Rapid and sensitive phenotypic marker detection on breast cancer cells using surface-enhanced Raman scattering (SERS) imaging

Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers

Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer. However, some patients develop resistance to this therapy; therefore, monitoring its efficacy is essential. Here, we describe a deep learning-assisted monitoring of trastuzumab efficacy based on a surface-enhanced Raman spectroscopy (SERS) immunoassay against HER2-overexpressing mouse urinary exosomes. Individual Raman reporters bearing the desired SERS tag and exosome capture substrate were prepared for the SERS immunoassay; SERS tag signals were collected to prepare deep learning training data. Using this deep learning algorithm, various complicated mixtures of SERS tags were successfully quantified and classified. Exosomal antigen levels of five types of cell-derived exosomes were determined using SERS-deep learning analysis and compared with those obtained via quantitative reverse transcription polymerase chain reaction and western blot analysis. Finally, drug efficacy was monitored via SERS-deep learning analysis using urinary exosomes from trastuzumab-treated mice. Use of this monitoring system should allow proactive responses to any treatment-resistant issues.

Designing SERS nanotags for profiling overexpressed surface markers on single cancer cells: A review

This review focuses on the chemical design and the use of Surface-Enhanced Raman Scattering (SERS)-active nanotags for measuring surface markers that can be overexpressed at the surface of single cancer cells. Indeed, providing analytical tools with true single-cell measurements capabilities is capital, especially since cancer research is increasingly leaning toward single-cell analysis, either to guide treatment decisions or to understand complex tumor behaviour including the single-cell heterogeneity and the appearance of treatment resistance. Over the past two decades, SERS nanotags have triggered significant interest in the scientific community owing their advantages over fluorescent tags, mainly because SERS nanotags resist photobleaching and exhibit sharper signal bands, which reduces possible spectral overlap and enables the discrimination between the SERS signals and the autofluorescence background from the sample itself. The extensive efforts invested in harnessing SERS nanotags for biomedical purposes, particularly in cancer research, highlight their potential as the next generation of optical labels for single-cell studies. The review unfolds in two main parts. The first part focuses on the structure of SERS nanotags, detailing their chemical composition and the role of each building block of the tags. The second part explores applications in measuring overexpressed surface markers on single-cells. The latter encompasses studies using single nanotags, multiplexed measurements, quantitative information extraction, monitoring treatment responses, and integrating phenotype measurements with SERS nanotags on single cells isolated from complex biological matrices. This comprehensive review anticipates SERS nanotags to persist as a pivotal technology in advancing single-cell analytical methods, particularly in the context of cancer research and personalized medicine.

iSERS: from nanotag design to protein assays and ex vivo imaging

Proteins are an eminently important class of ubiquitous biomacromolecules with diverse biological functions, and numerous techniques for their detection, quantification, and localisation have been developed. Many of these methods exploit the selectivity arising from molecular recognition of proteins/antigens by immunoglobulins. The combination of surface-enhanced Raman scattering (SERS) with such "immuno"-techniques to immuno-SERS (iSERS) is the central topic of this review, which is focused on colloidal SERS nanotags, i.e., molecularly functionalised noble metal nanoparticles conjugated to antibodies, for their use in protein assays and ex vivo imaging. After contrasting the fundamental differences between label-free SERS and iSERS, including a balanced description of the advantages and drawbacks of the latter, we describe the usual workflow of iSERS experiments. Milestones in the development of the iSERS technology are summarised from a historical perspective. By highlighting selected examples from the literature, we illustrate the conceptual progress that has been achieved in the fields of iSERS-based protein assays and ex vivo imaging. Finally, we attempt to predict what is necessary to fully exploit the transformative potential of the iSERS technology by stimulating the transition from research in academic labs into applications for the benefit of our society.

Combined SERS-Raman screening of HER2-overexpressing or silenced breast cancer cell lines

BACKGROUND

Breast cancer (BC) is a heterogeneous neoplasm characterized by several subtypes. One of the most aggressive with high metastasis rates presents overexpression of the human epidermal growth factor receptor 2 (HER2). A quantitative evaluation of HER2 levels is essential for a correct diagnosis, selection of the most appropriate therapeutic strategy and monitoring the response to therapy.

RESULTS

In this paper, we propose the synergistic use of SERS and Raman technologies for the identification of HER2 expressing cells and its accurate assessment. To this end, we selected SKBR3 and MDA-MB-468 breast cancer cell lines, which have the highest and lowest HER2 expression, respectively, and MCF10A, a non-tumorigenic cell line from normal breast epithelium for comparison. The combined approach provides a quantitative estimate of HER2 expression and visualization of its distribution on the membrane at single cell level, clearly identifying cancer cells. Moreover, it provides a more comprehensive picture of the investigated cells disclosing a metabolic signature represented by an elevated content of proteins and aromatic amino acids. We further support these data by silencing the HER2 gene in SKBR3 cells, using the RNA interference technology, generating stable clones further analysed with the same combined methodology. Significant changes in HER2 expression are detected at single cell level before and after HER2 silencing and the HER2 status correlates with variations of fatty acids and downstream signalling molecule contents in the context of the general metabolic rewiring occurring in cancer cells. Specifically, HER2 silencing does reduce the growth ability but not the lipid metabolism that, instead, increases, suggesting that higher fatty acids biosynthesis and metabolism can occur independently of the proliferating potential tied to HER2 overexpression.

CONCLUSIONS

Our results clearly demonstrate the efficacy of the combined SERS and Raman approach to definitely pose a correct diagnosis, further supported by the data obtained by the HER2 gene silencing. Furthermore, they pave the way to a new approach to monitor the efficacy of pharmacologic treatments with the aim to tailor personalized therapies and optimize patients' outcome.

SERS in 3D cell models: a powerful tool in cancer research

Unraveling the cellular and molecular mechanisms underlying tumoral processes is fundamental for the diagnosis and treatment of cancer. In this regard, three-dimensional (3D) cancer cell models more realistically mimic tumors compared to conventional 2D cell cultures and are more attractive for performing such studies. Nonetheless, the analysis of such architectures is challenging because most available techniques are destructive, resulting in the loss of biochemical information. On the contrary, surface-enhanced Raman spectroscopy (SERS) is a non-invasive analytical tool that can record the structural fingerprint of molecules present in complex biological environments. The implementation of SERS in 3D cancer models can be leveraged to track therapeutics, the production of cancer-related metabolites, different signaling and communication pathways, and to image the different cellular components and structural features. In this review, we highlight recent progress in the use of SERS for the evaluation of cancer diagnosis and therapy in 3D tumoral models. We outline strategies for the delivery and design of SERS tags and shed light on the possibilities this technique offers for studying different cellular processes, through either biosensing or bioimaging modalities. Finally, we address current challenges and future directions, such as overcoming the limitations of SERS and the need for the development of user-friendly and robust data analysis methods. Continued development of SERS 3D bioimaging and biosensing systems, techniques, and analytical strategies, can provide significant contributions for early disease detection, novel cancer therapies, and the realization of patient-tailored medicine.

