Differentiation and prognostic stratification of acute myeloid leukemia by serum-based spectroscopy coupling with metabolic fingerprints.

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by complex molecular and cytogenetic abnormalities. New approaches to predict the prognosis of AML have increasingly attracted attention. There were 98 non-M3 AML cases and 48 healthy controls were enrolled in the current work. Clinically routine assays for cytogenetic and molecular genetic analyses were performed on the bone marrow samples of patients with AML. Meanwhile, metabolic profiling of these AML subjects was also performed on the serum samples by combining Ag nanoparticle-based surface-enhanced Raman spectroscopy (SERS) with proton nuclear magnetic resonance (NMR) spectroscopy. Although most of the routine biochemical test showed no significant differences between the M0-M2 and M5 groups, the metabolic profiles were significantly different either between AML subtypes or between prognostic risk subgroups. Specific SERS bands were screened to serve as potential markers for AML subtypes. The results demonstrated that the classification models for M0-M2 and M5 shared two bands (i.e., 1328 and 741 cm-1 ), all came from nucleic acid signals. Furthermore, Metabolic profiles provided various differential metabolites responsible for different AML subtypes, and we found altered pathways mainly included energy metabolism like glycolysis, pyruvate metabolism, and metabolisms of nucleic acid bases as well as specific amino acid metabolisms. It is concluded that integration of SERS and NMR provides the rational and could be reliable to reveal AML differentiation, and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and prognostic evaluation.

Ratiometric SERS-based assay with "sandwich" structure for detection of serotonin.

A ratiometric nanoensemble-functionalized Surface-Enhanced Raman Spectroscopy (SERS) chip is proposed and an ultrasensitive "sandwich" structure introduced for the detection of 5-HT to achieve early diagnosis of colon cancer. The SERS-based chip contains core-shell SERS active substrates coded by different Raman tags with Raman-silent region peaks (Au@EBP@Au NR arrays and Au@MBN@Ag NPs) and then identify-function molecule modification to construct the "sandwich" structure (Au@EBP@Au NR arrays/5-HT/Au@MBN@Ag NPs). Au@EBP@Au NR arrays showed excellent SERS performance, including good uniformity with an RSD of 5.53% and an enhancement factor (EF) of 2.13 × 107. The intensity ratio of the peaks in the Raman silent region was proportional to the concentration of 5-HT in the range 5 × 10-7-1 × 10-3 M, with a detection limit (LOD) of 4.9 × 10-9 M. Excellent assay accuracy was also demonstrated, with recoveries in the range 96.80% to 104.96%. Finally, we found that 5-HT expression levels in normal human sera were much lower than those in colon cancer patients by using a SERS-based chip for determination of the concentration of 5-HT in clinical colon cancer serum. This result suggested that the proposed approach has potential for detecting 5-HT by ratiometric SERS-based chips for early diagnosis of colon cancer.

Reusable 3D silver superposed silica SERS substrate based on the Griess reaction for the ratiometric detection of nitrite.

When nitrite is ingested and absorbed by the body, it can be converted into highly toxic nitrosamines (carcinogens, teratogens, and mutagens), posing health risks to the general population. Therefore, it calls for establishing a method for determination of nitrite. In this paper, the glass-SiO2-Ag surface-enhanced Raman scattering (SERS) substrate with a large number of "hot spots" were prepared by two kinds of silane coupling agents. The SERS substrate had high sensitivity and repeatability. Silicon dioxide supported the silver nanoparticles (Ag NPs), which increased surface roughness of the substrate, generated a great quantity of hot spots and enhanced the SERS signal. In the SERS spectrum, the intensity ratio of the two characteristic peaks (1287 cm-1 and 1076 cm-1) had a good linear correlation with the logarithm of the concentration of nitrite, R2 = 0.9652. The recoveries of 50 µM and 100 µM nitrite in three kinds of foods, three kinds of cosmetics and tap water were 90.9-105.3%.

Silver nanocube coupling with a nanoporous silver film for dual-molecule recognition based ultrasensitive SERS detection of dopamine.

