Label-Free Electrochemical Biosensor Platforms for Cancer Diagnosis: Recent Achievements and Challenges

Modeling Electrochemical Impedance Spectroscopy Using Time-Dependent Finite Element Method

A time-dependent electrochemical impedance spectroscopy (EIS) model is presented using the finite element method (FEM) to simulate a 2D interdigitated electrode in an aqueous NaCl electrolyte. Developed in COMSOL Multiphysics, the model incorporates ion transport, electric field distribution, Stern layer effects, and electrode sheet resistance, governed by the Poisson and Nernst-Planck equations. This model can predict the transient current response to an applied excitation voltage, which gives information about the dynamics of the electrochemical system. The simulation results are compared with the experimental data, reproducing key features of the measurements. The transient current response indicates the need for multiple excitation cycles to stabilize the impedance measurement. At low frequencies (<1 kHz), the voltage drop at the Stern layer is significant, while at higher frequencies (>100 kHz), the voltage drop due to sheet resistance dominates. Moreover, the amplitude of the excitation voltage influences the EIS measurement, higher amplitudes (above 0.1 V) lead to non-linear impedance behavior, particularly at low ion concentrations. Discrepancies at low frequencies suggest that Faradaic processes may need to be incorporated for improved accuracy. Overall, this model provides quantitative insights for optimizing EIS sensor design and highlights critical factors for high-frequency and low-concentration conditions, laying the foundation for future biosensing applications with functionalized electrodes.

Gold-Graphene Quantum Dot Hybrid Nanoparticle for Smart Diagnostics of Prostate Cancer

Prostate cancer is one of the most prevalent cancers afflicting men worldwide, often detected at advanced stages, leading to increased mortality rates. Addressing this challenge, we present an innovative approach employing electrochemical biosensing for early-stage prostate cancer detection. This study used Indium-Tin Oxide (ITO) as a substrate and a deposited gold-graphene quantum dot (Au-GQD) nanohybrid to establish electrochemical sensing platforms for DNA-hybridization assays. A capturing DNA probe, PCA3, was covalently immobilized on the surface of the Au-GQDs and deposited electrochemically onto the ITO electrode surface. The Au-GQDs enabled the capturing of the target PCA3 biomarker probe. The sensor achieved a limit of detection (LoD) of up to 211 fM and presented a linear detection range spanning 1 µM to 100 fM. A rapid 5-min response time was also achieved. The tested shelf life of the pre-immobilized sensor was approximately 19 ± 1 days, with pronounced selectivity for its intended target amidst various interferants. The sensing device has the potential to revolutionize prostate cancer management by facilitating early-stage detection and screening with enhanced treatment efficacy.

Diagnosis of viral infectious diseases through sensitive detection of human serum antibodies using a modified label-free electrochemical biosensor

Rapid virus identification is crucial for preventing outbreaks. The COVID-19 pandemic has highlighted the critical nature of rapid virus detection. Here, we designed a label-free electrochemical biosensor modified with gold nanoparticles (AuNPs) to detect IgG antibodies from human serum, enabling rapid point-of-care diagnostics. AuNPs were synthesized and characterized. A multivariate optimization was carried out to determine the optimal condition for functionalizing AuNPs with anti-IgG. Subsequently, using a glassy carbon electrode (GCE), a modified AuNPs/GCE electrochemical biosensor was developed for IgG detection. The results indicated that AuNPs displayed a spherical morphology with a size distribution of 19.54 nm. Additionally, the zeta potential was recorded at -7.84 mV. Central composite design (CCD) analysis determined the optimal conditions for functionalizing AuNPs to be an anti-IgG concentration of 320 µg mL-1, a temperature of 25 °C, and pH of 7.4. The characterization study confirmed the successful synthesis and functionalization of AuNPs. Through electrochemical impedance spectroscopy measurement, the biosensor demonstrated a limit of detection (LOD) of 0.2 ng mL-1 and limit of quantification (LOQ) of 0.8 ng mL-1. Furthermore, tests in real samples showed the interaction between IgG antibodies in serum samples and AuNPs/GCE, confirming the biosensor's ability to detect and quantify IgG in clinical samples.