Multimodal Imaging of Pancreatic Cancer Microenvironment in Response to an Antiglycolytic Drug

Lipid metabolism and glycolysis play crucial roles in the progression and metastasis of cancer, and the use of 3-bromopyruvate (3-BP) as an antiglycolytic agent has shown promise in killing pancreatic cancer cells. However, developing an effective strategy to avoid chemoresistance requires the ability to probe the interaction of cancer drugs with complex tumor-associated microenvironments (TAMs). Unfortunately, no robust and multiplexed molecular imaging technology is currently available to analyze TAMs. In this study, the simultaneous profiling of three protein biomarkers using SERS nanotags and antibody-functionalized nanoparticles in a syngeneic mouse model of pancreatic cancer (PC) is demonstrated. This allows for comprehensive information about biomarkers and TAM alterations before and after treatment. These multimodal imaging techniques include surface-enhanced Raman spectroscopy (SERS), immunohistochemistry (IHC), polarized light microscopy, second harmonic generation (SHG) microscopy, fluorescence lifetime imaging microscopy (FLIM), and untargeted liquid chromatography and mass spectrometry (LC-MS) analysis. The study reveals the efficacy of 3-BP in treating pancreatic cancer and identifies drug treatment-induced lipid species remodeling and associated pathways through bioinformatics analysis.

Impact of Nanomedicine in Women's Metastatic Breast Cancer

Metastatic breast cancer is responsible for 90% of mortalities among women suffering from various types of breast cancers. Traditional cancer treatments such as chemotherapy and radiation therapy can cause significant side effects and may not be effective in many cases. However, recent advances in nanomedicine have shown great promise in the treatment of metastatic breast cancer. For example, nanomedicine demonstrated robust capacity in detection of metastatic cancers at early stages (i.e., before the metastatic cells leave the initial tumor site), which gives clinicians a timely option to change their treatment process (for example, instead of endocrine therapy they may use chemotherapy). Here recent advances in nanomedicine technology in the identification and treatment of metastatic breast cancers are reviewed.

SERS Signature of SARS-CoV-2 in Saliva and Nasopharyngeal Swabs: Towards Perspective COVID-19 Point-of-Care Diagnostics

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(-) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value-RMSEC and RMSECV below 0.3 and R²_cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease.

A clinically feasible diagnostic spectro-histology built on SERS-nanotags for multiplex detection and grading of breast cancer biomarkers

Simultaneous detection of multiple biomarkers is always an obstacle in immunohistochemical (IHC) analysis. Herein, a straightforward spectroscopy-driven histopathologic approach has emerged as a paradigm of Raman-label (RL) nanoparticle probes for multiplex recognition of pertinent biomarkers in heterogeneous breast cancer. The nanoprobes are constructed by sequential incorporation of signature RL and target specific antibodies on gold nanoparticles, which are coined as Raman-Label surface enhanced Raman scattering (RL-SERS)-nanotags to evaluate simultaneous recognition of clinically relevant breast cancer biomarkers i.e., estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor2 (HER2). As a foot-step assessment, breast cancer cell lines having varied expression levels of the triple biomarkers are investigated. Subsequently, the optimized detection strategy using RL-SERS-nanotags is subjected to clinically confirmed, retrospective formalin-fixed paraffin embedded (FFPE) breast cancer tissue samples to fish out the quick response of singleplex, duplex as well as triplex biomarkers in a single tissue specimen by adopting a ratiometric signature RL-SERS analysis which enabled to minimize the false negative and positive results. Significantly, sensitivity and specificity of 95% and 92% for singleplex, 88% and 85% for duplex, and 75% and 67% for triplex biomarker has been achieved by assessing specific Raman fingerprints of the respective SERS-tags. Furthermore, a semi-quantitative evaluation of HER2 grading between 4+/2+/1+ tissue samples was also achieved by the Raman intensity profiling of the SERS-tag, which is fully in agreement with the expensive fluorescent in situ hybridization analysis. Additionally, the practical diagnostic applicability of RL-SERS-tags has been achieved by large area SERS imaging of areas covering 0.5-5 mm2 within 45 min. These findings unveil an accurate, inexpensive and multiplex diagnostic modality envisaging large-scale multi-centric clinical validation.

Design and Synthesis of SERS Materials for In Vivo Molecular Imaging and Biosensing

Surface-enhanced Raman scattering (SERS) is a feasible and ultra-sensitive method for biomedical imaging and disease diagnosis. SERS is widely applied to in vivo imaging due to the development of functional nanoparticles encoded by Raman active molecules (SERS nanoprobes) and improvements in instruments. Herein, the recent developments in SERS active materials and their in vivo imaging and biosensing applications are overviewed. Various SERS substrates that have been successfully used for in vivo imaging are described. Then, the applications of SERS imaging in cancer detection and in vivo intraoperative guidance are summarized. The role of highly sensitive SERS biosensors in guiding the detection and prevention of diseases is discussed in detail. Moreover, its role in the identification and resection of microtumors and as a diagnostic and therapeutic platform is also reviewed. Finally, the progress and challenges associated with SERS active materials, equipment, and clinical translation are described. The present evidence suggests that SERS could be applied in clinical practice in the future.

Integrated SERS-Vertical Flow Biosensor Enabling Multiplexed Quantitative Profiling of Serological Exosomal Proteins in Patients for Accurate Breast Cancer Subtyping

Protein profiles of exosomes (EXOs) in clinical samples of cancer patients have become a promising diagnostic and therapeutic biomarker. However, simultaneous quantitative analysis of multiple exosomal proteins of interest remains challenging. To address the unmet need, we develop a paper-based surface-enhanced Raman spectroscopy (SERS)-vertical flow biosensor, named iREX (integrated Raman spectroscopic EXO) biosensor, for multiplexed quantitative profiling of exosomal proteins in clinical serum samples of patients. Utilizing this iREX biosensor, we are able to quantitatively profile MUC1, HER2 and CEA in EXO samples derived from various breast cancer cell subtypes. The results show discriminative expression profiles of the three exosomal proteins in these cell subtypes, which allows for accurate diagnosis and molecular subtyping of breast cancer. We further validate the clinical utility of the iREX biosensor for simultaneous quantitative analysis of MUC1, HER2 and CEA in patient's blood serums, thereby aiding in noninvasive breast cancer subtyping and longitudinal treatment monitoring. Our iREX biosensor integrating the SERS detection in a vertical flow diagnostic device offers great advantages of high sensitivity, molecular specificity, powerful multiplexing capability, and high diagnostic accuracy. We believe that the iREX biosensor could be a promising clinical tool for comprehensive analysis of exosomal proteins in clinical samples for personalized diagnosis and precise management of breast cancer.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

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.

