AC Electrokinetics Research Articles

Single step capture and assessment of multiple plasma extracellular vesicle biomarkers in Alzheimer's disease detection.

Blood tests for Alzheimer's disease (AD) that measure biomarkers related to neuropathology have demonstrated to be useful, minimally-invasive ways to identify patients for screening into clinical trials. While some AD biomarkers can be detected in plasma, greater sensitivity is needed to make plasma AD tests more effective. Extracellular vesicles (EVs) in plasma carry AD-related biomarkers from the brain and could offer a concentrated source of brain-related biomarkers, though the methodological complexities involved in isolating plasma EVs have hampered its validation for clinical use. To explore the feasibility and effectiveness of developing blood tests for AD utilizing extracellular vesicle-bound protein biomarkers. We developed a simplified method for isolating EVs directly from plasma using an alternating current electrokinetic (ACE) microchip. No sample pretreatment steps were needed. Protein biomarkers on the EVs were detected by adding fluorescent antibodies to the plasma samples before capture by the chip. This allowed measurement of EV biomarker levels directly on the chip. AD or non-AD control plasma was measured for ten different AD-related biomarkers. EV-associated NCAM1, pTau231, α-synuclein, and TDP-43 levels were able to distinguish a group of 10 AD, 10 mild cognitive impairment (MCI), and 10 non-AD subjects. pTau231 was different between AD and non-AD (p = 0.0300) and α-synuclein differentiated AD from MCI (p = 0.0148). This study shows how ACE microfluidic chip technology can help differentiate AD and MCI patients from non-AD controls with clinical relevance. This work also highlights the important diagnostic role of plasma EV biomarkers in neurodegenerative disease.

Editorial for the Special Issue on AC Electrokinetics in Microfluidic Devices, Volume II

The use of AC electric fields in manipulating and characterizing liquids and suspended particles in microfluidic systems continues to drive innovation in several fields, such as colloidal science, microelectronics, and biotechnology [...]

Flexible and simultaneous multi-scale bioparticle manipulation to actuate cell and drug delivery utilizing AC electrokinetic -powered microswimmer

Bioparticle trapping and transporting are essential processes for developing an integrated cell and drug delivery system. Herein, we present a unique platform that effectively combines magnetic field and alternating current (AC) electrokinetics for the simultaneous manipulation of bioparticles across scales. The magnetic field is used to control the moving direction of Janus swimmers, and the AC electrokinetics incorporating dielectrophoresis (DEP) and induced charge electroosmosis (ICEO) flow are utilized to power Janus swimmers to manipulate bioparticles. Numerical characterization of the stagnant regions generated by DEP and ICEO elucidates the trapping mechanisms for both micro and nano bioparticles. We demonstrate that the Janus swimmers are capable of navigating along varied trajectories at speeds of up to hundreds of micrometers per second. Developed phase maps, derived from AC frequency and medium conductivity parameters, delineate three distinct bioparticle loading positions, offering a versatile guide for the manipulation of cells and nanodrugs. The platform’s adaptability is further highlighted by its success in performing mobile trapping of cells and nanodrugs along user-defined trajectories, targeted trapping of nanoparticle aggregations, and simultaneous multi-scale bioparticle capture. The presented multi-scale bioparticle trapping strategy, together with its unique features of simple geometric configuration, facile operation and broad applicability, can broaden utility in cellular and pharmaceutical research.

A universal AC electrokinetics-based strategy toward surface antifouling of underwater optics

The practical applications of underwater optical devices, such as cameras or sensors, often suffer from widespread surface biofouling. Current antifouling techniques are primarily hindered by low efficiency, poor compatibility, as well as environmental pollution issues. This paper presents a transparent electrode coating as antifouling system of underwater optics as potential substitute for alternating current electrokinetic (ACEK)-based systems. A strong-coupling model is established to predict the Joule heating induced fluid flows and the negative dielectrophoretic (nDEP) effect for mobilizing organisms or deposited sediments on optic surfaces. The performance of the proposed antifouling system is numerically evaluated through simulations of electrostatic, fluid and temperature fields as well as trajectories of submicron particles, which is then experimentally verified and found to be in good agreement. A parametric study revealed that the degree of electrodes asymmetry is the key factor affecting the flow pattern and therefore the overall performance of the system. This ACEK-based universal strategy is expected to shed light on designing high performance and non-toxic platforms toward energy-efficient surface antifouling applications of underwater optics.