Label-free electrochemical biosensor based on dual amplification of gold nanoparticles and polycaprolactones for CEA detection

Carcinoembryonic Antigen (CEA), an acidic glycoprotein with human embryonic antigen properties, is found on the surface of cancer cells that have differentiated from endodermal cells. This paper presents a label-free electrochemical immunoassay for the dual amplification detection of CEA using gold nanoparticles loaded with polypyrrole polydopamine (Au/PPy-PDA) and polymerized polycaprolactone (Ng-PCL) prepared by ring-opening polymerization (ROP). First, the composite Au/PPy-PDA was adhered to the electrode surface. Then, gold nanoparticles form a Au-S bond with the sulfhydryl group in Apt1 to secure it on the electrode surface. Subsequently, the non-specific binding sites on the electrodes surface are closed by bovine serum albumin (BSA). Next, CEA is dropped onto the electrode surface, which is immobilized by antigen-antibody specific recognition, and the carboxyl-functionalized Apt2 forms a "sandwich structure" of antibody-antigen-antibody by specific recognition. Polymeric Ng-PCL is adhered to the electrode surface, leading to an increase in the electrochemical impedance signal, resulting in a complete chain of signal analysis. Finally, the response signal is detected by electrochemical impedance spectroscopy (EIS). Under optimal experimental conditions, the method has the advantages of high sensitivity and wide linear range (1 pg mL-1∼100 ng mL-1), and the lower limit of detection (LOD) is 0.234 pg mL-1. And it has the same high sensitivity, selectivity and interference resistance for the real samples detection. Thus, it provides a new way of thinking about biomedical and clinical diagnosis.

Emerging electrochemical biosensors for lung cancer-associated protein biomarker and miRNA detection

Lung cancer remains a major driver of global morbidity and mortality, and diagnosing lung tumors early in their development is vital to maximizing treatment efficacy and patient survival. Several biomarkers, including CYFRA 21-1, NSE, ProGRP, CEA, and miRNA, have been identified as reliable indicators for early lung cancer detection and monitoring treatment progress. However, the minute changes in the levels of these biomarkers during the early stages of disease necessitate advanced detection platforms. In this space, electrochemical biosensors have currently emerged as robust tools for early lung cancer screening and diagnosis owing to their low costs, rapid responses, and superior sensitivity and selectivity. This review provides an up-to-date overview of the application of electrochemiluminescence, photoelectrochemical, and other electrochemical analytical strategies for detecting lung cancer-associated protein biomarkers, and miRNA. This review compares these techniques to provide a concise overview of the principles underlying these electrochemical analytical methods, the preparation of their components, and the performance of the resulting biosensors. Lastly, a discussion of the challenges and opportunities associated with electrochemical biosensors detection of lung cancer-associated biomarkers are provided.

Optimization of Nanowell-Based Label-Free Impedance Biosensor Based on Different Nanowell Structures

Nanowell-based impedance-based label-free biosensors have demonstrated significant advantages in sensitivity, simplicity, and accuracy for detecting cancer biomarkers and macromolecules compared to conventional impedance-based biosensors. Although nanowell arrays have previously been employed for biomarker detection, a notable limitation exists in the photolithography step of their fabrication process, leading to a reduced efficiency rate. Historically, the diameter of these nanowells has been 2 μm. To address this issue, we propose alternative geometries for nanowells that feature larger surface areas while maintaining a similar circumference, thereby enhancing the fabrication efficiency of the biosensors. We investigated three geometries: tube, spiral, and quatrefoil. Impedance measurements of the samples were conducted at 10 min intervals using a lock-in amplifier. The study utilized interleukin-6 (IL-6) antibodies and antigens/proteins at a concentration of 100 nM as the target macromolecules. The results indicated that tube-shaped nanowells exhibited the highest sensitivity for detecting IL-6 protein, with an impedance change of 9.55%. In contrast, the spiral, quatrefoil, and circle geometries showed impedance changes of 0.91%, 0.95%, and 1.62%, respectively. Therefore, the tube-shaped nanowell structure presents a promising alternative to conventional nanowell arrays for future studies, potentially enhancing the efficiency and sensitivity of biosensor fabrication.

