Abstract 3058: Colocalization of cancer-associated biomarkers on single extracellular vesicles for early-cancer detection

Introduction: Extracellular vesicles (EVs) are abundant in biological fluids and increasingly recognized for their diagnostic and therapeutic potential. Unlike circulating tumor DNA which scales in abundance with tumor size and is a product of tumor cell death; tumor EVs are secreted continuously, are remarkably stable, and used by cancer cells as messengers to benefit tumor growth and metastasis, suggesting they may be a better indicator of early-stage cancer. Tumor-derived EVs reflect their cell of origin, making them an ideal analyte for liquid biopsy diagnostic assays. We describe a platform technology, Mercy Halo™, which interrogates millions of individual EVs within a plasma or serum sample to capture and detect cancer cell derived EVs. Using panels of antibodies targeting up to three cancer-associated biomarkers simultaneously, we demonstrate Mercy Halo enables sensitive and specific detection of early-stage high-grade serous ovarian carcinoma (HGSOC) with excellent reproducibility in a proof-of-concept (PoC) study.

Methods: Following purification of a sample by size-exclusion chromatography, EVs were captured using antibody-functionalized beads and interrogated using proximity ligation qPCR. EVs were characterized and biomarker expression confirmed by traditional immunoassay and Mercy Halo. The colocalization of specific biomarkers on single EVs was measured using a panel of antibodies against biomarkers upregulated in HGSOC and human cancer cell lines. Optimized antibody panels were then used in a feasibility study using EVs purified from plasma samples from early- and late-stage HGSOC, benign ovarian masses, and healthy controls.

Results: Mercy Halo detects colocalized biomarkers specifically and sensitively on the surface of tumor derived EVs. Surface biomarkers expressed by cancer cells were detected in our assay and signal strength correlated with protein expression, demonstrating that EVs can be used as a surrogate to indicate the presence or absence of cancer. We demonstrate that biomarkers present on cancer cells are colocalized on EVs derived from a tumor and are readily detectable using the Mercy Halo platform. A positive signal was dependent on the presence of all biomarkers on the same EV. Importantly, there was significant improvement in both the specificity and sensitivity of the assay as the number of biomarker antibodies used to interrogate the EVs increases. Finally, in a small clinical cohort PoC study, we demonstrate improved detection of early stage HGSOC relative to CA125 ELISA.

Conclusions: Tumor-derived EVs are a robust analyte for liquid-biopsy assays which can readily be detected using our platform technology. This PoC study suggests Mercy Halo can discriminate all stages of HGSOC from benign and healthy samples in human plasma with high sensitivity and specificity and is being investigated for extensibility in other cancers and diseases.

Citation Format: Daniel P. Salem, Laura T. Bortolin, Anthony D. Couvillon, Dan Gusenleitner, Jonian Grosha, Sanchari Banerjee, Kelly M. Biette, Ibukunoluwapo O. Zabroski, Christopher R. Sedlak, Delaney M. Byrne, Peter A. Duff, Bilal F. Hamzeh, MacKenzie S. King, Lauren T. Cuoco, Emily S. Winn-Deen, Eric K. Huang, Joseph C. Sedlak. Colocalization of cancer-associated biomarkers on single extracellular vesicles for early-cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3058.

Abstract 3390: Preliminary results for a novel single extracellular vesicle assay for early stage ovarian cancer: The power of co-localized detection of surface biomarkers

Introduction: Ovarian cancer (OC) is one of the deadliest cancers, with 314,000 new cases and 207,000 deaths globally in 2020. Serum CA125 has been explored as an OC biomarker for the past 40 years, but lacks sensitivity for early stage OC and is not recommended for screening average-risk, asymptomatic women. We hypothesize that co-localization of biomarkers on the surface of individual extracellular vesicles (EVs), which are shed into the circulation by cancer cells, may lead to development of a blood test for early stage OC. We evaluated the potential of our approach in detecting early stage OC in clinical samples.

