Quantification Of Protein Biomarkers Research Articles

Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning.

Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC > 0.5. We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Lab-in-a-Vial Rapid Test for Internet of Things-Embedded Point-of-Healthcare Protein Biomarker Detection in Bodily Fluids.

Amateurs often struggle with detecting and quantifying protein biomarkers in body fluids due to the high expertise required. This study introduces a Lab-in-a-Vial (LV) rapid diagnostic platform, featuring hydrangea-like platinum nanozymes (PtNH), for rapid, accurate detection and quantification of protein biomarkers on-site within 15min. This method significantly enhances detection sensitivity for various biomarkers in body fluids, surpassing traditional methods such as enzyme-linked immunosorbent assays (ELISA) and lateral flow assays (LFA) by ≈250 to 1300 times. The LV platform uses a glass vial coated with specific bioreceptors such as antigens or antibodies, enabling rapid in vitro evaluation of disease risk from small fluid samples, similar to a personal ELISA-like point-of-care test (POCT). It overcomes challenges in on-site biomarker detection, allowing both detection and quantification through a portable wireless spectrometer for healthcare internet of things (H-IoT). The platform's effectiveness and adaptability are confirmed using IgG/IgM antibodies from SARS-CoV-2 infected patients and nuclear matrix protein (NMP22) from urothelial carcinoma (UC) patients as biomarkers. These tests demonstrated its accuracy and flexibility. This approach offers vast potential for diverse disease applications, provided that the relevant protein biomarkers in bodily fluids are identified.

Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains.

Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of multi-material heterochains, which show improved sensitivity, throughput, and accuracy compared to standard ELISA kits. By controlling the material combination and the number of ligand nanoparticles (NPs), we observe robust near-field enhancement as well as both strong electromagnetic resonance in polymer-semiconductor heterochains. In particular, their optical signals show a linear response to the coordination number of the semiconductor NPs in a wide range. Accordingly, a visible nanophotonic biosensor is developed by functionalizing antibodies on central polymer chains that can identify target proteins attached to semiconductor NPs. This allows for the specific detection of multiple protein biomarkers from healthy people and pancreatic cancer patients in one step with an ultralow detection limit (1 pg/mL). Furthermore, rapid and high-throughput quantification of protein expression levels in diverse clinical samples such as buffer, urine, and serum is achieved by combining a neural network algorithm, with an average accuracy of 97.3%. This work demonstrates that the heterochain-based biosensor is an exemplary candidate for constructing next-generation diagnostic tools and suitable for many clinical settings.

Differences in the proteome within extracellular vesicles between premalignant and malignant plasma cell disorders.

Precursor plasma cell disorders such as monoclonal gammopathy of undetermined significance (MGUS) always precede the development of active malignancies such as multiple myeloma (MM). There is a need for novel biomarkers to identify those patients with such precursor plasma cell disorders who rapidly progress to MM. Plasma-derived extracellular vesicles (EVs) may serve as a reservoir of potential biomarkers that can shed light on the pathogenesis and disease biology of MM. This study isolated small EVs (SEVs) and large EVs (LEVs) from the platelet-poor peripheral blood plasma of MGUS (n = 9) and MM (n = 12) patients using the size exclusion chromatography-based method and evaluated their proteome using a label-free proteomics workflow. In total, 2055 proteins were identified in SEVs, while 2794 proteins were identified in LEVs. The transferrin receptor (or CD71) protein was upregulated in both populations of EVs derived from MM patients compared to MGUS patients and was of prognostic significance. Similarly, three isoforms of serum amyloid A (SAA) protein, SAA1, SAA2, and SAA4, were also highly upregulated in SEVs within MM patients relative to MGUS patients. Finally, CD40 expression was also higher in the LEVs derived from MM patients than in MGUS patients. This study demonstrates the feasibility of successfully isolating both SEVs and LEVs from the peripheral blood of patients with plasma cell disorders and quantifying protein biomarkers within these EVs that could be of prognostic and diagnostic interest.