Dopamine (DA) is one of the catecholamine neurotransmitters used for the treatment of neural disorders. In this study, a novel sensor based on surface-enhanced Raman scattering (SERS) with dual molecule-recognition for ultrasensitive detection of DA was presented, with a limit of detection (LOD) of 40 fM, without any pretreatment of clinical samples. To realize the sensitive and selective detection of DA in complex samples, the nanoporous silver film (AgNF) surfaces were functionalized with mercaptopropionic acid (MPA) to accurately capture DA, while silver nanocubes (AgNCs) were modified with 4-mercaptobenzene boronic acid (4-MPBA) as a Raman reporter for the quantitative detection of DA. The nanogaps between AgNCs and the AgNF led to the generation of an abundance of hot spots for the SERS signal and thus effectively improved the sensitivity of DA detection. Measurements of DA concentrations in clinical body fluids such as human serum and urine samples are also demonstrated, showing excellent performance for DA detection in a complex environment. Our results demonstrate the promising potential for the ultrasensitive detection of DA for the potential diagnosis of DA-related diseases.

Metabolite profiling of human blood by surface-enhanced Raman spectroscopy for surgery assessment and tumor screening in breast cancer.

Mammography, a standard screening method for breast cancer, is effective for reducing the rate of death; however, it suffers from frequent false positive alarm and radiation risk. Besides, surgery treatment has a vital impact on the clinical outcomes of breast cancer, offering enormous benefits for breast cancer care and management. In this work, we analyzed the peripheral blood sample from breast cancer patients with pre- and post-surgery and healthy volunteers using label-free surface-enhanced Raman spectroscopy technology based on silver nanoparticles. Results showed that distinct patterns of blood belonging to specific subjects could be profiled, and corresponding accuracies of 95% and 100% were achieved by multivariate diagnostic algorithm for pre-surgery vs. post-surgery and pre-surgery vs. normal groups, respectively, providing a unique blood analysis method for surgery evaluation as well as tumor screening in breast cancer. Graphical abstract.

Metabolic characteristics revealing cell differentiation of nasopharyngeal carcinoma by combining NMR spectroscopy with Raman spectroscopy.

BACKGROUND: The staging system of nasopharyngeal carcinoma (NPC) has close relationship with the degree of cell differentiation, but most NPC patients remain undiagnosed until advanced phases. Novel metabolic markers need to be characterized to support diagnose at an early stage. METHODS: Metabolic characteristics of nasopharyngeal normal cell NP69 and two types of NPC cells, including CNE1 and CNE2 associated with high and low differentiation degrees were studied by combining 1H NMR spectroscopy with Raman spectroscopy. Statistical methods were also utilized to determine potential characteristic metabolites for monitoring differentiation progression. RESULTS: Metabolic profiles of NPC cells were significantly different according to differentiation degrees. Various characteristic metabolites responsible for different differentiated NPC cells were identified, and then disordered metabolic pathways were combed according to these metabolites. We found disordered pathways mainly included amino acids metabolisms like essential amino acids metabolisms, as well as altered lipid metabolism and TCA cycle, and abnormal energy metabolism. Thus our results provide evidence about close relationship between differentiation degrees of NPC cells and the levels of intracellular metabolites. Moreover, Raman spectrum analysis also provided complementary and confirmatory information about intracellular components in single living cells. Eight pathways were verified to that in NMR analysis, including amino acids metabolisms, inositol phosphate metabolism, and purine metabolism. CONCLUSIONS: Methodology of NMR-based metabolomics combining with Raman spectroscopy could be powerful and straightforward to reveal cell differentiation development and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and therapeutic evaluation.

Label-free liquid biopsy based on blood circulating DNA detection using SERS-based nanotechnology for nasopharyngeal cancer screening.

Development of a sensitive, rapid and easy-to-use liquid biopsy method is of imperative clinical value for point-of-care caner diagnostics. Here, a label-free and modification-free nanotechnology based on surface-enhanced Raman spectroscopy (SERS) was employed for DNA analysis. Using the SERS signals of phosphate backbone as internal standard, quantitative detection for nucleobases was achieved even at single base level. The method combined with principal component analysis and linear discriminant analysis was further applied for real blood circulating DNA detection for the first time, and an ideal diagnostic sensitivity of 83.3% and specificity of 82.5% could be obtained for differentiating the nasopharyngeal cancer from the normal group, demonstrating promising potential as an alternative nanotechnology for nasopharyngeal cancer screening based on liquid biopsy.