Methods: We isolated EVs using size-exclusion chromatography and immunoaffinity capture, and detected biomarkers co-localized on the surface of individual EVs with proximity ligation qPCR. Using this approach, we evaluated 49 antibody combinations recognizing 2 or more biomarkers. Each combination consisted of 1 capture antibody and 2 oligonucleotide-tagged detection antibodies. We tested plasma samples from women with early stage I/II high-grade serous ovarian carcinoma (HGSOC)(n=18; 48-80 yr, med 57) and late stage HGSOC (n=24; 37-80 yr, med 54). HGSOC samples were sourced from 2 commercial vendors. Controls comprised samples from women with benign ovarian masses (n=26; 23-76 yr, med 39.5) sourced from a single vendor, and samples prospectively collected by Mercy from healthy women with no cancer history (n=24; 22-72 yr, med 52.5). PCR cycle threshold (Ct) values were measured for each of 49 combinations and data was evaluated using univariate analysis. Performance was compared to plasma CA125 measured at Mercy by commercial ELISA.

Results: 8 of 49 combinations distinguished all stages of HGSOC relative to benign and healthy controls with AUCs ranging from 0.86 (95% CI 0.78-0.94) to 0.95 (95% CI 0.90-1.00), comparable to CA125 with an AUC of 0.87 (95% CI 0.79-0.95). One of the most effective combinations (STn, BST2, MUC1) had a sensitivity of 0.78 (95% CI 0.52-0.94) at a specificity of 0.96 (95% CI 0.87-0.99) in detecting early stage HGSOC. This combination also detected HGSOC in 6 of 11 women (3 early stage, 3 late stage) with normal CA125 (< 25 U/mL) and correctly classified 7 of 8 women with benign masses and high CA125 (> 25 U/mL).

Conclusions: These preliminary data suggest that co-localization of surface biomarkers in single EVs may provide an effective means to identify women with early stage HGSOC, including those with normal CA125, while avoiding false positives in women with benign masses and high CA125. Despite the inherent challenges associated with commercial samples, our finding that several combinations detected early stage HGSOC is promising. Statistically powered studies with curated repository specimens are underway to refine combinations and independently validate our assay for early stage OC detection.

Citation Format: Laura T. Bortolin, Daniel P. Salem, Sanchari Banerjee, Kelly M. Biette, Delaney M. Byrne, Anthony D. Couvillon, Peter A. Duff, Jonian Grosha, MacKenzie Sadie King, Christopher R. Sedlak, Ibukunoluwapo O. Zabroski, Claire Alexander, Karen Copeland, Daniel Gusenleitner, Emily S. Winn-Deen, Eric K. Huang, Bo R. Rueda, Joseph Charles Sedlak. Preliminary results for a novel single extracellular vesicle assay for early stage ovarian cancer: The power of co-localized detection of surface biomarkers [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 3390.

Abstract 2232: Preliminary results for a novel single extracellular vesicle assay for early lung cancer: The power of co-localized detection of surface biomarkers

Introduction: Screening for lung cancer (LC), the leading cause of cancer deaths, with helical computerized tomography lowers mortality but uptake is poor. Investigations into new approaches such as using circulating tumor cells and circulating tumor DNA for LC detection have soared in the last decade. However, the low abundance of these targets has limited the performance of these approaches as screening tools. We hypothesize that co-localization of biomarkers on the surface of individual extracellular vesicles (EVs), which are shed into the circulation by cancer cells, may lead to development of a blood test for early stage LC. We evaluated the potential of our approach in detecting early stage LC in clinical samples.

Methods: EVs were purified from plasma using size-exclusion chromatography and immunoaffinity capture, and biomarkers co-localized on the EV surface were detected with proximity ligation qPCR. We used antibody combinations comprising 1 capture antibody and 2 oligonucleotide-tagged detection antibodies, recognizing 1, 2 or 3 unique biomarkers. We evaluated this approach by testing plasma samples from early stage I/II lung adenocarcinoma (LUAD) patients (15 smokers, 19 non-smokers), late stage III/IV LUAD patients (16 smokers, 18 non-smokers), and healthy donors (34 smokers, 33 non-smokers). Samples were from one vendor, processed using a standardized protocol. LUAD samples were sourced from a cancer research center and healthy samples from a primary care facility. PCR cycle threshold (Ct) values were generated for each combination and data was evaluated using univariate analysis.