Fabrication of rGO-decorated hBNNS hybrid nanocomposite via organic-inorganic interfacial chemistry for enhanced electrocatalytic detection of carcinoembryonic antigen

Organic-inorganic hybrid nanocomposites (OIHN), with tailored surface chemistry, offer ultra-sensitive architecture capable of detecting ultra-low concentrations of target analytes with precision. In the present work, a novel nano-biosensor was fabricated, acquainting dynamic synergy of reduced graphene oxide (rGO) decorated hexagonal boron nitride nanosheets (hBNNS) for detection of carcinoembryonic antigen (CEA). Extensive spectroscopic and microscopic analyses confirmed the successful hydrothermal synthesis of cross-linked rGO-hBNNS nanocomposite. Uniform micro-electrodes of rGO-hBNNS onto pre-hydrolyzed ITO were obtained via electrophoretic deposition (EPD) technique at low DC potential (15 V). Optimization of antibody incubation time, pH of supporting electrolyte, and immunoelectrode preparation was thoroughly investigated to enhance nano-biosensing efficacy. rGO-modified hBNNS demonstrated 29% boost in electrochemical performance over bare hBNNS, signifying remarkable electro-catalytic activity of nano-biosensor. The presence of multifunctional groups on the interface facilitated stable crosslinking chemistry, increased immobilization density, and enabled site-specific anchoring of Anti-CEA, resulting in improved binding affinity. The nano-biosensor demonstrated a remarkably low limit of detection of 5.47 pg/mL (R2 = 0.99963), indicating exceptional sensitivity and accuracy in detecting CEA concentrations from 0 to 50 ng/mL. The clinical evaluation confirmed its exceptional shelf life, minimal cross-reactivity, and robust recovery rates in human serum samples, thereby unraveling the potential for early, highly sensitive, and reliable CEA detection.

The multifaceted role of proteases and modern analytical methods for investigation of their catalytic activity

We discuss the diverse functions of proteases in the context of their biotechnological and medical significance, as well as analytical approaches used to determine the functional activity of these enzymes. An insight into modern approaches to studying the kinetics and specificity of proteases, based on spectral (absorption, fluorescence), mass spectrometric, immunological, calorimetric, and electrochemical methods of analysis is given. We also examine in detail electrochemical systems for determining the activity and specificity of proteases. Particular attention is given to exploring innovative electrochemical systems based on the detection of the electrochemical oxidation signal of amino acid residues, thereby eliminating the need for extra redox labels in the process of peptide synthesis. In the review, we highlight the main prospects for the further development of electrochemical systems for the study of biotechnologically and medically significant proteases, which will enable the miniaturization of the analytical process for determining the catalytic activity of these enzymes.

The Advancing Role of Nanocomposites in Cancer Diagnosis and Treatment

The relentless pursuit of effective cancer diagnosis and treatment strategies has led to the rapidly expanding field of nanotechnology, with a specific focus on nanocomposites. Nanocomposites, a combination of nanomaterials with diverse properties, have emerged as versatile tools in oncology, offering multifunctional platforms for targeted delivery, imaging, and therapeutic interventions. Nanocomposites exhibit great potential for early detection and accurate imaging in cancer diagnosis. Integrating various imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and fluorescence imaging, into nanocomposites enables the development of contrast agents with enhanced sensitivity and specificity. Moreover, functionalizing nanocomposites with targeting ligands ensures selective accumulation in tumor tissues, facilitating precise imaging and diagnostic accuracy. On the therapeutic front, nanocomposites have revolutionized cancer treatment by overcoming traditional challenges associated with drug delivery. The controlled release of therapeutic agents from nanocomposite carriers enhances drug bioavailability, reduces systemic toxicity, and improves overall treatment efficacy. Additionally, the integration of stimuli-responsive components within nanocomposites enables site-specific drug release triggered by the unique microenvironment of the tumor. Despite the remarkable progress in the field, challenges such as biocompatibility, scalability, and long-term safety profiles remain. This article provides a comprehensive overview of recent developments, challenges, and prospects, emphasizing the transformative potential of nanocomposites in revolutionizing the landscape of cancer diagnostics and therapeutics. In Conclusion, integrating nanocomposites in cancer diagnosis and treatment heralds a new era for precision medicine.