Abstract A011: Proteomic expression using exosomes in intraductal papillary mucinous neoplasms (IPMN) patients to inform risk stratification

Abstract Introduction Intraductal papillary mucinous neoplasm (IPMN), the most common type of pancreatic mucinous cysts, harbor risks of malignant progression of approximately 50% and 5% when found in the main duct (MD) and branch duct (BD), respectively. Surgical resection is standard of care in patients with high-risk stigmata and in some “indeterminate” cases, while surveillance modalities, which may include invasive imaging, are recommended for cases of cysts with “worrisome features”. Given the poor prognosis of late-stage pancreatic cancer, it is critical to accurately risk-stratify patients with IPMNs. We conducted a pilot study to evaluate the association of IPMN features with protein markers using extracellular vesicles (EVs), including exosomes, isolated from the blood of patients with resected IPMNs. Experimental procedure We evaluated 19 patients with IPMNs who underwent surgical resection (Whipple or distal pancreatectomy). Blood was collected before surgery and the EVs were isolated from plasma using an alternating current electrokinetics (ACE) platform. The concentration of 52 EV proteins was measured using a multiplex immunoassay. Surgical explant pathology reports were available and reviewed on all 19 patients. Data are presented as average concentration and 95% CI, and p-values represent the two-tailed t-test. Results Average age was 69 years (range: 47-83) and, of the 19 patients, 12 (63%) were male. Seventeen patients never smoked or were former smokers (quit > 20 years) before sample collection. A total of 14 patients had acute or chronic pancreatitis (7 historical; 7 found in surgical explant) while 4 patients had previously undiagnosed pancreatic intraepithelial neoplasia (PanIN) at the time of surgery. In our EV analysis, we found multiple EV protein biomarkers to be elevated in patients with various IPMN characteristics. Marker A was significantly elevated in patients with high-grade dysplasia (n=10) compared to low-grade dysplasia (n=9) (10.8 [8.4-13.2] vs. 7.5 [5.8 - 9.2] pg/mL, respectively, p = 0.0241), as defined by surgical explant pathology. When examining 13 patients with main-duct or mixed-type IPMNs, markers B, C, and D were elevated compared to the 6 patients with branch-duct or unspecified IPMNs (marker B: 1.9 [1.4-2.3] vs. 1.1 [0.9-1.4] ng/mL, p=0.0099; marker C: 524.3 [400.2-648.4] vs. 318.8 [209.9-427.7] pg/mL, p=0.0102; marker D: 65.8 [43.8-87.7] vs. 39.9 [31.7-48.1] pg/mL, p=0.0281). Conclusions In this pilot study that evaluated 19 patients with IPMNs, we identified multiple EV proteins that are differentially expressed in subgroups of patients. Our findings suggest that these differentially expressed proteomic markers can lead to the development of an algorithm for IPMN risk-stratification and possibly help discern histopathologic grade. Future studies will expand on these preliminary results with the aim of identifying a panel of biomarkers that can risk-stratify IPMNs to guide medical decision-making. Citation Format: Harmeet Dhani, Roberta V. Alexander, Juan Pablo Hinestrosa, Jesus Izaguirre-Carbonell, Dove Keith, Paul R. Billings, Gregory Cote', Rosalie Sears. Proteomic expression using exosomes in intraductal papillary mucinous neoplasms (IPMN) patients to inform risk stratification [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A011.

ACEK Biosensor for the Minute-Scale Quantification of Breast Cancer ctDNA.

Circulating tumor DNA (ctDNA) appears as a valuable liquid biopsy biomarker in the early diagnosis, treatment, and prognosis of cancer. Here, a biosensing method derived from the AC electrokinetics (ACEK) effect was constructed in this study for the simple, efficient, and rapid method of detection of ctDNA. In the proof-of-concept experiment, ctDNA from the PIK3CA E542K mutant in breast cancer was quantified by detecting a normalized capacitance change rate using a forked-finger gold electrode as the sensing electrode in combination with the ACEK effect. We compared two formats for the construction of the approach by employing varied immobilization strategies; one is to immobilize the DNA capture probe on the electrode surface by Au-S bonding, while the other immobilizes the probe on a self-assembled membrane on the electrode surface by amide bonding. Both formats demonstrated ultrafast detection speed by completing the ctDNA quantification within 1 min and a linear range of 10 fM-10 pM was observed. Meanwhile, the immobilization via the self-assembled membrane yielded improved stability, sensitivity, and specificity than its Au-S bonding counterpart. A detection limit of 1.94 fM was eventually achieved using the optimized approach. This research provides a label-free and minute-scale universal method for the detection of various malignant tumors. The ctDNA biosensors based on the ACEK effect improved according to the probe type or electrode structure and have potential applications in tumor drug efficacy prediction, drug resistance monitoring, screening of high-risk groups, differential diagnosis, monitoring of tiny residual lesions, and prognosis determination.