Results: Combinations recognizing 3 biomarkers were better in detecting all stages of LUAD (AUC=0.83, 95% CI 0.77-0.90), as compared to combinations recognizing 2 biomarkers (AUC=0.71, 95% CI 0.63-0.80) or 1 biomarker (AUC=0.50, 95% CI 0.35-0.55), demonstrating greater accuracy with an increasing number of co-localized biomarkers. In detecting LUAD (all stages) at a specificity of 0.80 (95% CI 0.69-0.88), sensitivity improved as the number of co-localized biomarkers increased from 1 (0.08, 95% CI 0.03-0.18) to 2 (0.60, 95% CI 0.48-0.72) to 3 (0.76, 95% CI 0.65-0.86). In detecting early stage I/II LUAD, the most effective combination used 3 biomarkers (STn, MUC1, CEACAM6) and had a sensitivity of 0.56 (95% CI 0.38-0.73).

Conclusions: These preliminary data highlight the potential of detecting biomarkers co-localized on the surface of single EVs as an effective tool for early stage LC detection, and the benefit of using 3 biomarkers simultaneously. Despite inherent challenges associated with commercial samples, our finding that detection of co-localized EV surface biomarkers distinguished LUAD is promising. Additional studies with LC cohorts beyond LUAD are underway to refine combinations and independently validate our assay for early stage LC detection.

Citation Format: Daniel P. Salem, Laura T. Bortolin, Sanchari Banerjee, Kelly M. Biette, Delaney M. Byrne, Anthony D. Couvillon, Peter A. Duff, Jonian Grosha, Daniel Gusenleitner, MacKenzie Sadie King, Christopher R. Sedlak, Ibukunoluwapo O. Zabroski, Karen Copeland, Emily S. Winn-Deen, Eric K. Huang, Christine D. Berg, Joseph C. Sedlak. Preliminary results for a novel single extracellular vesicle assay for early lung cancer: The power of co-localized detection of surface biomarkers [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 2232.

Extracellular vesicle-based biomarker assay for the detection of early-stage ovarian cancer

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Background: Detection of cancer with improved discrimination compared to current blood tests could be achieved using an approach that assesses extracellular vesicles (EVs). This approach should have high sensitivity (se) because of EVs abundance in blood and high specificity (sp) by assaying EVs with multiple cancer-related protein and glycosylation epitopes (PGEs) co-localized on their surfaces. We are developing a platform technology that detects multiple cancer-related PGEs co-localized on the same EV using immunoaffinity-capture and proximity-ligation qPCR. In this study, we compare the performance of this technology vs plasma CA125 for correctly categorizing early-stage high-grade serous ovarian cancer (HGSOC) vs healthy/benign ovarian tumors (OT). Methods: We evaluated our EV-based platform technology using 7 PGE combinations to discriminate HGSOC from benign adnexal masses. We first derived a prediction model on a retrospectively collected cohort of 42 HGSOC and 26 benign OT samples from 2 commercial vendors and 24 healthy controls (HC) using a machine-learning algorithm. We validated this model on an independent cohort [89 HGSOC: Stage I (17), II (35), III (37); 192 benign OT] from university-associated biobanks and 124 HC. We also assessed the assay’s performance in plasma from 87 women with off-target cancers and 42 women with inflammatory conditions from commercial vendors. For each sample, we also measured CA125 levels using a commercial ELISA. Results: The prediction model distinguishes HGSOC from benign and HC with an AUC of 0.965 (95% CI 0.93-0.99), with 89.9% (0.82-0.95) se at 98% sp. For stage I/II HGSOC, the model achieves an AUC of 0.942 (0.9-0.99), with 84.6% (0.72-0.93) se at 98% sp. By comparison, CA125 achieves an AUC of 0.875 (0.81-0.94) and 44.2% (0.3-0.59) se at 98% sp. Direct comparison of CA125 and our model shows a significant difference at 98% sp for both all and stage I/II HGSOC (McNemar p-val < 0.001). When comparing HGSOC to HC, there is no significant difference between our model and CA125 (p-val = 1.0). There is a significant difference when comparing patients with all stage and stage I/II HGSOC to patients with benign OT (p-val < 0.001). Our assay had 1 false positive and CA125 had 3 false positives out of 42 inflammatory cases. Conclusions: These preliminary data suggest our platform technology for detecting PGEs co-localized on individual EVs may detect all stages of HGSOC from plasma with high se at a very high sp. Our assay may improve on CA125 by distinguishing stage I/II HGSOC from benign OT and could have clinical utility for both early detection and surgical referral recommendation for benign and malignant OT. While the diverse cohorts in this study may present challenges in interpretation, the reproducibility in an independent cohort is encouraging and supports further investigation using cases and controls from well-defined cohort studies.