Paper-Based Analytical Devices for Cancer Liquid Biopsy

Liquid biopsies have caused a significant revolution in cancer diagnosis, and the use of point of care (PoC) platforms has the potential to bring liquid biopsy-based cancer detection closer to patients. These platforms provide rapid and on-site analysis by reducing the time between sample collection and results output. The aim of this tutorial content is to provide readers an in-depth understanding regarding the choice of the ideal sensing platform suitable for specific cancer-related biomarkers.

Integrative analysis of RNA expression data unveils distinct cancer types through machine learning techniques

Cancer is a highly complex and heterogeneous disease. Traditional methods of cancer classification based on histopathology have limitations in guiding personalized prognosis and therapy. Gene expression profiling provides a powerful approach to unraveling molecular intricacies and better-stratifying cancer subtypes. In this study, we performed an integrative analysis of RNA sequencing data from five cancer types - BRCA, KIRC, COAD, LUAD, and PRAD. A machine learning workflow consisting of dataset identification, normalization, feature selection, dimensionality reduction, clustering, and classification was implemented. The k-means algorithm was applied to categorize samples into distinct clusters based solely on gene expression patterns. Five unique clusters emerged from the unsupervised machine learning based analysis, significantly correlating with the known cancer types. BRCA aligned predominantly with one cluster, while COAD spanned three clusters. KIRC was represented within two main clusters. LUAD is associated strongly with a single cluster and PRAD with another cluster. This demonstrates the ability of machine learning approaches to unravel complex signatures within transcriptomic profiles that can delineate cancer subtypes. The proposed study highlights the potential of integrative analytics to derive meaningful biological insights from high-dimensional omics datasets. Molecular subtyping through machine learning clustering enhances our understanding of the intrinsic heterogeneities and pathways dysregulated in different cancers. Overall, this study exemplifies a powerful computational framework to classify gene expressions of patients having different types of cancers and guide personalized therapeutic decisions. Finally, Wide Neural Network demonstrates a significantly higher accuracy, achieving 99.834% on the validation set and an even more impressive 99.995% on the test set.

Label-free biomolecular and cellular methods in small molecule epigallocatechin-gallate research

Small molecule natural compounds are gaining popularity in biomedicine due to their easy access to wide structural diversity and their proven health benefits in several case studies. Affinity measurements of small molecules below 100 Da molecular weight in a label-free and automatized manner using small amounts of samples have now become a possibility and reviewed in the present work. We also highlight novel label-free setups with excellent time resolution, which is important for kinetic measurements of biomolecules and living cells. We summarize how molecular-scale affinity data can be obtained from the in-depth analysis of cellular kinetic signals. Unlike traditional measurements, label-free biosensors have made such measurements possible, even without the isolation of specific cellular receptors of interest. Throughout this review, we consider epigallocatechin gallate (EGCG) as an exemplary compound. EGCG, a catechin found in green tea, is a well-established anti-inflammatory and anti-cancer agent. It has undergone extensive examination in numerous studies, which typically rely on fluorescent-based methods to explore its effects on both healthy and tumor cells. The summarized research topics range from molecular interactions with proteins and biological films to the kinetics of cellular adhesion and movement on novel biomimetic interfaces in the presence of EGCG. While the direct impact of small molecules on living cells and biomolecules is relatively well investigated in the literature using traditional biological measurements, this review also highlights the indirect influence of these molecules on the cells by modifying their nano-environment. Moreover, we underscore the significance of novel high-throughput label-free techniques in small molecular measurements, facilitating the investigation of both molecular-scale interactions and cellular processes in one single experiment. This advancement opens the door to exploring more complex multicomponent models that were previously beyond the reach of traditional assays.