An ultra-sensitive and rapid immunosensor for the onsite detection of circulating tumor DNA in breast cancer.

Breast cancer currently stands as the most prevalent form of cancer worldwide and the primary cause of cancer-related deaths among women. However, the current diagnostic methods for breast cancer exhibit several limitations, including invasiveness, high costs, and limited sensitivity and specificity. The detection of the PIK3CA-H1047R variant is of paramount importance due to its close association with tumor growth and treatment resistance. Consequently, developing a straightforward, rapid, and highly sensitive approach for detecting PIK3CA-H1047R is of utmost importance. We have been working on the development of a rapid and ultrasensitive biosensor, leveraging the alternating current (AC) electrokinetic (ACEK) capacitive sensing method. This biosensor involves modifying the surface of interdigital electrodes with antibodies, facilitating the antibody-antigen-binding process through AC electrokinetic techniques. Our sensor strategy directly measures the interface capacitance, and the rate of change serves as a quantitative marker for event identification. Remarkably, our biosensor successfully detects the PIK3CA-H1047R antigen within a concentration range of 1ng/mL to 1μg/mL. In conclusion, this study proposes a fast and highly sensitive biosensor for the detection of a key breast cancer marker, the PIK3CA-H1047R variant. This technology is expected to improve breast cancer diagnosis, address the limitations of current methods, and provide patients with better treatment options. This detection method offers a promising avenue for on-site and real-time sensitive detection of the PIK3CA-H1047R antigen, potentially revolutionizing breast cancer diagnosis.

Development of a blood-based extracellular vesicle classifier for detection of early-stage pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) has an overall 5-year survival rate of just 12.5% and thus is among the leading causes of cancer deaths. When detected at early stages, PDAC survival rates improve substantially. Testing high-risk patients can increase early-stage cancer detection; however, currently available liquid biopsy approaches lack high sensitivity and may not be easily accessible.MethodsExtracellular vesicles (EVs) were isolated from blood plasma that was collected from a training set of 650 patients (105 PDAC stages I and II, 545 controls). EV proteins were analyzed using a machine learning approach to determine which were the most informative to develop a classifier for early-stage PDAC. The classifier was tested on a validation cohort of 113 patients (30 PDAC stages I and II, 83 controls).ResultsThe training set demonstrates an AUC of 0.971 (95% CI = 0.953–0.986) with 93.3% sensitivity (95% CI: 86.9–96.7) at 91.0% specificity (95% CI: 88.3–93.1). The trained classifier is validated using an independent cohort (30 stage I and II cases, 83 controls) and achieves a sensitivity of 90.0% and a specificity of 92.8%.ConclusionsLiquid biopsy using EVs may provide unique or complementary information that improves early PDAC and other cancer detection. EV protein determinations herein demonstrate that the AC Electrokinetics (ACE) method of EV enrichment provides early-stage detection of cancer distinct from normal or pancreatitis controls.

Effect of coating nanostructure on the electrokinetics of polyelectrolyte-coated particles. Grafted vs adsorbed polymer