Highly Reusable Electrochemical Immunosensor for Ultrasensitive Protein Detection

AbstractThe detection and quantification of protein biomarkers in bodily fluids is important for many clinical applications, including disease diagnosis and health monitoring. Current techniques for ultrasensitive protein detection, such as enzyme‐linked immunosorbent assay (ELISA) and electrochemical sensing, involve long incubation times (1.5–3 h) and rely on single‐use sensing electrodes which can be costly and generate excessive waste. This work demonstrates a reusable electrochemical immunosensor employing magnetic nanoparticles (MNPs) and dually labeled gold nanoparticles (AuNPs) for ultrasensitive measurements of protein biomarkers. As proof of concept, this platform is used to detect C‐X‐C motif chemokine ligand 9 (CXCL9), a biomarker associated with kidney transplant rejection, immune nephritis from checkpoint inhibitor therapy, and drug‐associated acute interstitial nephritis, in human urine. The sensor successfully detects CXCL9 at concentrations as low as 27 pg mL−1 within ≈1 h. This immunosensor was also adapted onto a handheld smartphone‐based diagnostic device and used for measurements of CXCL9, which exhibited a lower limit of detection of 65 pg mL−1. Lastly, this work demonstrates that the sensing electrodes can be reused for at least 100 measurements with a negligible loss in analytical performance, reducing the costs and waste associated with electrochemical sensing.

Ultrasensitive Electrochemical Immunosensor for Multiplex Sandwich Bioassaying Based on the Functional Antibodies.

In vitro diagnostics (IVDs) based on electrochemical immunosensors are crucial for disease screening, diagnosis, prognosis, and treatment monitoring. However, label-free electrochemical immunosensors commonly suffer from poor specificity, leading to false positives. To address this issue, we propose a highly sensitive and precise electrochemical immunosensor for protein marker detection. This approach involves directly labeling the detection antibodies (Ab2) with thionine (Thi). The Ab2 labeled by Thi exhibits a distinct redox peak upon targeted voltage stimulation, enabling accurate quantification of protein biomarkers. Thi-modified antibodies provide significant advantages over traditional antibody modification methods, such as enhanced detection sensitivity, improved accuracy, and specificity in protein marker identification. The method is straightforward and efficient, ensuring specific analyte detection while minimizing interference from other substances in the sample. Additionally, a multielectrode detection method was employed, achieving remarkably low limits of detection (LoDs) for tumor necrosis factor-alpha (TNF-alpha), cardiac troponin I (cTnI), and interleukin-6 (IL-6), with LoDs of 9.38 fg/mL, 1.70 fg/mL, and 8.14 fg/mL, respectively. The proposed electrochemical immunosensor also exhibited high selectivity and repeatability, with relative standard deviations (RSD) of 6.39% for TNF-alpha, 2.42% for cTnI, and 2.72% for IL-6 (n = 5). Moreover, it demonstrated high sensitivity and was evaluated for serum detection using the standard addition method. The results highlight the great potential of the proposed electrochemical immunosensor for clinical applications, offering a novel approach for future utilization in clinical settings.

Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring.

Existing mass spectrometric assays used for sensitive and specific measurements of target proteins across multiple samples, such as selected/multiple reaction monitoring (SRM/MRM) or parallel reaction monitoring (PRM), are peptide-based methods for bottom-up proteomics. Here, we describe an approach based on the principle of PRM for the measurement of intact proteoforms by targeted top-down proteomics, termed proteoform reaction monitoring (PfRM). We explore the ability of our method to circumvent traditional limitations of top-down proteomics, such as sensitivity and reproducibility. We also introduce a new software program, Proteoform Finder (part of ProSight Native), specifically designed for the easy analysis of PfRM data. PfRM was initially benchmarked by quantifying three standard proteins. The linearity of the assay was shown over almost 3 orders of magnitude in the femtomole range, with limits of detection and quantification in the low femtomolar range. We later applied our multiplexed PfRM assay to complex samples to quantify biomarker candidates in peripheral blood mononuclear cells (PBMCs) from liver-transplanted patients, suggesting their possible translational applications. These results demonstrate that PfRM has the potential to contribute to the accurate quantification of protein biomarkers for diagnostic purposes and to improve our understanding of disease etiology at the proteoform level.

Microneedle patch-based enzyme-linked immunosorbent assay to quantify protein biomarkers of tuberculosis.

