Localized fluorescent imaging of multiple proteins on individual extracellular vesicles using rolling circle amplification for cancer diagnosis

Toward Clarity in Single Extracellular Vesicle Research: Defining the Field and Correcting Missteps

Single extracellular vesicle (EV) research holds the potential to revolutionize our understanding of cellular communication and enable breakthroughs in diagnostics and therapeutics. However, the lack of a clear, consensus-driven definition of single EV research has led to methodological inconsistencies, overgeneralized interpretations, and, in some cases, misleading claims. In this perspective, we propose a framework for defining single EV research, critique current challenges and misconceptions in this field, and discuss its implications for biomedical applications. We argue that precise experimental design, rigorous validation, and interdisciplinary collaboration approaches are needed to establish single EV research as a cornerstone of precision medicine.

Tethered Catalytic Hairpin Assembly with Plasmon-Enhanced Fluorescence Readout for Single Molecule Detection

Here a novel digital bioassay readout concept is reported that does not rely on enzymatic amplification nor compartmenting of an analyzed liquid sample. Rather, it is based on counting individual affinity-captured target biomolecules via the use of a tethered catalytic hairpin assembly (tCHA) deployed on a solid sensor surface with spatial confinement utilized by a flexible polymer linker (FPL). Wide-field plasmon-enhanced fluorescence (PEF) imaging is employed for optical real-time probing of the reaction kinetics, where affinity-captured target molecules are manifested as spatially distinct bright fluorescent spots. The effect of the length of the FPLs is investigated, and the analytical performance of the dual amplification tCHA-PEF concept is tested by using a model short single-stranded DNA analyte. When applied in a sandwich immunoassay, the detection of target proteins at sub-femtomolar concentrations is demonstrated. The reported experiments are supported by diffusion-limited mass transfer models and document the potential of tCHA-PEF as a new class of generic enzyme-free bioanalytical tools enabling the ultrasensitive analysis of trace amounts of protein and nucleic acid analytes, making it attractive for future molecular diagnostics and research applications.

Logic-Measurer: A Multienzyme-Assisted Ultrasensitive Circuit for Logical Detection of Exosomal MicroRNAs

The logic profiling of exosomal microRNAs (miRNAs) offers broad potential applications in the accurate diagnosis and staging of cancer. However, the logical detection of low-abundance exosomal miRNAs in complex clinical samples remains challenging. This study introduces a logic analysis system termed "Measurer" (a multi-enzyme-assisted ultrasensitive circuit) that offers ultrasensitive and versatile method for detecting multiple exosomal miRNAs. The Logic-Measurer comprises three modules: a stem-loop hairpin-enhanced CRISPR/Cas13a, a polymerase-driven primer exchange reaction, and an exonuclease III-mediated fluorescence output. The efficient Logic-Measurer was switched by the faster rate of trans-cleavage activity of Cas13a due to its improved affinity for hairpin RNA structures. The mechanistic model of hairpin-enhanced CRISPR/Cas13a was confirmed by molecular dynamics simulations. The Logic-Measurer accurately detected exosomal miRNA-21 or miRNA-375 down to 2.1 and 4.4 fM, with superior specificity, and enabled in situ detection of miRNA-21 and miRNA-375 in as low as 1.4 × 102 particles/mL exosomes via membrane fusion. In addition, this method demonstrated 87.3 and 82.1% accuracy in the diagnosis and early detection of breast cancer, respectively, among a cohort of 315 individuals. Subsequent subgroup analysis further confirmed the method's ability to accurately differentiate estrogen receptor-positive patients from healthy individuals. Therefore, the Logic-Measurer offers valuable insights into the development of a CRISPR/Cas-based enhanced diagnostic platform and the next generation of diagnostic technology based on enzyme circuits.

Identification of blood-derived exosomal tumor RNA signatures as noninvasive diagnostic biomarkers for multi-cancer: a multi-phase, multi-center study

BACKGROUND

Cancer remains a leading global cause of mortality, making early detection crucial for improving survival outcomes. The study aims to develop a machine learning-enabled blood-derived exosomal RNA profiling platform for multi-cancer detection and localization.

METHODS

In this multi-phase, multi-center study, we analyzed RNA from exosomes derived from peripheral blood plasma in 818 participants across eight cancer types during the discovery phase. Machine learning techniques were applied to identify potential pan-cancer biomarkers. During the screening and model validation phases, the sample size was progressively expanded to 1,385 participants in two steps, while the candidate biomarkers were refined into a set of 12 exosomal tumor RNA signatures (ETR.sig). In the subsequent model construction phase, diagnostic models were developed using the expanded cohort and ETR.sig. Statistical analyses included the calculation of receiver operating characteristic (ROC) curves and AUC values to assess the models' ability to distinguish cancer cases from controls and determine tumor origins. To further validate and explore the biological relevance of the identified biomarkers, we integrated tissue RNA-seq, single-cell data, and clinical information.

RESULTS

Machine learning analysis initially identified 33 candidate biomarkers, which were narrowed down to 20 ETR.sig in the screening phase and 12 ETR.sig in the validation phase. In the model construction phase, a diagnostic model based on ETR.sig, built using the Random Forest (RF) algorithm, showed excellent performance with an AUC of 0.915 for distinguishing pan-cancer from controls. The multi-class classification model also demonstrated strong classification power, with macro-average and micro-average AUCs of 0.983 and 0.985, respectively, for differentiating between eight cancer types. Additionally, tumor origin classification using the RF-based diagnostic models achieved high AUC values: BRCA 0.976, COAD 0.98, KIRC 0.947, LIHC 0.967, LUAD 0.853, OV 0.972, PAAD 0.977, and PRAD 0.898. Integration of tissue RNA-seq, single-cell data, and clinical information revealed key associations between ETR.sig-related genes and tumor development.

CONCLUSIONS

The study demonstrates the robust potential of exosomal RNA as a minimally invasive biomarker resource for cancer detection. The developed ETR.sig platform offers a promising tool for precision oncology and broad-spectrum cancer screening, integrating advanced computational models with nanoscale vesicle biology for accurate and rapid diagnosis.