Hybrid Impedimetric Biosensors for Express Protein Markers Detection

Impedimetric biosensors represent a powerful and promising tool for studying and monitoring biological processes associated with proteins and can contribute to the development of new approaches in the diagnosis and treatment of diseases. The basic principles, analytical methods, and applications of hybrid impedimetric biosensors for express protein detection in biological fluids are described. The advantages of this type of biosensors, such as simplicity and speed of operation, sensitivity and selectivity of analysis, cost-effectiveness, and an ability to be integrated into hybrid microfluidic systems, are demonstrated. Current challenges and development prospects in this area are analyzed. They include (a) the selection of materials for electrodes and formation of nanostructures on their surface; (b) the development of efficient methods for biorecognition elements' deposition on the electrodes' surface, providing the specificity and sensitivity of biosensing; (c) the reducing of nonspecific binding and interference, which could affect specificity; (d) adapting biosensors to real samples and conditions of operation; (e) expanding the range of detected proteins; and, finally, (f) the development of biosensor integration into large microanalytical system technologies. This review could be useful for researchers working in the field of impedimetric biosensors for protein detection, as well as for those interested in the application of this type of biosensor in biomedical diagnostics.

Optimizing an Optical Cavity-Based Biosensor for Enhanced Sensitivity

The rapid advancement of biosensor technology has revolutionized healthcare, offering improved sensitivity, specificity, and portability. We have developed an optical cavity-based biosensor (OCB) as a promising solution due to its label-free detection, high sensitivity, real-time monitoring, multiplexing capability, and versatility. The OCB consists of an optical cavity structure (OCS), optical components, and a low-cost camera. The OCS is created by two partially reflective surfaces separated by a small gap, where the interaction between target analytes and immobilized receptors leads to a shift in the resonance transmission spectrum, caused by minute changes in the local refractive index (RI). In our previous work, we successfully detected these small changes with a simple OCS and cost-effective components using a differential detection method. Building upon these achievements, this study focuses on optimizing the OCS, improving the camera settings, and enhancing the differential detection approach. By increasing the reflectance of the surfaces and optimizing the optical cavity widths correspondingly, we achieved an improved limit of detection (LOD). We also investigated how the charge-coupled device (CCD) camera shutter time affects the LOD. Additionally, we introduced a new differential equation to further enhance the sensitivity of our system. Through these advancements, we could improve the LOD of the OCB by 7.2 times, specifically for an OCS with a cavity thickness of 9.881 μm and a silver thickness of 46.87 nm. These findings not only contribute to the ongoing effort of optimizing the OCB, but also pave the way for the development of advanced point-of-care biosensors with enhanced detection capabilities.

Circulating Tumor Cells Adhesion: Application in Biosensors

The early and non-invasive diagnosis of tumor diseases has been widely investigated by the scientific community focusing on the development of sensors/biomarkers that act as a way of recognizing the adhesion of circulating tumor cells (CTCs). As a challenge in this area, strategies for CTCs capture and enrichment currently require improvements in the sensors/biomarker's selectivity. This can be achieved by understanding the biological recognition factors for different cancer cell lines and also by understanding the interaction between surface parameters and the affinity between macromolecules and the cell surface. To overcome some of these concerns, electrochemical sensors have been used as precise, fast-response, and low-cost transduction platforms for application in cytosensors. Additionally, distinct materials, geometries, and technologies have been investigated to improve the sensitivity and specificity properties of the support electrode that will transform biochemical events into electrical signals. This review identifies novel approaches regarding the application of different specific biomarkers (CD44, Integrins, and EpCAm) for capturing CTCs. These biomarkers can be applied in electrochemical biosensors as a cytodetection strategy for diagnosis of cancerous diseases.

Label-Free Biosensor

Label-free biosensors have become an indispensable tool for analyzing intrinsic molecular properties, such as mass, and quantifying molecular interactions without interference from labels, which is critical for the screening of drugs, detecting disease biomarkers, and understanding biological processes at the molecular level [...].