Modeling EV Kinetics for Use in Early Cancer Detection

Stoichiometric constraints for detection of EV-borne biomarkers in blood

Stochiometric issues, encompassing both the quantity and heterogeneity of extracellular vesicles (EVs) derived from tumour or other tissues in blood, pose important challenges across various stages of biomarker discovery and detection, affecting the integrity of data, introducing losses and artifacts during blood processing, EV purification and analysis. These challenges shape the diagnostic utility of EVs especially within the framework of established and emerging methodologies. By addressing these challenges, we aim to delineate crucial parameters and requirements for tumour-specific EV detection, or more precisely, for tumour identification via EV based assays. Our endeavour involves a comprehensive examination of the layers that mask or confound the traceability of EV markers such as nucleic acids and proteins, and focus on 'low prevalence-low concentration' scenario. Finally, we evaluate the advantages versus limitations of single-particle analysers over more conventional bulk assays, suggesting that the combined use of both to capture and interpret the EV signals, in particular the EV surface displayed proteins, may ultimately provide quantitative information on their absolute abundance and distribution.

Squeezable Hydrogel Microparticles for Single Extracellular Vesicle Protein Profiling

Extracellular vesicles (EVs) are promising for molecular diagnostics, but current analyses are limited by the rarity and compositional heterogeneity of EV protein expression. Therefore, single EV profiling methods require high sensitivity, multiplexing, and throughput to address these issues. Here a single EV analysis technique that utilizes squeezable methacrylated hyaluronic acid hydrogel microparticles (MHPs) is described as a scaffold to immobilize EVs and perform an integrated rolling circle amplification (RCA) assay for an ultra-sensitive and multiplex analysis of single EV proteins. EVs are prepared into MHPs in a high-throughput manner with droplet microfluidics and optimally labeled with antibody-oligonucleotide conjugates in MHPs without steric limitations. By designing MHPs with high compressibility, single EV protein signals are amplified as RCA products that can be aligned on the same plane by physically squeezing MHPs and visualized with low magnification. This method provides a simple and scalable single EV imaging analysis pipeline for identifying multiplex marker expression patterns from single EVs. For validation, the single EV heterogeneity of highly expressed cancer cell markers is profiled across different cancer cell lines. These findings exemplify squeezable MHPs as a robust platform with high sensitivity, multiplexing, and scalability for resolving single EV heterogeneity and advancing molecular assay technologies.

The Role of Exosomes in Cancer Progression and Therapy

Exosomes are small extracellular vesicles and are crucial in intercellular communication. Interestingly, tumor-derived exosomes carry oncogenic molecules, such as proteins and microRNAs, which can reprogram recipient cells, promote angiogenesis, and stimulate cancer pre-metastatic niche, supporting cancer growth and metastasis. On the other hand, their biocompatibility, stability, and ability to cross biological barriers make them attractive candidates for drug delivery. Recent advances have shown the potential for exosomes to be used in early disease detection and in targeted drug therapy by delivering therapeutic agents specifically to tumor sites. Despite the promising applications, a number of challenges remain, including exosome isolation and characterization, as well as their inherent heterogeneity. Thus, the current review aims to describe the roles of exosomes in health and disease, and discuss the challenges that hinder their development into becoming useful medical tools.

Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort

The low incidence of ovarian cancer (OC) dictates that any screening strategy needs to be both highly sensitive and highly specific. This study explored the utility of detecting multiple colocalized proteins or glycosylation epitopes on single tumor-associated extracellular vesicles from blood. The novel Mercy Halo Ovarian Cancer Test (OC Test) uses immunoaffinity capture of tumor-associated extracellular vesicles, followed by proximity-ligation real-time quantitative PCR to detect combinations of up to three biomarkers to maximize specificity, and measures multiple combinations to maximize sensitivity. A high-grade serous carcinoma (HGSC) case-control training set of EDTA plasma samples from 397 women was used to lock down the test design, the data interpretation algorithm, and the cutoff between cancer and noncancer. Performance was verified and compared with cancer antigen 125 in an independent blinded case-control set of serum samples from 390 women (132 controls, 66 HGSC, 83 non-HGSC OC, and 109 benign). In the verification study, the OC Test showed a specificity of 97.0% (128/132; 95% CI, 92.4%-99.6%), a HGSC sensitivity of 97.0% (64/66; 95% CI, 87.8%-99.2%), and an area under the curve of 0.97 (95% CI, 0.93-0.99) and detected 73.5% (61/83; 95% CI, 62.7%-82.6%) of the non-HGSC OC cases. This test exhibited fewer false positives in subjects with benign ovarian tumors, nonovarian cancers, and inflammatory conditions when compared with cancer antigen 125. The combined sensitivity and specificity of this new test suggests that it may have potential in OC screening.