Metal Carbonyls for the Biointerference-Free Ratiometric Surface-Enhanced Raman Spectroscopy-Based Assay for Cell-Free Circulating DNA of Epstein-Barr Virus in Blood.

By taking advantage of the spectral properties of metal carbonyls, we have designed a surface-enhanced Raman spectroscopy (SERS) ratiometric assay for measuring cell-free circulating DNA (cfDNA) from Epstein-Barr virus in blood for nasopharyngeal carcinoma (NPC). This assay consists of a rhenium carbonyl (Re-CO) to serve as a DNA probe, an osmium carbonyl (Os-CO) embedded within the SERS-active substrate as an internal reference, and a streptavidin layer on the surface of the substrate. Hybridization of cfDNA with biotinylated-capture sequence leads to immobilization of cfDNA on the substrate. The binding of Re-CO via daunorubicin (DNR) to cfDNA is accompanied by an appearance of a strong symmetry stretching vibrations peak at 2113 cm-1, which has spectral overlap with Os-CO (2025 cm-1). This results in an increase in the I2113/ I2025 ratio and quantitatively correlates with cfDNA. This SERS assay can be readily used to detect cfDNA in blood samples from patients due to the intensity ratio of I2113/ I2025 lying in a silent region (1780-2200 cm-1) in the SERS spectrum of the biomolecules.

Diagnostic potential of polarized surface enhanced Raman spectroscopy technology for colorectal cancer detection.

The purpose of this study was to develop a more powerful blood analysis method based on polarized surface enhanced Raman spectroscopy (SERS) technology for non-invasive and sensitive colorectal cancer (CRC) detection. The efficiency of different polarized scattering signals (non-polarization, parallel polarization and perpendicular polarization) on blood serum SERS was explored for the first time. Results demonstrated that polarized SERS was more sensitive to explore distinctive spectral differences between cancer and normal groups. And higher diagnostic accuracy of 91.6% could be achieved using polarized SERS integrated with PCA-LDA for classification of the two serum groups in comparison to conventional SERS technology. This exploratory study demonstrated that the nanobiosensor based on polarized SERS technique in conjunction with PCA-LDA provided a novel strategy for blood SERS analysis, and had the potential as a clinical complement for CRC screening.

Label-free optical sensor based on red blood cells laser tweezers Raman spectroscopy analysis for ABO blood typing.

The clinical significance of ABO blood typing extends beyond transfusion medicine and is demonstrated to be associated with susceptibility to various diseases, even including cancer. In this study, a home-made laser tweezers Raman spectroscopy (LTRS) system was applied to detect red blood cells (RBCs) with the aim to develop a label-free, simple and objective blood typing method for the first time. High-quality Raman spectra of RBCs in the fingerprint region of 420-1700 cm-1 can be obtained, meanwhile exciting blood typing results can be achieved, especially with an accuracy of 100% for identifying Type AB from other blood types with the use of multivariate statistical analysis based on principal component analysis (PCA) combined with linear discriminant analysis (LDA). This primary work demonstrates that the label-free RBCs LTRS analysis in conjunction with PCA-LDA diagnostic algorithms has great potential as a biosensor for ABO blood typing.

[Surfaced-Enhanced Raman Scattering Spectroscopic Study on Sheng-Di-Dang-Gui Decoction].