Nanosupernova: a new anisotropic nanostructure for SERS

Gold and/or silver nanostars are interesting anisotropic nanoparticles that have been used in surface-enhanced Raman scattering (SERS). In particular SERS nanotags consisting of gold nanostars and Raman reporter molecules have been widely utilised in biosensing and bioimaging. To improve the SERS activity of gold/silver nanostars, this paper details the development of a simple synthesis method that results in the formation of quasi-spherical SERS nanotags and larger highly anisotropic nanoparticles with a novel structure, which we have designated nanosupernova. The resulting SERS nanotags and nanosupernova contain gold/silver nanostars at their core, a self-assembled monolayer of Raman reporter molecules, and a final silver coating. The silver coating is the essential step responsible for the formation of the two types of particles, with incubation time, and type of Raman reporter molecule, the defining factor as to which forms. We discovered that the Raman reporter molecule, 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB), plays a crucial role in controlling the morphology of nanosupernova. We believe the larger highly anisotropic nanoparticles will open new applications in material sciences and in optical and electronic devices in the future.

Nanomaterials meet surface-enhanced Raman scattering towards enhanced clinical diagnosis: a review

Surface-enhanced Raman scattering (SERS) is a very promising tool for the direct detection of biomarkers for the diagnosis of i.e., cancer and pathogens. Yet, current SERS strategies are hampered by non-specific interactions with co-existing substances in the biological matrices and the difficulties of obtaining molecular fingerprint information from the complex vibrational spectrum. Raman signal enhancement is necessary, along with convenient surface modification and machine-based learning to address the former issues. This review aims to describe recent advances and prospects in SERS-based approaches for cancer and pathogens diagnosis. First, direct SERS strategies for key biomarker sensing, including the use of substrates such as plasmonic, semiconductor structures, and 3D order nanostructures for signal enhancement will be discussed. Secondly, we will illustrate recent advances for indirect diagnosis using active nanomaterials, Raman reporters, and specific capture elements as SERS tags. Thirdly, critical challenges for translating the potential of the SERS sensing techniques into clinical applications via machine learning and portable instrumentation will be described. The unique nature and integrated sensing capabilities of SERS provide great promise for early cancer diagnosis or fast pathogens detection, reducing sanitary costs but most importantly allowing disease prevention and decreasing mortality rates.

An Enzymatic Multiplexed Impedimetric Sensor Based on α-MnO2/GQD Nano-Composite for the Detection of Diabetes and Diabetic Foot Ulcer Using Micro-Fluidic Platform

Diabetes is widely considered as a silent killer which affects the internal organs and ultimately has drastic impacts on our day-to-day activities. One of the fatal outcomes of diabetes is diabetic foot ulcer (DFU); which, when becomes chronic, may lead to amputation. The incorporation of nanotechnology in developing bio-sensors enables the detection of desired biomarkers, which in our study are glucose and L-tyrosine; which gets elevated in patients suffering from diabetes and DFUs, respectively. Herein, we report the development of an enzymatic impedimetric sensor for the multi-detection of these biomarkers using an electrochemical paper-based analytical device (µ-EPADs). The structure consists of two working electrodes and a counter electrode. One working electrode is modified with α-MnO2-GQD/tyrosinase hybrid to aid L-tyrosine detection, while the other electrode is coated with α-MnO2-GQD/glucose oxidase hybrid for glucose monitoring. Electrochemical impedance spectroscopy has been employed for the quantification of glucose and L-tyrosine, within a concentration range of 50–800 mg/dL and 1–500 µmol/L, respectively, using a sample volume of approximately 200 µL. The impedance response exhibited a linear relationship over the analyte concentration range with detection limits of ~58 mg/dL and ~0.3 µmol/L for glucose and tyrosine respectively, with shelf life ~1 month. The sensing strategy was also translated to Arduino-based device applications by interfacing the µ-EPADs with miniaturized electronics.

From Raman to SESORRS: moving deeper into cancer detection and treatment monitoring

Raman spectroscopy is a non-invasive technique that allows specific chemical information to be obtained from various types of sample. The detailed molecular information that is present in Raman spectra permits monitoring of biochemical changes that occur in diseases, such as cancer, and can be used for the early detection and diagnosis of the disease, for monitoring treatment, and to distinguish between cancerous and non-cancerous biological samples. Several techniques have been developed to enhance the capabilities of Raman spectroscopy by improving detection sensitivity, reducing imaging times and increasing the potential applicability for in vivo analysis. The different Raman techniques each have their own advantages that can accommodate the alternative detection formats, allowing the techniques to be applied in several ways for the detection and diagnosis of cancer. This feature article discusses the various forms of Raman spectroscopy, how they have been applied for cancer detection, and the adaptation of the techniques towards their use for in vivo cancer detection and in clinical diagnostics. Despite the advances in Raman spectroscopy, the clinical application of the technique is still limited and certain challenges must be overcome to enable clinical translation. We provide an outlook on the future of the techniques in this area and what we believe is required to allow the potential of Raman spectroscopy to be achieved for clinical cancer diagnostics.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

A SERS-Active Electrospun Polymer Mesh for Spatially Localized pH Measurements of the Cellular Microenvironment

Extracellular pH (pHe) is an important chemical factor in many cellular processes and disease pathologies. The routine sampling of pHe in vitro could lead to innovative advances in therapeutics. To this end, we have fabricated a novel gold-coated polymer mesh, which facilitates the real-time measurement of pHe via surface-enhanced Raman scattering (SERS). In this proof of concept study, we apply our SERS sensor to measure metabolically induced changes in the pHe of carcinoma-derived cell line HepG2/C3A. We demonstrate that gold-coated polyurethane electrospun nanofibers (AuNF) have strong and reproducible SERS spectra of surface-adsorbed analytes. By functionalizing AuNF with pH-responsive reporter 4-mercaptobenzoic acid (MBA), we have developed an accurate pH SERS sensor for the extracellular microenvironment. We cultured HepG2/C3A on the surface of MBA-AuNF and measured an acidic shift in pHe at the cell-fiber interface. Following exposure to staurosporine, an apoptosis-inducing drug, we observed changes in the HepG2/C3A cellular morphology indicative of controlled cell death, and detected an increase in the pHe of HepG2/C3A. These results demonstrate how subtle changes in pHe, induced by the metabolic activity of cells, can be measured with our novel SERS sensor MBA-AuNF. The excellent pH measurement performance of MBA-AuNF provides a unique platform to study extracellular pH on the microscale and will help to deepen our understanding of pHe in disease pathology.