In this work, the electrokinetic response of nanoparticles suspensions under the action of alternating electric fields is analyzed for the case that the particles are coated with a shell of polyelectrolyte. This is an important field of application of colloidal systems, as the coating is necessary or even unavoidable for control of the stability or functionalization of the particles for a specific use. Characterization of the coating in situ is not an easy task, and electrokinetics can help in answering this question, if one goes beyond the simple routine evaluation of the electrophoretic mobility of the particles, which will provide information on the sign (and perhaps a sort of effective amount) of the surface charge and potential, but little more. The richness and rigour of the information is much more significant if AC fields are used. This is the case for the techniques evaluated in the present investigation, namely, AC electrophoresis and dielectric dispersion. They jointly sweep several decades in frequency, and are sensitive in different manners to the size of the particles, the charge of the core and the shell, the thickness and rigidity of the latter, etc. In addition, an important distinction is made between coatings with a soft or adsorbed layer structure and those with a grafted, ideally radially arranged (brush-like) polyelectrolyte. A model is first described for the AC electrokinetics in both cases, and it is demonstrated that the brush structure magnifies the Maxwell-Wagner (or double layer) polarization, leading to an elevation in the AC mobility for frequencies around the MHz, and it very much raises the amplitude of the alpha- or concentration-polarization relaxation detected in the dielectric dispersion. The distribution of the charge in a thicker region for the brush structure explains these results. Experimental investigations are carried out with silica spheres coated by PDADMAC (+) and PSS (-) polyelectrolytes in the soft-layer case, and by (vinylbenzyl)trimethylammonium chloride (+) and sodium 4-vinylbenzenesulfonate (-) monomers that were polymerized (grafted) on the particles. The results show that the brush coating produces the expected MW elevation of the mobility, mostly in the case of the cationic polymer, apparently better attached to the particles by electrostatic attraction to the negative charge of the core silica particles. In contrast, a rather monotonous decrease of the mobility in absolute value is measured for the soft coatings, indicating that the inertia of the particles sets out at lower frequencies because of aggregation. Dielectric spectra confirm the better stability in the presence of the grafted polymer, although a low-frequency elevation in the logarithmic derivative of the permittivity is a proof of the existence of aggregates, less abundant in any case than for soft coatings. Dielectric data also confirm the different amounts of charge, larger for grafted cationic layers than for anionic ones. Finally, the model elaborated can fit the experimental results yielding quantitative values of the main parameters of the coated particles, namely, effective size, overall charge of the coating, and thickness and ionic permeability of the latter.

An alternating current electrokinetics biosensor for rapid on-site serological screening of Taenia solium cysticercosis infection.

Cysticercosis, caused by Taenia solium infection, is a leading cause of acquired epilepsy in many developing countries. Several types of immunoassays have been developed for the detection of Taenia solium infection in both infected humans and livestock animals. However, these methods require central laboratory facilities and are both time- and labor-consuming with longer than desired turnaround time. In this work, we demonstrated that AC electrokinetics (ACEK) capacitive sensing can be used to realize point-of-care immunosensor in general, with the on-site screening of Taenia solium infection as an example here. The sensor employs interdigitated microelectrodes (IDME) functionalized with a recombinant Taenia solium antigen, rT24H, to detect anti-rT24H antibodies in clinical serum samples. ACEK capacitive sensing method interrogates the IDME sensors with a special AC signal, which serves the dual purposes of enriching target antibodies by ACEK effects and directly measuring the capacitance change induced by specific binding. First, to characterize the ACEK biosensor as an immunosensor in general, IgG in phosphate-buffered saline buffer was tested against IDME sensors functionalized with anti-IgG. The limit of detection of the sensor was 24.1fg/mL, and the linear dynamic range was 0.1-100pg/mL. To test the clinical usage of this sensor, ACEK capacitive sensors with rT24H probe were used to test clinical serum samples from patients with or without Taenia solium infection. The diagnostic sensitivity of the ACEK capacitive sensor for Taenia solium infection was found to be 88.24%. ACEK capacitive immunosensors have shown good potential for point-of-care diagnostics.

Abstract 5082: Proteomic analysis of extracellular vesicles from oncology donor samples purified using an alternating current electrokinetic microelectrode chip