To reveal the relationship between the single decoction and prescription, the surface-enhanced Raman scattering (SERS) spectroscopy of Sheng-Di-Dang-Gui decoction (SDDGD), Sheng-Di decoction (SDD) and Dang-Gui decoction (DGD) were tested and analyzed. Mainly seventeen Raman signals (538, 622, 732, 761, 835, 876, 959, 1 145, 1 245, 1 276, 1 326, 1 402, 1 456, 1 470, 1 518, 1 546 and 1 605 cm(-1)) in three decoctions were discussed. The characteristic Raman bands of three decoctions were tentatively assigned. Fifteen obvious Raman bands (538, 732, 761, 835, 876, 959, 1 145, 1 245, 1 276, 1 326, 1 402, 1 456, 1 470, 1 518 and 1 605 cm(-1)) were observed in the SERS spectroscopy of SDDGD, thirteen obvious Raman bands (538, 761, 835, 876, 959, 1 145, 1 245, 1 276, 1 326, 1 402, 1 470, 1 518 and 1 546 cm(-1)) were observed in the SERS spectroscopy of SDD, ten obvious Raman bands (538, 622, 732, 761, 835, 876, 959, 1 245, 1 326 and 1 402 cm(-1)) were observed in the SERS spectroscopy of DGD. Some Raman bands in SERS spectra of SDD and DGD were retained in the SDDGD, however some Raman bands in two kinds of decoctions never appeared in the SDDGD. And new Raman bands (1 456 and 1 605 cm(-1)) were generated in the SDDGD, resulted in the fact that new chemical compositions were created. Medical ingredients in the SDDGD were not the simple addition of SDD and DGD. The results showed that the SERS spectroscopy might provide a new kind of novel, effective and simple detecting method for the prescription research.

[Advances in Raman Spectroscopy for Nasopharyngeal Carcinoma Tissue].

Nasopharyngeal carcinoma is a unique malignant tumor that has a distinct geographic and racial distribution, with a high incidence in southeast Asia and southern China. High degree of malignancy, poor prognosis and difficulty in early diagnosis remain a problem in nasopharyngeal carcinoma. Raman spectroscopy technique based on inelastic scattering is a rapid and nonivasive detection method, which is capable of providing the information of biochemical components at molecular vibration level.This article reviewed the recent research progress of nasopharyngeal carcinoma based on Raman spectroscopy. It mainly introduces the study of detecting nasopharyngeal carcinoma tissue by using Raman spectroscopy as well as surface-enhanced Raman scattering spectroscopy (SERS). The emphasis is put on the latest works by our research group, including high wavenumber Raman spectroscopy of tissue, Raman spectroscopy of tissue smears, and a specially designed endoscopic device combined with Raman spectroscopy for in vivo nasopharyngeal cancerous tissue detection, which was firstly developed by our group. Finally, the prospects of the development of Raman spectroscopy for nasopharyngeal carcinoma were discussed.

[Studies of Male Fertility with Raman Spectroscopy].

Raman spectroscopy which belongs to scattering spectroscopy obtained molecular vibrational and rotational information to achieve detection and analysis of molecular structure and corresponding changes through recording the frequency shift when light interacted with materials. Compared with routine biochemical analysis, Raman spectroscopy has the advantage of non-invasive, label-free and no sample requirement. Raman spectroscopy has been widely applied in biomedical field such as human tissue, organs, cells and human body fluids for disease diagnosis. This article mainly focuses on recent research advances of Raman spectroscopy in human semen. Firstly, Raman spectroscopy(including surface-enhanced Raman spectroscopy, SERS) employed in forensic science for semen analysis, and some related data processing methods were introduced, then Raman spectroscopy involved investigations of male fertility was highlighted, more specifically, the Raman-based qualitative and quantitative analysis which assist the objective detection and evaluation of male fertility. Furthermore, studies of single sperm cell based on micro-Raman system to characterize and evaluate sperm quality and the preliminarily obtained Raman biomarkers which indicate high-quality sperm cell were introduced. Finally, the potential development of Raman spectroscopy involved in reproduction and fertility field was also discussed.

Ultrasound-mediated method for rapid delivery of nano-particles into cells for intracellular surface-enhanced Raman spectroscopy and cancer cell screening.

