cyc-DEP: Cyclic immunofluorescence profiling of particles collected using dielectrophoresis.

Cancer is a highly heterogenous disease that requires precise detection tools and active surveillance methods. Liquid biopsy assays provide an agnostic way to follow the complex trajectory of cancer, providing better patient stratification tools for optimized treatment. Here, we present the development of a low-volume liquid biopsy assay called cyc-DEP (cyclic immunofluorescent imaging on dielectrophoretic chip) to profile biomarkers collected on a dielectrophoretic microfluidic chip platform. To enable on-chip cyclic imaging, we optimized a fluorophore quenching method and sequential rounds of on-chip staining with fluorescently conjugated primary antibodies. cyc-DEP allows for the quantification of a multiplex array of proteins using 25 µl of a patient plasma sample. We utilized nanoparticles from a prostate adenocarcinoma (LNCaP) cell line and a panel of six target proteins to develop our proof-of-concept technique. We then used cyc-DEP to quantify blood plasma levels of target proteins from healthy individuals, low-grade and high-grade prostate cancer patients (n = 3 each) in order to demonstrate that our platform is suitable for liquid biopsy analysis in its present form. To ensure accurate quantification of signal intensities and comparisons between different samples, we incorporated a signal intensity normalization method (fluorescent beads) and a custom signal intensity quantification algorithm that account for the distribution of signal across hundreds of collection regions on each chip. Our technique enabled a threefold improvement in multiplicity for detecting proteins associated with fluid samples, opening doors for early detection, and active surveillance through quantification of a multiplex array of biomarkers from low-volume liquid biopsies.

Effects of ex vivo blood anticoagulation and preanalytical processing time on the proteome content of platelets.

BACKGROUND: Ex vivo assays of platelet function critically inform mechanistic and clinical hematology studies, where effects of divergent blood processing methods on platelet composition are apparent, but unspecified. OBJECTIVE: Here, we evaluate how different blood anticoagulation options and processing times affect platelet function and protein content ex vivo. METHODS: Parallel blood samples were collected from healthy human donors into sodium citrate, acid citrate dextrose, EDTA or heparin, and processed over an extended time course for functional and biochemical experiments, including platelet proteome quantification with multiplexed tandem mass tag (TMT) labeling and triple quadrupole mass spectrometry (MS). RESULTS: Each anticoagulant had time-dependent effects on platelet function in whole blood. For instance, heparin enhanced platelet agonist reactivity, platelet-monocyte aggregate formation and platelet extracellular vesicle release, while EDTA increased platelet α-granule secretion. Following platelet isolation, TMT-MS quantified 3357 proteins amongst all prepared platelet samples. Altogether, >400 proteins were differentially abundant in platelets isolated from blood processed at 24 h versus 1 h post-phlebotomy, including proteins pertinent to membrane trafficking and exocytosis. Anticoagulant-specific effects on platelet proteomes included increased complement system and decreased α-granule proteins in platelets from EDTA-anticoagulated blood. Platelets prepared from heparinized blood had higher levels of histone and neutrophil-associated proteins in a manner related to neutrophil extracellular trap (NET) formation and platelet:NET interactions in whole blood ex vivo. CONCLUSION: Our results demonstrate that different anticoagulants routinely used for blood collection have varying effects on platelets ex vivo, where methodology-associated alterations in platelet proteome may influence mechanistic, translational and biomarker studies.

Hybrid Silica-Coated PLGA Nanoparticles for Enhanced Enzyme-Based Therapeutics.

Some cancer cells rely heavily on non-essential biomolecules for survival, growth, and proliferation. Enzyme based therapeutics can eliminate these biomolecules, thus specifically targeting neoplastic cells; however, enzyme therapeutics are susceptible to immune clearance, exhibit short half-lives, and require frequent administration. Encapsulation of therapeutic cargo within biocompatible and biodegradable poly(lactic-co-glycolic acid) nanoparticles (PLGA NPs) is a strategy for controlled release. Unfortunately, PLGA NPs exhibit burst release of cargo shortly after delivery or upon introduction to aqueous environments where they decompose via hydrolysis. Here, we show the generation of hybrid silica-coated PLGA (SiLGA) NPs as viable drug delivery vehicles exhibiting sub-200 nm diameters, a metastable Zeta potential, and high loading efficiency and content. Compared to uncoated PLGA NPs, SiLGA NPs offer greater retention of enzymatic activity and slow the burst release of cargo. Thus, SiLGA encapsulation of therapeutic enzymes, such as asparaginase, could reduce frequency of administration, increase half-life, and improve efficacy for patients with a range of diseases.