Abstract In this study, we evaluated the ability to detect novel proteins on extracellular vesicles (EVs) following isolation using an alternating current electrokinetic (ACE) microarray. EVs circulating in blood contain a wealth of biomarkers that are thought to reflect the tumor’s proteome; however, detecting the full diversity of EV proteins may depend on choice of method to purify EVs for analysis. We compared an ACE microarray isolation method with a conventional chemical precipitation method to isolate EVs from blood plasma cancer and control samples. EVs were isolated from 1 mL each of control or pancreatic cancer patient plasma using the ExoVerita platform (Biological Dynamics) or ExoQuick Ultra kit (System Biosciences). Purified EVs were processed using tandem mass tag (TMT)-based multiplexing mass spectrometry proteomics (ThermoFisher Scientific) and the resulting peptide spectra were analyzed and quantified to determine the proteins present. Additional analyses, such as bioanalyzer measurements of contaminating plasma proteins and nanoparticle tracking analysis were performed in parallel to further characterize the isolated EVs. Cancer EVs isolated by ACE were enriched in proteins related to cancer functions when compared to non-cancer control EVs. They also showed enrichment in ontology clusters such as NABA core matrisome proteins, with depressed expression of wound healing family proteins. In contrast, EVs isolated using chemical purification demonstrated enrichment chiefly in proteins functionally grouped into immune system or blood regulation functions. After analyzing EVs isolated by ACE, a total of fifty-one (51) proteins were observed to be upregulated in the cancer donor samples. EV isolation method choice significantly impacted the proteomic profile observed. EV isolation using ACE-based technology can provide more insights into understanding the proteome by possibly reducing or removing non-specific proteins from the EVs. With better separation of EVs from blood proteins, the EV proteins identified may have greater biological significance. Citation Format: Juan P. Hinestrosa, Jean M. Lewis, David J. Searson, Heath I. Balcer, David J. Gonzalez, Rajaram Krishnan. Proteomic analysis of extracellular vesicles from oncology donor samples purified using an alternating current electrokinetic microelectrode chip [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5082.

Abstract 5960: Blood-based extracellular vesicle biomarker test for detection of early-stage pancreatic cancer

Abstract Pancreatic cancer is an almost uniformly lethal malignancy, in large part because is it rarely detected in its early, curable stages. We recently conducted a study to evaluate the use of proteins associated with extracellular vesicles (EVs) isolated using an alternating current electrokinetic (ACE) system for the early detection of pancreatic ductal adenocarcinoma. Because earlier detection of pancreatic cancer greatly improves outcomes, we sought to devise a blood-based test with high specificity for detecting early-stage PDAC based on identification of EV-bound biomarkers. EVs were purified from control or stage I-II pancreatic ductal adenocarcinoma (PDAC) patient plasma using an ACE microelectrode array. Following collection of EVs onto the electrodes, contaminating plasma elements were washed away, and the electric field was turned off to release EVs into buffer. The isolated EV/exosome samples were then tested using bead-based multiplex immunoassay kits to determine relative concentrations of biomarkers of interest. Sample cohorts were divided into a training set (controls, N=146; PDAC cases, N=33) to develop a logistic regression-based classification model, and a validation set (controls, N=139; PDAC cases, N=35) to generate a probability-based score for predicting the presence of PDAC. For the training set, the algorithm identified six protein biomarkers associated with the presence of stages I-II cancer in PDAC patient plasma, with a receiver-operating characteristic (AUC) of 0.997 (95% CI: 0.978-1.000) compared to control plasma samples. For the validation set, the algorithm had a sensitivity of 82.9% (95% CI: 67.3% - 91.9%) at a specificity of 99.3% (95% CI: 96.0% - 99.9%), generating an AUC = 0.978 (95% CI=0.954-0.995). The exosomal PDAC assay shows feasibility for developing minimally invasive liquid biopsies that allow low-risk, routine screening of high-risk patients. Those patients identified by the test would be able to undergo additional testing to determine if there is PDAC present. The additional screening and testing of these patients may increase the likelihood of curative treatment. Further work in large datasets is warranted. Citation Format: Juan P. Hinestrosa, Jean M. Lewis, Heath I. Balcer, Razelle Kurzrock, Scott Lippman, Rajaram Krishnan. Blood-based extracellular vesicle biomarker test for detection of early-stage pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5960.

Abstract 727: Detection of early-stage lung cancer using a liquid biopsy test based on extracellular vesicle proteins