Exosomes, circadian rhythms, and cancer precision medicine: New frontiers

"The environment shapes people's actions," a well-known proverb, strongly dictates that a change in our way of life changes our behavior. Circadian rhythms have been identified as a mechanism for maintaining homeostasis in the body, which, if disrupted by sleeping patterns, could result in significant metabolic alterations that adversely affect our health. The changes induced by circadian rhythm alter the secretion and cargo selection in exosomes which are nanovesicles important for intercellular communication. Exosomes were formerly known as "junk particles" but are now recognized as miniature copies of a cell's genetic material. Dysregulation of circadian rhythm has shown that it changes the gene expression of a cell to some extent and significantly alters the exosomal release. Meanwhile, cells secrete exosomes continuously to align the rhythmicity of the biological clock. In this study, we integrate circadian rhythms and exosomes with precision medicines to find better approaches to early diagnosis and treatment of disease.

Colocalization of Cancer-Associated Biomarkers on Single Extracellular Vesicles for Early Detection of Cancer

Detection of cancer early, when it is most treatable, remains a significant challenge because of the lack of diagnostic methods sufficiently sensitive to detect nascent tumors. Early-stage tumors are small relative to their tissue of origin, heterogeneous, and infrequently manifest in clinical symptoms. The detection of early-stage tumors is challenging given the lack of tumor-specific indicators (ie, protein biomarkers, circulating tumor DNA) to enable detection using a noninvasive diagnostic assay. To overcome these obstacles, we have developed a liquid biopsy assay that interrogates circulating extracellular vesicles (EVs) to detect tumor-specific biomarkers colocalized on the surface of individual EVs. We demonstrate the technical feasibility of this approach in human cancer cell line-derived EVs, where we show strong correlations between assay signal and cell line gene/protein expression for the ovarian cancer-associated biomarkers bone marrow stromal antigen-2, folate receptor-α, and mucin-1. Furthermore, we demonstrate that detecting distinct colocalized biomarkers on the surface of EVs significantly improves discrimination performance relative to single biomarker measurements. Using this approach, we observe promising discrimination of high-grade serous ovarian cancer versus benign ovarian masses and healthy women in a proof-of-concept clinical study.

Serum Exosomes Expressing CD9, CD63 and HER2 From Breast-Cancer Patients Decreased After Surgery of the Primary Tumor: A Potential Biomarker of Tumor Burden

BACKGROUND/AIM

Exosomes are extracellular vesicles produced by both normal and cancer cells. Previous research has demonstrated that circulating exosomes derived from cancer cells may create a niche for future metastasis, distant from the primary tumor. In the present report, circulating exosomes were captured and quantified based on exosome-surface proteins in pre- and post-operative serum of breast cancer patients, focusing on the exosome markers CD9 and CD63, as well as HER2, a therapeutic target for breast cancer.

MATERIALS AND METHODS

Eight breast cancer patients were recruited, and their pre- and post-operative serum samples were analyzed for CD63 and CD9; or CD9 and human epidermal growth factor receptor-2 (HER2), double-positive exosomes. An ExoCounter with antibody-conjugated beads was used to capture serum-derived exosomes. Sera from patients with tumors larger than 10 mm were used for analysis. The resected breast cancer was also histopathologically analyzed for the presence of HER2.

RESULTS

CD63 and CD9 double-positive serum exosomes and CD9 and HER2 double-positive serum exosomes decreased after surgery in breast-cancer patients whose tumors expressed HER2, as determined by histopathological analysis.

CONCLUSION

Serum exosomes expressing CD9, CD63 and HER2 are candidate biomarkers of tumor burden in HER2-positive breast-cancer patients.

Ultrasensitive quantification of PD-L1+ extracellular vesicles in melanoma patient plasma using a parallelized high throughput droplet digital assay

The expression of programmed death-ligand 1 (PD-L1) on extracellular vesicles (EVs) is an emerging biomarker for cancer, and has gained particular interest for its role mediating immunotherapy. However, precise quantification of PD-L1+ EVs in clinical samples remains challenging due to their sparse concentration and the enormity of the number of background EVs in human plasma, limiting applicability of conventional approaches. In this study, we develop a high-throughput droplet-based extracellular vesicle analysis (DEVA) assay for ultrasensitive quantification of EVs in plasma that are dual positive for both PD-L1 and tetraspanin (CD81) known to be expressed on EVs. We achieve a performance that significantly surpasses conventional approaches, demonstrating 360× enhancement in the limit of detection (LOD) and a 750× improvement in the limit of quantitation (LOQ) compared to conventional plate enzyme-linked immunoassay (ELISA). Underlying this performance is DEVA's high throughput analysis of individual EVs one at a time and the high specificity to targeted EVs versus background. We achieve a 0.006% false positive rate per droplet by leveraging avidity effects that arise from EVs having multiple copies of their target ligands on their surface. We use parallelized optofluidics to rapidly process 10 million droplets per minute, ∼100× greater than conventional approaches. A validation study on a cohort of 14 patients with melanoma confirms DEVA's ability to match conventional ELISA measurements with reduced plasma sample volume and without the need for prior EV purification. This proof-of-concept study demonstrates DEVA's potential for clinical utility to enhance prognosis as well as guide treatment for cancer.