There is a clinical need for differential diagnosis of the latent versus active stages of tuberculosis (TB) disease by a simple-to-administer test. Alpha-crystallin (Acr) and early secretory antigenic target-6 (ESAT-6) are protein biomarkers associated with the latent and active stages of TB, respectively, and could be used for differential diagnosis. We therefore developed a microneedle patch (MNP) designed for application to the skin to quantify Acr and ESAT-6 in dermal interstitial fluid by enzyme-linked immunosorbent assay (ELISA). We fabricated mechanically strong microneedles made of polystyrene and coated them with capture antibodies against Acr and ESAT-6. We then optimized assay sensitivity to achieve a limit of detection of 750 pg/ml and 3,020 pg/ml for Acr and ESAT-6, respectively. This study demonstrates the feasibility of an MNP-based ELISA for differential diagnosis of latent TB disease.

Metal-organic framework-interfaced ELISA probe enables ultrasensitive detection of extracellular vesicle biomarkers.

The enzyme-linked immunosorbent assay (ELISA) remains the prevailing method for quantifying protein biomarkers. Enzymatic signal generation and amplification are key mechanisms that govern its analytical performance. This study reports the synthesis and application of microscale metal-organic framework (MOF)/enzyme composite particles as a novel detection probe to substantially enhance the sensitivity of ELISA. An optimal one-pot approach was established to incorporate a substantial amount of streptavidin-horseradish peroxidase (SA-HRP) either within or on the surface of the metal-azolate framework (MAF-7) microparticles. This approach enables the labeling of a single sandwich antibody-antigen complex with numerous enzymes, which markedly amplifies the enzymatic colorimetric signal generation. Moreover, MAF-7 caging was found to enhance the reactivity of the caged HRP enzyme, further promoting the overall detection sensitivity of ELISA. Compared to other developments that are often associated with more complicated detection modalities, our method is compatible with standard immunoassays and commonly used photometrical signal detection. The implementation of this strategy in the detection of CD147 results in a remarkably low limit of detection of 2.8 fg mL-1, representing a 105-fold improvement compared to that obtained with the standard ELISA. Moreover, the heightened sensitivity of this technique renders it particularly suitable for diagnosing breast cancer, thus presenting a promising tool for the early detection of the disease in clinical settings.

A wireless patch for the monitoring of C-reactive protein in sweat.

The quantification of protein biomarkers in blood at picomolar-level sensitivity requires labour-intensive incubation and washing steps. Sensing proteins in sweat, which would allow for point-of-care monitoring, is hindered by the typically large interpersonal and intrapersonal variations in its composition. Here we report the design and performance of a wearable and wireless patch for the real-time electrochemical detection of the inflammatory biomarker C-reactive (CRP) protein in sweat. The device integrates iontophoretic sweat extraction, microfluidic channels for sweat sampling and for reagent routing and replacement, and a graphene-based sensor array for quantifying CRP (via an electrode functionalized with anti-CRP capture antibodies-conjugated gold nanoparticles), ionic strength, pH and temperature for the real-time calibration of the CRP sensor. In patients with chronic obstructive pulmonary disease, with active or past infections or who had heart failure, the elevated concentrations of CRP measured via the patch correlated well with the protein's levels in serum. Wearable biosensors for the real-time sensitive analysis of inflammatory proteins in sweat may facilitate the management of chronic diseases.

Flow-Based CL-SMIA for the Quantification of Protein Biomarkers from Nasal Secretions in Comparison with Sandwich ELISA.

Protein biomarkers in nasal secretions can be used as a measure to differentiate between allergies, airway diseases and infections for non-invasive diagnostics. The point-of-care quantification of biomarker levels using flow-based microarray facilitates precise and rapid diagnosis and displays the potential for targeted and effective treatment. For the first time, we developed a flow-based chemiluminescence sandwich microarray immunoassay (CL-SMIA) for the quantification of nasal interferon-beta (IFN-β) on the Microarray Chip Reader-Research (MCR-R). Polycarbonate foils are used as a cost-effective surface for immobilizing capture antibodies. By using a commercially available set of anti-human IFN-β antibodies, the CL-SMIA can be compared directly to an enzyme-linked immunosorbent assay (ELISA) performed in microtiter plates concerning the bioanalytical performance and economic issues. Pre-incubation of the sample with detection antibodies facilitates the lower consumption of detection antibodies, as this allows for a longer interaction time between the antibody and the biomarker. The direct injection of pre-incubated samples into the microarray chips eliminates the adsorption of proteins in the tubing as well as the contamination of the tubing and valves of the MCR-R with clinical samples. The small flow cell allows for a low sample volume of 50 μL. The limit of detection of 4.53 pg mL-1 was slightly increased compared to a sandwich ELISA performed on microtiter plates which were 1.60 pg mL-1. The possibility to perform the CL-SMIA in a multiplexed mode makes it a promising assay for the rapid and cost-effective non-invasive detection of biomarkers in nasal secretions.