Characterization of Protein Aggregation Using Hydrogel-Encapsulated nIR Fluorescent Nanoparticle Sensors

The monitoring of biopharmaceutical critical quality attributes in-process, at both the process development and manufacturing stages, is necessary for the implementation of process analytical technology and quality-by-design principles. Among these attributes, it is important to monitor and control protein aggregation during the manufacturing of biological therapeutics to prevent adverse immunogenic responses and minimize negative impacts on drug deliverability. In this work, we explore hydrogel-encapsulated, label-free fluorescent nanosensors for the characterization of protein aggregation. A mathematical model is used to describe the diffusion and binding of a series of stressed pharmaceutical samples to such sensors, describing their dynamic response. We use mathematical modeling to map the influence of hydrogel properties on the separation performance, given the composition of UV-stressed IgG₁ samples. Using this modified model, the compositions of light-stressed IgG₁ samples were fit to experimental data and correlated with size-exclusion chromatography data. The results demonstrate the ability to detect the presence of high-molecular-weight protein species at a concentration as low as 1%. This work represents a significant step toward the development and deployment of rapid process analytical technologies for biopharmaceutical characterization.

Immobilization and Function of nIR-Fluorescent Carbon Nanotube Sensors on Paper Substrates for Fluidic Manipulation

Nanoparticle-based optical sensors are capable of highly sensitive and selective chemical interactions and can form the basis of molecular recognition for various classes of analytes. However, their incorporation into standardized in vitro assays has been limited by their incompatibility with packaging or form factors necessary for specific applications. Here, we have developed a technique for immobilizing nIR-fluorescent single-walled carbon nanotube (SWCNT) sensors on seven different types of paper substrates including nitrocellulose, nylon, poly(vinylidene fluoride), and cellulose. Sensors remain functional upon immobilization and exhibit nIR fluorescence in nonaqueous solvent systems. We then extend this system to the Corona Phase Molecular Recognition (CoPhMoRe) approach of synthetic molecular recognition by screening ssDNA-wrapped SWCNTs with different sequences against a panel of fat-soluble vitamins in canola oil, identifying a sensor which responds to β-carotene with a dissociation constant of 2.2 μM. Moreover, we pattern hydrophobic regions onto nitrocellulose using the wax printing method and form one-dimensional sensor barcodes for rapid multiplexing. Using a sensor array of select ssDNA wrappings, we are able to distinguish between Cu(II), Cd(II), Hg(II), and Pb(II) at a concentration of 100 μM. Finally, we demonstrate that immobilized sensors remain fluorescent and responsive for nearly 60 days when stability is addressed. This work represents a significant step toward the deployment of fluorescent nanoparticle sensors for point-of-use applications.