An electro-optical platform for the ultrasensitive detection of small extracellular vesicle sub-types and their protein epitope counts

Methods for detecting proteins in small extracellular vesicles (sEVs) lack sensitivity and quantitative accuracy, missing clues about health and disease. Our study introduces the Nano-Extracellular Omics Sensing (NEXOS) platform, merging electrical (E-NEXOS) and optical detection (O-NEXOS). E-NEXOS determines the concentration of target sEV sub-types, and O-NEXOS quantifies the concentration of target protein epitopes (TEPs) on those TEVs. In this work, both technologies were compared to several sEV detection tools, showing superior detection limits for CD9+CD81+ and CD9+HER2+ sEVs. Furthermore, the additional information on TEVs and TEPs from bulk sEV samples, provided new phenotyping capabilities. We determined the average number of CD81 and HER2 proteins on CD9+ sEVs, a number which was later validated on spiked human plasma. These results highlight the compatibility of NEXOS with complex biofluids and, as importantly, hint at its many potential applications, ranging from basic research to the anticipated clinical translation of sEVs.

Colocalization of protein and microRNA markers reveals unique extracellular vesicle subpopulations for early cancer detection

Extracellular vesicles (EVs) play important roles in cell-cell communication but are highly heterogeneous, and each vesicle has dimensions smaller than 200 nm with very limited amounts of cargos encapsulated. The technique of NanOstirBar (NOB)-EnabLed Single Particle Analysis (NOBEL-SPA) reported in the present work permits rapid inspection of single EV with high confidence by confocal fluorescence microscopy, thus enables colocalization assessment for selected protein and microRNA (miRNA) markers in the EVs produced by various cell lines, or present in clinical sera samples. EV subpopulations marked by the colocalization of unique protein and miRNA combinations were discovered to be able to detect early-stage (stage I or II) breast cancer (BC). NOBEL-SPA can be adapted to analyze other types of cargo molecules or other small submicron biological particles. Study of the sorting of specific cargos to heterogeneous vesicles under different physiological conditions can help discover distinct vesicle subpopulations valuable in clinical examination and therapeutics development and gain better understanding of their biogenesis.

Small extracellular vesicles from surviving cancer cells as multiparametric monitoring tools of measurable residual disease and therapeutic efficiency

Although conventional anti-cancer therapies remove most cells of the tumor mass, small surviving populations may evolve adaptive resistance strategies, which lead to treatment failure. The size of the resistant population initially may not reach the threshold of clinical detection (designated as measurable residual disease/MRD) thus, its investigation requires highly sensitive and specific methods. Here, we discuss that the specific molecular fingerprint of tumor-derived small extracellular vesicles (sEVs) is suitable for longitudinal monitoring of MRD. Furthermore, we present a concept that exploiting the multiparametric nature of sEVs may help early detection of recurrence and the design of dynamic, evolution-adjusted treatments.

Extracellular Vesicles as Liquid Biopsy Biomarkers across the Cancer Journey: From Early Detection to Recurrence

BACKGROUND

Cancer is a dynamic process and thus requires highly informative and reliable biomarkers to help guide patient care. Liquid-based biopsies have emerged as a clinical tool for tracking cancer dynamics. Extracellular vesicles (EVs), lipid bilayer delimited particles secreted by cells, are a new class of liquid-based biomarkers. EVs are rich in selectively sorted biomolecule cargos, which provide a spatiotemporal fingerprint of the cell of origin, including cancer cells.

CONTENT

This review summarizes the performance characteristics of EV-based biomarkers at different stages of cancer progression, from early malignancy to recurrence, while emphasizing their potential as diagnostic, prognostic, and screening biomarkers. We discuss the characteristics of effective biomarkers, consider challenges associated with the EV biomarker field, and report guidelines based on the biomarker discovery pipeline.

SUMMARY

Basic science and clinical trial studies have shown the potential of EVs as precision-based biomarkers for tracking cancer status, with promising applications for diagnosing disease, predicting response to therapy, and tracking disease burden. The multi-analyte cargos of EVs enhance the performance characteristics of biomarkers. Recent technological advances in ultrasensitive detection of EVs have shown promise with high specificity and sensitivity to differentiate early-cancer cases vs healthy individuals, potentially outperforming current gold-standard imaging-based cancer diagnosis. Ultimately, clinical translation will be dictated by how these new EV biomarker-based platforms perform in larger sample cohorts. Applying ultrasensitive, scalable, and reproducible EV detection platforms with better design considerations based upon the biomarker discovery pipeline should guide the field towards clinically useful liquid biopsy biomarkers.

