Surface Plasmon Resonance Technology Research Articles

Marine-derived EGFR inhibitors: novel compounds targeting breast cancer growth and drug resistance

Breast cancer (BC) continues to be a major health challenge globally, ranking as the fifth leading cause of cancer mortality among women, despite advancements in cancer detection and treatment. In this study, we identified four novel compounds from marine organisms that effectively target and inhibit the Epidermal Growth Factor Receptor (EGFR), crucial for BC cell growth and proliferation. These compounds not only induced early apoptosis through Caspase-3 activation but also showed significant inhibitory effects on EGFR mutations associated with drug resistance (T790M, L858R, and L858R/T790M), demonstrating high EGFR kinase selectivity. Cell Thermal Shift Assay (CETSA) experiments indicated that Tandyukisin stabilizes EGFR in a concentration-dependent manner. Furthermore, binding competition assays using surface plasmon resonance technology revealed that Tandyukisin and Trichoharzin bound to distinct sites on EGFR and that their combined use enhanced apoptosis in BC cells. This discovery may pave the way for developing new marine-derived EGFR inhibitors, offering a promising avenue for innovative cancer treatment strategies and addressing EGFR-mediated drug resistance.

Enhanced detection of ligand-PPARγ binding based on surface plasmon resonance through complexation with SRC1- or NCOR2-related polypeptide

A previous study reported the use of a biosensing technique based on surface plasmon resonance (SPR) for the ligand binding detection of peroxisome proliferator activator receptor gamma (PPARγ). This detection was designed based on the structural properties of PPARγ. Because of cross-linked protein inactivation and the low molecular weight of conventional ligands, direct ligand binding detection based on SPR has low stability and repeatability. In this study, we report an indirect response methodology based on SPR technology in which anti-His CM5 chip binds fresh PPARγ every cycle, resulting in more stable detection. We developed a remarkable improvement in ligand–protein binding detectability in vitro by introducing two coregulator-related polypeptides into this system. In parallel, a systematic indirect response methodology can reflect the interaction relationship between ligands and proteins to some extent by detecting the changes in SA-SRC1 and GST-NCOR2 binding to PPARγ. Rosiglitazone, a PPARγ agonist with strong affinity, is a potent insulin-sensitizing agent. Some ligands may be competitively exerted at the same sites of PPARγ (binding rosiglitazone). We demonstrated using indirect response methodology that selective PPARγ modulator (SPPARM) candidates of PPARγ can be found by competing for the binding of the rosiglitazone site on PPARγ, although they may have no effect on polypeptides and PPARγ binding.

High-sensitivity concentration detection of trace doxycycline in solution by molecular imprinting based on surface plasmon resonance technology

The abuse of doxycycline (DC) will lead to the presence of its residues in animals and water environments, which threatens human health. It is of great significance to detect the micro-content of DC in solution. Based on surface plasmon resonance (SPR) technology, we develop a detection method for trace DC in solution by modifying the SPR sensor chip with a molecular imprinting technique. The results show that the SPR sensor could specifically recognize DC in solution, and the detection limit of this method reaches 10−6µg/mL, which is 100 times lower than that of the ELISA method. The detection signal has good linearity in the concentration range of 10−6−10µg/mL. This method has the advantages of a low detection limit, large linear range, and high specificity for DC detection.

Network pharmacology, computational biology integrated surface plasmon resonance technology reveals the mechanism of ellagic acid against rotavirus