DNA Self-Assembly Generated by Aptamer-Triggered Rolling Circle Amplification Cascades for Profiling Colorectal Cancer-Derived Small Extracellular Vesicles

The analysis of small extracellular vesicles (sEVs) has shown clinical significance in early cancer diagnostics and considerable potential in prognostic assessment and therapeutic monitoring, offering possibilities for precise clinical intervention. Despite recent diagnostic progress based on blood-derived sEVs, the inability to specifically profile multiple parameters of sEVs proteins has hampered advancement in clinical applications. Herein, we report an approach to profile colorectal cancer (CRC)-derived sEVs by using multiaptamer-triggered rolling circle amplification (RCA) cascades. In practice, in the presence of target sEVs, the complementary strands are released from the duplexes of the structure-switching aptamer. Then, the RCA cascade occurs but only when the specific DNA strand pair is presented. As a result, the noncanonical DNA assemblies are generated whose size reaches micrometers that can be directly analyzed by conventional flow cytometry, thereby facilitating facile clinical diagnostics. In this study, the developed diagnostic method is verified on cell-derived sEVs, followed by achieving modeling based on clinical samples. The final diagnostic results from the clinical cohort indicate promising diagnostic efficacy for CRC-derived sEVs with 92% sensitivity, 86.7% specificity, and 90% overall accuracy, highlighting the substantial potential of sEVs as biomarkers for CRC diagnosis and significantly advancing the development of clinical tools for early disease diagnosis.

A colorimetric nano-enzyme assay with Ni@Pt nanoparticles as signal labels for rapid and sensitive detection of exosomal Aβ42 in plasma

A nano-enzyme sandwich assay (SWzyme assay), a colorimetric system based on a biochip and inorganic nano-enzyme for rapid and simple determination of exosomal Aβ42 in plasma is proposed. Anti-CD63 antibody-modified biochips were prepared for plasma exosome capture and synthesized highly catalytic Ni@Pt nanozymes for detecting exosomal Aβ42. The method was able to detect exosomal Aβ42 with a limit of detection (LOD) as low as 4.2×104 particles/mL and a linear range from 104 to 108 particles/mL. By determination of exosomal Aβ42, the SWzyme assay successfully distinguished plasma from Alzheimer's desease (AD) and healthy mice. The SWzyme assay holds promise to serve as diagnostic tools for the early detection of AD and supporting the development of personalized medicine.

Immuno-Rolling Circle Amplification (Immuno-RCA): Biosensing Strategies, Practical Applications, and Future Perspectives

In the rapidly evolving field of life sciences and biomedicine, detecting low-abundance biomolecules, and ultraweak biosignals presents significant challenges. This has spurred a rapid development of analytical techniques aiming for increased sensitivity and specificity. These advancements, including signal amplification strategies and the integration of biorecognition events, mark a transformative era in bioanalytical precision and accuracy. A prominent method among these innovations is immuno-rolling circle amplification (immuno-RCA) technology, which effectively combines immunoassays with signal amplification via RCA. This process starts when a targeted biomolecule, such as a protein or cell, binds to an immobilized antibody or probe on a substrate. The introduction of a circular DNA template triggers RCA, leading to exponential amplification and significantly enhanced signal intensity, thus the target molecule is detectable and quantifiable even at the single-molecule level. This review provides an overview of the biosensing strategy and extensive practical applications of immuno-RCA in detecting biomarkers. Furthermore, it scrutinizes the limitations inherent to these sensors and sets forth expectations for their future trajectory. This review serves as a valuable reference for advancing immuno-RCA in various domains, such as diagnostics, biomarker discovery, and molecular imaging.

High-throughput, multiplexed quantification, and sorting of single EVs at single-molecule level

We have developed a platform for the high-throughput, multiplexed, and ultra-sensitive profiling of individual extracellular vesicles (EVs) directly in plasma, which we call BDEVS - Agarose B ead-based D igital Single Molecule-Single EV S orting. Unlike conventional approaches, BDEVS achieves single molecule sensitivity and moderate multiplexing (demonstrated 3-plex) without sacrificing the throughput (processing ten thousand of EVs per minute) necessary to resolve EVs directly in human plasma. Our platform integrates rolling circle amplification (RCA) of EV surface proteins, which are cleaved from single EVs, and amplified within agarose droplets, followed by flow cytometry-based readout and sorting, overcoming steric hindrance, non-specific binding, and the lack of quantitation of multiple proteins on EVs that have plagued earlier approaches. We evaluated the analytical capabilities of BDEVS through head-to-head comparison with gold-standard technologies, and demonstrated a ∼100x improvement in the limit of detection of EV subpopulations. We demonstrate the high throughput (∼100k beads / minute) profiling of individual EVs for key immune markers PD-L1, CD155, and the melanoma tumor marker TYRP-1, and showed that BDEVS can precisely quantify and sort EVs, offering unprecedented resolution for analyzing tumor-immune interactions and detecting rare EV subpopulations in complex clinical specimens. We demonstrate BDEVS's potential as a transformative tool for EV-based diagnostics and therapeutic monitoring in the context of cancer immunology by analyzing plasma samples from patients with melanoma, where EV heterogeneity plays a critical role in disease progression and response to therapy.

Quantitative Analysis of Cell-Free RNA at Attomolar Level Using CRISPR/Cas Digital Imaging Platform

Quantitative analysis of cell-free RNA (cfRNA) in plasma sample can be used for screening, diagnosing, and prognosticating of multiple diseases. Here, we report a quantitative CRISPR/Cas digital imaging platform (qCasdip) for the detection of various cfRNAs, including circular RNAs and miRNAs, in clinical samples at the attomolar (aM) level without the need for preamplification. Digital counting strategy provides qCasdip quantitative ability with a linear detection range of 102-106 aM. Meanwhile, qCasdip demonstrated cfRNA profiling in clinical plasma samples, improving the diagnosis of breast cancer. These data highlight the potential of qCasdip to quantitatively assess the molecular patterns of specific cfRNA panels in plasma, thereby providing a novel liquid biopsy solution to enhance disease diagnosis.

Aggregation-Induced Emission Luminogen: Role in Biopsy for Precision Medicine

Biopsy, including tissue and liquid biopsy, offers comprehensive and real-time physiological and pathological information for disease detection, diagnosis, and monitoring. Fluorescent probes are frequently selected to obtain adequate information on pathological processes in a rapid and minimally invasive manner based on their advantages for biopsy. However, conventional fluorescent probes have been found to show aggregation-caused quenching (ACQ) properties, impeding greater progresses in this area. Since the discovery of aggregation-induced emission luminogen (AIEgen) have promoted rapid advancements in molecular bionanomaterials owing to their unique properties, including high quantum yield (QY) and signal-to-noise ratio (SNR), etc. This review seeks to present the latest advances in AIEgen-based biofluorescent probes for biopsy in real or artificial samples, and also the key properties of these AIE probes. This review is divided into: (i) tissue biopsy based on smart AIEgens, (ii) blood sample biopsy based on smart AIEgens, (iii) urine sample biopsy based on smart AIEgens, (iv) saliva sample biopsy based on smart AIEgens, (v) biopsy of other liquid samples based on smart AIEgens, and (vi) perspectives and conclusion. This review could provide additional guidance to motivate interest and bolster more innovative ideas for further exploring the applications of various smart AIEgens in precision medicine.