Electrokinetically enhanced label-free plasmonic sensing for rapid detection of tumor-derived extracellular vesicles

ANALYSIS

of rare circulating extracellular vesicles (EV) from early cancers or different types of host cells requires extremely sensitive EV sensing technologies. Nanoplasmonic EV sensing technologies have demonstrated good analytical performances, but their sensitivity is often limited by EVs' diffusion to the active sensor surface for specific target EV capture. Here, we developed an advanced plasmonic EV platform with electrokinetically enhanced yields (KeyPLEX). The KeyPLEX system effectively overcomes diffusion-limited reactions with applied electroosmosis and dielectrophoresis forces. These forces bring EVs toward the sensor surface and concentrate them in specific areas. Using the keyPLEX, we showed significant improvements in detection sensitivity by ∼100-fold, leading to the sensitive detection of rare cancer EVs from human plasma samples in 10 min. The keyPLEX system could become a valuable tool for point-of-care rapid EV analysis.

Exosomes in the Diagnosis and Treatment of Renal Cell Cancer

Renal cell carcinoma (RCC) is the most prevalent type of kidney cancer originating from renal tubular epithelial cells, with clear cell RCC comprising approximately 80% of cases. The primary treatment modalities for RCC are surgery and targeted therapy, albeit with suboptimal efficacies. Despite progress in RCC research, significant challenges persist, including advanced distant metastasis, delayed diagnosis, and drug resistance. Growing evidence suggests that extracellular vesicles (EVs) play a pivotal role in multiple aspects of RCC, including tumorigenesis, metastasis, immune evasion, and drug response. These membrane-bound vesicles are released into the extracellular environment by nearly all cell types and are capable of transferring various bioactive molecules, including RNA, DNA, proteins, and lipids, aiding intercellular communication. The molecular cargo carried by EVs renders them an attractive resource for biomarker identification, while their multifarious role in the RCC offers opportunities for diagnosis and targeted interventions, including EV-based therapies. As the most versatile type of EVs, exosomes have attracted much attention as nanocarriers of biologicals, with multi-range signaling effects. Despite the growing interest in exosomes, there is currently no widely accepted consensus on their subtypes and properties. The emerging heterogeneity of exosomes presents both methodological challenges and exciting opportunities for diagnostic and clinical interventions. This article reviews the characteristics and functions of exosomes, with a particular reference to the recent advances in their application to the diagnosis and treatment of RCC.

Modeling and optimization of parallelized immunomagnetic nanopore sorting for surface marker specific isolation of extracellular vesicles from complex media

The isolation of specific subpopulations of extracellular vesicles (EVs) based on their expression of surface markers poses a significant challenge due to their nanoscale size (< 800 nm), their heterogeneous surface marker expression, and the vast number of background EVs present in clinical specimens (1010-1012 EVs/mL in blood). Highly parallelized nanomagnetic sorting using track etched magnetic nanopore (TENPO) chips has achieved precise immunospecific sorting with high throughput and resilience to clogging. However, there has not yet been a systematic study of the design parameters that control the trade-offs in throughput, target EV recovery, and ability to discard background EVs in this approach. We combine finite-element simulation and experimental characterization of TENPO chips to elucidate design rules to isolate EV subpopulations from blood. We demonstrate the utility of this approach by reducing device background > 10× relative to prior published designs without sacrificing recovery of the target EVs by selecting pore diameter, number of membranes placed in series, and flow rate. We compare TENPO-isolated EVs to those of gold-standard methods of EV isolation and demonstrate its utility for wide application and modularity by targeting subpopulations of EVs from multiple models of disease including lung cancer, pancreatic cancer, and liver cancer.

Extracellular vesicle analysis of plasma allows differential diagnosis of atypical pancreatic serous cystadenoma

Increased use of cross-sectional imaging has resulted in frequent detection of incidental cystic pancreatic lesions. Serous cystadenomas (SCAs) are benign cysts that do not require surgical intervention unless symptomatic. Unfortunately, up to half of SCAs do not have typical imaging findings ("atypical SCAs"), overlap with potentially malignant precursor lesions, and thus pose a diagnostic challenge. We tested whether the analysis of circulating extracellular vesicle (EV) biomarkers using a digital EV screening technology (DEST) could enhance the discrimination of cystic pancreatic lesions and avoid unnecessary surgical intervention in these atypical SCAs. Analysis of 25 different protein biomarkers in plasma EV from 68 patients identified a putative biomarker signature of Das-1, Vimentin, Chromogranin A, and CAIX with high discriminatory power (AUC of 0.99). Analysis of plasma EV for multiplexed markers may thus be helpful in clinical decision-making.