Surface-enhanced Raman spectroscopy (SERS) is a powerful technology for providing finger-printing information of cells. A big challenge has been the long time duration and inefficient uptake of metal nano-particles into living cells as substrate for SERS analysis. Herein, a simple method (based on ultrasound) for the rapid transfer of silver nanoparticles (NPs) into living cells for intracellular SERS spectroscopy was presented. In this study, the ultrasound-mediated method for NP delivery overcame the shortcoming of 'passive uptake', and achieved quick acquisition of reproducible SERS spectra from living human nasopharyngeal carcinoma cell lines (C666 and CNE1) and normal nasopharyngeal cell line (NP69). Tentative assignment of the Raman bands in the measured SERS spectra showed cancer cell specific biomolecular differences, including significantly lower DNA concentrations and higher protein concentrations in cancerous nasopharyngeal cells as compared to those of normal cells. Combined with PCA-LDA multivariate analysis, ultrasound-mediated cell SERS spectroscopy differentiated the cancerous cells from the normal nasopharyngeal cells with high diagnostic accuracy (98.7%), demonstrating great potential for high-throughput cancer cell screening applications.

An outlier removal method based on PCA-DBSCAN for blood-SERS data analysis.

Surface-enhanced Raman spectroscopy (SERS) has shown promising potential in cancer screening. In practical applications, Raman spectra are often affected by deviations from the spectrometer, changes in measurement environments, and anomalies in spectrum characteristic peak intensities due to improper sample storage. Previous research has overlooked the presence of outliers in categorical data, leading to significant impacts on model learning outcomes. In this study, we propose a novel method, called Principal Component Analysis and Density Based Spatial Clustering of Applications with Noise (PCA-DBSCAN) to effectively remove outliers. This method employs dimensionality reduction and spectral data clustering to identify and remove outliers. The PCA-DBSCAN method introduces adjustable parameters (Eps and MinPts) to control the clustering effect. The effectiveness of the proposed PCA-DBSCAN method is verified through modeling on outlier-removed datasets. Further refinement of the machine learning model and PCA-DBSCAN parameters resulted in the best cancer screening model, achieving 97.41% macro-average recall and 97.74% macro-average F1-score. This paper introduces a new outlier removal method that significantly improves the performance of the SERS cancer screening model. Moreover, the proposed method serves as inspiration for outlier detection in other fields, such as biomedical research, environmental monitoring, manufacturing, quality control, and hazard prediction.

Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.

Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predicting the radioresistance that is the main reason for treatment failure. Herein, the molecular profiles of patient plasma from NPC with radiotherapy sensitivity and resistance groups as well as healthy group, respectively, were explored by label-free surface enhanced Raman spectroscopy (SERS) based on surface plasmon resonance for the first time. Especially, the components with different molecular weight sizes were analyzed via the separation process, helping to avoid the possible missing of diagnostic information due to the competitive adsorption. Following that, robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was employed to extract the feature of blood-SERS data and establish an effective predictive model with the accuracy of 96.7% for identifying the radiotherapy resistance subjects from sensitivity ones, and 100% for identifying the NPC subjects from healthy ones. This work demonstrates the potential of molecular separation-assisted label-free SERS combined with machine learning for NPC screening and treatment strategy guidance in clinical scenario.

Non-invasive screening and subtyping for breast cancer by serum SERS combined with LGB-DNN algorithms.

Early detection of breast cancer and its molecular subtyping is crucial for guiding clinical treatment and improving survival rate. Current diagnostic methods for breast cancer are invasive, time consuming and complicated. In this work, an optical detection method integrating surface-enhanced Raman spectroscopy (SERS) technology with feature selection and deep learning algorithm was developed for identifying serum components and building diagnostic model, with the aim of efficient and accurate noninvasive screening of breast cancer. First, the high quality of serum SERS spectra from breast cancer (BC), breast benign disease (BBD) patients and healthy controls (HC) were obtained. Chi-square tests were conducted to exclude confounding factors, enhancing the reliability of the study. Then, LightGBM (LGB) algorithm was used as the base model to retain useful features to significantly improve classification performance. The DNN algorithm was trained through backpropagation, adjusting the weights and biases between neurons to improve the network's predictive ability. In comparison to traditional machine learning algorithms, this method provided more accurate information for breast cancer classification, with classification accuracies of 91.38 % for BC and BBD, and 96.40 % for BC, BBD, and HC. Furthermore, the accuracies of 90.11 % for HR+/HR- and 88.89 % for HER2+/HER2- can be reached when evaluating BC patients' molecular subtypes. These results demonstrate that serum SERS combined with powerful LGB-DNN algorithm would provide a supplementary method for clinical breast cancer screening.