Shedding Light on Cellular Secrets: A Review of Advanced Optical Biosensing Techniques for Detecting Extracellular Vesicles with a Special Focus on Cancer Diagnosis

In the relentless pursuit of innovative diagnostic tools for cancer, this review illuminates the cutting-edge realm of extracellular vesicles (EVs) and their biomolecular cargo detection through advanced optical biosensing techniques with a primary emphasis on their significance in cancer diagnosis. From the sophisticated domain of nanomaterials to the precision of surface plasmon resonance, we herein examine the diverse universe of optical biosensors, emphasizing their specified applications in cancer diagnosis. Exploring and understanding the details of EVs, we present innovative applications of enhancing and blending signals, going beyond the limits to sharpen our ability to sense and distinguish with greater sensitivity and specificity. Our special focus on cancer diagnosis underscores the transformative potential of optical biosensors in early detection and personalized medicine. This review aims to help guide researchers, clinicians, and enthusiasts into the captivating domain where light meets cellular secrets, creating innovative opportunities in cancer diagnostics.

CRISPR/Cas12a and aptamer-chemiluminescence based analysis for the relative abundance determination of tumor-related protein positive exosomes for breast cancer diagnosis

Exosomes, as novel biomarker for liquid biopsy, exhibit huge important potential value for cancer diagnosis. However, various proteins show different expression levels on exosomal membrane, and the absolute concentration of exosomes in clinical samples is easily influenced by a number of factors. Here, we developed a CRISPR/Cas12a and aptamer-chemiluminescence based analysis (CACBA) for the relative abundance determination of tumor-related protein positive exosomes in plasma for breast cancer diagnosis. The total concentration of exosomes was determined through captured CD63 using a CRISPR/Cas12a-based method with the LoD of 8.97 × 103 particles/μl. Meanwhile, EpCAM and MUC1 positive exosomes were quantitatively detected by aptamer-chemiluminescence (ACL) based method with the LoD of 1.45 × 102 and 3.73 × 102 particles/μl, respectively. It showed that the percentages of EpCAM and MUC1 positive exosomes offered an excellent capability to differentiate breast cancer patients and healthy donors. The high sensitivity, strong specificity, outstanding anti-interference capability, and steady recovery rate of this approach offered higher accuracy and robustness than the commercialized method in clinical trial. In addition with good stability, easy preparation and low cost, this method not only provides a new approach to rapid analysis of exosome proteins, it may be quickly extended to the diagnoses of various cancers.

DNA Nanomaterial-Empowered Surface Engineering of Extracellular Vesicles

Extracellular vesicles (EVs) are cell-secreted biological nanoparticles that are critical mediators of intercellular communication. They contain diverse bioactive components, which are promising diagnostic biomarkers and therapeutic agents. Their nanosized membrane-bound structures and innate ability to transport functional cargo across major biological barriers make them promising candidates as drug delivery vehicles. However, the complex biology and heterogeneity of EVs pose significant challenges for their controlled and actionable applications in diagnostics and therapeutics. Recently, DNA molecules with high biocompatibility emerge as excellent functional blocks for surface engineering of EVs. The robust Watson-Crick base pairing of DNA molecules and the resulting programmable DNA nanomaterials provide the EV surface with precise structural customization and adjustable physical and chemical properties, creating unprecedented opportunities for EV biomedical applications. This review focuses on the recent advances in the utilization of programmable DNA to engineer EV surfaces. The biology, function, and biomedical applications of EVs are summarized and the state-of-the-art achievements in EV isolation, analysis, and delivery based on DNA nanomaterials are introduced. Finally, the challenges and new frontiers in EV engineering are discussed.

Simultaneous detection of membrane protein and mRNA at single extracellular vesicle level by droplet microfluidics for cancer diagnosis

INTRODUCTION

Simultaneous detection of proteins and mRNA within a single extracellular vesicle (EV) enables comprehensive analysis of specific EVs subpopulations, significantly advancing cancer diagnostics. However, developing a sensitive and user-friendly approach for simultaneously detecting multidimensional biomarkers in single EV is still challenging.

OBJECTIVES

To facilitate the analysis of multidimensional biomarkers in EVs and boost its clinical application, we present a versatile droplet digital system facilitating the concurrent detection of membrane proteins and mRNA at the single EV level with high sensitivity and specificity.

METHODS

The antibody-DNA conjugates were firstly prepared for EVs protein biomarkers recognition and signal transformation. Coupling with the assembled triplex droplet digital PCR system, a versatile droplet digital analysis assay for simultaneous detection of membrane protein and mRNA at a single EV level was developed.

RESULTS

Our new droplet digital system displayed high sensitivity and specificity. Additionally, its clinical application was validated in a breast cancer cohort. As expected, this assay has demonstrated superior performance in distinguishing breast cancer from healthy individuals and benign controls through combined detection of EVs protein and mRNA markers compared to any single kind marker detections, especially for patients with breast cancer at early stage (AUC=0.9229).

CONCLUSION

Consequently, this study proposes a promising strategy for accurately identifying and analyzing specific EV subgroups through the co-detection of proteins and mRNA at the single EV level, holding significant potential for future clinical applications.

Surface Sialic Acid Detection of Small Extracellular Vesicles at the Single-Particle Level by Nano-Flow Cytometry

Glycans, particularly sialic acids (SAs), play crucial roles in diverse biological processes. Despite their significance, analyzing specific glycans, such as sialic acids, on individual small extracellular vesicles (sEVs) has remained challenging due to the limited glycan capacity and substantial heterogeneity of sEVs. To tackle this issue, we introduce a chemical modification method of surface SAs on sEVs named PALEV-nFCM, which involves periodate oxidation and aniline-catalyzed oxime ligation (PAL), in conjunction with single-particle analysis using a laboratory-built nano-flow cytometer (nFCM). The specificity of the PALEV labeling method was validated using SA-decorated liposomes, enzymatic removal of terminal SA residues, lectin preblocking, and cellular treatment with an endogenous sialyltransferase inhibitor. Comprehensive mapping of SA distributions was conducted for sEVs derived from different sources, including conditioned cell culture medium (CCCM) of various cell lines, human saliva, and human red blood cells (RBCs). Notably, treatment with the calcium ionophore substantially increases the population of SA-positive RBC sEVs and enhances the SA content on individual RBC sEVs as well. nFCM provides a sensitive and versatile platform for mapping SAs of individual sEVs, which could significantly contribute to resolving the heterogeneity of sEVs and advancing the understanding of their glycosignature.