The target and mechanism of ellagic acid (EA) against rotavirus (RV) were investigated by network pharmacology, computational biology, and surface plasmon resonance verification. The target of EA was obtained from 11 databases such as HIT and TCMSP, and RV-related targets were obtained from the Gene Cards database. The relevant targets were imported into the Venny platform to draw a Venn diagram, and their intersections were visualized. The protein–protein interaction networks (PPI) were constructed using STRING, DAVID database, and Cytoscape software, and key targets were screened. The target was enriched by Gene Ontology (GO) and KEGG pathway, and the ‘EA anti-RV target-pathway network’ was constructed. Schrodinger Maestro 13.5 software was used for molecular docking to determine the binding free energy and binding mode of ellagic acid and target protein. The Desmond program was used for molecular dynamics simulation. Saturation mutagenesis analysis was performed using Schrodinger's Maestro 13.5 software. Finally, the affinity between ellagic acid and TLR4 protein was investigated by surface plasmon resonance (SPR) experiments. The results of network pharmacological analysis showed that there were 35 intersection proteins, among which Interleukin-1β (IL-1β), Albumin (ALB), Nuclear factor kappa-B1 (NF-κB1), Toll-Like Receptor 4 (TLR4), Tumor necrosis factor alpha (TNF-α), Tumor protein p53 (TP53), Recombinant SMAD family member 3 (SAMD3), Epidermal growth factor (EGF) and Interleukin-4 (IL-4) were potential core targets of EA anti-RV. The GO analysis consists of biological processes (BP), cellular components (CC), and molecular functions (MF). The KEGG pathways with the highest gene count were mainly related to enteritis, cancer, IL-17 signaling pathway, and MAPK signaling pathway. Based on the crystal structure of key targets, the complex structure models of TP53-EA, TLR4-EA, TNF-EA, IL-1β-EA, ALB-EA, NF-κB1-EA, SAMD3-EA, EGF-EA, and IL-4-EA were constructed by molecular docking (XP mode of flexible docking). The MMGBS analysis and molecular dynamics simulation were also studied. The Δaffinity of TP53 was highest in 220 (CYS → TRP), 220 (CYS → TYR), and 220 (CYS → PHE), respectively. The Δaffinity of TLR4 was highest in 136 (THR → TYR), 136 (THR → PHE), and 136 (THR → TRP). The Δaffinity of TNF-α was highest in 150 (VAL → TRP), 18 (ALA → GLU), and 144 (PHE → GLY). SPR results showed that ellagic acid could bind TLR4 protein specifically. TP53, TLR4, and TNF-α are potential targets for EA to exert anti-RV effects, which may ultimately provide theoretical basis and clues for EA to be used as anti-RV drugs by regulating TLR4/NF-κB related pathways.

Abstract 3525: Towards the efficient design of shared neoantigen peptide cancer vaccines using artificial intelligence

Abstract Background: The advent of immune checkpoint inhibitors has improved morbidity and mortality for some cancers, and recent breakthroughs in gene & cell therapy have shed light on curing some types of blood cancers. However, many cancers remain intractable and the development of novel, effective and safe therapies continue to be a priority. Cancer vaccines as a cancer immunotherapy approach has seen a resurgence in recent years, due to the success of mRNA vaccines for the COVID-19. However, the accurate prediction of immunogenicity of cancer vaccines remains elusive. Methods: Our models predict the probability of a given peptide derived from the protein of interest to be presented by MHC-I or MHC-II. For MHC-I antigen presentation model development, over 17 million entries in the dataset were collected from published literature and available databases, e.g., IEDB, with peptide lengths ranging from 8 to 11. The peptides were restricted to 150 unique MHC-I alleles. Similarly, ~4 million entries with peptide lengths ranging from 13 to 21 were collected for MHC-II antigen presentation model development, and the peptides were restricted to 19 unique MHC-II alleles. To develop advanced antigen presentation models, a language model was chosen as the backbone network and contrast learning was used to better discriminate the peptide-MHC match versus mismatch. Overall, both MHC-I and MHC-II presentation models were constructed with about 30 million parameters. To validate the model prediction accuracy, automated peptide synthesis and surface plasmon resonance (SPR) technologies were applied. Results: Using open-sourced data, our developed AI models surpassed the performance of state-of-the-art prediction algorithms, the latest versions of NetMHCpan and MixMHCpred, for both MHC-I and MHC-II antigen presentation. Furthermore, to validate the algorithm accuracy and the peptide immunogenicity, 28 predicted patentable peptides derived from mutated TP53 protein were synthesized and their binding to respective common HLA alleles were validated using SPR. We found that greater than 80% of the peptides display binding affinities that are stronger than the positive control, suggesting that AI significantly improves neoantigen peptide vaccine design. Conclusions: We developed advanced AI algorithms to rapidly design shared neoantigen T cell epitopes with predicted strong binding affinity to MHC-I and MHC-II. We envision that the epitopes predicted and designed by our AI algorithms possess great potential in advancing the field of off-the-shelf cancer vaccine development and hold the promise of significantly benefiting patients, once translated into the clinic. Citation Format: Genwei Zhang, Jiewen Du, Xiangrui Gao, Tianyuan Wang, Zhenghui Wang, Qingxia Zhang, Tongren Liu, Dong Chen, Ruohan Zhu, Yalong Zhao, Chi Han Samson Li, Melvin Toh, Lipeng Lai. Towards the efficient design of shared neoantigen peptide cancer vaccines using artificial intelligence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3525.