Abstract We have recently conducted a study to evaluate the use of proteins associated with extracellular vesicles (EVs) isolated using an alternating current electrokinetic (ACE) system for the detection of early stage (I & II) non-small cell lung cancer (NSCLC). Most lung cancers are diagnosed at advanced stages when treatments are less effective, pointing to the need for developing non-invasive screening strategies such as liquid biopsies. We tested the feasibility of detecting the presence of early stage (I-II) lung cancer using protein biomarkers carried by EVs in patient blood. Using an ACE microelectrode array, EVs were purified from NSCLC patient (N = 62; Stage I = 39, Stage II = 23) or control plasma (N = 390) and tested for the presence of cancer biomarker proteins with bead-based multiplex immunoassay kits. A machine learning algorithm based on recursive feature elimination with cross-validation was developed to identify the most important features for differentiation between cases and controls. The algorithm identified 10 protein biomarkers that were able to distinguish between the NSCLC and control patient samples with a receiver-operator characteristic (AUC) of 0.986 (95% CI: 0.976 - 0.996). Sensitivity was 66.1% at 99.2% specificity, rising to 79.0% and 93.6% sensitivity at 98.2% and 95.1% specificity, respectively. When further stratified, Stage I sensitivity was 53.8% and stage II sensitivity was 86.7% at the 99.2% specificity level. These results suggest that it is possible to detect early-stage NSCLC when treatments may be more effective, that EVs may carry the earliest signals of cancer development, and that a test based on blood-based EV-protein biomarkers can yield high sensitivity and specificity. Our results warrant investigation in larger datasets to validate the current observations with the potential application of this methodology for routine screening of at-risk populations. Citation Format: Juan P. Hinestrosa, Jean M. Lewis, Gregor Schroder, Heath I. Balcer, Razelle Kurzrock, Rajaram Krishnan. Detection of early-stage lung cancer using a liquid biopsy test based on extracellular vesicle proteins [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 727.

Detection of early-stage ovarian cancer using a liquid biopsy test based on extracellular vesicle proteins.

e17558 Background: We have recently conducted a study to evaluate the predictive value of proteins associated with extracellular vesicles (EVs) isolated using an alternating current electrokinetic (ACE) system, for the detection of early stage (I & II) ovarian cancer cases. Ovarian cancer patients, typically, have few symptoms in stages I & II; the disease is often undetected until it is advanced. Currently, only 15% of cases are detected at early stages when clinical treatment outcomes are improved. Methods: We tested the feasibility of detecting the presence of early stage (I-II) ovarian cancer using protein biomarkers carried by EVs in patient blood. Using an ACE microelectrode array, EVs were purified from ovarian cancer patient plasma (N = 70; Stage I = 51, Stage II = 19) and female non-cancer donors (N = 290) and tested for the presence of cancer biomarker proteins with multiple bead-based multiplex immunoassay kits. An adaptive boosted trees machine learning algorithm with 100x cross-validation was developed to identify the most important features for differentiation between cases and controls. Results: The machine learning algorithm identified relevant biomarkers for the detection of ovarian cancer with a receiver-operator characteristic area under the curve (AUC) of 0.952 (95% CI: 0.918 – 0.985). Overall sensitivity was 72.9% at 99% specificity, rising to 84.3% at 95% specificity. When further stratified, Stage I sensitivity was 70.6% and stage II sensitivity was 78.9% at the 99% specificity level, as expected. We also separated the cases into endometroid carcinoma (N = 24) and serous carcinoma (N = 36). At the 99% specificity level, the sensitivity was 87.5% and 63.9%, respectively. Conclusions: These results suggest that it is possible to detect early-stage ovarian cancer by analyzing the EV-bound proteins isolated with the ACE technology. EVs may carry the earliest signals of cancer development and a blood-based EV-protein biomarker test can yield high sensitivity and specificity. Stable biomarker detection with small input volumes may be possible. These results require further investigation in larger datasets to validate the current observations with the potential application for general, routine screening, as well as for populations at elevated disease risk.