Simultaneous single-cell phenotype analysis of hepatocellular carcinoma CTCs using a SERS-aptamer based microfluidic chip

Hepatocellular carcinoma (HCC) is a harmful malady that truly debilitates human health, and hence it is of significance to isolate and on-line profile the phenotype of HCC cells for further diagnosis and therapy. We developed a novel strategy for efficient capture and in situ heterogeneous phenotype analysis of circulating tumor cells (CTCs) at the single-cell level based on surface-enhanced Raman scattering (SERS) fingerprint characteristics. Herein, a new microfluidic chip with lantern-like bypass structure was designed to capture CTCs by their large size from whole blood. Furthermore, two types of SERS-aptamer nanotags were fabricated, realizing spectral recognition of single CTCs in accordance with the surface membrane protein expression. Up to 84% of CTCs with a purity of 95% were captured from whole blood samples using the present SERS-aptamer based microfluidic chip at 20 μL min^-1. The results showed that the proposed strategy can successfully identify HCC cell subtypes by SERS measurements, which was related to the clinical surface biomarkers. This may open a new avenue for serving as a powerful tool of cancer diagnosis and prognosis evaluation.

Characterisation of estrogen receptor alpha (ERα) expression in breast cancer cells and effect of drug treatment using targeted nanoparticles and SERS

The detection and identification of estrogen receptor alpha (ERα), one of the main biomarkers in breast cancer, is crucial for the clinical diagnosis and therapy of the disease. Here, we use a non-destructive approach for detecting and localising ERα expression at the single cell level using surface enhanced Raman spectroscopy (SERS) combined with functionalised gold nanoparticles (AuNPs). Antibody functionalised nanotags (ERα-AuNPs) showed excellent biocompatibility and enabled the spatial and temporal understanding of ERα location in breast cancer cell lines with different ERα expression status. Additionally, we developed an approach based on the percentage area of SERS response to qualitatively measure expression level in ERα positive (ERα+) breast cancer cells. Specifically, the calculation of relative SERS response demonstrated that MCF-7 cells (ERα+) exhibited higher nanotag accumulation resulting in a 4.2-times increase in SERS signal area in comparison to SKBR-3 cells (ERα-). These results confirmed the strong targeting effect of ERα-AuNPs towards the ERα receptor. The functionalised ERα-AuNP nanotags were also used to investigate the activity of fulvestrant, the first-in-class approved selective estrogen receptor degrader (SERD). SERS mapping confirmed that ERα degradation occurred after fulvestrant treatment since a weaker SERS signal, and hence accumulation of nanotags, was observed in MCF-7 cells treated with fulvestrant. Most importantly, a correlation coefficient of 0.9 between the SERS response and the ERα expression level, obtained by western blot, was calculated. These results confirmed the strong relationship between the two approaches and open up the possibilities of using SERS as a tool for the estimation of ERα expression levels, without the requirement of destructive and time-consuming techniques. Therefore, the potential of using SERS as a rapid and sensitive method to understand the activity of SERDs in breast cancer is demonstrated.

Identifying functioning and nonfunctioning adrenal tumors based on blood serum surface-enhanced Raman spectroscopy

Adrenal tumors are common tumors in urology and they can be further divided into functioning and nonfunctioning tumors according to whether there is uncommon endocrine function. In clinical practice, the early identification and accurate assessment of adrenal tumors are essential for the guidance of subsequent treatment. However, a nonfunctioning adrenal tumor often lacks obvious clinical symptoms, making it difficult to be timely and precisely diagnosed by conventional examinations. Therefore, a rapid and accurate method for identifying the functioning and nonfunctioning adrenal tumors is urgently required to achieve precise treatment of adrenal tumors. In this study, surface-enhanced Raman spectroscopy was investigated as a diagnostic tool to identify the blood serum samples from healthy volunteers as well as the patients with functioning and nonfunctioning adrenal tumors. Based on the SERS peak analysis, abnormal glycolysis, DNA/RNA, and amino acid metabolites were found to be potential biomarkers for identifying patients with adrenal tumors, while metabolites related to disordered protein catabolism and excessive hormone secretion were expected to further differentiate functioning adrenal tumors from nonfunctioning adrenal tumors. In addition, principal component analysis followed by support vector machine (PCA-SVM) was further applied on those serum SERS measurements, and the classification accuracies of 96.8% and 84.5% were achieved for differentiating healthy group versus adrenal tumor group and functioning adrenal tumor group versus nonfunctioning adrenal tumor group, respectively. The results have demonstrated the prodigious potential of precise adrenal tumor diagnosis by using the blood serum surface-enhanced Raman spectroscopy technique.

Stable and scalable SERS tags conjugated with neutravidin for the detection of fibroblast activation protein (FAP) in primary fibroblasts

SERS tags are a class of nanoparticles with great potential in advanced imaging experiments. The preparation of SERS tags however is complex, as they suffer from the high variability of the SERS signals observed even at the slightest sign of aggregation. Here, we developed a method for the preparation of SERS tags based on the use of gold nanostars conjugated with neutravidin. The SERS tags here obtained are extremely stable in all biological buffers commonly employed and can be prepared at a relatively large scale in very mild conditions. The obtained SERS tags have been used to monitor the expression of fibroblast activation protein alpha (FAP) on the membrane of primary fibroblasts obtained from patients affected by Crohn's disease. The SERS tags allowed the unambiguous identification of FAP on the surface of cells thus suggesting the feasibility of semi-quantitative analysis of the target protein. Moreover, the use of the neutravidin-biotin system allows to apply the SERS tags for any other marker detection, for example, different cancer cell types, simply by changing the biotinylated antibody chosen in the analysis.