Colocalization of Protein and microRNA Markers Reveals Unique Extracellular Vesicle Sub-Populations for Early Cancer Detection

Extracellular vesicles (EVs) play important roles in cell-cell communication but they are highly heterogeneous, and each vesicle has dimensions smaller than 200 nm thus encapsulates very limited amounts of cargos. We report the technique of NanOstirBar (NOB)-EnabLed Single Particle Analysis (NOBEL-SPA) that utilizes NOBs, which are superparamagnetic nanorods easily handled by a magnet or a rotating magnetic field, to act as isolated "islands" for EV immobilization and cargo confinement. NOBEL-SPA permits rapid inspection of single EV with high confidence by confocal fluorescence microscopy, and can assess the colocalization of selected protein/microRNA (miRNA) pairs in the EVs produced by various cell lines or present in clinical sera samples. Specific EV sub-populations marked by the colocalization of unique protein and miRNA combinations have been revealed by the present work, which can differentiate the EVs by their cells or origin, as well as to detect early-stage breast cancer (BC). We believe NOBEL-SPA can be expanded to analyze the co-localization of other types of cargo molecules, and will be a powerful tool to study EV cargo loading and functions under different physiological conditions, and help discover distinct EV subgroups valuable in clinical examination and therapeutics development.

Multiplexed analysis of EV reveals specific biomarker composition with diagnostic impact

Exosomes and extracellular vesicles (EV) are increasingly being explored as circulating biomarkers, but their heterogenous composition will likely mandate the development of multiplexed EV technologies. Iteratively multiplexed analyses of near single EVs have been challenging to implement beyond a few colors during spectral sensing. Here we developed a multiplexed analysis of EV technique (MASEV) to interrogate thousands of individual EVs during 5 cycles of multi-channel fluorescence staining for 15 EV biomarkers. Contrary to the common belief, we show that: several markers proposed to be ubiquitous are less prevalent than believed; multiple biomarkers concur in single vesicles but only in small fractions; affinity purification can lead to loss of rare EV subtypes; and deep profiling allows detailed analysis of EV, potentially improving the diagnostic content. These findings establish the potential of MASEV for uncovering fundamental EV biology and heterogeneity and increasing diagnostic specificity.

Plasmon-Enhanced Single Extracellular Vesicle Analysis for Cholangiocarcinoma Diagnosis

Cholangiocarcinoma (CCA) is a fatal disease often detected late in unresectable stages. Currently, there are no effective diagnostic methods or biomarkers to detect CCA early with high confidence. Analysis of tumor-derived extracellular vesicles (tEVs) harvested from liquid biopsies can provide a new opportunity to achieve this goal. Here, an advanced nanoplasmonic sensing technology is reported, termed FLEX (fluorescence-amplified extracellular vesicle sensing technology), for sensitive and robust single EV analysis. In the FLEX assay, EVs are captured on a plasmonic gold nanowell surface and immunolabeled for cancer-associated biomarkers to identify tEVs. The underlying plasmonic gold nanowell structures then amplify EVs' fluorescence signals, an effective amplification process at the single EV level. The FLEX EV analysis revealed a wide heterogeneity of tEVs and their marker levels. FLEX also detected small tEVs not detected by conventional EV fluorescence imaging due to weak signals. Tumor markers (MUC1, EGFR, and EPCAM) are identified in CCA, and this marker combination is applied to detect tEVs in clinical bile samples. The FLEX assay detected CCA with an area under the curve of 0.93, significantly better than current clinical markers. The sensitive and accurate nanoplasmonic EV sensing technology can aid in early CCA diagnosis.

Prostate cancer extracellular vesicle digital scoring assay - a rapid noninvasive approach for quantification of disease-relevant mRNAs

Optimizing outcomes in prostate cancer (PCa) requires precision in characterization of disease status. This effort was directed at developing a PCa extracellular vesicle (EV) Digital Scoring Assay (DSA) for detecting metastasis and monitoring progression of PCa. PCa EV DSA is comprised of an EV purification device (i.e., EV Click Chip) and reverse-transcription droplet digital PCR that quantifies 11 PCa-relevant mRNA in purified PCa-derived EVs. A Met score was computed for each plasma sample based on the expression of the 11-gene panel using the weighted Z score method. Under optimized conditions, the EV Click Chips outperformed the ultracentrifugation or precipitation method of purifying PCa-derived EVs from artificial plasma samples. Using PCa EV DSA, the Met score distinguished metastatic (n = 20) from localized PCa (n = 20) with an area under the receiver operating characteristic curve of 0.88 (95% CI:0.78-0.98). Furthermore, longitudinal analysis of three PCa patients showed the dynamics of the Met scores reflected clinical behavior even when disease was undetectable by imaging. Overall, a sensitive PCa EV DSA was developed to identify metastatic PCa and reveal dynamic disease states noninvasively. This assay may complement current imaging tools and blood-based tests for timely detection of metastatic progression that can improve care for PCa patients.