Highly sensitive ZnO/Ag/BaTiO3/MoS2 hybrid structure-based surface plasmon biosensor for the detection of mycobacterium tuberculosis bacteria

This study presents a novel biosensor utilizing surface plasmon resonance (SPR) technology, comprising og zinc oxide (ZnO), silver (Ag), barium titanate (BaTiO3), and molybdenum disulfide (MoS2). The detection of mycobacterium tuberculosis bacteria was accomplished through the utilization of the hybrid structure. The transfer matrix method (TMM) and finite element method are employed to analyze the suggested surface plasmon resonance (SPR) structure. A comparative analysis has been conducted to evaluate the angular sensitivity between normal blood samples (NBS) and cells affected by tuberculosis (TB). The optimization of the performance of the surface plasmon resonance (SPR) structure involves adjusting the thickness of ZnO, Ag and BaTiO3 layer. The accurate measurement of the full width at half maximum (FWHM), detection accuracy (DA), quality factor and figure of merits (FOM) has also been conducted. The optimal angular sensitivity has been determined to be 10 nm for ZnO, 40 nm for Ag, 1.5 nm for BaTiO3, and one layer of MoS2 with a sensitivity of 525 deg./RIU. Additionally, this study compared the effects on sensitivity of two dimensional materials graphene, WS2 and MoS2. In contrast to the currently available biosensor utilizing surface plasmon resonance (SPR), the suggested structure exhibits higher angular sensitivity. Due to its improved sensitivity, the biosensor under consideration exhibits potential for detecting a wide range of biological analytes and organic compounds.

Diagnosis of thrombotic thrombocytopenic purpura: easy-to-use fiber optic surface plasmon resonance immunoassays for automated ADAMTS-13 antigen and conformation evaluation

BackgroundLaboratory diagnosis of immune-mediated thrombotic thrombocytopenic purpura (iTTP) remains challenging when ADAMTS-13 activity ranges between 10% and 20%. To prevent misdiagnosis, open ADAMTS-13 conformation gained clinical attention as a novel biomarker, especially to diagnose acute iTTP in patients with diagnostic undecisive ADAMTS-13 activity. Plasma ADAMTS-13 conformation analysis corrects for ADAMTS-13 antigen, with both parameters being characterized in enzyme-linked immunosorbent assay (ELISA)-based reference assays requiring expert technicians. ObjectivesTo design ADAMTS-13 antigen and conformation assays on automated, easy-to-use fiber optic surface plasmon resonance (FO-SPR) technology to promote assay accessibility and diagnose challenging iTTP patients. MethodsADAMTS-13 antigen and conformation assays were designed on FO-SPR technology. Plasma of 20 healthy donors and 20 acute iTTP patients were quantified, and data from FO-SPR and ELISA reference assays were compared. ResultsFollowing assay design, both antigen and conformation FO-SPR assays were optimized and characterized, presenting strong analytical sensitivity (detection limit of 0.001 μg/mL) and repeatability (interassay variation of 14.4%). Comparative analysis suggested positive correlation (Spearman r of .92) and good agreement between FO-SPR and ELISA assays. As expected, FO-SPR assays showed a closed or open ADAMTS-13 conformation in healthy donors and acute iTTP patients, respectively. ConclusionBoth ADAMTS-13 antigen and conformation assays were transferred onto automated, easy-to-use FO-SPR technology, displaying potent analytical sensitivity and reproducibility. ADAMTS-13 antigen and conformation were determined for healthy donors and acute iTTP patients showing strong correlation with ELISA reference. Introducing FO-SPR technology in clinical context could support routine diagnosis of acute iTTP patients, notably when ADAMTS-13 activity fluctuates between 10% and 20%.

Unraveling the Dynamics of SARS-CoV-2 Mutations: Insights from Surface Plasmon Resonance Biosensor Kinetics.

