Development of a Nanostructured Platform for Identifying HER2-Heterogeneity of Breast Cancer Cells by Surface-Enhanced Raman Scattering

Label-free electrochemical cancer cell detection leveraging hemoglobin-encapsulated silver nanoclusters and Cu-MOF nanohybrids on a graphene-assisted dual-modal probe

Breast cancer detection at an early stage significantly increases the chances of successful treatment and survival. This study presents an electrochemical biosensor for detecting breast cancer cells, utilizing silver nanoclusters encapsulated by hemoglobin and Cu (II)-porphyrin-metal organic framework (BioMOF) in a graphene-incorporated nanohybrid probe. This Hb-AgNCs@MOF-G probe demonstrates high electrochemical activity, superior dispersity, porosity, and a large surface area for effective functionalization. Using a green ultrasonic-assisted stirring method, we fabricate ultra-small 5 nm particles that readily immobilize on a glassy carbon electrode, generating a detection signal when interacting with ferricyanide/ferrocyanide redox probes. The resulting immunosensor detects as few as 2 cells/mL using Electrochemical Impedance Spectroscopy (EIS) "signal on" and 16 cells/mL via Square Wave Voltammetry (SWV) "signal off", within a broad range of cell concentrations (102-5 × 104 cells/mL). Our designed sensor shows improved selectivity (5- to 16-fold) and robust detection in human blood with a recovery efficiency between 94.8-106% (EIS method) and 95.4-111% (SWV method). This sensor could streamline early cancer diagnosis and monitor patient treatment without requiring labelling or signal amplification. As a pioneering endeavor, we've utilized integrated porous MOFs with Hb-encapsulated silver nanoclusters in cancer detection, where these components collectively enhance the overall functionality.

Combined Morphological and Spectroscopic Diagnostic of HER2 Expression in Breast Cancer Tissues Based on Label-Free Surface-Enhanced Raman Scattering

Breast cancer is the most commonly diagnosed cancer type worldwide. Overexpression of human epidermal growth factor receptor 2 (HER2) is an important subtype of breast cancer and results in an increased risk of recurrence and metastasis in patients. At present, immunohistochemistry (IHC) is used to detect the expression of HER2 in breast cancer tissues as the golden standard. However, IHC has some shortcomings, such as large subjective impact, long time consumption, expensive reagents, etc. In this paper, a combined morphological and spectroscopic diagnostic method based on label-free surface-enhanced Raman scattering (SERS) for HER2 expression in breast cancer is proposed. It can not only quantitively detect HER2 expression in breast cancer tissues by spectroscopic measurements but also give morphological images reflecting the distribution of HER2 in tissues. The results show that the consistency between this method and IHC is 95% and achieves the annotation of tumor regions on tissue sections. This method is time-consuming, quantifiable, intuitive, scalable, and easy to understand. Combined with deep learning approaches, it is expected to promote the development of clinical detection and diagnosis technology for breast cancer and other cancers.

Diagnosing molecular subtypes of breast cancer by means of Raman spectroscopy

OBJECTIVES

Raman spectroscopy has been used to discriminate human breast cancer and its different tumor molecular subtypes (luminal A, luminal B, HER2, and triple-negative) from normal tissue in surgical specimens.

MATERIALS AND METHODS

Breast cancer and normal tissue samples from 31 patients were obtained by surgical resection and submitted for histopathology. Before anatomopathological processing, the samples had been submitted to Raman spectroscopy (830 nm, 25 mW excitation laser parameters). In total, 424 Raman spectra were obtained. Principal component analysis (PCA) was used in an exploratory analysis to unveil the compositional differences between the tumors and normal tissues. Discriminant models were developed to distinguish the different cancer subtypes by means of partial least squares (PLS) regression.

RESULTS

PCA vectors showed spectral features referred to the biochemical constitution of breast tissues, such as lipids, proteins, amino acids, and carotenoids, where lipids were decreased and proteins were increased in breast tumors. Despite the small spectral differences between the different subtypes of tumor and normal tissues, the discriminant model based on PLS was able to discriminate the spectra of the breast tumors from normal tissues with an accuracy of 97.3%, between luminal and nonluminal subtypes with an accuracy of 89.9%, between nontriple-negative and triple-negative with an accuracy of 94.7%, and each molecular subtype with an accuracy of 73.0%.

CONCLUSION

PCA could reveal the compositional difference between tumors and normal tissues, and PLS could discriminate the Raman spectra of breast tissues regarding the molecular subtypes of cancer, being a useful tool for cancer diagnosis.

A Comprehensive Review on Raman Spectroscopy Applications

Raman spectroscopy is a very powerful tool for material analysis, allowing for exploring the properties of a wide range of different materials. Since its discovery, Raman spectroscopy has been used to investigate several features of materials such carbonaceous and inorganic properties, providing useful information on their phases, functions, and defects. Furthermore, techniques such as surface and tip enhanced Raman spectroscopy have extended the field of application of Raman analysis to biological and analytical fields. Additionally, the robustness and versatility of Raman instrumentations represent a promising solution for performing on-field analysis for a wide range of materials. Recognizing the many hot applications of Raman spectroscopy, we herein overview the main and more recent applications for the investigation of a wide range of materials, such as carbonaceous and biological materials. We also provide a brief but exhaustive theoretical background of Raman spectroscopy, also providing deep insight into the analytical achievements.