Importance and implications of exosomes in nephrology and urology

Exosomes are extracellular vesicles that are formed by two invaginations of the plasma membrane and can be released by all eukaryotic cells. Because of their bioactive contents, including nucleic acids and proteins, exosomes can activate a variety of functions in their recipient cells. Due to the plethora of physiological and pathophysiological functions, exosomes have received a lot of attention from researchers over the past few years. However, there is still no consensus regarding isolation and characterization protocols of exosomes and their subtypes. This heterogeneity poses a lot of methodical challenges but also offers new clinical opportunities simultaneously. So far, exosome-based research is still mostly limited to preclinical experiments and early-stage clinical trials since the translation of experimental findings remains difficult. Exosomes could potentially play an important role as future diagnostic and prognostic agents and might also be part of the development of new treatment strategies. Therefore, they have previously been investigated in a variety of nephrological and urological conditions such as acute kidney injury or prostate cancer.

Future of Digital Assays to Resolve Clinical Heterogeneity of Single Extracellular Vesicles

Extracellular vesicles (EVs) are complex lipid membrane vehicles with variable expressions of molecular cargo, composed of diverse subpopulations that participate in the intercellular signaling of biological responses in disease. EV-based liquid biopsies demonstrate invaluable clinical potential for overhauling current practices of disease management. Yet, EV heterogeneity is a major needle-in-a-haystack challenge to translate their use into clinical practice. In this review, existing digital assays will be discussed to analyze EVs at a single vesicle resolution, and future opportunities to optimize the throughput, multiplexing, and sensitivity of current digital EV assays will be highlighted. Furthermore, this review will outline the challenges and opportunities that impact the clinical translation of single EV technologies for disease diagnostics and treatment monitoring.

Profiling of extracellular vesicles of metastatic urothelial cancer patients to discover protein signatures related to treatment outcome

The prognosis of metastatic urothelial carcinoma (mUC) patients is poor, and early prediction of systemic therapy response would be valuable to improve outcome. In this exploratory study, we investigated protein profiles in sequential plasma‐isolated extracellular vesicles (EVs) from a subset of mUC patients treated within a Phase I trial with vinflunine combined with sorafenib. The isolated EVs were of exosome size and expressed exosome markers CD9, TSG101 and SYND‐1. We found, no association between EVs/ml plasma at baseline and progression‐free survival (PFS). Protein profiling of EVs, using an antibody‐based 92‐plex Proximity Extension Assay on the Oncology II^® platform, revealed a heterogeneous protein expression pattern. Qlucore bioinformatic analyses put forward a protein signature comprising of SYND‐1, TNFSF13, FGF‐BP1, TFPI‐2, GZMH, ABL1 and ERBB3 to be putatively associated with PFS. Similarly, a protein signature from EVs that related to best treatment response was found, which included FR‐alpha, TLR 3, TRAIL and FASLG. Several of the markers in the PFS or best treatment response signatures were also identified by a machine learning classification algorithm. In conclusion, protein profiling of EVs isolated from plasma of mUC patients shows a potential to identify protein signatures that may associate with PFS and/or treatment response.

Single-EV analysis (sEVA) of mutated proteins allows detection of stage 1 pancreatic cancer

Tumor cell-derived extracellular vesicles (EVs) are being explored as circulating biomarkers, but it is unclear whether bulk measurements will allow early cancer detection. We hypothesized that a single-EV analysis (sEVA) technique could potentially improve diagnostic accuracy. Using pancreatic cancer (PDAC), we analyzed the composition of putative cancer markers in 11 model lines. In parental PDAC cells positive for KRASmut and/or P53mut proteins, only ~40% of EVs were also positive. In a blinded study involving 16 patients with surgically proven stage 1 PDAC, KRASmut and P53mut protein was detectable at much lower levels, generally in <0.1% of vesicles. These vesicles were detectable by the new sEVA approach in 15 of the 16 patients. Using a modeling approach, we estimate that the current PDAC detection limit is at ~0.1-cm3 tumor volume, below clinical imaging capabilities. These findings establish the potential for sEVA for early cancer detection.

Utilising extracellular vesicles for early cancer diagnostics: benefits, challenges and recommendations for the future

To increase cancer patient survival and wellbeing, diagnostic assays need to be able to detect cases earlier, be applied more frequently, and preferably before symptoms develop. The expansion of blood biopsy technologies such as detection of circulating tumour cells and cell-free DNA has shown clinical promise for this. Extracellular vesicles released into the blood from tumour cells may offer a snapshot of the whole of the tumour. They represent a stable and multifaceted complex of a number of different types of molecules including DNA, RNA and protein. These represent biomarker targets that can be collected and analysed from blood samples, offering great potential for early diagnosis. In this review we discuss the benefits and challenges of the use of extracellular vesicles in this context and provide recommendations on where this developing field should focus their efforts to bring future success.