In Search of Spectroscopic Signatures of Periodontitis: A SERS-Based Magnetomicrofluidic Sensor for Detection of Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans

Recently, Porphyromonas gingivalis, the keystone pathogen implicated in the development of gum disease (periodontitis), was detected in the brains of Alzheimer’s disease patients, opening up a fascinating possibility that it is also involved in the pathobiology of this neurodegenerative illness. To verify this hypothesis, an unbiased, specific, and sensitive method to detect this pathogen in biological specimens is needed. To this end, our interdisciplinary studies demonstrate that P. gingivalis can be easily identified by surface-enhanced Raman scattering (SERS). Moreover, based on SERS measurements, P. gingivalis can be distinguished from another common periodontal pathogen, Aggregatibacter actinomycetemcomitans, and also from ubiquitous oral Streptococcus spp. The results were confirmed by principal component analysis (PCA). Furthermore, we have shown that different P. gingivalis and A. actinomycetemcomitans strains can easily adsorb to silver-coated magnetic nanoparticles (Fe₂O₃@AgNPs). Thus, it is possible to magnetically separate investigated bacteria from other components of a specimen using the microfluidic chip. To obtain additional enhancement of the Raman signal, the NPs adsorbed to bacterial cells were magnetically attracted to the Si/Ag SERS platform. Afterward, the SERS spectra could be recorded. Such a time-saving procedure can be very helpful in rapid medical diagnostics and thus in starting the appropriate pharmacological therapy to prevent the development of periodontitis and associated comorbidities, e.g., Alzheimerʼs disease.

Detection of Estrogen Receptor Alpha and Assessment of Fulvestrant Activity in MCF-7 Tumor Spheroids Using Microfluidics and SERS

Breast cancer is one of the leading causes of cancer death in women. Novel in vitro tools that integrate three-dimensional (3D) tumor models with highly sensitive chemical reporters can provide useful information to aid biological characterization of cancer phenotype and understanding of drug activity. The combination of surface-enhanced Raman scattering (SERS) techniques with microfluidic technologies offers new opportunities for highly selective, specific, and multiplexed nanoparticle-based assays. Here, we explored the use of functionalized nanoparticles for the detection of estrogen receptor alpha (ERα) expression in a 3D tumor model, using the ERα-positive human breast cancer cell line MCF-7. This approach was used to compare targeted versus nontargeted nanoparticle interactions with the tumor model to better understand whether targeted nanotags are required to efficiently target ERα. Mixtures of targeted anti-ERα antibody-functionalized nanotags (ERα-AuNPs) and nontargeted (against ERα) anti-human epidermal growth factor receptor 2 (HER2) antibody-functionalized nanotags (HER2-AuNPs), with different Raman reporters with a similar SERS signal intensity, were incubated with MCF-7 spheroids in microfluidic devices and spectroscopically analyzed using SERS. MCF-7 cells express high levels of ERα and no detectable levels of HER2. 2D and 3D SERS measurements confirmed the strong targeting effect of ERα-AuNP nanotags to the MCF-7 spheroids in contrast to HER2-AuNPs (63% signal reduction). Moreover, 3D SERS measurements confirmed the differentiation between the targeted and the nontargeted nanotags. Finally, we demonstrated how nanotag uptake by MCF-7 spheroids was affected by the drug fulvestrant, the first-in-class approved selective estrogen receptor degrader (SERD). These results illustrate the potential of using SERS and microfluidics as a powerful in vitro platform for the characterization of 3D tumor models and the investigation of SERD activity.

Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

The epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600-1800 cm-1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey's multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.

Rapid on-site identification of pesticide residues in tea by one-dimensional convolutional neural network coupled with surface-enhanced Raman scattering

In this study, a novel analytical approach is proposed for the identification of pesticide residues in tea by combining surface-enhanced Raman scattering (SERS) with a deep learning method one-dimensional convolutional neural network (1D CNN). First, a handheld Raman spectrometer was used for rapid on-site collection of SERS spectra. Second, the collected SERS spectra were augmented by a data augmentation strategy. Third, based on the augmented SERS spectra, the 1D CNN models were established on the cloud server, and then the trained 1D CNN models were used for subsequent pesticide residue identification analysis. In addition, to investigate the identification performance of the 1D CNN method, four conventional identification methods, including partial least square-discriminant analysis (PLS-DA), k-nearest neighbour (k-NN), support vector machine (SVM) and random forest (RF), were also developed on the basis of the augmented SERS spectra and applied for pesticide residue identification analysis. The comparative studies show that the 1D CNN method possesses better identification accuracy, stability and sensitivity than the other four conventional identification methods. In conclusion, the proposed novel analytical approach that exploits the advantages of SERS and a deep learning method (1D CNN) is a promising method for rapid on-site identification of pesticide residues in tea.

SERS-based immunoassay and degradation of CA19-9 mediated by gold nanowires anchored magnetic-semiconductor nanocomposites

Here, straight upward Au nanowires (NWs) were successfully grown onto Fe₃O₄@TiO₂ matrix through a seed-mediated strategy to intensively improve its photocatalysis and SERS performances, facilitating a peculiar recyclable surface-enhanced Raman spectroscopy (SERS)-based immunoassay of CA19-9 in liquid form based on visible light irradiation. Such immunoassay was also supported by a smart heterobifunctional cross-linking agent-mediated probe of anti-CA19-9/4-MBA without metal nanoparticles. A low limit of detection of 5.65 × 10^-4 IUmL^-1 and a wide linear range from 1000 to 0.001 IUmL^-1 were demonstrated through repeated constructing the sandwich immunostructure with only one batch of nanocomposites. Moreover, the actual levels of CA19-9 for colorectal cancer patients were readily measured by the recyclable immunoassay, the results of which are principally consistent with the conventional CLIA detection. Thus, such a green strategy of visible light-induced recyclable immunoassay could be expected to have a potential practicability in the clinical diagnoses of cancer.

Structural control and biomedical applications of plasmonic hollow gold nanospheres: A mini review

Hollow gold nanospheres (HGNs) are core/shell structures with a dielectric material core, usually composed of solvent, and a gold metal shell. Such structures have two metal/dielectric interfaces to allow interaction between the gold metal with the interior and external dielectric environment. Upon illumination by light, HGNs exhibit unique surface plasmon resonance (SPR) properties compared to solid gold nanoparticles. Their SPR absorption/scattering can be tuned by changing their diameter, shell thicknesses, and surface morphologies. In addition to the low toxicity, easy functionalization, resistance to photobleaching, and sensitivity to changes in surrounding medium of gold, the enhanced surface-to-volume ratio and tunable SPR of HGNs make them highly attractive for different applications in the fields of sensing, therapy, and theranostics. In this article, we review recent progress on the synthesis and structural control of HGNs and applications of their SPR properties in biomedical sensing and theranostics. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > in vitro Nanoparticle-Based Sensing Diagnostic Tools > in vivo Nanodiagnostics and Imaging.