Surface Plasmon Resonance (SPR) technology is known to be a powerful tool for studying biomolecular interactions because it offers real-time and label-free multiparameter analysis with high sensitivity. This article summarizes the results that have been obtained from the use of SPR technology in studying the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations. This paper will begin by introducing the working principle of SPR and the kinetic parameters of the sensorgram, which include the association rate constant (ka), dissociation rate constant (kd), equilibrium association constant (KA), and equilibrium dissociation constant (KD). At the end of the paper, we will summarize the kinetic data on the interaction between angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 obtained from the results of SPR signal analysis. ACE2 is a material that mediates virus entry. Therefore, understanding the kinetic changes between ACE2 and SARS-CoV-2 caused by the mutation will provide beneficial information for drug discovery, vaccine development, and other therapeutic purposes.

Kinetic Binding Analysis of Biomolecular Interactions Using Surface Plasmon Resonance System

Surface plasmon resonance (SPR) technology is a versatile and sensitive tool widely used for kinetic studies of interactions between unlabelled biomolecules in real time. The interactions of 4-carboxy benzene sulfonamide (4-CBS) inhibitor, with the enzyme carbonic anhydrase II (CA II) and Interleukin 2 with its antibody (IL 2 antibody) were determined at different concentrations by injecting at a flow rate of 100 μl.min-1 for 60s (100 μl) for a 1 min association phase, which was followed by a 2 min dissociation phase. Langmuir model yielded the rate constants ka and kd , which were of the order of 1.58E+3 M-1. s-1 and 0.04 s-1, respectively, and equilibrium dissociation constant was 2.45E-7 M. Automatic artifact removal, using software options and double referencing (by injection of running buffer to nullify non-specific interactions), further improved the quality of response. Langmuir model yielded the rate constants ka and kd , which were of the order of 2.79E+5 M-1.s-1 and 1.43E-4 s-1, respectively, and equilibrium dissociation constant was 5.17E-7 M. The results illustrate the potential of such kinetic analysis in disease management, drug discovery and for detection of pathogens, toxins, pesticides and antibiotic residues based on either enzyme inhibition or antigen-antibody binding

Surface Plasmon Resonance Biosensors: A Review of Molecular Imaging with High Spatial Resolution.

Surface plasmon resonance (SPR) is a powerful tool for determining molecular interactions quantitatively. SPR imaging (SPRi) further improves the throughput of SPR technology and provides the spatially resolved capability for observing the molecular interaction dynamics in detail. SPRi is becoming more and more popular in biological and chemical sensing and imaging. However, SPRi suffers from low spatial resolution due to the imperfect optical components and delocalized features of propagating surface plasmonic waves along the surface. Diverse kinds of approaches have been developed to improve the spatial resolution of SPRi, which have enormously impelled the development of the methodology and further extended its possible applications. In this minireview, we introduce the mechanisms for building a high-spatial-resolution SPRi system and present its experimental schemes from prism-coupled SPRi and SPR microscopy (SPRM) to surface plasmonic scattering microscopy (SPSM); summarize its exciting applications, including molecular interaction analysis, molecular imaging and profiling, tracking of single entities, and analysis of single cells; and discuss its challenges in recent decade as well as the promising future.

Numerical investigation into impact of halide perovskite material on the optical performance of prism-loaded hybrid surface plasmon resonance biosensor: A strategy to increase sensitivity

The technology of surface plasmon resonance (SPR) is widely recognized and valued for its ability to rapidly and sensitively investigate biomolecular interactivities in real-time. Herein, we numerically investigate the collective influence of metal/ transition metal dichalcogenide (TMDC)/halide perovskite (HP)/2D carbon (C) and phosphorus (P) allotropes on the functionality of an SPR biosensor deploying Kretschmann configuration. The incident light wavelength is held constant at 633 nm, and radiative properties of the hybrid structure are determined using the attenuated total reflection and transfer matrix techniques. Crucial performance metrics such as quality factor (QF), figure of merit (FoM), sensitivity, and detection accuracy are calculated. The comparison is conducted and evaluated against the current literature using performance outcomes in terms of several prisms such as BK7, BAK1, BAF10, SF5, SF10, SF11, 2S2G, CaF2, and CsF, several TMDCs such as WS2, MoS2, WSe2, MoSe2, and PtSe2, several HPs such as CsPbI3, KSnI3, CsSnI3, and FASnI3, and 2D C/P allotropes such as Graphene, MXene, Black phosphorene (BP), and Blue phosphorene (BlueP) in order to search optimum parameters, and then we implement the best one in each layer of this biosensor design. It is noticed that the SPR heterostructure based on BAK1 prism, plasmonic metal Ag, tungsten disulfide (WS2) TMDC, formamidinium tin iodide (FASnI3) HP and 2D BP exhibits outstanding performance with regard to sensor performance characteristics. The observed FoM and sensitivity are 48.2/RIU and 402°/RIU, respectively. The investigation of the electric field distribution within this biosensor along the normal to the interface is also conducted using the finite difference time domain (FDTD) approach to demonstrate the unique contribution of FASnI3. The findings presented in this study are anticipated to play a key role in the improvement of plasmonic resonance-based biosensing domains like DNA hybridization or formalin detection by employing halide perovskite as an additional layer in SPR biosensors.