Recent Advances in Device Engineering and Computational Analysis for Characterization of Cell-Released Cancer Biomarkers

During cancer progression, tumors shed different biomarkers into the bloodstream, including circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA). The analysis of these biomarkers in the blood, known as 'liquid biopsy' (LB), is a promising approach for early cancer detection and treatment monitoring, and more recently, as a means for cancer therapy. Previous reviews have discussed the role of CTCs and ctDNA in cancer progression; however, ctDNA and EVs are rapidly evolving with technological advancements and computational analysis and are the subject of enormous recent studies in cancer biomarkers. In this review, first, we introduce these cell-released cancer biomarkers and briefly discuss their clinical significance in cancer diagnosis and treatment monitoring. Second, we present conventional and novel approaches for the isolation, profiling, and characterization of these markers. We then investigate the mathematical and in silico models that are developed to investigate the function of ctDNA and EVs in cancer progression. We convey our views on what is needed to pave the way to translate the emerging technologies and models into the clinic and make the case that optimized next-generation techniques and models are needed to precisely evaluate the clinical relevance of these LB markers.

Multiplexed electrokinetic sensor for detection and therapy monitoring of extracellular vesicles from liquid biopsies of non-small-cell lung cancer patients

Liquid biopsies based on extracellular vesicles (EVs) represent a promising tool for treatment monitoring of tumors, including non-small-cell lung cancers (NSCLC). In this study, we report on a multiplexed electrokinetic sensor for surface protein profiling of EVs from clinical samples. The method detects the difference in the streaming current generated by EV binding to the surface of a functionalized microcapillary, thereby estimating the expression level of a marker. Using multiple microchannels functionalized with different antibodies in a parallel fluidic connection, we first demonstrate the capacity for simultaneous detection of multiple surface markers in small EVs (sEVs) from NSCLC cells. To investigate the prospects of liquid biopsies based on EVs, we then apply the method to profile sEVs isolated from the pleural effusion (PE) fluids of five NSCLC patients with different genomic alterations (ALK, KRAS or EGFR) and applied treatments (chemotherapy, EGFR- or ALK-tyrosine kinase inhibitors). The vesicles were targeted against CD9, as well as EGFR and PD-L1, two treatment targets in NSCLC. The electrokinetic signals show detection of these markers on sEVs, highlighting distinct interpatient differences, e.g., increased EGFR levels in sEVs from a patient with EGFR mutation as compared to an ALK-fusion one. The sensors also detect differences in PD-L1 expressions. The analysis of sEVs from a patient prior and post ALK-TKI crizotinib treatment reveals significant increases in the expressions of some markers (EGFR and PD-L1). These results hold promise for the application of the method for tumor treatment monitoring based on sEVs from patient liquid biopsies.

Intelligent Probabilistic System for Digital Tracing Cellular Origin of Individual Clinical Extracellular Vesicles

Extracellular vesicles (EVs) are small vesicles secreted by various cell types to mediate cell-to-cell communication through the transfer of macromolecules. EVs carry multiple cargo molecules that reflect the origins of their donor cells; thus, they can be considered reliable biomarkers for early cancer diagnosis. However, the diverse cellular origin of EV masks the detection signals generated by both tumor- and nontumor-derived cells. Thereby, the capability to recognize the cellular origin of EVs is the prerequisite for their diagnostic applications. In the present study, we develop an intelligent probabilistic system for tracing the cellular origin of individual EVs using single-molecule multicolor imaging. Through the analysis of the expression profile of two typical membrane protein markers, CD9 and CD63, on single EVs, accurate and rapid probabilistic recognition of EVs derived from individual tumor and nontumor cells in clinical samples is achieved. The correlation between cellular origin and surface protein phenotyping on single EVs is also exemplified. The proposed system holds great potential for advancing EVs as reliable clinical indicators and exploring their biological functions.

Extracellular Vesicle Analysis Allows for Identification of Invasive IPMN

BACKGROUND AND AIMS

Advances in cross-sectional imaging have resulted in increased detection of intraductal papillary mucinous neoplasms (IPMNs), and their management remains controversial. At present, there is no reliable noninvasive method to distinguish between indolent and high risk IPMNs. We performed extracellular vesicle (EV) analysis to identify markers of malignancy in an attempt to better stratify these lesions.

METHODS

Using a novel ultrasensitive digital extracellular vesicle screening technique (DEST), we measured putative biomarkers of malignancy (MUC1, MUC2, MUC4, MUC5AC, MUC6, Das-1, STMN1, TSP1, TSP2, EGFR, EpCAM, GPC1, WNT-2, EphA2, S100A4, PSCA, MUC13, ZEB1, PLEC1, HOOK1, PTPN6, and FBN1) in EV from patient-derived cell lines and then on circulating EV obtained from peripheral blood drawn from patients with IPMNs. We enrolled a total of 133 patients in two separate cohorts: a clinical discovery cohort (n = 86) and a validation cohort (n = 47).