Empowering Exosomes with Aptamers for Precision Theranostics

As information messengers for cell-to-cell communication, exosomes, typically small membrane vesicles (30-150 nm), play an imperative role in the physiological and pathological processes of living systems. Accumulating studies have demonstrated that exosomes are potential biological candidates for theranostics, including liquid biopsy-based diagnosis and drug delivery. However, their clinical applications are hindered by several issues, especially their unspecific detection and insufficient targeting ability. How to upgrade the accuracy of exosome-based theranostics is being widely explored. Aptamers, benefitting from their admirable characteristics, are used as excellent molecular recognition elements to empower exosomes for precision theranostics. With high affinity against targets and easy site-specific modification, aptamers can be incorporated with platforms for the specific detection of exosomes, thus providing opportunities for advancing disease diagnostics. Furthermore, aptamers can be tailored and functionalized on exosomes to enable targeted therapeutics. Herein, this review emphasizes the empowering of exosomes by aptamers for precision theranostics. A brief introduction of exosomes and aptamers is provided, followed by a discussion of recent progress in aptamer-based exosome detection for disease diagnosis, and the emerging applications of aptamer-functionalized exosomes for targeted therapeutics. Finally, current challenges and opportunities in this research field are presented.

Recent advances in chemical biology tools for protein and RNA profiling of extracellular vesicles

Extracellular vesicles (EVs) are nano-sized vesicles secreted by cells that contain various cellular components such as proteins, nucleic acids, and lipids from the parent cell. EVs are abundant in body fluids and can serve as circulating biomarkers for a variety of diseases or as a regulator of various biological processes. Considering these characteristics of EVs, analysis of the EV cargo has been spotlighted for disease diagnosis or to understand biological processes in biomedical research. Over the past decade, technologies for rapid and sensitive analysis of EVs in biofluids have evolved, but detection and isolation of targeted EVs in complex body fluids is still challenging due to the unique physical and biological properties of EVs. Recent advances in chemical biology provide new opportunities for efficient profiling of the molecular contents of EVs. A myriad of chemical biology tools have been harnessed to enhance the analytical performance of conventional assays for better understanding of EV biology. In this review, we will discuss the improvements that have been achieved using chemical biology tools.

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.

High-Throughput Single-Cell, Single-Mitochondrial DNA Assay Using Hydrogel Droplet Microfluidics

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Cancer Screening: Present Recommendations, the Development of Multi-Cancer Early Development Tests, and the Prospect of Universal Cancer Screening

Cancer continues to pose a considerable challenge to global health. In the search for innovative strategies to combat this complex enemy, the concept of universal cancer screening has emerged as a promising avenue for early detection and prevention. In contrast to targeted approaches that focus on specific populations or high-risk individuals, universal screening seeks to cast a wide net to detect incipient malignancies in different demographic groups. This paradigm shift in cancer care underscores the importance of comprehensive screening programs that go beyond conventional boundaries. As our understanding of the complex molecular and genetic basis of cancer deepens, the need to develop comprehensive screening methods becomes increasingly apparent. In this article, we look at the rationale and potential benefits of universal cancer screening.

GLIPR2: a potential biomarker and therapeutic target unveiled - Insights from extensive pan-cancer analyses, with a spotlight on lung adenocarcinoma

Background

Glioma pathogenesis related-2 (GLIPR2), an emerging Golgi membrane protein implicated in autophagy, has received limited attention in current scholarly discourse.

Methods

Leveraging extensive datasets, including The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC), we conducted a comprehensive investigation into GLIPR2 expression across diverse human malignancies. Utilizing UALCAN, OncoDB, MEXPRESS and cBioPortal databases, we scrutinized GLIPR2 mutation patterns and methylation landscapes. The integration of bulk and single-cell RNA sequencing facilitated elucidation of relationships among cellular heterogeneity, immune infiltration, and GLIPR2 levels in pan-cancer. Employing ROC and KM analyses, we unveiled the diagnostic and prognostic potential of GLIPR2 across diverse cancers. Immunohistochemistry provided insights into GLIPR2 expression patterns in a multicenter cohort spanning various cancer types. In vitro functional experiments, including transwell assays, wound healing analyses, and drug sensitivity testing, were employed to delineate the tumor suppressive role of GLIPR2.

Results

GLIPR2 expression was significantly reduced in neoplastic tissues compared to its prevalence in healthy tissues. Copy number variations (CNV) and alterations in methylation patterns exhibited discernible correlations with GLIPR2 expression within tumor tissues. Moreover, GLIPR2 demonstrated diagnostic and prognostic implications, showing pronounced associations with the expression profiles of numerous immune checkpoint genes and the relative abundance of immune cells in the neoplastic microenvironment. This multifaceted influence was evident across various cancer types, with lung adenocarcinoma (LUAD) being particularly prominent. Notably, patients with LUAD exhibited a significant decrease in GLIPR2 expression within practical clinical settings. Elevated GLIPR2 expression correlated with improved prognostic outcomes specifically in LUAD. Following radiotherapy, LUAD cases displayed an increased presence of GLIPR2+ infiltrating cellular constituents, indicating a notable correlation with heightened sensitivity to radiation-induced therapeutic modalities. A battery of experiments validated the functional role of GLIPR2 in suppressing the malignant phenotype and enhancing treatment sensitivity.

Conclusion

In pan-cancer, particularly in LUAD, GLIPR2 emerges as a promising novel biomarker and tumor suppressor. Its involvement in immune cell infiltration suggests potential as an immunotherapeutic target.

