Plasma Extracellular Vesicles for Cardiovascular Disease
Dominique PV de Kleijn, Professor Experimental Vascular Surgery, Professor Netherlands Heart Institute, University Medical Center Utrecht, The Netherlands, Netherlands

Cardiovascular Disease (CVD) is with the cardiovascular events of Ischemic Heart Disease and Stroke, the number 1 and 2 cause of death in the world and expect to increase especially in Asia. We use plasma extracellular vesicle (EV) protein content of vesicles from plasma subfractions on plasma of stroke and periferal artery disease(PAD) patients, patients after carotid atherectomy (CEA) and patients suspected for chronic coronary syndrome (CCS). Using 25 ul of plasma, we developed an automated 96-well based protocol using sequential precipitation. Using samples of the AtheroExpress, the largest ongoing CEA biobank we try to early detect the risk of a second Major Adverse Cardiovascular Event (MACE: myocardial infarction, stroke or cardiovascular death) in PAD and CEA patients. Identification of such high risk patients is very important for possible (expensive) add-on pharmaceutical therapy or the decision to operate or not. Sequential procipitation for EV isolation is also used for the diagnosis of CCS.

Versatile and Multiplexed Extracellular Vesicle and Single Extracellular Vesicle Analysis
David Juncker, Professor and Chair, McGill University, Canada

Extracellular vesicles (EVs) have emerged as a fundamental cell signaling and cargo system. EV proteomic analysis face challenges such difficulty to detect internal EV proteins, difficult to normalize concentration, co-expression, and lack of reproducibility. Single EV analysis, while highly desirable, still suffers from imprecision owing to lack of a protein markers universally expressed in EVs, low fluorescence of single molecules, and low scattering signals and the ensuing difficulty to detect small EVs. Here our efforts to address these challenges will be presented including multiplexed (i) inner and outer protein profiling in EVs; (ii) co-enrichment analysis which builds on co-expression analysis and quantifies protein co-enrichment, either negative or positive, and is illustrated with >100 protein pairs in EVs from metastatic, organotropic breast cancer cell lines. Next, (iii) a single EV analysis platform for label-free interference scattering (iSCAT) on a common (fluorescence) microscope will be introduced, and sizing of EVs from ~35 nm to ~200 nm in diameter shown, outperforming existing methods such as nanoflow cytometry; (iv) the co-expression and co-enrichment profiles of ~20 proteins on single EVs will be demonstrated by combining iSCAT, fluorescence imaging, and microfluidic exchange of DNA-barcoded antibodies. These new EV analysis methods will be useful to detect, profile and analyse EVs in health and disease, and deepen our understanding of their function.

Chip-Based Flow-Cytometry: From CTCs to Extracellular Vesicles
Andrew J deMello, Professor of Biochemical Engineering & Institute Chair, ETH Zürich, Switzerland

Imaging flow cytometry (IFC) marries the advantages of optical microscopy and flow cytometry to enable the high-throughput imaging of cells within flowing environments. I will describe how we have leveraged the capabilities of simple microfluidic systems to form novel platforms able to manipulate, process and assay cells in a controlled and high-throughput manner. Using inertial and viscoelastic effects, these systems can operate at throughputs exceeding 400,000 cells/s, extract fluorescence, brightfield, and darkfield images and are capable of multi-parametric quantification and sub-cellular localization of structures down to 500 nm. Additionally, I will describe more recent activities in which similar viscoelastic microfluidic platforms are used to measure the mechanical properties of cells at high-throughput and also isolate and analyse CTCs and extracellular vesicles in a rapid and efficient manner.

Extracellular Vesicles: From Technology Towards Biomedical Applications
An Hendrix, Professor, Ghent University, Belgium

Extracellular vesicles (EVs) are membrane-enclosed communicative particles released in body fluids that carry cell-type-specific biomolecular patterns. Knowledge on their origin, fate and function in the human body is required to accelerate clinical applications but hampered by a plethora of technological pitfalls (PMID:33568799). We created the EV-TRACK knowledgebase to stimulate transparency and steer reproducibility (PMID:28245209). We designed reference EVs, that are trackable and distinguishable from sample EVs, to support instrument calibration and data normalization (PMID:31337761; 33452501). We established reproducible protocols to separate EVs from other particles (PMID:31776460). This supporting ecosystem has steered us towards the pioneering discovery of systemic bacterial EVs in non-septicemic patients, including cancer patients (PMID:30518529; 35033427).