PD53-07 DETECTION OF EARLY-STAGE BLADDER CANCER USING PLASMA EXTRACELLULAR VESICLE PROTEIN BIOMARKERS

You have accessJournal of UrologyCME1 May 2022PD53-07 DETECTION OF EARLY-STAGE BLADDER CANCER USING PLASMA EXTRACELLULAR VESICLE PROTEIN BIOMARKERS Juan Hinestrosa, Jean Lewis, Gregor Schroder, Heath Balcer, and Rajaram Krishnan Juan HinestrosaJuan Hinestrosa More articles by this author , Jean LewisJean Lewis More articles by this author , Gregor SchroderGregor Schroder More articles by this author , Heath BalcerHeath Balcer More articles by this author , and Rajaram KrishnanRajaram Krishnan More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002630.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: There is a need for earlier bladder cancer screening to reduce lifetime costs and improve patient outcomes. Urinary protein biomarkers have shown some promise, but reported sensitivities appear compromised by low and/or variable biomarker concentrations. In this study, we investigated the potential of using extracellular vesicles (EV) circulating in the blood to detect stage I and II bladder cancer. Using an alternating current electrokinetic (ACE) platform to purify EVs from plasma, we show how a multi-marker EV protein-based methodology can be used to discriminate bladder cancer cases from controls in stage I and II cases. METHODS: Plasma samples were obtained from a biorepository. We used an ACE microelectrode array to isolate plasma EVs of stage I and II bladder cancer cases (N=58) or controls (N=387). EV proteins were quantified using multiplex protein immunoassays for 54 cancer-related proteins. EV protein expression patterns were analyzed using a boosted decision tree-based binary classification algorithm. To identify biomarker subsets that optimized sensitivity of the model, the permutation importance at sensitivity >99% was calculated for each feature. To evaluate biomarker and algorithm performance, a round of 10 repetitions of 5-fold cross validation was done using both the optimized hyper-parameters and the features selected via the permutation importance. RESULTS: We found that relative concentrations of a set of protein biomarkers carried by circulating plasma EVs was sufficient to discriminate bladder cancer cases from controls, with enough sensitivity to detect stage I and II cancers. The EV protein-based classifier had an overall area under curve (AUC) of 0.964 (95% CI: 0.947–0.981) with a sensitivity of 56.9% (95% CI: 44.1%–68.8%) at 99.2% specificity (95% CI: 97.8%-99.7%). At a lower 95.6% specificity (95% CI: 93.1%-97.2%) the sensitivity was 72.4% (95% CI: 59.8%-82.3%). CONCLUSIONS: Testing of EV-associated plasma proteins may enable early-stage I and II bladder cancer detection where treatment is simpler and does not require bladder resection. The classifier’s performance in this pilot, case-control study showed encouraging results for the initial 54 biomarkers studied. Since we have observed much higher specificities for other early-stage cancer types, the performance for bladder cancer will likely be improved by inclusion of additional biomarker proteins. Future efforts will include examining additional cancer types and evaluating classifier performance using samples from donors with related benign conditions with the aim of a pan-cancer early detection assay. Source of Funding: Biological Dynamics © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e912 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Juan Hinestrosa More articles by this author Jean Lewis More articles by this author Gregor Schroder More articles by this author Heath Balcer More articles by this author Rajaram Krishnan More articles by this author Expand All Advertisement PDF DownloadLoading ...

Early-stage multi-cancer detection using an extracellular vesicle protein-based blood test

BackgroundDetecting cancer at early stages significantly increases patient survival rates. Because lethal solid tumors often produce few symptoms before progressing to advanced, metastatic disease, diagnosis frequently occurs when surgical resection is no longer curative. One promising approach to detect early-stage, curable cancers uses biomarkers present in circulating extracellular vesicles (EVs). To explore the feasibility of this approach, we developed an EV-based blood biomarker classifier from EV protein profiles to detect stages I and II pancreatic, ovarian, and bladder cancer.MethodsUtilizing an alternating current electrokinetics (ACE) platform to purify EVs from plasma, we use multi-marker EV-protein measurements to develop a machine learning algorithm that can discriminate cancer cases from controls. The ACE isolation method requires small sample volumes, and the streamlined process permits integration into high-throughput workflows.ResultsIn this case-control pilot study, comparison of 139 pathologically confirmed stage I and II cancer cases representing pancreatic, ovarian, or bladder patients against 184 control subjects yields an area under the curve (AUC) of 0.95 (95% CI: 0.92 to 0.97), with sensitivity of 71.2% (95% CI: 63.2 to 78.1) at 99.5% (97.0 to 99.9) specificity. Sensitivity is similar at both early stages [stage I: 70.5% (60.2 to 79.0) and stage II: 72.5% (59.1 to 82.9)]. Detection of stage I cancer reaches 95.5% in pancreatic, 74.4% in ovarian (73.1% in Stage IA) and 43.8% in bladder cancer.ConclusionsThis work demonstrates that an EV-based, multi-cancer test has potential clinical value for early cancer detection and warrants future expanded studies involving prospective cohorts with multi-year follow-up.