High-throughput single-cell, single-mitochondrial DNA assay using hydrogel droplet microfluidics

There is growing interest in understanding the biological implications of single cell heterogeneity and intracellular heteroplasmy of mtDNA, but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95% mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology

While the field of precision oncology is rapidly expanding and more targeted options are revolutionizing cancer treatment paradigms, therapeutic resistance particularly to immunotherapy remains a pressing challenge. This can be largely attributed to the dynamic tumor-stroma interactions that continuously alter the microenvironment. While to date most advancements have been made through examining the clinical utility of tissue-based biomarkers, their invasive nature and lack of a holistic representation of the evolving disease in a real-time manner could result in suboptimal treatment decisions. Thus, using minimally-invasive approaches to identify biomarkers that predict and monitor treatment response as well as alert to the emergence of recurrences is of a critical need. Currently, research efforts are shifting towards developing liquid biopsy-based biomarkers obtained from patients over the course of disease. Liquid biopsy represents a unique opportunity to monitor intercellular communication within the tumor microenvironment which could occur through the exchange of extracellular vesicles (EVs). EVs are lipid bilayer membrane nanoscale vesicles which transfer a plethora of biomolecules that mediate intercellular crosstalk, shape the tumor microenvironment, and modify drug response. The capture of EVs using innovative approaches, such as microfluidics, magnetic beads, and aptamers, allow their analysis via high throughput multi-omics techniques and facilitate their use for biomarker discovery. Artificial intelligence, using machine and deep learning algorithms, is advancing multi-omics analyses to uncover candidate biomarkers and predictive signatures that are key for translation into clinical trials. With the increasing recognition of the role of EVs in mediating immune evasion and as a valuable biomarker source, these real-time snapshots of cellular communication are promising to become an important tool in the field of precision oncology and spur the recognition of strategies to block resistance to immunotherapy. In this review, we discuss the emerging role of EVs in biomarker research describing current advances in their isolation and analysis techniques as well as their function as mediators in the tumor microenvironment. We also highlight recent lung cancer and melanoma studies that point towards their application as predictive biomarkers for immunotherapy and their potential clinical use in precision immuno-oncology.

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.

Advanced extracellular vesicle bioinformatic nanomaterials: from enrichment, decoding to clinical diagnostics

Extracellular vesicles (EVs) are membrane nanoarchitectures generated by cells that carry a variety of biomolecules, including DNA, RNA, proteins and metabolites. These characteristics make them attractive as circulating bioinformatic nanocabinets for liquid biopsy. Recent advances on EV biology and biogenesis demonstrate that EVs serve as highly important cellular surrogates involved in a wide range of diseases, opening up new frontiers for modern diagnostics. However, inefficient methods for EV enrichment, as well as low sensitivity of EV bioinformatic decoding technologies, hinder the use of EV nanocabinet for clinical diagnosis. To overcome these challenges, new EV nanotechnology is being actively developed to promote the clinical translation of EV diagnostics. This article aims to present the emerging enrichment strategies and bioinformatic decoding platforms for EV analysis, and their applications as bioinformatic nanomaterials in clinical settings.

Extracellular Vesicles: Techniques and Biomedical Applications Related to Single Vesicle Analysis

Extracellular vesicles (EVs) are extensively dispersed lipid bilayer membrane vesicles involved in the delivery and transportation of molecular payloads to certain cell types to facilitate intercellular interactions. Their significant roles in physiological and pathological processes make EVs outstanding biomarkers for disease diagnosis and treatment monitoring as well as ideal candidates for drug delivery. Nevertheless, differences in the biogenesis processes among EV subpopulations have led to a diversity of biophysical characteristics and molecular cargos. Additionally, the prevalent heterogeneity of EVs has been found to substantially hamper the sensitivity and accuracy of disease diagnosis and therapeutic monitoring, thus impeding the advancement of clinical applications. In recent years, the evolution of single EV (SEV) analysis has enabled an in-depth comprehension of the physical properties, molecular composition, and biological roles of EVs at the individual vesicle level. This review examines the sample acquisition tactics prior to SEV analysis, i.e., EV isolation techniques, and outlines the current state-of-the-art label-free and label-based technologies for SEV identification. Furthermore, the challenges and prospects of biomedical applications based on SEV analysis are systematically discussed.

Precise Identification and Profiling of Surface Proteins of Ultra Rare Tumor Specific Extracellular Vesicle with Dynamic Quantitative Plasmonic Imaging

Specific detection of tumor-derived EVs (tEVs) in plasma is complicated by nontumor EVs and non-EV particles. To accurately identify tEVs and profile their surface protein expression at single tEV resolution directly with clinical plasma is still an unmet need. Here, we present a Dynamic Immunoassay for Single tEV surface protein Profiling (DISEP), a kinetic assay based on surface plasmon resonance microscopy (SPRM) for specific single tEV profiling. DISEP adopts a pair of low-affinity oligonucleotide probes to respectively label EV surface proteins and functionalize an SPRM biosensor interface. tEVs labeled with the oligonucleotide probes possess distinctive binding kinetics from nonspecific particles in plasma, which permits accurate digital plasmonic counting of single EVs. We demonstrate DISEP for recognizing target EVs among 350-fold background plasma particles with high sensitivity (4677 EVs per μL). Clinical plasma samples were analyzed to discriminate between pancreatic cancer patients (n = 40) and healthy donors (n = 45). With a panel of biomarker signatures (EpCAM, HER2, and GPC1), DISEP only requires 10 μL primary sample from each donor to classify tumor patients with an area under the curve of 0.98. DISEP provides a highly specific EV detection and surface protein profiling strategy for early cancer diagnosis.

Critical considerations in determining the surface charge of small extracellular vesicles

Small extracellular vesicles (EVs) have emerged as a focal point of EV research due to their significant role in a wide range of physiological and pathological processes within living systems. However, uncertainties about the nature of these vesicles have added considerable complexity to the already difficult task of developing EV-based diagnostics and therapeutics. Whereas small EVs have been shown to be negatively charged, their surface charge has not yet been properly quantified. This gap in knowledge has made it challenging to fully understand the nature of these particles and the way they interact with one another, and with other biological structures like cells. Most published studies have evaluated EV charge by focusing on zeta potential calculated using classical theoretical approaches. However, these approaches tend to underestimate zeta potential at the nanoscale. Moreover, zeta potential alone cannot provide a complete picture of the electrical properties of small EVs since it ignores the effect of ions that bind tightly to the surface of these particles. The absence of validated methods to accurately estimate the actual surface charge (electrical valence) and determine the zeta potential of EVs is a significant knowledge gap, as it limits the development of effective label-free methods for EV isolation and detection. In this study, for the first time, we show how the electrical charge of small EVs can be more accurately determined by accounting for the impact of tightly bound ions. This was accomplished by measuring the electrophoretic mobility of EVs, and then analytically correlating the measured values to their charge in the form of zeta potential and electrical valence. In contrast to the currently used theoretical expressions, the employed analytical method in this study enabled a more accurate estimation of EV surface charge, which will facilitate the development of EV-based diagnostic and therapeutic applications.