Multiplexed Nanobiosensors: Current Trends in Early Diagnostics

The ever-growing demand for fast, cheap, and reliable diagnostic tools for personalised medicine is encouraging scientists to improve existing technology platforms and to create new methods for the detection and quantification of biomarkers of clinical significance. Simultaneous detection of multiple analytes allows more accurate assessment of changes in biomarker expression and offers the possibility of disease diagnosis at the earliest stages. The concept of multiplexing, where multiple analytes can be detected in a single sample, can be tackled using several types of nanomaterial-based biosensors. Quantum dots are widely used photoluminescent nanoparticles and represent one of the most frequent choices for different multiplex systems. However, nanoparticles that incorporate gold, silver, and rare earth metals with their unique optical properties are an emerging perspective in the multiplexing field. In this review, we summarise progress in various nanoparticle applications for multiplexed biomarkers.

SERS imaging-based aptasensor for ultrasensitive and reproducible detection of influenza virus A

Surface-enhanced Raman scattering (SERS)-based aptasensors display high sensitivity for influenza A/H1N1 virus detection but improved signal reproducibility is required. Therefore, in this study, we fabricated a three-dimensional (3D) nano-popcorn plasmonic substrate using the surface energy difference between a perfluorodecanethiol (PFDT) spacer and the Au layer. This energy difference led to Au nanoparticle self-assembly; neighboring nanoparticles then created multiple hotspots on the substrate. The localized surface plasmon effects at the hot spots dramatically enhanced the incident field. Quantitative evaluation of A/H1N1 virus was achieved using the decrease of Raman peak intensity resulting from the release of Cy3-labeled aptamer DNAs from nano-popcorn substrate surfaces via the interaction between the aptamer DNA and A/H1N1 virus. The use of a Raman imaging technique involving the fast mapping of all pixel points enabled the reproducible quantification of A/H1N1 virus on nano-popcorn substrates. Average ensemble effects obtained by averaging all randomly distributed hot spots mapped on the substrate made it possible to reliably quantify target viruses. The SERS-based imaging aptasensor platform proposed in this work overcomes the issues inherent in conventional approaches (the time-consuming and labor-intensiveness of RT-PCR and low sensitivity and quantitative analysis limits of lateral flow assay kits). Our SERS-based assay for detecting A/H1N1 virus had an estimated limit of detection of 97 PFU mL-1 (approximately three orders of magnitude more sensitive than that determined by the enzyme-linked immunosorbent assay) and the approximate assay time was estimated to be 20 min. Thus, this approach provides an ultrasensitive, reliable platform for detecting viral pathogens.

Rapid and label-free identification of different cancer types based on surface-enhanced Raman scattering profiles and multivariate statistical analysis

Rapid detection and classification of cancer cells with label-free and non-destructive methods are helpful for rapid screening of cancer patients in clinical settings. Here, surface-enhanced Raman scattering (SERS) was used for rapid, unlabeled, and non-destructive detection of seven different cell types, including human cancer cells and non-tumorous cells. Au nanoparticles were used as enhanced substrates and directly added to cell surfaces. The single cellular SERS signals could be easily and stably collected in several minutes, and the cells maintained structural integrity over one hour. Different types of cells had unique Raman phenotypes. By applying multivariate statistical analysis to the Raman phenotypes, the cancer cells and non-tumorous cells were accurately identified. The high sensitivity enabled this method to discriminate subtle molecular changes in different cell types, and the accuracy reached 81.2% with principal components analysis and linear discriminant analysis. The technique provided a rapid, unlabeled, and non-destructive method for the detection and identification of various cancer types.

6-Color/1-Target Immuno-SERS Microscopy on the Same Single Cancer Cell

There is an urgent clinical need for multicolor imaging of single cancer cells (no ensemble averaging) for identifying heterogenous expression of predictive biomarkers. Specifically, the comprehensive characterization of single disseminated tumor cells (sDTCs) responsible for metastatic relapse is the key to personalized therapy for patients. Current bioimaging methods lack the necessary multicolor capacity and suffer from background/autofluorescence. Both these central limitations can be overcome by immuno-SERS microscopy using SERS nanotags conjugated to antibodies. Here, we demonstrate the proof of concept for 6-color iSERS microscopy on the same single cancer cell. Human epidermal growth factor receptor 2 (HER2), the most prominent breast cancer marker, is localized on the membrane of single SkBr-3 cells, which overexpress HER2 and are an accepted model for sDTCs in breast cancer. This work paves the way for future multicolor/multitarget imaging for characterizing heterogeneous protein expression at the single-cell level.

Investigation of cellular uptake mechanism of functionalised gold nanoparticles into breast cancer using SERS

Gold nanoparticles (AuNPs) are widely used in various applications such as cancer imaging and drug delivery. The functionalisation of AuNPs has been shown to affect their cellular internalisation, accumulation and targeting efficiency. The mechanism of cellular uptake of functionalised AuNPs by different cancer cells is not well understood. Therefore, a detailed understanding of the molecular processes is necessary to improve AuNPs for their selective uptake and fate in specific cellular systems. This knowledge can greatly help in designing nanotags with higher cellular uptake for more selective and specific targeting capabilities with less off-target effects. Here, we demonstrate for the first time a straightforward and non-destructive 3D surface enhanced Raman spectroscopy (SERS) imaging approach to track the cellular uptake and localisation of AuNPs functionalised with an anti-ERα (estrogen receptor alpha) antibody in MCF-7 ERα-positive human breast cancer cells under different conditions including temperature and dynamin inhibition. 3D SERS enabled information rich monitoring of the intracellular internalisation of the SERS nanotags. It was found that ERα-AuNPs were internalised by MCF-7 cells in a temperature-dependent manner suggesting an active endocytosis-dependent mechanism. 3D SERS cell mapping also indicated that the nanotags entered MCF-7 cells using dynamin dependent endocytosis, since dynamin inhibition resulted in the SERS signal being obtained from, or close to, the cell surface rather than inside the cells. Finally, ERα-AuNPs were found to enter MCF-7 cells using an ERα receptor-mediated endocytosis process. This study addresses the role of functionalisation of SERS nanotags in biological environments and highlights the benefits of using 3D SERS for the investigation of cellular uptake processes.