Pattern recognition of breast tumor based on image dynamic enhancement technique

At present, the diagnosis of breast tumors is affected by many factors, which leads to certain errors in the diagnosis results. Therefore, it is necessary to improve the diagnosis in combination with the actual situation. This study used the whole tumor ADC histogram to identify the heterogeneous features of benign and malignant breast lesions and used the diffusion characteristics of the whole tumor to construct a diagnostic model suitable for breast tumor image feature recognition. Simultaneously, this study combined the actual situation to construct a system framework of image enhancement algorithm based on Retinex theory, and combined image processing algorithms to improve the model. In addition, this study converted the pixel data type of the grayscale image of each color channel into a double type and converted each color channel image into a logarithmic domain. Finally, in order to study the performance of the algorithm, this study designed a comparative test for performance analysis. The research shows that the algorithm has certain clinical effects and can provide theoretical reference for subsequent related research.

Cancer Cell Detection on the Surface of Top-Gated Monolayer Graphene via Raman Spectroscopy

A label-free biosensor is described based on the Raman spectroscopic signatures of monolayer graphene, which are modified in the compartment of cancer cells because of electron-phonon coupling in monolayer graphene. Specifically, the Raman spectra of electrostatically gated monolayer graphene on SiO₂/Si substrates, in the voltage range from 0 to 5 V, were studied in the absence and the presence of cancer cells. Density functional theory simulations afforded a correlation between cancer cells and the observed Raman spectra, through the regulation of the intensities of the G and 2D Raman vibrational modes with applied voltage. The C-H and N-H bonds of phenylalanine enabled the detection of this biosensing activity. Significantly, this detection can be carried out even in the absence of cancer cell-culturing steps.

Evaluation of aromatic amino acids as potential biomarkers in breast cancer by Raman spectroscopy analysis

The scope of the work undertaken in this paper was to explore the feasibility and reliability of using the Raman signature of aromatic amino acids as a marker in the detection of the presence of breast cancer and perhaps, even the prediction of cancer development in very early stages of cancer onset. To be able to assess this hypothesis, we collected most recent and relevant literature in which Raman spectroscopy was used as an analytical tool in the evaluation of breast cell lines and breast tissue, re-analyzed all the Raman spectra, and extracted all spectral bands from each spectrum that were indicative of aromatic amino acids. The criteria for the consideration of the various papers for this study, and hence, the inclusion of the data that they contained were two-fold: (1) The papers had to focus on the characterization of breast tissue with Raman spectroscopy, and (2) the spectra provided within these papers included the spectral range of 500-1200 cm-1, which constitutes the characteristic region for aromatic amino acid vibrational modes. After all the papers that satisfied these criteria were collected, the relevant spectra from each paper were extracted, processed, normalized. All data were then plotted without bias in order to decide whether there is a pattern that can shed light on a possible diagnostic classification. Remarkably, we have been able to demonstrate that cancerous breast tissues and cells decidedly exhibit overexpression of aromatic amino acids and that the difference between the extent of their presence in cancerous cells and healthy cells is overwhelming. On the basis of this analysis, we conclude that it is possible to use the signature Raman bands of aromatic amino acids as a biomarker for the detection, evaluation and diagnosis of breast cancer.

An overview of surface-enhanced Raman scattering substrates by pulsed laser deposition technique: fundamentals and applications

Metallic nanoparticles (NPs), as an efficient substrate for surface-enhanced Raman scattering (SERS), attract much interests because of their various shapes and sizes. The appropriate size and morphology of metallic NPs are critical to serve as the substrate for achieving an efficient SERS. Pulsed laser deposition (PLD) is one of the feasible physical methods employed to synthesize metallic NPs with controllable sizes and surface characteristics. It has been recognized to be a successful tool for the deposition of SERS substrates due to its good controllability and high reproducibility in the manufacture of metallic NPs. This review provides an overview about the recent advances for the preparation of SERS substrates by PLD technique. The influences of parameters on the sizes and morphologies of metallic NPs during the deposition processes in PLD technique including laser output parameters, gas medium, liquid medium, substrate temperature, and properties of 3D substrate are presented. The applications of SERS substrates produced by PLD in the environmental monitoring and biomedical analysis are summarized. This knowledge could serve as a guideline for the researchers in exploring further applications of PLD technique in the production of SERS substrate.