Surface Plasmon Resonance Application for Bacteria Pathogen Detection: A Minireview

Detection of pathogenic bacteria requires a fast and accurate process so technological developments related to the sensitivity and selectivity of a sensor are very concerned. Surface Plasmon Resonance (SPR) technology has great potential to detect pathogenic bacteria that are not only used for medical diagnostics, but food safety surveillance and environmental monitoring are also applications of SPR. The success of SPR has proven the advantages of real-time detection without the need for fluorescent markers or additional dyes. The development of sensor surface systems of SPR with nanomaterials is one of the discussions in this paper. The recent development of SPR in recent years is summarized by linking future prospective applications.

The role of phosphorylation in calmodulin-mediated gating of human AQP0.

Aquaporin-0 (AQP0) is the main water channel in the mammalian lens and is involved in accommodation and maintaining lens transparency. AQP0 binds the Ca2+-sensing protein calmodulin (CaM) and this interaction is believed to gate its water permeability by closing the water-conducting pore. Here, we express recombinant and functional human AQP0 in Pichia pastoris and investigate how phosphorylation affects the interaction with CaM in vitro as well as the CaM-dependent water permeability of AQP0 in proteoliposomes. Using microscale thermophoresis and surface plasmon resonance technology we show that the introduction of the single phospho-mimicking mutations S229D and S235D in AQP0 reduces CaM binding. In contrast, CaM interacts with S231D with similar affinity as wild type, but in a different manner. Permeability studies of wild-type AQP0 showed that the water conductance was significantly reduced by CaM in a Ca2+-dependent manner, whereas AQP0 S229D, S231D and S235D were all locked in an open state, insensitive to CaM. We propose a model in which phosphorylation of AQP0 control CaM-mediated gating in two different ways (1) phosphorylation of S229 or S235 abolishes binding (the pore remains open) and (2) phosphorylation of S231 results in CaM binding without causing pore closure, the functional role of which remains to be elucidated. Our results suggest that site-dependent phosphorylation of AQP0 dynamically controls its CaM-mediated gating. Since the level of phosphorylation increases towards the lens inner cortex, AQP0 may become insensitive to CaM-dependent gating along this axis.

Advances of fluorescent DNA nanostructures in biomedical applications

<p>With the rapid development of DNA nanotechnology, the emergence of fluorescent DNA nanostructures (FDNs) has enlarged the biological applications. FDNs have great advantages of precise localization and real-time tracing in bioimaging. In this review, the recent biomedical developments of FDNs have been reviewed, including the design of FDNs, and the corresponding applications on biomarker sensing, bioimaging, cancer diagnosis and therapy. Firstly, the development of DNA nanostructures and the corresponding DNA-based nanomaterials were briefly introduced. Simultaneously, to make a better demonstration, the background and theory of the fluorescence detections were briefly introduced. Thereafter, the synthetic strategies of DNA nanostructure were summarized and classified, which facilitated the multiple functionalizations for sensing and bioimaging. Subsequently, the biomedical applications of FDNs are comprehensively summarized based on different detection strategies, including fluorescence resonance energy transfer (FRET), aggregation-induced emission (AIE), near-infrared (NIR)-photoactivation, nucleic acid amplification (NAT), small fluorescent dyes loading, and surface plasmon resonance (SPR) technologies. Finally, an insight into the challenges and future perspectives is provided. As reviewed, FDNs are important tools in precision medicine, showing great potential in both <i>in vivo</i> and <i>in vitro</i> cancer diagnosis and treatments. Undoubtedly, FDN-based technology is a promising strategy for constructing versatile nanodevices in biological applications and will excel in human healthcare.</p>

Biophysical studies do not reveal direct interactions between human PF4 and Ad26.COV2.S vaccine