Polymerase-Driven Logic Signal Amplification for the Detection of Small Extracellular Vesicle Surface Proteins and the Identification of Breast Cancer

Small extracellular vesicles (sEVs) derived from tumors contain a vast amount of cellular information and are regarded as a potential diagnostic biomarker for noninvasive cancer diagnosis. Nevertheless, it remains challenging to accurately measure sEVs from clinical samples due to the low abundance of these vesicles as well as their phenotypic heterogeneity. Herein, a polymerase-driven logic signal amplification system (PLSAS) was developed for the high-sensitivity detection of sEV surface proteins and breast cancer (BC) identification. Aptamers were introduced to serve as sensing modules to specifically recognize target proteins. By changing the input DNA sequences, two polymerase-driven primer exchange reaction systems were rationally designed for DNA logic computing. This allows for autonomous targeting of a limited number of targets using "OR" and "AND" logic, leading to a significant increase in fluorescence signals and enabling the specific and ultrasensitive detection of sEV surface proteins. In this work, we investigated surface proteins of mucin 1 (MUC1) and the epithelial cell adhesion molecule (EpCAM) as model proteins. When MUC1 or EpCAM proteins were used as single signal input in the "OR" DNA logic system, the detection limit of sEVs was 24 or 58 particles/μL, respectively. And MUC1 and EpCAM proteins of sEVs can be simultaneously detected in the AND logic method, which can significantly reduce the effect of phenotypic heterogeneity of sEVs to distinguish the source of sEVs derived from various mammary cell lines, such as MCF-7, MDA MB 231, SKBR3, and MCF-10A. The approach has achieved high discrimination in serologically tested positive BC samples (AUC 98.1%) and holds significant potential in advancing the early diagnosis and prognostic assessments of BC.

Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests

Cancer remains a leading cause of death worldwide, partly owing to late detection which entails limited and often ineffective therapeutic options. Most cancers lack validated screening procedures, and the ones available disclose several drawbacks, leading to low patient compliance and unnecessary workups, adding up the costs to healthcare systems. Hence, there is a great need for innovative, accurate, and minimally invasive tools for early cancer detection. In recent years, multi-cancer early detection (MCED) tests emerged as a promising screening tool, combining molecular analysis of tumor-related markers present in body fluids with artificial intelligence to simultaneously detect a variety of cancers and further discriminate the underlying cancer type. Herein, we aim to provide a highlight of the variety of strategies currently under development concerning MCED, as well as the major factors which are preventing clinical implementation. Although MCED tests depict great potential for clinical application, large-scale clinical validation studies are still lacking.

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.

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.

Recent advances of small extracellular vesicle biomarkers in breast cancer diagnosis and prognosis

Current clinical tools for breast cancer (BC) diagnosis are insufficient but liquid biopsy of different bodily fluids has recently emerged as a minimally invasive strategy that provides a real-time snapshot of tumour biomarkers for early diagnosis, active surveillance of progression, and post-treatment recurrence. Extracellular vesicles (EVs) are nano-sized membranous structures 50-1000 nm in diameter that are released by cells into biological fluids. EVs contain proteins, nucleic acids, and lipids which play pivotal roles in tumourigenesis and metastasis through cell-to-cell communication. Proteins and miRNAs from small EVs (sEV), which range in size from 50-150 nm, are being investigated as a potential source for novel BC biomarkers using mass spectrometry-based proteomics and next-generation sequencing. This review covers recent developments in sEV isolation and single sEV analysis technologies and summarises the sEV protein and miRNA biomarkers identified for BC diagnosis, prognosis, and chemoresistance. The limitations of current sEV biomarker research are discussed along with future perspective applications.

Detection of Breast Cancer-Specific Extracellular Vesicles with Fiber-Optic SPR Biosensor

Extracellular vesicles (EVs) have attracted great attention as potential biomarkers for cancer diagnostics. Although several technologies have been developed for EV detection, many of them are still not applicable to clinical settings as they rely on complex EV isolation processes, while lacking sensitivity, specificity or standardization. To solve this problem, we have developed a sensitive breast cancer-specific EV detection bioassay directly in blood plasma using a fiber-optic surface plasmon resonance (FO-SPR) biosensor, previously calibrated with recombinant EVs. First, we established a sandwich bioassay to detect SK-BR-3 EVs by functionalizing the FO-SPR probes with anti-HER2 antibodies. A calibration curve was built using an anti-HER2/^Banti-CD9 combination, resulting in an LOD of 2.1 × 10⁷ particles/mL in buffer and 7 × 10⁸ particles/mL in blood plasma. Next, we investigated the potential of the bioassay to detect MCF7 EVs in blood plasma using an anti-EpCAM/^Banti-mix combination, obtaining an LOD of 1.1 × 10 ⁸ particles/mL. Finally, the specificity of the bioassay was proven by the absence of signal when testing plasma samples from 10 healthy people unknown to be diagnosed with breast cancer. The remarkable sensitivity and specificity of the developed sandwich bioassay together with the advantages of the standardized FO-SPR biosensor highlight outstanding potential for the future of EV analysis.

The emerging applications and advancements of Raman spectroscopy in pediatric cancers

Although the survival rate of pediatric cancer has significantly improved, it is still an important cause of death among children. New technologies have been developed to improve the diagnosis, treatment, and prognosis of pediatric cancers. Raman spectroscopy (RS) is a non-destructive analytical technique that uses different frequencies of scattering light to characterize biological specimens. It can provide information on biological components, activities, and molecular structures. This review summarizes studies on the potential of RS in pediatric cancers. Currently, studies on the application of RS in pediatric cancers mainly focus on early diagnosis, prognosis prediction, and treatment improvement. The results of these studies showed high accuracy and specificity. In addition, the combination of RS and deep learning is discussed as a future application of RS in pediatric cancer. Studies applying RS in pediatric cancer illustrated good prospects. This review collected and analyzed the potential clinical applications of RS in pediatric cancers.

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.

Current Advances in Technologies for Single Extracellular Vesicle Analysis and Its Clinical Applications in Cancer Diagnosis

Extracellular vesicles (EVs) have been regarded as one of the most potential diagnostic biomarkers for different cancers, due to their unique physiological and pathological functions. However, it is still challenging to precisely analyze the contents and sources of EVs, due to their heterogeneity. Herein, we summarize the advances in technologies for a single EV analysis, which may provide new strategies to study the heterogeneity of EVs, as well as their cargo, more specifically. Furthermore, the applications of a single EV analysis on cancer early diagnosis are also discussed.