Title to be Confirmed.
Jennifer Jones, NIH Stadtman Investigator, Head of Transnational Nanobiology, Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, United States of America

Screening Tests Using Micro- and Nanofluidics for Early Disease Detection at the Point-of-Care
Steve Soper, Foundation Distinguished Professor, Director, Center of BioModular Multi-Scale System for Precision Medicine, The University of Kansas, United States of America

We are developing screening tests consisting of novel hardware, biomarkers, and assays to service a number of diseases, including the early detection of cancer and viral infections. The commonality in these tests is that they consist of microfluidic devices made from plastics via injection molding. Thus, our tests can be mass produced at low-cost that facilitates bench-to-bedside transition and point-of-care testing (PoCT) for large scale screening. The assays are based on the use of liquid biopsy markers as the input, which can be secured in a non- to minimally-invasive manner appropriate for screening. Recently we have focused on developing plastic nanofluidic devices, which provides unique opportunities for single-entity analyses. In this presentation, we will talk about the evolution of our fabrication efforts of plastic-based microfluidic and nanofluidic devices as well as their surface modification to make devices biocompatible. Then, we will discuss two applications of these devices and the assays for selection of rare liquid biopsy targets from clinical samples to serve as screening tests: (1) Analysis of extracellular vesicles (EVs) for the early detection of ovarian cancer; and (2) detection of viral particles from saliva samples, in particular SARS-CoV-2.  Ovarian cancer is the 5th most deadly cancer for women in the US and has a 46.2% 5-y survival rate. Unfortunately, ~85% of cases are diagnosed at a late stage of disease, which demands new strategies for early detection. The screening test we are developing consists of a microfluidic chip for EV selection, which consists of a high density array of pillars surface-decorated with antibodies to efficiently select EVs followed by the label-free enumeration to determine elevated levels of EVs in the plasma of patients suspected of having ovarian cancer. Unique surface proteins were discovered for selection of ovarian cancer EV selection specifically for the early detection of disease. The infectious disease diagnostic accepts saliva samples and searches for viral particles using aptamers and counts the number of viral particles. For both disease examples, the selected particles were counted using a label-free approach; nano-Coulter Counter chip (nCC) consisting of in-plane nanopores. Both steps of the screening test described here were carried out using a microfluidic and nanofluidic chip. The chips were integrated to a control board for automating sample processing with results in <20 min.

Nanotechnologies for Isolating and Characterizing Extracellular Nanocarriers of Biomarkers
Hsueh-Chia Chang, Bayer Professor of Chemical and Biomolecular Engineering, University of Notre Dame, Interim Chief Technology Officer, Aopia Biosciences, United States of America

We review a suite of nanotechnologies from our lab for high-throughput and scalable purification, enrichment and characterization of extracellular vesicles. The technologies are designed for medical diagnostics and biomarker discovery with physiological samples and for large-volume manufacturing of therapeutic exosomes. The relevant nanocarriers are exosomes, lipoproteins or protein-RNA complexes that carry potential protein and nucleic acid biomarkers for cancer, cardiovascular, neurodegenerative and even mental diseases.  The technologies include size-based ultrafiltration membranes with conic nanopores to reduce protein fouling, bipolar membranes that can split water and actuate on-chip pH gradient to allow rapid and continuous isoelectric separation of nanocarriers by charge, superparamagnetic traps of immuno-nanobeads for rapid affinity and activity assay of specific nanocarriers, electrokinetic nanoporous microsensors that can profile surface proteins of nanocarriers, solid-state nanopore sensor for profiling microRNA cargoes etc.

Plasma Extracellular Vesicle-Associated microRNAs for On-Treatment Response Monitoring and Prediction
D. Michiel Pegtel, Associate Professor, Amsterdam University Medical Center, Netherlands

Response monitoring and outcome prediction is essential in the clinical management of hematological malignancies. Extracellular Vesicle associated microRNAs (EV-miRNAs) are considered promising liquid biopsy-based biomarkers for hematological malignancies. We performed small RNA sequencing of plasma samples collected during therapy and applied machine learning to build signatures for response prediction in Multiple Myeloma (MM) and patients with high grade B-cell lymphoma (HGBL). We collected plasma samples from multiple clinical trials and obtained 'real-world' samples. In HGBL, response was assessed by an end-of-treatment (EOT) PET/CT while in MM we defined response based in part on M protein levels. We isolated plasma EVs with size exclusion chromatography as confirmed with transmission electron microscopy (TEM), tunable resistive pulse sensing (TRPS), and western blotting. Library preparation was done according to our IsoSeek method. We applied machine learning to build models with EV-miRNAs for early response prediction (HGBL) and monitoring (MM). We could generate robust signatures for HGBL that can predict EOT response after one cycle of R-CHOP. If validated in independent cohorts, this novel approach could potentially, in combination with other modalities, guide early risk-adapted treatment strategies. In addition, we show that EV-miRNAs distinguish MM patients with active disease from those in remission. Together our data suggests plasma EV-miRNA sequencing is a versatile platform technology for minimally invasive response evaluation and prediction.