Surface-enhanced Raman spectroscopy analysis of mast cell degranulation induced by low-intensity laser

SERS analysis of single cells and subcellular components: A review

SERS is a rapidly advancing and non-destructive technique that has been proven to be more reliable and convenient than other traditional analytical methods. Due to its sensitivity and specificity, this technique is earning its place as a routine and powerful tool in biological and medical studies, especially for the analysis of living cells and subcellular components. This paper reviewed the research progress of single-cell SERS that has been made in the last few years and discussed challenges and future perspectives of this technique. The reviewed SERS platforms have been categorized according to their nature into the following types: (1) colloid-based, substrate-based, or hybrid; (2) ligand-based or ligand-free, and (3) label-based or label-free. The advantages and disadvantages of each type and their potential applications in various fields are thoroughly discussed.

Nasopharyngeal carcinoma cell screening based on nuclear targeting Surface-Enhanced Raman Scattering (SERS) detection

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a malignant epithelial carcinoma arising from the nasopharyngeal mucosal lining. Diagnosis of NPC at early stage can improve the outcome of patients and facilitate reduction in cancer mortality. The most significant change between cancer cells and normal cells is the variation of cell nucleus. Therefore, accurately detecting the biochemical changes in nucleus between cancer cells and normal cells has great potential to explore diagnostic molecular markers for NPC. Highly sensitive surface-enhanced Raman scattering (SERS) could reflect the biochemical changes in the process of cell cancerization at the molecular level. However, rapid nuclear targeting SERS detection remains a challenge.

RESULTS

A novel and accurate nuclear-targeting SERS detection method based on electroporation was proposed. With the assistance of electric pulses, nuclear-targeting nanoprobes were rapidly introduced into different NPC cells (including CNE1, CNE2, C666 cell lines) and normal nasopharyngeal epithelial cells (NP69 cell line), respectively. Under the action of nuclear localization signaling peptides (NLS), the nanoprobes entering cells were located to the nucleus, providing high-quality nuclear SERS signals. Hematoxylin and eosin (H&E) staining and in situ cell SERS imaging confirmed the excellent nuclear targeting performance of the nanoprobes developed in this study. The comparison of SERS signals indicated that there were subtle differences in the biochemical components between NPC cells and normal nasopharyngeal cells. Furthermore, SERS spectra combined with principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to diagnose and distinguish NPC cell samples, and high sensitivity, specificity, and accuracy were obtained in the screening of NPC cells from normal nasopharyngeal epithelial cells.

SIGNIFICANCE

To the best of our knowledge, this is the first study that employing nuclear-targeting SERS testing to screen nasopharyngeal carcinoma cells. Based on the electroporation technology, nanoprobes can be rapidly introduced into living cells for intracellular biochemical detection. Nuclear-targeting SERS detection can analyze the biochemical changes in the nucleus of cancer cells at the molecular level, which has great potential for early cancer screening and cytotoxicity analysis of anticancer drugs.

Label-free screening of common urinary system tumors from blood plasma based on surface-enhanced Raman spectroscopy

BACKGROUND

The incidence of common urinary system tumors has been rising rapidly in recent years, and most urinary system-derived tumors lack specific biomarkers.

OBJECTIVES

To explore the efficacy of surface-enhanced Raman spectroscopy (SERS) of blood plasma in screening three common urinary system tumors, including bladder cancer (BC), prostate cancer (PCa), and renal cell carcinoma (RCC).

METHODS

SERS plasma spectra from 125 plasma samples, including 25 PCa, 38 RCC, 24 BC patients, and 38 normal volunteers, were collected. All candidates had no other comorbidities. The Diagnosis was based on the combination of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), and the effectiveness of the diagnostic algorithms was verified using the Receiver Operating Characteristic Curve (ROC).

RESULTS

There are significant differences in SERS signals between PCa, BC, RCC, and normal plasma, especially at 639, 889, 1010, 1136, and 1205 cm-1. The PCA-LDA results show that high sensitivity (100 %), specificity (100 %), and accuracy (100 %) could be achieved for screening the PCa, RCC, BC group vs. the normal group, the PCa group vs. the BC and RCC group, respectively. The diagnostic sensitivity, specificity, and accuracy for the BC group vs. the RCC group are 79.2 %, 71.1 %, and 75.15 %, respectively. The integrated area under the ROC curve (AUC) is 1.0, 1.0, and 1.0 for the PCa, RCC, and BC group vs. the normal group, respectively. The AUC of the PCa group vs. the BC group and RCC group and the BC group vs. the RCC group are 1.0, 1.0, and 0.842, respectively.

CONCLUSIONS

Label-free plasma-SERS technology with PCA-LDA analysis could be a useful screening method for detecting urinary system tumors (PCa, RCC, and BC) in this exploratory study.

A microsphere nanoparticle based-serum albumin targeted adsorption coupled with surface-enhanced Raman scattering for breast cancer detection

The serum albumin level is inseparable associated with survival in patients with breast cancer, and simultaneously serve as a good indicator of prognosis of cancer. Here, we proposed a novel extraction-isolation analysis method of albumin for breast cancer detection utilizing hydroxyapatite particles (HAp) to targeted adsorb albumin from serum relying on its specific adsorption capacity. An ideal protein-release reagent was used for isolating albumin from the surface of HAp, and meanwhile ensuring that the structure and property of albumin was not suffered damage. The surface-enhanced Raman scattering (SERS) signal of extracted albumin was obtained, and partial least squares (PLS) and linear discriminant analysis (LDA) analysis approach were employed to analyze SERS spectra data, with the aim to assess the capability of HAp method for identifying breast cancer, yielding an ideal diagnostic accuracy of 98.6%, demonstrating promising potential as a non-invasive and sensitive nanotechnology for breast cancer screening.

Label-free determination of liver cancer stages using surface-enhanced Raman scattering coupled with preferential adsorption of hydroxyapatite microspheres

Here, we explored a label-free albumin targeted analysis method by utilizing hydroxyapatite (HAp) to adsorb-release serum albumin, in conjunction with surface-enhanced Raman scattering (SERS) for screening liver cancer (LC) at different tumor (T) stages. Excitingly, albumin can be preferentially adsorbed by HAp as compared with other serum proteins. Moreover, we developed a novel strategy using a high concentration of PO₄^3- solution as the albumin-release agent. This method overcomes the shortcomings of the traditional purification technology of serum albumin, which requires acid to release protein, and ensures that the structure and properties of albumin are not damaged. The SERS spectra of serum albumin obtained from three sample groups were analyzed to verify the feasibility of this new method: healthy volunteers (n = 35), LC patients with T1 stage (n = 25) and LC patients with T2-T4 stage (n = 23). Furthermore, principal component analysis (PCA) combined with linear discriminant analysis (LDA) was employed to classify the early T (T1) stage LC vs. normal group and advanced T (T2-T4) stage LC vs. normal group, yielding high diagnostic accuracies of 90.00% and 96.55%, respectively, which showed a 10% improvement in diagnostic accuracy for the early stage detection of cancer as compared with previous studies. The results of this exploratory work demonstrated that HAp-adsorbed-released serum albumin combined with SERS analysis has great potential for label-free, noninvasive and sensitive detection of different T stages of liver cancer.