Single-Step and Highly Sensitive Imaging of Exosomal PD-L1 through Aptamer-Activated Cascade Primer Exchange Reaction-Generated Branched DNA Nanostructures

Exosomal PD-L1 plays a critical role in tumor progress and immunotherapy. However, accurately analyzing exosomal PD-L1 is greatly limited by the small-sized and free-floating nature of exosomes and the few proteins each exosome carries. We described herein a single-step and highly sensitive method, termed aptamer-triggered cascade primer exchange reaction (PER)-generated branched DNA nanostructures, for the quantification and imaging of exosomal PD-L1. The presence of exosomal PD-L1 converted the conformation of the recognition probe, accompanied by the exposure of primer 1. Then, primer 1 actuated the cascade PER, which generated branched DNA nanostructures containing numerous G-quadruplex for binding to thioflavin T (ThT) dye, leading to an amplified fluorescence signal. Profiting from directly growing branched DNA nanostructures on the surface of exosomes, the size of exosomes was enlarged and the movement of exosomes was limited, achieving the imaging of exosomal PD-L1 by conventional optical microscopy in a wash- and label-free fashion. Analyzing exosomal PD-L1 from serum samples of 15 cancer patients and 15 healthy volunteers demonstrated that this simple strategy could distinguish NSCLC patients from healthy donors with high clinical accuracy. Therefore, the developed assay has great potential as a transformative diagnostic toolkit for cancer detection and immunotherapy monitoring.

Characterization of glycosylation regulator-mediated glycosylation modification patterns and tumor microenvironment infiltration in hepatocellular carcinoma

Background: Previous studies have shown that glycosylation of proteins ofen plays an important role in HCC. However, the potential mechanism of glycosylation in HCC has not been described systematically. Methods: We comprehensively evaluated the glycosylation patterns in HCC samples based on 43 glycosylation regulators, and annotated the modification patterns with the enrichment of immune cells and stromal cells. Considering the heterogeneity of HCC patients, the glycosylation score was constructed using single-sample gene set enrichment analysis (ssGSEA). We also explored the drugs that different HCC patients were sensitive to based on glycosylation mode and score. Results: We identified three glycosylation-regulated gene subtypes. By annotating the subtypes, it was found that the glycosylation regulated gene subtypes was highly matched with three immunophenotypes of HCC (immune-inflamed, immune-excluded, and immune-desert), regardless of the characteristics of immune cell infiltration or prognosis. Based on the characteristic genes of glycosylation-regulated gene subtypes, we constructed a glycosylation-related model, and found that glycosylation-related model was highly consistent with the glycosylation regulated gene subtypes. The glycosylation score that evaluates the glycosylation characteristics of a single HCC sample has high prognostic value, and the prognosis of patients with high glycosylation score is significantly worse. Interestingly, we found that the glycosylation score was closely related to tumor node metastasis (TNM) staging. By applying glycosylation-regulated gene subtypes and glycosylation score to explore the sensitivity of different patients to anticancer drugs, it was found that the sensitivity of Thapsigargin, Shikonin, Embelin and Epothilone. B was closely related to the glycosylation mode. Conclusion: This study reveals that the diversity of glycosylation patterns plays an important role in HCC. Therefore, evaluating the glycosylation patterns of patients with HCC will be helpful in identifying the characteristics of immune cell infiltration and selecting accurate treatment methods.

Extracellular vesicle isolation, purification and evaluation in cancer diagnosis

Strategies for non-invasive biomarker discovery in early detection of cancer are an urgent need. Extracellular vesicles (EVs) have generated increasing attention from the scientific community and are under intensive investigations due to their unique biological profiles and their non-invasive nature. EVs are membrane-enclosed vesicles with variable sizes and function. Such vesicles are actively secreted from multiple cell types and are considered as key vehicles for inter-cellular communications and signalling. The stability and potential to easily cross biological barriers enable EVs for exerting durable effects on target cells. These along with easy access to such vesicles, the consistent secretion from tumour during all stages of tumorigenesis and their content providing a reservoir of molecules as well as mirroring the identity of the cell of origin are virtues that have made EVs appealing to be assessed in liquid biopsy approaches and for using as a promising resource of biomarkers in cancer diagnosis and therapy and monitoring targeted cancer therapy. Early detection of EVs will guide time-scheduled personalised therapy. Surveying reliable and sensitive methods for rapid isolation of EVs from biofluids, the purity of isolated vesicles and their molecular profiling and marker specification for clinical translation in patients with cancer are issues in the area and the hot topics of many recent studies. Here, the focus is over methods for EV isolation and stratification for digging more information about liquid biopsy-based diagnosis. Extending knowledge regarding EV-based strategies is a key to validate independent patient follow-up for cancer diagnosis at early stages and inspecting the efficacy of therapeutics.

Integrated microfluidic-SERS for exosome biomarker profiling and osteosarcoma diagnosis

Osteosarcoma is one of the most frequent primary sarcoma of bone among adolescents. Early diagnosis of osteosarcoma is the key factor to achieve high survival rate of patients. Nevertheless, traditional histological biopsy is highly invasive and associated with the risk of arousing tumor spread. Herein, we develop a method integrating microfluidics and surface-enhanced Raman spectroscopy (SERS) to isolate plasma-derived exosomes and profile multiple exosomal biomarkers for the diagnosis of osteosarcoma. The method showed highly efficient isolation of exosomes directly from human plasma and can profile exosomes based on protein biomarkers, with the detection limit down to 2 exosomes per μL. The whole assay can be performed in 5 h and only consumed 50 μL of plasma for one analysis. With the method, we analyzed the level of three protein biomarkers, i.e., CD63, vimentin (VIM) and epithelial cell adhesion molecule (EpCAM), on plasma-derived exosomes from 20 osteosarcoma patients and 20 heathy controls. Significantly higher levels of CD63, VIM and EpCAM were observed on plasma exosomes from the osteosarcoma patients compared to the healthy controls. Based on the level of the exosomal biomarkers, a classification model was built for the rapid diagnosis of osteosarcoma, with the sensitivity, specificity and accuracy of 100%, 90% and 95%, respectively. The proposed method does not require complex operations nor expensive equipment, and has great promise in clinical diagnosis of cancer as a liquid biopsy technique.