RESULTS

From 16 validated EV proteins in plasma samples collected from the discovery cohort, only MUC5AC showed significantly higher levels in high-grade lesions. Of the 11 patients with invasive IPMN (inv/HG), 9 had high MUC5AC expression in plasma EV of the 11 patients with high-grade dysplasia alone, only 1 had high MUC5AC expression (sensitivity of 82%, specificity of 100%). These findings were corroborated in a separate validation cohort. The addition of MUC5AC as a biomarker to imaging and high-riskstigmata allowed detection of all cases requiring surgery, whereas imaging and high-risk stigmata alone would have missed 5 of 14 cases (36%).

CONCLUSIONS

MUC5AC in circulating EV can predict the presence of invasive carcinoma within IPMN. This approach has the potential to improve the management and follow-up of patients with IPMN including avoiding unnecessary surgery.

Detection of Tumor-Associated Membrane Receptors on Extracellular Vesicles from Non-Small Cell Lung Cancer Patients via Immuno-PCR

Simple Summary

Lung cancer is often detected at late stages when metastases are present and the genomic make-ups of the tumors are heterogeneous. Analyses of genomic alterations in non-small-cell lung cancer (NSCLC) have revealed mutated tumor-associated membrane receptors and fusion proteins, which can be targeted via tyrosine kinase inhibitors (TKIs). TKIs initially often have a good effect, but a fraction of the tumor lesions may develop resistance through additional mutations in the targeted kinases or by increased expression/function of other membrane receptors. Detection of TKI-bypassing mechanisms is difficult in tissue biopsies as these analyze only a subpart of tumors or lesions. Liquid biopsies based on tumor-secreted small extracellular vesicles (sEVs) into body fluids can assess tumor heterogeneity. We present an immuno-PCR method for the detection of the epidermal growth factor receptor (EGFR), the human epidermal growth factor receptor 2 (HER2), and the insulin-like growth factor 1 receptor (IGF-1R) on sEVs. Initial investigations of sEVs from EGFR-mutant NSCLC tumor cells or pleural effusion (PE) fluid from patients with NSCLC or benign diseases showed different protein profiles for individual sEV samples. Further development of the immuno-PCR could complement DNA/mRNA-based assays detecting kinase mutations to allow longitudinal treatment monitoring of diverse TKI-bypassing mechanisms.

Abstract

Precision cancer medicine for non-small-cell lung cancer (NSCLC) has increased patient survival. Nevertheless, targeted agents towards tumor-associated membrane receptors only result in partial remission for a limited time, calling for approaches which allow longitudinal treatment monitoring. Rebiopsy of tumors in the lung is challenging, and metastatic lesions may have heterogeneous signaling. One way ahead is to use liquid biopsies such as circulating tumor DNA or small extracellular vesicles (sEVs) secreted by the tumor into blood or other body fluids. Herein, an immuno-PCR-based detection of the tumor-associated membrane receptors EGFR, HER2, and IGF-1R on CD9-positive sEVs from NSCLC cells and pleural effusion fluid (PE) of NSCLC patients is developed utilizing DNA conjugates of antibody mimetics and affibodies, as detection agents. Results on sEVs purified from culture media of NSCLC cells treated with anti-EGFR siRNA, showed that the reduction of EGFR expression can be detected via immuno-PCR. Protein profiling of sEVs from NSCLC patient PE samples revealed the capacity to monitor EGFR, HER2, and IGF-1R with the immuno-PCR method. We detected a significantly higher EGFR level in sEVs derived from a PE sample of a patient with an EGFR-driven NSCLC adenocarcinoma than in sEVs from PE samples of non-EGFR driven adenocarcinoma patients or in samples from patients with benign lung disease. In summary, we have developed a diagnostic method for sEVs in liquid biopsies of cancer patients which may be used for longitudinal treatment monitoring to detect emerging bypassing resistance mechanisms in a noninvasive way.

3D Cell Cultures as Prospective Models to Study Extracellular Vesicles in Cancer

The improvement of culturing techniques to model the environment and physiological conditions surrounding tumors has also been applied to the study of extracellular vesicles (EVs) in cancer research. EVs role is not only limited to cell-to-cell communication in tumor physiology, they are also a promising source of biomarkers, and a tool to deliver drugs and induce antitumoral activity. In the present review, we have addressed the improvements achieved by using 3D culture models to evaluate the role of EVs in tumor progression and the potential applications of EVs in diagnostics and therapeutics. The most employed assays are gel-based spheroids, often utilized to examine the cell invasion rate and angiogenesis markers upon EVs treatment. To study EVs as drug carriers, a more complex multicellular cultures and organoids from cancer stem cell populations have been developed. Such strategies provide a closer response to in vivo physiology observed responses. They are also the best models to understand the complex interactions between different populations of cells and the extracellular matrix, in which tumor-derived EVs modify epithelial or mesenchymal cells to become protumor agents. Finally, the growth of cells in 3D bioreactor-like systems is appointed as the best approach to industrial EVs production, a necessary step toward clinical translation of EVs-based therapy.