Compact conical beam shaper and freeform segmented reflector for SERS analysis

We present a Raman spectroscopy setup containing a conical beam shaper in combination with a freeform segmented reflector for surface enhanced Raman scattering (SERS) analysis. The freeform segmented reflector and the conical beam shaper are designed by numerical approaches and fabricated by means of ultra-precision diamond tooling. The segmented reflector has a numerical aperture of 0.984 and a working distance of 1mm for SERS measurements. We perform systematic simulations using non-sequential ray tracing to assess the detecting abilities of the designed SERS-based system. We implement a proof-of-concept setup and demonstrate the confocal behavior by measuring the SERS signal of 10µM rhodamine B solution. The experimental results agree well with the simulations concerning the misalignment tolerances of the beam shaper with respect to the segmented reflector and the misalignment tolerances of the collecting fiber. In addition, we conduct benchmark SERS measurements by using a 60× objective lens with a numerical aperture of 0.85. We find that the main Raman intensity of rhodamine B at 1502 cm^-1 obtained by our segmented reflector working together with the conical beam shaper is approximately 30% higher compared to the commercial objective lens.

Nanoplasmonic sensor for foodborne pathogens detection. Towards development of ISO-SERS methodology for taxonomic affiliation of Campylobacter spp

According to EU summary report on zoonoses, zoonotic agents and food-borne outbreaks in 2017, Campylobacter was the most commonly reported gastrointestinal bacterial pathogen in humans in the EU. Unfortunately, the standard methods for the detection of thermotolerant Campylobacter spp. in foods are time-consuming. Additionally, the qualified staff is obligatory. For this reason, new methods of pathogens detection are needed. The present work demonstrates that surface-enhanced Raman scattering (SERS) is a reliable and fast method for detection of Campylobacter spp. in food samples. The proposed method combines the SERS measurements performed on an Ag/Si substrate with two initial steps of the ISO standard procedure. Finally, the principal component analysis (PCA) allows for statistical classification of the studied bacteria. By applying the proposed ISO-SERS-PCA method in the case of Campylobacter bacteria the total detection time may be reduced from 7 to 8 days required by ISO method to 3 to 4 days in the case of SERS-based approach.

SERS using two-photon polymerized nanostructures for mycotoxin detection

Improved chemical- and bio-sensing with Surface Enhanced Raman Spectroscopy (SERS) requires nanostuctures that can be flexibly designed and fabricated with different physical and optical properties. Here, we present nano-pillar arrays ranging from 200 nm to 600 nm as SERS substrates for mycotoxin detection that are fabricated by means of two-photon polymerization. We built a nominal shape and a voxel-based model for simulating the enhancement of the electric field of the nano-pillar arrays using the Finite-Difference Time-Domain (FDTD) method. A new model was built based on the Atomic Force Microscopy (AFM) data obtained from the fabricated nanostructures and introduced into a FDTD model. We demonstrated the enhancement behavior by measuring the Raman spectrum of Rhodamine B solutions. Both the simulations and experimental results suggest that the 200 nm nano-pillar array has the highest Enhancement Factor (EF). Besides, we determined the limit of detection of the 200 nm pillar array by performing Raman measurements on Rhodamine B solutions with different concentrations. The detection limit of our 200 nm nano-pillar array is 0.55 μM. Finally we discriminated 1 ppm deoxynivalenol and 1.25 ppm fumonisin b1 in acetonitrile solutions by our SERS substrate in combination with principal component analysis. This versatile approach for SERS substrates fabrication gives new opportunities for material characterization in chemical and biological applications.

Nano-pillar arrays are presented ranging from 200 nm to 600 nm as SERS substrates for mycotoxin detection, fabricated by two-photon polymerization. This versatile approach gives new opportunities for material characterization in chemical and biological applications.

Dynamic Imaging of Transferrin Receptor Molecules on Single Live Cell with Bridge Gaps-Enhanced Raman Tags

A metal nanoparticles-based surface-enhanced Raman scattering (SERS) technique has been developed for biosensing and bioimaging due to its advantages in ultra-narrow line width for multiplexing, ultra-high sensitivity and excellent photostability. However, the "hotspots" effect between nanoparticles usually leads to unstable and nonuniform Raman enhancement, and this will greatly reduce the quality of SERS imaging. In this study, we employ the bridge gaps-enhanced Raman tags (BGERTs) to perform SERS imaging, in which BGERTs can not only reduce the influence of the "hotspots" effect between nanoparticles on Raman signal intensity but provide a great Raman enhancement when the Gold (Au) shell is thick enough. Based on BGERTs and its conjugation with the thiol-terminated polyethylene glycol (PEG) and transferrin, we construct a targeted Transferrin (TF)-PEG-BGERTs SERS nanoprobe and achieve the dynamic imaging of transferrin receptor (TfR) molecules on a single live cell, in which the role of transferrin-conjugated PEG-BGERT is for targeting TfR molecules located in cellular membrane surface. Importantly, this BGERTs-based SERS imaging could potentially provide a useful tool for studying the precise mechanism during the receptor-mediated nanoparticles endocytosis or cell proliferation, apoptosis, and other complicated molecular events.

Multicolor Cocktail for Breast Cancer Multiplex Phenotype Targeting and Diagnosis Using Bioorthogonal Surface-Enhanced Raman Scattering Nanoprobes

Early precise diagnosis of cancers is crucial to realize more effective therapeutic interventions with minimal toxic effects. Cancer phenotypes may also alter greatly among patients and within individuals over the therapeutic process. The identification and characterization of specific biomarkers expressed on tumor cells are in high demand for diagnosis and treatment, but they are still a challenge. Herein, we designed three new bioorthogonal surface-enhanced Raman scattering (SERS) nanoprobes and successfully applied the cocktail of them for MDA-MB-231 and MCF-7 breast cancer multiplex phenotype detection. The SERS nanoprobes containing Raman reporters with diynl, azide, or cyano moieties demonstrated apparent Raman shift peaks in 2205, 2120, and 2230 cm-1, respectively, in the biologically Raman-silent region. Three target ligands, including oligonucleotide aptamer (AS1411), arginine-glycine-aspatic acid (RGD) peptide, and homing cell adhesion molecule antibody (anti-CD44), were separately conjugated to the nanoprobes for active recognition capability. The cocktail of the nanoprobes manifested minimal cytotoxicity and simultaneously multiplex phenotype imaging of MDA-MB-231 and MCF-7 cells. Quantitative measurement of cellular uptake by inductively coupled plasma mass spectrometry (ICPMS) verified that MDA-MB-231 cells harbored a much higher expression level of CD44 receptor than MCF-7 cells. For in vivo SERS detection, Raman shift peaks of 2120, 2205, and 2230 cm-1 in the micro-tumor were clearly observed, representing the existence of three specific biomarkers of nucleolin, integrin αvβ3, and CD44 reporter, which could be used for early cancer phenotype identification. The biodistribution results indicated that target ligand modified nanoprobes exhibited much more accumulation in tumors than those nanoprobes without target ligands. The multicolor cocktail of bioorthogonal SERS nanoprobes offers an attractive and insightful strategy for early cancer multiplex phenotype targeting and diagnosis in vivo that is noninvasive and has low cross-talk, unique spectral-molecular signature, high sensitivity, and negligible background interference.