Surface-Enhanced Raman Spectroscopy Characterization of Breast Cell Phenotypes: Effect of Nanoparticle Geometry

The use of surface-enhanced Raman spectroscopy (SERS) to delineate between the breast epithelial cell lines MCF10A, SK-BR-3, and MDA-MB-231 is explored utilizing varied morphologies of gold nanoparticles. The nanoparticles studied had spherical, star-like, and quasi-fractal (nanocaltrop) morphologies and possessed varying degrees of surface inhomogeneity and complexity. The efficacy of Raman enhancement of these nanoparticles was a function of their size, their surface morphology, and the associated density of "hot spots," as well as their cellular uptake. The spherical and star-like nanoparticles provided strong signal enhancement that allowed for the discernment among the three cell phenotypes based solely on the acquired Raman spectra. The presence of overlapping Raman band spectral regions, as well as unique spectral bands, suggests that the underlying biological differences between these cells can be accessed without the need for tagging the nanoparticles or for specific cell targeting, demonstrating the potential ubiquity of this technique in imaging any cancer. This work provides clear evidence for the potential application of SERS as a tool for mapping cancerous lesions, possibly during surgery and under histopathological analysis.

An Electrochemical Sandwich Immunosensor for the Detection of HER2 using Antibody-Conjugated PbS Quantum Dot as a label

A facile electrochemical sandwich immunosensor for the detection of a breast cancer biomarker, the human epidermal growth factor receptor 2 (HER2), was designed, using lead sulfide quantum dots-conjugated secondary HER2 antibody (Ab2-PbS QDs) as a label. Using Ab2-PbS QDs in the development of electrochemical immunoassays leads to many advantages such as straightforward synthesis and well-defined stripping signal of Pb(II) through acid dissolution, which in turn yields better sensing performance for the sandwiched immunosensor. In the bioconjugation of PbS QDs, the available amine and hydroxyl groups from secondary anti-HER2 and capped PbS QDs were bound covalently together via carbonyldiimidazole (CDI) acting as a linker. In order to quantify the biomarker, SWV signal was obtained, where the Pb²⁺ ions after acid dissolution in HCl was detected. The plated mercury film SPCE was also detected in situ. Under optimal conditions, HER2 was detected in a linear range from 1-100 ng/mL with a limit of detection of 0.28 ng/mL. The measures of satisfactory recoveries were 91.3% to 104.3% for the spiked samples, displaying high selectivity. Therefore, this method can be applied to determine HER2 in human serum.

Bimetallic ZrHf-based metal-organic framework embedded with carbon dots: Ultra-sensitive platform for early diagnosis of HER2 and HER2-overexpressed living cancer cells

We report here a new bimetallic ZrHf metal-organic framework (ZrHf-MOF) embedded with abundant carbon dots (CDs) (denoted as CDs@ZrHf-MOF), which exhibits strong fluorescence and rich-amino-functionalization. The CDs@ZrHf-MOF can be applied as the scaffold for anchoring aptamer strands to determine human epidermal growth factor receptor-2 (HER2) and living HER2-overexpressed MCF-7 cells. The basic characterizations reveal that the CDs are embedded within the interior cavities of ZrHf-MOF without varying the nanostructure, leading to good biocompatibility, strong fluorescence, and high electrochemical activity of CDs@ZrHf-MOF. As compared with the pristine ZrHf-MOF, the CDs@ZrHf-MOF-based electrochemical aptasensor displays better sensing performances toward both HER-2 and MCF-7 cells, giving an extremely low detection limit of 19 fg mL^-1 (HER2 concentration range: 0.001-10 ng mL^-1) and 23 cell mL^-1 (cell concentration range: 1 × 10²~1 × 10⁵ cell mL^-1), with good selectivity, stability, reproducibility, and acceptable applicability. The proposed strategy for developing CDs@ZrHf-MOF-based aptasensor is promising for the early and sensitive detection of cancer markers and living cancer cells.

Design of Therapeutic Self-Assembled Monolayers of Thiolated Abiraterone

The aim of our work was to synthetize of a new analogue of abiraterone-thiolated abiraterone (HS-AB) and design a gold surface monolayer, bearing in mind recent advances in tuning monolayer structures and using them as efficient drug delivery systems. Therapeutic self-assembled monolayers (TSAMs) were prepared by chemically attaching HS-AB to gold surfaces. Their properties were studied by voltammetry and atomic force microscopy (AFM). A gold electrode with immobilized thioglycolic acid (HS-GA) was used for comparison. The surface concentration of HS-AB on the gold surface was 0.572 nmol/cm², determined from the area of the voltammetric reduction peaks (desorption process). The area per one molecule estimated from the voltammetry experiments was 0.291 nmol/cm². The capacity of thus prepared electrode was also tested. The calculated capacity for the HS-AB modified electrode is 2.90 μF/cm². The obtained value indicates that the monolayer on the gold electrode is quite well ordered and well-packed. AFM images show the formation of gold nanoparticles as a result of immersing the HS-AB modified gold electrode in an aqueous solution containing 1 mM HAuCl₄·3H₂O. These structures arise as a result of the interaction between the HS-AB compound adsorbed on the electrode and the AuCl₄^- ions. The voltammetric experiments also confirm the formation of gold structures with specific catalytic properties in the process of oxygen reduction.