A multiparametric extraction method for Vn96-isolated plasma extracellular vesicles and cell-free DNA that enables multi-omic profiling

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.

Small RNA sequencing analysis of peptide-affinity isolated plasma extracellular vesicles distinguishes pancreatic cancer patients from non-affected individuals

Pancreatic ductal adenocarcinoma (PDAC) has a high fatality rate, mainly due to its asymptomatic nature until late-stage disease and therefore delayed diagnosis that leads to a lack of timely treatment intervention. Consequently, there is a significant need for better methods to screen populations that are at high risk of developing PDAC. Such advances would result in earlier diagnosis, more treatment options, and ultimately better outcomes for patients. Several recent studies have applied the concept of liquid biopsy, which is the sampling of a biofluid (such as blood plasma) for the presence of disease biomarkers, to develop screening approaches for PDAC; several of these studies have focused on analysis of extracellular vesicles (EVs) and their cargoes. While these studies have identified many potential biomarkers for PDAC that are present within EVs, their application to clinical practice is hindered by the lack of a robust, reproducible method for EV isolation and analysis that is amenable to a clinical setting. Our previous research has shown that the Vn96 synthetic peptide is indeed a robust and reproducible method for EV isolation that has the potential to be used in a clinical setting. We have therefore chosen to investigate the utility of the Vn96 synthetic peptide for this isolation of EVs from human plasma and the subsequent detection of small RNA biomarkers of PDAC by Next-generation sequencing (NGS) analysis. We find that analysis of small RNA from Vn96-isolated EVs permits the discrimination of PDAC patients from non-affected individuals. Moreover, analyses of all small RNA species, miRNAs, and lncRNA fragments are most effective at segregating PDAC patients from non-affected individuals. Several of the identified small RNA biomarkers have been previously associated with and/or characterized in PDAC, indicating the validity of our findings, whereas other identified small RNA biomarkers may have novel roles in PDAC or cancer in general. Overall, our results provide a basis for a clinically-amendable detection and/or screening strategy for PDAC using a liquid biopsy approach that relies on Vn96-mediated isolation of EVs from plasma.

Multi-omics of extracellular vesicles: An integrative representation of functional mediators and perspectives on lung disease study

Extracellular vesicles are secreted by almost all cell types. EVs include a broader component known as exosomes that participate in cell-cell and tissue-tissue communication via carrying diverse biological signals from one cell type or tissue to another. EVs play roles as communication messengers of the intercellular network to mediate different physiological activities or pathological changes. In particular, most EVs are natural carriers of functional cargo such as DNA, RNA, and proteins, and thus they are relevant to advancing personalized targeted therapies in clinical practice. For the application of EVs, novel bioinformatic models and methods based on high-throughput technologies and multi-omics data are required to provide a deeper understanding of their biological and biomedical characteristics. These include qualitative and quantitative representation for identifying cargo markers, local cellular communication inference for tracing the origin and production of EVs, and distant organ communication reconstruction for targeting the influential microenvironment and transferable activators. Thus, this perspective paper introduces EVs in the context of multi-omics and provides an integrative bioinformatic viewpoint of the state of current research on EVs and their applications.

Recent developments in isolating methods for exosomes

Exosomes are the smallest extracellular vesicles that can be released by practically all cell types, and range in size from 30 nm to 150 nm. As the major marker of liquid biopsies, exosomes have great potential for disease diagnosis, therapy, and prognosis. However, their inherent heterogeneity, the complexity of biological fluids, and the presence of nanoscale contaminants make the isolation of exosomes a great challenge. Traditional isolation methods of exosomes are cumbersome and challenging with complex and time-consuming operations. In recent years, the emergence of microfluidic chips, nanolithography, electro-deposition, and other technologies has promoted the combination and innovation of the isolation methods. The application of these methods has brought very considerable benefits to the isolation of exosomes such as ultra-fast, portable integration, and low loss. There are significant functional improvements in isolation yield, isolation purity, and clinical applications. In this review, a series of methods for the isolation of exosomes are summarized, with emphasis on the emerging methods, and in-depth comparison and analysis of each method are provided, including their principles, merits, and demerits.

Peptide-Affinity Isolation of Extracellular Vesicles and Cell-Free DNA From Human Plasma

Extracellular vesicles (EVs) are membrane-bound nanoparticles that carry DNA, RNA, and protein cargoes and are found in a variety of biofluids. EVs, along with cell-free DNA (cfDNA), have attracted interest as a source of biomarker material for liquid biopsy, a process in which a sample of body fluid is used for the detection or monitoring of disease. The Vn96 synthetic peptide facilitates the isolation of both EVs and cfDNA from multiple body fluids, including human plasma, placing it as a versatile tool for the capture of multiple biomarker materials for disease detection and/or treatment monitoring. In this chapter, we describe an optimized protocol for Vn96-mediated isolation of EVs and cfDNA from human plasma samples, as well as downstream methods for EV enumeration and DNA, RNA, and protein extraction from the material captured by Vn96 for use in biomarker discovery or detection.

Recent Advances in the Discovery of Biomarkers for Canine Osteosarcoma

Canine osteosarcoma (OSA) is an aggressive malignancy that frequently metastasizes to the lung and bone. Not only has there been essentially no improvement in therapeutic outcome over the past 3 decades, but there is also a lack of reliable biomarkers in clinical practice. This makes it difficult to discriminate which patients will most benefit from the standard treatment of amputation and adjuvant chemotherapy. The development of reliable diagnostic biomarkers could aid in the clinical diagnosis of primary OSA and metastasis; while prognostic, and predictive biomarkers could allow clinicians to stratify patients to predict response to treatment and outcome. This review summarizes biomarkers that have been explored in canine OSA to date. The focus is on molecular biomarkers identified in tumor samples as well as emerging biomarkers that have been identified in blood-based (liquid) biopsies, including circulating tumor cells, microRNAs, and extracellular vesicles. Lastly, we propose future directions in biomarker research to ensure they can be incorporated into a clinical setting.

Longitudinal stability of urinary extracellular vesicle protein patterns within and between individuals

The protein content of urinary extracellular vesicles (EVs) is considered to be an attractive non-invasive biomarker source. However, little is known about the consistency and variability of urinary EV proteins within and between individuals over a longer time-period. Here, we evaluated the stability of the urinary EV proteomes of 8 healthy individuals at 9 timepoints over 6 months using data-independent-acquisition mass spectrometry. The 1802 identified proteins had a high correlation amongst all samples, with 40% of the proteome detected in every sample and 90% detected in more than 1 individual at all timepoints. Unsupervised analysis of top 10% most variable proteins yielded person-specific profiles. The core EV-protein-interaction network of 516 proteins detected in all measured samples revealed sub-clusters involved in the biological processes of G-protein signaling, cytoskeletal transport, cellular energy metabolism and immunity. Furthermore, gender-specific expression patterns were detected in the urinary EV proteome. Our findings indicate that the urinary EV proteome is stable in longitudinal samples of healthy subjects over a prolonged time-period, further underscoring its potential for reliable non-invasive diagnostic/prognostic biomarkers.