BackgroundCOVID-19 vaccines have been widely used to control the SARS-CoV-2 pandemic. In individuals receiving replication-incompetent, adenovirus vector–based COVID-19 vaccines (eg, ChAdOx1 nCoV-19 [AstraZeneca] or Ad26.COV2.S [Johnson & Johnson/Janssen] vaccines), a very rare but serious adverse reaction has been reported and described as vaccine-induced immune thrombotic thrombocytopenia (VITT). The exact mechanism of VITT following Ad26.COV2.S vaccination is under investigation. Antibodies directed against human platelet factor 4 (PF4) are considered critical in the pathogenesis of VITT, suggesting similarities with heparin-induced thrombocytopenia. It has been postulated that components of these vaccines mimic the role of heparin by binding to PF4, triggering production of these anti-PF4 antibodies. ObjectivesThis study aimed to investigate the potential interaction between human PF4 and Ad26.COV2.S vaccine using several biophysical techniques. MethodsDirect interaction of PF4 with Ad26.COV2.S vaccine was investigated using dynamic light scattering, biolayer interferometry, and surface plasmon resonance. For both biosensing methods, the Ad26.COV2.S vaccine was immobilized to the sensor surface and PF4 was used as analyte. ResultsNo direct interactions between PF4 and Ad26.COV2.S vaccine could be detected using dynamic light scattering and biolayer interferometry. Surface plasmon resonance technology was shown to be unsuitable to investigate these types of interactions. ConclusionOur findings make it very unlikely that direct binding of PF4 to Ad26.COV2.S vaccine or components thereof is driving the onset of VITT, although the occurrence of such interactions after immunization (potentially facilitated by unknown plasma or cellular factors) cannot be excluded. Further research is warranted to improve the understanding of the full mechanism of this adverse reaction.

Level of blood Tau and p‐Tau : a non‐invasive approach for the diagnosis of Alzheimer’s Disease(AD)

AbstractBackgroundProminent expression of Tau and phosphorylated Tau in cerebrospinal fluid (CSF) is one of the well‐known hallmarks of the Alzheimer’s disease (AD). High levels of p‐Tau can easily differentiate AD from other neurodegenerative disease. However, the serum levels of these proteins in AD patients are not well explored. This study provides an alternative non‐invasive approach to diagnose the disease by evaluating the level of Tau and p‐Tau181 in serum samples.MethodBlood samples were collected from 39 AD patients, 37 MCI patients and 37 elderly individuals as controls. Quantification of tau and pTau in serum samples was done with the help of a label free real time Surface Plasmon Resonance technology, and further validated by Western Blot. Statistical analysis, including Receiver Operating Characteristic (ROC), was done for further affirmation.ResultThe concentrations of serum Tau and p‐Tau181 were significantly higher (p<0.00001) in AD (Tau; 47.49±9.00ng/µL, p‐Tau181; 0.161±0.04 ng/µL) compared to MCI (Tau; 39.26±7.78 ng/µL, p‐Tau181; 0.135±0.02 ng/µL) and were further compared to elderly controls (Tau; 34.92±6.58 ng/µL, p‐Tau181; 0.122±0.01 ng/ µL). A significant (p<0.0001) downhill correlation was found between Tau as well as p‐Tau181 levels with HMSE and MoCA score.ConclusionThis study for the first time reports the concentration of Tau and p‐Tau181 in serum of AD and MCI patients. The cut‐off values of Tau and p‐Tau181 of AD and MCI patients with sensitivity and specificity reveal that serum level of these proteins can be used as a predictive marker for AD and MCI.

Recent Advances in Surface Plasmon Resonance (SPR) Technology for Detecting Ovarian Cancer Biomarkers

Epithelial Ovarian Cancer (EOC) is a leading cause of cancer-related deaths among women, mainly due to a lack of early detection and screening methods. Advanced immunoassay techniques, such as Luminex and proximity extension assay (PEA) technology, show promise in improving EOC detection by utilizing highly sensitive and specific multiplex panels to detect multiple combinations of biomarkers. However, these advanced immunoassay techniques have certain limitations, especially in validating the performance characteristics such as specificity, sensitivity, limit of detection (LOD), and dynamic range for each EOC biomarker within the panel. Implementing multiplexing in point-of-care (POC) biosensors can enhance EOC biomarker detection, with Surface Plasmon Resonance (SPR) being a versatile option among optical biosensors. There is no study on multiplex SPR biosensors specifically tailored for diagnosing EOC. Recent studies have shown promising results in the single detection of EOC biomarkers using SPR, with LOD for cancer antigen 125 (CA125) at 0.01 U/mL−1 and human epididymis protein 4 (HE4) at 1pM. This study proposes a potential roadmap for scientists and engineers in academia and industry to develop a cost effective yet highly efficient SPR biosensor platform for detecting EOC.