Relevance of circulating hybrid cells as a non-invasive biomarker for myriad solid tumors.

Metastatic progression defines the final stages of tumor evolution and underlies the majority of cancer-related deaths. The heterogeneity in disseminated tumor cell populations capable of seeding and growing in distant organ sites contributes to the development of treatment resistant disease. We recently reported the identification of a novel tumor-derived cell population, circulating hybrid cells (CHCs), harboring attributes from both macrophages and neoplastic cells, including functional characteristics important to metastatic spread. These disseminated hybrids outnumber conventionally defined circulating tumor cells (CTCs) in cancer patients. It is unknown if CHCs represent a generalized cancer mechanism for cell dissemination, or if this population is relevant to the metastatic cascade. Herein, we detect CHCs in the peripheral blood of patients with cancer in myriad disease sites encompassing epithelial and non-epithelial malignancies. Further, we demonstrate that in vivo-derived hybrid cells harbor tumor-initiating capacity in murine cancer models and that CHCs from human breast cancer patients express stem cell antigens, features consistent with the potential to seed and grow at metastatic sites. Finally, we reveal heterogeneity of CHC phenotypes reflect key tumor features, including oncogenic mutations and functional protein expression. Importantly, this novel population of disseminated neoplastic cells opens a new area in cancer biology and renewed opportunity for battling metastatic disease.

Automated fluorescence quantification of extracellular vesicles collected from blood plasma using dielectrophoresis.

Tumor-secreted exosomes and other extracellular vesicles (EVs) in circulation contain valuable biomarkers for early cancer detection and screening. We have previously demonstrated collection of cancer-derived nanoparticles (NPs) directly from whole blood and plasma with a chip-based technique that uses a microelectrode array to generate dielectrophoretic (DEP) forces. This technique enables direct recovery of NPs from whole blood and plasma. The biomarker payloads associated with collected particles can be detected and quantified with immunostaining. Accurately separating the fluorescence intensity of stained biomarkers from background (BG) levels becomes a challenge when analyzing the blood from early-stage cancer patients in which biomarker concentrations are low. To address this challenge, we developed two complementary techniques to standardize the quantification of fluorescently immunolabeled biomarkers collected and concentrated at predictable locations within microfluidic chips. The first technique was an automated algorithm for the quantitative analysis of fluorescence intensity at collection regions within the chip compared to levels at adjacent regions. The algorithm used predictable locations of particle collection within the chip geometry to differentiate regions of collection and BG. We successfully automated the identification and removal of optical artifacts from quantitative calculations. We demonstrated that the automated system performs nearly the same as a human user following a standard protocol for manual artifact removal with Pearson's r-values of 0.999 and 0.998 for two different biomarkers (n = 36 patients). We defined a usable dynamic range of fluorescence intensities corresponding to 1 to 2000 arbitrary units (a.u.). Fluorescence intensities within the dynamic range increased linearly with respect to exposure time and particle concentration. The second technique was the implementation of an internal standard to adjust levels of biomarker fluorescence based on the relative collection efficiency of the chip. Use of the internal standard reduced variability in measured biomarker levels due to differences in chip-to-chip collection efficiency, especially at low biomarker concentrations. The internal standard did not affect linear trends between fluorescence intensity and exposure time. Adjustments using the internal standard improved linear trends between fluorescence intensity and particle concentration. The optical quantification techniques described in this paper can be easily adapted for other lab-on-a-chip platforms that have predefined regions of biomarker or particle collection and that rely on fluorescence detection.

A highly scalable peptide-based assay system for proteomics.

We report a scalable and cost-effective technology for generating and screening high-complexity customizable peptide sets. The peptides are made as peptide-cDNA fusions by in vitro transcription/translation from pools of DNA templates generated by microarray-based synthesis. This approach enables large custom sets of peptides to be designed in silico, manufactured cost-effectively in parallel, and assayed efficiently in a multiplexed fashion. The utility of our peptide-cDNA fusion pools was demonstrated in two activity-based assays designed to discover protease and kinase substrates. In the protease assay, cleaved peptide substrates were separated from uncleaved and identified by digital sequencing of their cognate cDNAs. We screened the 3,011 amino acid HCV proteome for susceptibility to cleavage by the HCV NS3/4A protease and identified all 3 known trans cleavage sites with high specificity. In the kinase assay, peptide substrates phosphorylated by tyrosine kinases were captured and identified by sequencing of their cDNAs. We screened a pool of 3,243 peptides against Abl kinase and showed that phosphorylation events detected were specific and consistent with the known substrate preferences of Abl kinase. Our approach is scalable and adaptable to other protein-based assays.