A multiple signal amplification sandwich-type SERS biosensor for femtomolar detection of miRNA

MicroRNAs are widely used as tumor markers for cancer diagnosis and prognosis. Herein, a multiple signal amplification sandwich-type SERS biosensor for femtomolar detection of miRNA is reported. The signal unit consisted of giant Au vesicles, DNA sequences and deposited silver nanoparticles. The giant Au vesicles provided large-volume hot spots because of sharp tips and abundant hotspot gaps, thus enhancing the electromagnetic intensity for the SERS performance. Further silver stain would easily lead to second-stage amplification of Raman signal. In addition, more SERS signal molecules R6G adsorbed on the signal unit with the aid of HCR and the controlled nanogaps between adjacent AgNPs, brought about the third-stage amplification. The capture unit, prepared by immobilizing the capture probe (CP) on the Fe₃O₄@AuNPs, could easily capture target miRNA and greatly simplify the separation step to improve reproducibility. The higher concentration of target miRNA definitely formed more sandwich-type structures with combination of capture unit and signal unit, resulting in multiple amplification of SERS signals. The proposed multiple signal amplification sandwich-type SERS biosensor could detect miRNA-141 at the femtomolar level with a low detection limit of 0.03 fM. Meanwhile, it exhibited high selectivity and accuracy, even for practical analysis in human serum. Therefore, the designed multiple signal amplification sandwich-type SERS biosensor would be a very promising alternative tool for the detection of miRNA and analogs in the field of biomedical diagnosis.

Improving the SERS signals of biomolecules using a stacked biochip containing Fe2O3/Au nanoparticles and a DC magnetic field

This study proposes a magnetic biochip that uses surface-enhanced Raman scattering (SERS) for antigen detection. The biochip was a sandwich structure containing alternating layers of gold and magnetic Fe₂O₃ nanoparticles. Both single (Au/Fe₂O₃/Au) and multilayer (Au/Fe₂O₃/Au/Fe₂O₃/Au) chips containing Fe₂O₃ nanoparticles were fabricated to detect bovine serum albumin (BSA). The single-layer chip detected the BSA antigen at a signal-to-noise ratio (SNR) of 5.0. Peaks detected between 1000 and 1500 cm^-1 corresponded to various carbon chains. With more Fe₂O₃ layers, bond resonance was enhanced via the Hall effect. The distribution of electromagnetic field enhancement was determined via SERS. The signal from the single-layer chip containing Au nanoparticles was measured in an external magnetic field. Maximum signal strength was recorded in a field strength of 12.5 gauss. We observed peaks due to other carbon-hydrogen molecules in a 62.5-gauss field. The magnetic field could improve the resolution and selectivity of sample observations.

Multiplex Label Free Characterization of Cancer Cell Lines Using Surface Plasmon Resonance Imaging

Rapid multiplex cell surface marker analysis can expedite investigations in which large number of antigens need to be analyzed. Simultaneous analysis of multiple surface antigens at the same level of sensitivity is however limited in the current golden standard analysis method, flow cytometry. In this paper we introduce a surface plasmon resonance imaging (SPRi)-based technique for 44-plex parameter analysis using a single sample, in less than 20 min. We analyzed the expression on cells from five different cancer cell lines by SPRi on a 44-plex antibody array including 4 negative controls and compared the output with flow cytometry. The combined correlation of the markers that showed expression by flow cytometry was 0.76. The results demonstrate as a proof of principle that SPRi can be applied for rapid semi-quantitative multiplex cell surface marker analysis.

Rapid SERS-based recognition of cell secretome on the folic acid-functionalized gold gratings

Nowadays, functionalization of the plasmon-supported nanostructured surface is considered as a powerful tool for tumour cell recognition. In this study, the SERS on a surface plasmon polariton-supported gold grating functionalized with folic acid was used to demonstrate an unpretentious recognition of melanoma-associated fibroblasts. Using cultivation media conditioned by different cells, we were able to detect reproducible differences in the secretome of melanoma-associated and normal control fibroblasts. The homogeneous distribution of plasmon energy along the grating surface was proved to provide excellent SERS signal reproducibility, while, to increase the affinity of (bio)molecules to SERS substrate, folic acid molecules were covalently grafted to the gold gratings. As proof of concept, fibroblasts were cultured in vitro, and culture media from the normal and tumour-associated lines were collected and analysed with our proposed SERS substrates. Identifying individual peaks of the Raman spectra as well as comparing their relative intensities, we showed that the proposed functional SERS platform can recognise the melanoma-associated cells without the need for further statistical spectral evaluation directly. We also demonstrated that the SERS chip created provided a stable SERS signal over a period of 90 days without loss of sensitivity. Graphical abstract.

Cellular interface supported toehold strand displacement cascade for amplified dual-electrochemical signal and its application for tumor cell analysis

In this work, toehold strand displacement cascade (TSDC) has been delicately designed and carried out on the cellular interface for the amplification and output of dual-electrochemical signal. Specifically, antibody cross-linked T strand can recognize cell which is linked with immune-magnetic bead. Subsequently, T strand on the cellular interface can mediate the occurrence of TSDC, resulting the change of SN₃/S1-MB to SN₃/S2-Fc ratio in the supernatant after magnetic separation. The resultant SN₃/S1-MB and SN₃/S2-Fc can be immobilized on the electrode interface through click chemistry and give the amplified double electrochemical signal. So the tumor cell amount can closely correlate with the change of the double signal. Except for output of the double signal for improvement of analytical accuracy, the double magnetic separation not only eliminate the interference of the complicated substances in serum, but also remove the influence of cell on click reaction on the electrode interface. So based on cellular interface supported TSDC for amplified dual-electrochemical signal, the established method has been successfully applied to analyze the tumor cells in serum accurately and sensitively.