Combined Ultrasensitive Detection of Renal Cancer Proteins and Cells Using an Optical Microfiber Functionalized with Ti3C2 MXene and Gold Nanorod-Nanosensitized Interfaces.

The ultrasensitive and quantitative detection of renal cancer protein biomarkers present at ultralow concentrations for early-stage cancer diagnosis requires a biosensing probe possessing ultrahigh detection sensitivity and remarkable biosensing selectivity. Here, we report an optical microfiber integrated with Ti3C2-supported gold nanorod hybrid nanointerfaces for implementation in ultrasensitive sensing of the carbonic anhydrase IX (CAIX) protein and renal cancer cells. Because the evanescent field of the fiber is strongly coupled with nanointerfaces in the near-infrared region, the proposed optical microfiber biosensor achieves ultrahigh-sensitivity detection of the CAIX protein biomarker with ultralow limits of detection (LODs) of 13.8 zM in pure buffer solution and 0.19 aM in 30% serum solution. In addition, the proposed sensor also successfully and specifically recognizes living renal cancer cells in cell culture media with a LOD of 180 cells/mL. This strategy may serves as a powerful biosensing platform that combines the quantification of protein biomarkers and cancer cells, resulting in a higher accuracy of early-stage renal cancer diagnosis and screenings.

Signature peptide selection workflow for biomarker quantification using LC-MS-based targeted proteomics.

In contrast to quantification of biotherapeutics, endogenous protein biomarker and target quantification using LC-MSbased targeted proteomics can require a much more stringent and time-consuming tryptic signature peptide selection for each specific application. While some general criteria exist, there are no tools currently available in the public domain to predict the ionization efficiency for a given signature peptide candidate. Lack of knowledge of the ionization efficiencies forces investigators to choose peptides blindly, thus hindering method development for lowabundantprotein quantification. Here, the authors propose a tryptic signature peptide selection workflow to achieve a more efficient method development and to improve success rates in signature peptide selection for lowabundantendogenous target and protein biomarker quantification.

Metal–Organic Framework-Mediated Bioorthogonal Reaction to Immobilize Bacteria for Ultrasensitive Fluorescence Counting Immunoassays

Ultrasensitive quantification of protein biomarkers has significant implications in disease diagnosis. Herein, we report a fluorescent bacteria counting immunoassay (FBCIA) strategy for protein biomarker detection based on a cascade signal conversion and amplification strategy including the copper metal-organic framework (Cu-MOF)-mediated Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) for fluorescent bacteria immobilization that converted the concentration of target protein to countable bacterial number and the further self-proliferation of bacteria to amplify the detectable bacterial number. The developed low-background and enzyme-free cascade methodology achieved highly sensitive detection of carcinoembryonic antigen (CEA) and prostate-specific antigen (PSA) with detection limits down to 0.8 pg/mL and 64.5 fg/mL, respectively. On top of that, we also developed a smartphone device for visualizing individual bacteria and point-of-care counting of the resulting bacteria for the detection of clinical samples. The good consistency between FBCIA and clinical enzyme-linked immunosorbent assay (ELISA) validated the high reliability and promising potential of our developed platform in clinical applications.

On-bead DNA synthesis triggered by allosteric probe for detection of carcinoembryonic antigen.