Multi-omics analysis revealed the role of extracellular vesicles in hepatobiliary & pancreatic tumor

Liquid biopsy is rapidly growing into a hot research field due to its unique advantages of minimal invasiveness, and extracellular vesicle (EVs) are also expected to become an important pillar in the diagnostic technology system as a newly discovered active substance carrier. More and more research has highlighted the important contribution of EVs in the progress of tumor. Molecular changes during disease progression could be detected in EVs. However, the diagnostic applications of EVs are not generally understood. Combined with the characteristics of hepatobiliary and pancreatic tumor, we summarized the recent developments in various omics analysis of EVs. Furtherly, we explored the role of EVs in the early diagnosis of hepatobiliary and pancreatic tumors by multi-omics analysis.

Current and Developing Liquid Biopsy Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer and leading cause of cancer mortality among woman worldwide. The techniques of diagnosis, prognosis, and therapy monitoring of breast cancer are critical. Current diagnostic techniques are mammography and tissue biopsy; however, they have limitations. With the development of novel techniques, such as personalized medicine and genetic profiling, liquid biopsy is emerging as the less invasive tool for diagnosing and monitoring breast cancer. Liquid biopsy is performed by sampling biofluids and extracting tumor components, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell-free mRNA (cfRNA) and microRNA (miRNA), proteins, and extracellular vehicles (EVs). In this review, we summarize and focus on the recent discoveries of tumor components and biomarkers applied in liquid biopsy and novel development of detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and microfluidic devices.

Fast quantification of extracellular vesicles levels in early breast cancer patients by Single Molecule Detection Array (SiMoA)

PURPOSE

Preliminary reports suggest that extracellular vesicles (EVs) might be a promising biomarker for breast cancer (BC). However, the quantification of plasmatic levels of EVs is a complex task. To overcome these limitations, we developed a new, fast, and easy to use assay for the quantification of EVs directly in plasma based on the use of Single-Molecule Array (SiMoA).

METHODS

By using SiMoA to identify CD9+/CD63+ EVs, we analyzed plasma samples of 181 subjects (95 BC and 86 healthy controls, HC). A calibration curve, made of a serial dilution of lyophilized standards from human plasma, was used in each run to ensure the obtainment of quantitative results from the assay. In a subgroup of patients, EVs concentrations were estimated in plasma before and after 30 days from cancer surgery. Additional information on the size of EVs were also acquired using a Nanosight system to obtain a clearer understanding of the mechanism underlying the releases of EVs associated with the presence of cancer.

RESULTS

The measured levels of EVs resulted significantly higher in BC patients (median values 1179.1 ng/µl vs 613.0 ng/µl, p < 0.0001). ROC curve was used to define the optimal cut-off level of the test at 1034.5 ng/µl with an AUC of 0.75 [95% CI 0.68-0.82]. EVs plasmatic concentrations significantly decreased after cancer surgery compared to baseline values (p = 0.014). No correlation was found between EVs concentration and clinical features of BC.

CONCLUSION

SiMoA assay allows plasmatic EVs levels detection directly without any prior processing. EVs levels are significantly higher in BC patients and significantly decreases after cancer surgery.

Extracellular Vesicles as Mediators of Therapy Resistance in the Breast Cancer Microenvironment

Resistance to various therapies, including novel immunotherapies, poses a major challenge in the management of breast cancer and is the leading cause of treatment failure. Bidirectional communication between breast cancer cells and the tumour microenvironment is now known to be an important contributor to therapy resistance. Several studies have demonstrated that crosstalk with the tumour microenvironment through extracellular vesicles is an important mechanism employed by cancer cells that leads to drug resistance via changes in protein, lipid and nucleic acid cargoes. Moreover, the cargo content enables extracellular vesicles to be used as effective biomarkers for predicting response to treatments and as potential therapeutic targets. This review summarises the literature to date regarding the role of extracellular vesicles in promoting therapy resistance in breast cancer through communication with the tumour microenvironment.

Ratiometric 3D DNA Machine Combined with Machine Learning Algorithm for Ultrasensitive and High-Precision Screening of Early Urinary Diseases

Urinary extracellular vesicles (uEVs) have received considerable attention as a potential biomarker source for the diagnosis of urinary diseases. Present studies mainly focus on the discovery of biomarkers based on high-throughput proteomics, while limited efforts have been paid to applying the uEVs' biomarkers for the diagnosis of early urinary disease. Herein, we demonstrate a diagnosis protocol to realize ultrasensitive detection of uEVs and accurate classification of early urinary diseases, by combing a ratiometric three-dimensional (3D) DNA machine with machine learning (ML). The ratiometric 3D DNA machine platform is constructed by conjugating a padlock probe (PLP) containing cytosine-rich (C-rich) sequences, anchor strands, and nucleic-acid-stabilized silver nanoclusters (DNA_AgNCs) onto the magnetic nanoparticles (MNPs). The competitive binding of uEVs with the aptamer releases the walker strand, thus the ratiometric 3D DNA machine was activated to undergo an accurate amplification reaction and produce a ratiometric fluorescence signal. The present biosensor offers a detection limit of 9.9 × 10³ particles mL^-1 with a linear range of 10⁴-10⁸ particles mL^-1 for uEVs. Two ML algorithms, K-nearest neighbor (KNN) and support vector machine (SVM), were subsequently applied for analyzing the correlation between the sensing signals of uEV multibiomarkers and the clinical state. The disease diagnostic accuracy of optimal biomarker combination reaches 95% and 100% by analyzing with KNN and SVM, and the disease type classification exhibits an accuracy of 94.7% and 89.5%, respectively. Moreover, the protocol results in 100% accurate visual identification of clinical uEV samples from individuals with disease or as healthy control by a t-distributed stochastic neighbor embedding (tSNE) algorithm.

Multiplexed Profiling of Extracellular Vesicles for Biomarker Development

Extracellular vesicles (EVs) are cell-derived membranous particles that play a crucial role in molecular trafficking, intercellular transport and the egress of unwanted proteins. They have been implicated in many diseases including cancer and neurodegeneration. EVs are detected in all bodily fluids, and their protein and nucleic acid content offers a means of assessing the status of the cells from which they originated. As such, they provide opportunities in biomarker discovery for diagnosis, prognosis or the stratification of diseases as well as an objective monitoring of therapies. The simultaneous assaying of multiple EV-derived markers will be required for an impactful practical application, and multiplexing platforms have evolved with the potential to achieve this. Herein, we provide a comprehensive overview of the currently available multiplexing platforms for EV analysis, with a primary focus on miniaturized and integrated devices that offer potential step changes in analytical power, throughput and consistency.