Front Cover: Enhancing affinity‐based electroanalytical biosensors by integrated AC electrokinetic enrichment—A mini review

DOI: 10.1002/elps.202100168 The cover picture shows how affinity-based electroanalytical biosensors can be enhanced by integrated AC electrokinetic (ACEK) effects. ACEK effects, including AC electrothermal (ACET) effect, AC electroosmosis (ACEO) effect and dielectrophoretic (DEP) effect, are produced by applying AC signals to the interdigitated electrode arrays. ACEK effects induce directed movement of microflows and particles (e.g., proteins, nucleic acids, bacteria, small molecules, etc.) in the solution, so that the analytes in the solution can be quickly routed toward the surface of biosensors, thus improving the binding efficiency between the analytes and the probes on the surface of the sensor. Studies have shown that the method holds great promise for achieving high sensitivity, low detection limit and rapid turnaround.

Arsenic(III) Stripping Electroanalysis Enhanced by AC Electrokinetics at Hot Microelectrodes

Inorganic arsenic is regarded as a human carcinogen and is highly toxic to the environment. In this work, we investigated the detection of As(III) at a 25 μm bare gold disk microelectrode polarized by a high-frequency (ca. 100 MHz) alternating current (hot microelectrode). Square wave voltammetry method was employed to determine low arsenic concentration (nanomolar range), which was below the concentration limit set by the US Environmental Protection Agency (130 nM). Nitric acid was used as a supporting electrolyte; a deposition potential was −0.6 V and the deposition time 120 s. A linear relationship from 0 to 60 nM was observed and the sensitivity of detection was 0.0064 nA nM−1 with a limit of detection (LOD) of 8.8 nM, which can be further lowered by increasing the deposition time. For a real-sample analysis, filtered tap water was spiked with known concentrations of arsenic, and a calibration curve was obtained.

Enhancing affinity-based electroanalytical biosensors by integrated AC electrokinetic enrichment-A mini review.

Biosensors play a central role in moving diagnostics to being on-site or decentralized. Affinity biosensor, an important category of biosensors, has important applications in clinical diagnosis, pharmaceuticals, immunology, and other fields. Affinity biosensors rely on specific binding between target analytes and biological ligands such as antibodies, nucleic acids, or other receptors to generate measurable signals. Oftentimes the target analytes in practical samples are of low abundance in a complex matrix. Traditional affinity biosensors mainly rely on random diffusion of analytes in solution to conjugate with biorecognition elements on the sensor surface of electrodes. The process may take hours or even days, which is not conducive to rapid and sensitive detection of biosensors. Therefore, it is strongly desired to incorporate an enrichment mechanism for target analytes into biosensor-based detection. AC electrokinetic (ACEK) effect can realize rapid enrichment of analytes by application of AC electric fields, which holds great promise for achieving high sensitivity, low detection limit, and rapid turnaround. This article reviews the studies of affinity biosensors integrated with ACEK enrichment in the past decade, and summarizes the latest detection methods, detection devices and applications, hoping to provide some insights and references for researchers in related fields.

A Sensitive and Specific Genomic RNA Sensor for Point-of-Care Screening of Zika Virus from Serum.

This work presents a sensitive and specific single-step RNA sensor for Zika virus (ZIKV) in serum. Using AC electrokinetics (ACEK)-enhanced capacitive sensing technology, ZIKV genomic RNA (gRNA) can be directly detected from serum. The sensors are interdigitated electrodes modified with oligonucleotide probes complementary to the conserved regions of ZIKV gRNA. The ACEK capacitive sensing applies an optimized AC excitation signal over the sensor, which induces ACEK microfluidic enrichment of analytes and also simultaneously performs real-time monitoring of hybridization of ZIKV gRNA on the sensor surface. Hence, the sensing procedures are simple with rapid turn-around time and good specificity and sensitivity. A series of experiments are conducted to optimize the sensor performance. The performance of the sensor is investigated for three different probes, two functionalization buffers, and different hybridization buffers. With the optimized sensing protocol, this method can detect spiked ZIKV gRNA from human serum within 30 s and reach a limit of detection of 78.8 copies/μL in analytical samples and as low as 287.5 copies/μL in neat serum. The sensors can successfully differentiate between the RNAs of the ZIKV and dengue virus, two viruses with similar transmission paths and symptoms. The sensor is simple to use and requires no labeling or sophisticated process typically involved in a polymerase chain reaction, hybridization chain reaction, or nucleic acid sequence-based amplification.