Sensitive quantification of protein biomarkers is highly desired for clinical diagnosis and treatment. Yet, unlike DNA/RNA which can be greatly amplified by PCR/RT-PCR, the amplification and detection of trace amount of proteins remain a great challenge. Here, we combined allosteric probe (AP) with magnetic bead (MB) for assembling an on-bead DNA synthesis system (named as APMB) to amplify protein signals. The AP is designed and conjugated onto the MB, enabling the protein biomarker to be separated and enriched. Once recognizing the biomarker, the AP alters its conformation to initiate DNA synthesis on beads for primary signal amplification. During the DNA synthesis, biotin-dATPs are incorporated into the newly synthesized DNA strands. Then, the biotin-labeled DNA specifically captures streptavidin (STR)–conjugated horseradish peroxidase (HRP), which is used to catalyze a colorimetric reaction for secondary signal amplification. By using carcinoembryonic antigen (CEA) as a protein model, the APMB can quantify protein biomarkers of as low as 0.01 ng/mL. The response values measured by APMB are linearly related to the protein concentrations in the range 0.05 to 20 ng/mL. Clinical examination demonstrated good practicability of the APMB in quantifying serum protein biomarker. The on-bead DNA synthesis could be exploited to improve protein signal amplification, thus facilitating protein biomarker detection of low abundance for early diagnosis.Graphical abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s00604-022-05404-4.

Method development workflow for quantifying protein biomarkers by hybrid LC-MS/MS.

Background: Industry-standard guidance on method development and validation of hybrid LC-MS/MS assays for protein biomarkers, particularly on evaluation of parallelism, is lacking. Methods: Using a protein endogenous to humans and mice as a model analyte, a quantitative hybrid LC-MS/MS workflow was developed using a surrogate matrix approach with a recombinant form of the protein as the calibrant. Results: The developed workflow identified a surrogate matrix, established parallelism between the surrogate and authentic matrices and assessed parallelism between the recombinant and authentic forms of the protein. The final method was qualified usingprecision and accuracy with recoveryassessments. Conclusion: The established workflow can be used in future bioanalytical studies to develop effective hybrid LC-MS/MS methods for endogenous protein biomarkers.

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1–2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. This platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.

A High Throughput Antibody-Free Platform for Multiplexed, Sensitive Quantification of Protein Biomarkers in Complex Biomatrices

A High Throughput Antibody-Free Platform for Multiplexed, Sensitive Quantification of Protein Biomarkers in Complex Biomatrices

Application of Immunoaffinity Mass Spectrometry (IA-MS) for Protein Biomarker Quantification.

Immunoaffinity mass spectrometry (IA-MS) is a powerful analytical technique for the determination of protein biomarkers with high sensitivity and unparalleled specificity. Typically, the protein antigen of interest is captured from biofluids and tissue lysates using an antibody prior to mass spectrometric analysis. Here we describe the specific steps of the protein immunoaffinity component of the IA-MS workflow that is applicable to most protein antigens.

Prospective associations between neighborhood violence and monocyte pro-inflammatory transcriptional activity in children

Individuals exposed to persistent neighborhood violence are at increased risk for developing mental and physical health problems across the lifespan. The biological mechanisms underlying this phenomenon are not well understood. Thus, we examined the relationship between children’s exposure to neighborhood violence and inflammatory activity, a process involved in the pathogenesis of multiple health problems. 236 children from the Chicago area participated in a two-year longitudinal study (mean age at baseline, 13.9 years; 67% female; 39% White, 34% Black, 33% Hispanic). Neighborhood violence was measured as the homicide frequency in a child’s Census block group in the five years before study entry. Fasting blood was drawn at study entry and two years later (in eighth and tenth grade). The blood was used to quantify protein biomarkers of systemic inflammatory activity and perform genome-wide expression profiling of isolated monocytes. Neighborhood violence was associated with higher systemic inflammatory activity at both assessments. It also was associated with a monocyte transcriptional profile indicative of increased signaling along the nuclear factor-kappa B (NF-κB) and activator protein 1 (AP-1) control pathways, which are key orchestrators of pro-inflammatory effector functions. Neighborhood violence also was associated with transcriptional indications of higher beta-adrenergic and lower glucocorticoid signaling, which could function as neuroendocrine conduits linking threatening experiences with inflammatory activity. Neighborhood violence was not associated with two-year changes in protein biomarkers, although it did presage a transcriptional profile indicative of increasing AP-1 and declining glucocorticoid signaling over follow-up. Collectively, these observations highlight cellular and molecular pathways that could underlie health risks associated with neighborhood violence.