Developing a fluorescence immunosensor for detection of HER2-positive breast cancer based on graphene and magnetic nanoparticles

Graphene-Oxide Peptide-Containing Materials for Biomedical Applications

This review explores the application of graphene-based materials (GBMs) in biomedicine, focusing on graphene oxide (GO) and its interactions with peptides and proteins. GO, a versatile nanomaterial with oxygen-containing functional groups, holds significant potential for biomedical applications but faces challenges related to toxicity and environmental impact. Peptides and proteins can be functionalized on GO surfaces through various methods, including non-covalent interactions such as π-π stacking, electrostatic forces, hydrophobic interactions, hydrogen bonding, and van der Waals forces, as well as covalent bonding through reactions involving amide bond formation, esterification, thiol chemistry, and click chemistry. These approaches enhance GO's functionality in several key areas: biosensing for sensitive biomarker detection, theranostic imaging that integrates diagnostics and therapy for real-time treatment monitoring, and targeted cancer therapy where GO can deliver drugs directly to tumor sites while being tracked by imaging techniques like MRI and photoacoustic imaging. Additionally, GO-based scaffolds are advancing tissue engineering and aiding tissues' bone, muscle, and nerve tissue regeneration, while their antimicrobial properties are improving infection-resistant medical devices. Despite its potential, addressing challenges related to stability and scalability is essential to fully harness the benefits of GBMs in healthcare.

Advanced electrocatalytic materials based biosensors for cancer cell detection – A review

Herein, we have highlighted the latest developments on biosensors for cancer cell detection. Electrochemical (EC) biosensors offer several advantages such as high sensitivity, selectivity, rapid analysis, portability, low‐cost, etc. Generally, biosensors could be classified into other basic categories such as immunosensors, aptasensors, cytosensors, electrochemiluminescence (ECL), and photo‐electrochemical (PEC) sensors. The significance of the EC biosensors is that they could detect several biomolecules in human body including cholesterol, glucose, lactate, uric acid, DNA, blood ketones, hemoglobin, and others. Recently, various EC biosensors have been developed by using electrocatalytic materials such as silver sulfide (Ag2S), black phosphene (BPene), hexagonal carbon nitrogen tube (HCNT), carbon dots (CDs)/cobalt oxy‐hydroxide (CoOOH), cuprous oxide (Cu2O), polymer dots (PDs), manganese oxide (MnO2), graphene derivatives, and gold nanoparticles (Au‐NPs). In some cases, these newly developed biosensors could be able to detect cancer cells with a limit of detection (LOD) of 1 cell/mL. In addition, many remaining challenges have to be addressed and validated by testing more real samples and confirm that these EC biosensors are more accurate and reliable to measure cancer cells in the blood and salivary samples.

Liquid crystal-assisted optical biosensor for early-stage diagnosis of mammary glands using HER-2

Breast cancer (BC) is one of the most commonly diagnosed cancers and the second leading cause of cancer mortality among women around the world. The purpose of this study is to present a non-labeled liquid crystal (LC) biosensor, based on the inherent feature of nematic LCs, for the evaluation of BC using the human epidermal growth factor receptor-2 (HER-2) biomarker. The mechanism of this sensing is supported by surface modification with dimethyloctadecyl [3-(trimethoxysilyl) propyl] ammonium chloride (DMOAP) encouraging the long alkyl chains that induce a homeotropic orientation of the LC molecules at the interface. To enhance the binding efficacy of more HER-2 antibody (Ab) on LC aligning agents, a simple ultraviolet radiation-assisted method was also used to increase functional groups on the DMOAP coated slides, thereby improving binding affinity and efficiency onto HER-2 Abs. The designed biosensor makes use of the specific binding of HER-2 protein to HER-2 Ab and disruption of the orientation of LCs. This orientation change leads to a transition of the optical appearance from dark to birefringent, enabling the detection of HER-2. This novel biosensor exhibits a linear optical response to HER-2 concentration in the wide dynamic range of 10^-6-10² ng/mL, with an ultra-low detection limit of 1 fg/mL. As a proof of concept, the designed LC biosensor was successfully investigated for the quantification of HER-2 protein in patients suffering from BC. Owing to the sensitivity, selectivity, and label-free detection, this biosensor may amplify the application of LC-based biosensors for the detection of most types of cancers.