Intensity Interrogation-Based High-Sensitivity Surface Plasmon Resonance Imaging Biosensor for Apoptosis Detection in Cancer.

Intensity interrogation-based surface plasmon resonance imaging (ISPRi) sensing has a simple schematic design and is the most widely used surface plasmon resonance technology at present. In this study, we report the successful development of a novel high-sensitivity ISPRi biosensor and its application for apoptosis detection in cancer cells. By optimizing the excitation wavelength and excitation angle, we achieved a refractive index resolution (RIR) of 5.20 × 10-6 RIU. Importantly, the biosensor has been tested and validated for high-throughput and label-free detection of activated caspase-3 with its specific inhibitor Z-DEVD-FMK in apoptotic cells. Therefore, this study describes a novel molecular imaging system to monitor apoptosis in cancers for disease diagnosis and/or evaluation of therapeutic efficacy of anti-cancer drugs.

A Novel ASCT2 Inhibitor, C118P, Blocks Glutamine Transport and Exhibits Antitumour Efficacy in Breast Cancer.

The microtubule protein inhibitor C118P shows excellent anti-breast cancer effects. However, the potential targets and mechanisms of C118P in breast cancer remain unknown. Real-time cellular analysis (RTCA) was used to detect cell viability. Apoptosis and the cell cycle were detected by flow cytometry. Computer docking simulations, surface plasmon resonance (SPR) technology, and microscale thermophoresis (MST) were conducted to study the interaction between C118P and alanine-serine-cysteine transporter 2 (ASCT2). Seahorse XF technology was used to measure the basal oxygen consumption rate (OCR). The effect of C118P in the adipose microenvironment was explored using a co-culture model of adipocytes and breast cancer cells and mouse cytokine chip. C118P inhibited proliferation, potentiated apoptosis, and induced G2/M cell cycle arrest in breast cancer cells. Notably, ASCT2 was validated as a C118P target through reverse docking, SPR, and MST. C118P suppressed glutamine metabolism and mediated autophagy via ASCT2. Similar results were obtained in the adipocyte-breast cancer microenvironment. Adipose-derived interleukin-6 (IL-6) promoted the proliferation of breast cancer cells by enhancing glutamine metabolism via ASCT2. C118P inhibited the upregulation of ASCT2 by inhibiting the effect of IL-6 in co-cultures. C118P exerts an antitumour effect against breast cancer via the glutamine transporter ASCT2.

Elucidating Novel Targets for Ovarian Cancer Antibody-Drug Conjugate Development: Integrating In Silico Prediction and Surface Plasmon Resonance to Identify Targets with Enhanced Antibody Internalization Capacity.

Antibody-drug conjugates (ADCs) constitute a rapidly expanding category of biopharmaceuticals that are reshaping the landscape of targeted chemotherapy. The meticulous process of selecting therapeutic targets, aided by specific monoclonal antibodies' high specificity for binding to designated antigenic epitopes, is pivotal in ADC research and development. Despite ADCs' intrinsic ability to differentiate between healthy and cancerous cells, developmental challenges persist. In this study, we present a rationalized pipeline encompassing the initial phases of the ADC development, including target identification and validation. Leveraging an in-house, computationally constructed ADC target database, termed ADC Target Vault, we identified a set of novel ovarian cancer targets. We effectively demonstrate the efficacy of Surface Plasmon Resonance (SPR) technology and in vitro models as predictive tools, expediting the selection and validation of targets as ADC candidates for ovarian cancer therapy. Our analysis reveals three novel robust antibody/target pairs with strong binding and favourable antibody internalization rates in both wild-type and cisplatin-resistant ovarian cancer cell lines. This approach enhances ADC development and offers a comprehensive method for assessing target/antibody combinations and pre-payload conjugation biological activity. Additionally, the strategy establishes a robust platform for high-throughput screening of potential ovarian cancer ADC targets, an approach that is equally applicable to other cancer types.