Measuring the Accessible Surface Area within the Nanoparticle Corona Using Molecular Probe Adsorption

The corona phase-the adsorbed layer of polymer, surfactant, or stabilizer molecules around a nanoparticle-is typically utilized to disperse nanoparticles into a solution or solid phase. However, this phase also controls molecular access to the nanoparticle surface, a property important for catalytic activity and sensor applications. Unfortunately, few methods can directly probe the structure of this corona phase, which is subcategorized as either a hard, immobile corona or a soft, transient corona in exchange with components in the bulk solution. In this work, we introduce a molecular probe adsorption (MPA) method for measuring the accessible nanoparticle surface area using a titration of a quenchable fluorescent molecule. For example, riboflavin is utilized to measure the surface area of gold nanoparticle standards, as well as corona phases on dispersed single-walled carbon nanotubes and graphene sheets. A material balance on the titration yields certain surface coverage parameters, including the ratio of the surface area to dissociation constant of the fluorophore, q/KD, as well as KD itself. Uncertainty, precision, and the correlation of these parameters across different experimental systems, preparations, and modalities are all discussed. Using MPA across a series of corona phases, we find that the Gibbs free energy of probe binding scales inversely with the cube root of surface area, q. In this way, MPA is the only technique to date capable of discerning critical structure-property relationships for such nanoparticle surface phases. Hence, MPA is a rapid quantitative technique that should prove useful for elucidating corona structure for nanoparticles across different systems.

Analysis of Multiplexed Nanosensor Arrays Based on Near-Infrared Fluorescent Single-Walled Carbon Nanotubes

The high-throughput, label-free detection of biomolecules remains an important challenge in analytical chemistry with the potential of nanosensors to significantly increase the ability to multiplex such assays. In this work, we develop an optical sensor array, printable from a single-walled carbon nanotube/chitosan ink and functionalized to enable a divalent ion-based proximity quenching mechanism for transducing binding between a capture protein or an antibody with the target analyte. Arrays of 5 × 6, 200 μm near-infrared (nIR) spots at a density of ≈300 spots/cm² are conjugated with immunoglobulin-binding proteins (proteins A, G, and L) for the detection of human IgG, mouse IgM, rat IgG2a, and human IgD. Binding kinetics are measured in a parallel, multiplexed fashion from each sensor spot using a custom laser scanning imaging configuration with an nIR photomultiplier tube detector. These arrays are used to examine cross-reactivity, competitive and nonspecific binding of analyte mixtures. We find that protein G and protein L functionalized sensors report selective responses to mouse IgM on the latter, as anticipated. Optically addressable platforms such as the one examined in this work have potential to significantly advance the real-time, multiplexed biomolecular detection of complex mixtures.

Ionic Strength-Mediated Phase Transitions of Surface-Adsorbed DNA on Single-Walled Carbon Nanotubes

Single-stranded DNA oligonucleotides have unique, and in some cases sequence-specific molecular interactions with the surface of carbon nanotubes that remain the subject of fundamental study. In this work, we observe and analyze a generic, ionic strength-mediated phase transition exhibited by over 25 distinct oligonucleotides adsorbed to single-walled carbon nanotubes (SWCNTs) in colloidal suspension. The phase transition occurs as monovalent salts are used to modify the ionic strength from 500 mM to 1 mM, causing a reversible reduction in the fluorescence quantum yield by as much as 90%. The phase transition is only observable by fluorescence quenching within a window of pH and in the presence of dissolved O₂, but occurs independently of this optical quenching. The negatively charged phosphate backbone increases (decreases) the DNA surface coverage on an areal basis at high (low) ionic strength, and is well described by a two-state equilibrium model. The resulting quantitative model is able to describe and link, for the first time, the observed changes in optical properties of DNA-wrapped SWCNTs with ionic strength, pH, adsorbed O₂, and ascorbic acid. Cytosine nucleobases are shown to alter the adhesion of the DNA to SWCNTs through direct protonation from solution, decreasing the driving force for this phase transition. We show that the phase transition also changes the observed SWCNT corona phase, modulating the recognition of riboflavin. These results provide insight into the unique molecular interactions between DNA and the SWCNT surface, and have implications for molecular sensing, assembly, and nanoparticle separations.