A Highly Sensitive Fluorescence and Screen-Printed Electrodes—Electrochemiluminescence Immunosensor for Ricin Detection Based on CdSe/ZnS QDs with Dual Signal

A sensitive dual-readout immunosensor for fluorescence and electrochemiluminescence (ECL) detection of ricin was established, which was combined with a streptavidin–biotin signal amplification system. CdSe/ZnS quantum dots with fine fluorescence and ECL properties were used as the dual-signal function probes of the sandwich immunocomplex. Under the optimum experimental conditions, the dual signal intensity increased significantly with the rise in ricin concentration. The fluorescence intensity of the senor exhibited a good liner relationship toward the ricin concentrations with 0.1~100 ng/mL and the limit of detection (LOD) was 81.7 pg/mL; taking ECL as the detection signal, the sensor showed a linear relationship with the ricin concentrations ranging from 0.01 ng/mL to 100 ng/mL and the LOD was 5.5 pg/mL. The constructed sensor with high sensitivity had been successfully applied to the detection of ricin in complex matrices with satisfactory recoveries. The proposed immunosensor model can be extended to the analysis and detection of others target proteins.

High-Throughput Recognition of Tumor Cells Using Label-Free Elemental Characteristics Based on Interpretable Deep Learning

With cancer seriously hampering the increasing life expectancy of people, developing an instant diagnostic method has become an urgent objective. In this work, we developed a label-free laser-induced breakdown spectroscopy (LIBS) method for high-throughput recognition of tumor cells. LIBS spectra were straightly collected from cells dropped on a silicon substrate and built into a deep learning model for simultaneous classification of various cancers. To interpret the result of the deep learning algorithm, gradient-weighted class activation mapping was utilized to a one-dimensional convolution neural network (1D-CNN), and the saliency maps thus obtained amplified the differences between the spectra of cell lines. Overall results showed that the 1D-CNN algorithms achieved a mean sensitivity of 94.00%, a mean specificity of 98.47%, and a mean accuracy of 97.56%. Thus, the proposed method performed satisfactorily and is seen as an interpretable classification process for cancer cell lines.

Surface plasmon resonance biosensor for exosome detection based on reformative tyramine signal amplification activated by molecular aptamer beacon

Human epidermal growth factor receptor 2 (HER2)-positive exosomes play an extremely important role in the diagnosis and treatment options of breast cancers. Herein, based on the reformative tyramine signal amplification (TSA) enabled by molecular aptamer beacon (MAB) conversion, a label-free surface plasmon resonance (SPR) biosensor was proposed for highly sensitive and specific detection of HER2-positive exosomes. The exosomes were captured by the HER2 aptamer region of MAB immobilized on the chip surface, which enabled the exposure of the G-quadruplex DNA (G4 DNA) that could form peroxidase-like G4-hemin. In turn, the formed G4-hemin catalyzed the deposition of plentiful tyramine-coated gold nanoparticles (AuNPs-Ty) on the exosome membrane with the help of H₂O₂, generating a significantly enhanced SPR signal. In the reformative TSA system, the horseradish peroxidase (HRP) as a major component was replaced with nonenzymic G4-hemin, bypassing the defects of natural enzymes. Moreover, the dual-recognition of the surface proteins and lipid membrane of the desired exosomes endowed the sensing strategy with high specificity without the interruption of free proteins. As a result, this developed SPR biosensor exhibited a wide linear range from 1.0 × 10⁴ to 1.0 × 10⁷ particles/mL. Importantly, this strategy was able to accurately distinguish HER2-positive breast cancer patients from healthy individuals, exhibiting great potential clinical application.

Fluorescence immunoassay rapid detection of 2019-nCoV antibody based on the fluorescence resonance energy transfer between graphene quantum dots and Ag@Au nanoparticle

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has dramatically changed the world, is a highly contagious virus. The timely and accurate diagnosis of SARS-CoV-2 infections is vital for disease control and prevention. Here in this work, a fluorescence immunoassay was developed to detect 2019 Novel Coronavirus antibodies (2019-nCoV mAb). Fluorescent graphene quantum dots (GQDs) and Ag@Au nanoparticles (Ag@AuNPs) were successfully synthesized and characterized. Fluorescence resonance energy transfer (FRET) enables effective quenching of GQDs fluorescence by Ag@AuNPs. With the presence of 2019-nCoV mAb, a steric hindrance was observed between the Ag@AuNPs-NCP (2019-nCoV antigen) complex and GQDs, which reduced the FRET efficiency and restored the fluorescence of GQDs. The fluorescence enhancement efficiency has a satisfactory linear relationship with the logarithm of the 2019-nCoV mAb in a concentration range of 0.1 pg mL⁻¹–10 ng mL⁻¹, and the limit of detection was 50 fg mL⁻¹. The method has good selectivity. When the serum sample was spiked with 2019-nCoV mAb, the recovery rate was between 90.8% and 103.3%. The fluorescence immunosensor demonstrates the potential to complement the existing serological assays for COVID-19 diagnosis.