis EV protein composition matched samples showed that type-specific markers has more substantial prognostic potential than cells. To conclude, provide evidence proteomic can define cellular TME. This finding opens numerous avenues both for better understanding EV's role promotion/prevention improved diagnostics.

Language: Английский

Citations

8
Regulation of the Function and Expression of EpCAM DOI Creative Commons
Di Xiao, Mingrui Xiong, Xin Wei Wang

et al.

Biomedicines, Journal Year: 2024, Volume and Issue: 12(5), P. 1129 - 1129

Published: May 20, 2024

The epithelial cell adhesion molecule (EpCAM) is a single transmembrane protein on the surface. Given its strong expression cells and cell-derived tumors, EpCAM has been identified as biomarker for circulating tumor (CTCs) exosomes target cancer therapy. As molecule, crystal structure that indicates it forms cis-dimer first then probably trans-tetramer to mediate intercellular adhesion. Through regulated intramembrane proteolysis (RIP), proteolytic fragments are also able regulate multiple signaling pathways, Wnt in particular. Although great progress made, increasingly more findings have revealed context-specific function patterns of their regulation processes, which necessitates further studies determine structure, function, under both physiological pathological conditions, broadening application basic translational research.

Language: Английский

Citations

7
Addressing Heterogeneity in Direct Analysis of Extracellular Vesicles and Their Analogs by Membrane Sensing Peptides as Pan‐Vesicular Affinity Probes DOI Creative Commons
Alessandro Gori, Roberto Frigerio, Paola Gagni

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(29)

Published: May 31, 2024

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

Language: Английский

Citations

7
Advanced Nanoencapsulation-Enabled Ultrasensitive Analysis: Unraveling Tumor Extracellular Vesicle Subpopulations for Differential Diagnosis of Hepatocellular Carcinoma via DNA Cascade Reactions DOI
Xinyu Li,

Yuan-jie Liu,

Yunpeng Fan

et al.

ACS Nano, Journal Year: 2024, Volume and Issue: 18(17), P. 11389 - 11403

Published: April 17, 2024

Tumor-derived extracellular vesicles (tEVs) hold immense promise as potential biomarkers for the precise diagnosis of hepatocellular carcinoma (HCC). However, their clinical translation is hampered by inherent characteristics, such small size and high heterogeneity complex environment, including non-EV particles normal cell-derived EVs, which prolong separation procedures compromise detection accuracy. In this study, we devised a DNA cascade reaction-triggered individual EV nanoencapsulation (DCR-IEVN) strategy to achieve ultrasensitive specific tEV subpopulations via routine flow cytometry in one-pot, one-step fashion. DCR-IEVN enables direct selective packaging multiple serum samples into flower-like exceeding 600 nm. This approach bypasses need isolation, effectively reducing interference from nontumor EVs. Compared with conventional analytical technologies, exhibits superior efficacy diagnosing HCC owing its selectivity tEVs. Integration machine learning algorithms resulted differential accuracy 96.7% training cohort (

Language: Английский

Citations

5
An immune-related exosome signature predicts the prognosis and immunotherapy response in ovarian cancer DOI Creative Commons

Kaibo Zhu,

Jiao Ma,

Yiping Tian

et al.

BMC Women s Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Jan. 18, 2024

Abstract Background Cancer-derived exosomes contribute significantly in intracellular communication, particularly during tumorigenesis. Here, we aimed to identify two immune-related ovarian cancer-derived (IOCEs) subgroups cancer (OC) and establish a prognostic model for OC patients based on IOCEs. Methods The Cancer Genome Atlas (TCGA) database was used obtain RNA-seq data, as well clinical information. Consensus clustering analysis performed IOCEs-associated subgroups. Kaplan-Meier compare the overall survival (OS) between IOCEs-high IOCEs-low subtype. Gene Ontology (GO) Kyoto Encyclopedia of Genes Genomes (KEGG) analyses were conducted investigate mechanisms biological effects differentially expressed genes (DEGs) subtypes. Besides, an IOCE-related constructed by Lasso regression analysis, signature validated using GSE140082 validation set. Results In total, obtained 21 IOCEs OC, identified IOCE-associated consensus clustering. IOCE-low subgroup showed favorable prognosis while IOCE-high had higher level immune cell infiltration response. GSEA that pathways response mainly enriched subgroup. Thus, may benefit more immunotherapy treatment. addition, risk nine (CLDN4, AKT2, CSPG5, ALDOC, LTA4H, PSMA2, PSMA5, TCIRG1, ANO6). Conclusion We developed novel stratification system OV IOCE signature, which could be estimate patient.

Language: Английский

Citations

4