Target-triggered assembly of plasmon resonance nanostructures for quantitative detection of lncRNA in liver cancer cells via surface enhanced Raman spectroscopy.

Long-stranded non-coding RNAs (lncRNA) have important roles in disease as transcriptional regulators, mRNA processing regulators and protein synthesis factors. However, traditional methods for detecting lncRNA are time-consuming and labor-intensive, and the functions of lncRNA are still being explored. Here, we present a surface enhanced Raman spectroscopy (SERS) based biosensor for the detection of lncRNA associated with liver cancer (LC) as well as in situ cellular imaging. Using the dual SERS probes, quantitative detection of lncRNA (DAPK1-215) can be achieved with an ultra-low detection limit of 952 aM by the target-triggered assembly of core-satellite nanostructures. And the reliability of this assay can be further improved with the R2 value of 0.9923 by an internal standard probe that enables the signal dynamic calibration. Meanwhile, the high expression of DAPK1-215 mainly distributed in the cytoplasm was observed in LC cells compared with the normal ones using the SERS imaging method. Moreover, results of cellular function assays showed that DAPK1-215 promoted the migration and invasion of LC by significantly reducing the expression of the structural domain of death associated protein kinase. The development of this biosensor based on SERS can provide a sensitive and specific method for exploring the expression of lncRNA that would be a potential biomarker for the screening of LC.

Optical Nanobiosensor Based on Surface-Enhanced Raman Spectroscopy and Catalytic Hairpin Assembly for Early-Stage Lung Cancer Detection via Blood Circular RNA.

Lung cancer has become the leading cause of cancer-related deaths globally. However, early detection of lung cancer remains challenging, resulting in poor outcomes for the patients. Herein, we developed an optical biosensor integrating surface-enhanced Raman spectroscopy (SERS) with a catalyzed hairpin assembly (CHA) to detect circular RNA (circRNA) associated with tumor formation and progression (circSATB2). The signals of the Raman reporter were considerably enhanced by generating abundant SERS "hot spots" with a core-shell nanoprobe and 2D SERS substrate with calibration capabilities. This approach enabled the sensitive (limit of detection: 0.766 fM) and reliable quantitative detection of the target circRNA. Further, we used the developed biosensor to detect the circRNA in human serum samples, revealing that patients with lung cancer had higher circRNA concentrations than healthy subjects. Moreover, we characterized the unique circRNA concentration profiles of the early stages (IA and IB) and subtypes (IA1, IA2, and IA3) of lung cancer. These results demonstrate the potential of the proposed optical sensing nanoplatform as a liquid biopsy and prognostic tool for the early screening of lung cancer.

A dual-signal biosensor based on surface-enhanced Raman spectroscopy for high-sensitivity quantitative detection and imaging of circRNA in living cells.

Circular RNAs (circRNAs) are non-coding RNAs that play key roles in the development and progression of cancer through various mechanisms of action, making them promising biomarkers for cancer diagnosis, prognosis, and treatment. In the present study, a biosensor based on surface-enhanced Raman spectroscopy (SERS) was developed for rapid, simple, and sensitive quantitative detection of intracellular circRNAs for the first time. A dual-signal SERS nanoprobe with a 4MBN and ROX signal molecule was fabricated, and the ROX signal intensity was used to determine the concentration of target circSATB2. 4MBN was used as an internal standard to calibrate the ROX signal, thereby achieving highly sensitive and reliable detection of the target circRNA with a limit of detection of 0.043 pM. Furthermore, the relatively high expression of circSATB2 in lung cancer cells compared to that in normal lung epithelial cells was successfully characterized by the proposed SERS imaging method, which is consistent with the results of standard reverse transcription-polymerase chain reaction (RT-PCR). Monitoring of specific circRNAs using this SERS-based biosensor is a promising method for cancer diagnosis and gene therapy.