Nenrong Liu

Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening

Surface-enhanced Raman scattering (SERS) spectra of serum proteins purified from human serum samples were employed to detect colorectal cancer. Acetic acid as a new aggregating agent was introduced to increase the magnitude of the SERS enhancement. High-quality SERS spectra of serum proteins were acquired from 103 cancer patients and 103 healthy volunteers. Tentative assignments of SERS bands reflect that some specific biomolecular contents and protein secondary structures change with colorectal cancer progression. Principal component analysis combined with linear discriminant analysis was used to assess the capability of this approach for identifying colorectal cancer, yielding diagnostic accuracies of 100% (sensitivity: 100%; specificity: 100%) based on albumin SERS spectroscopy and 99.5% (sensitivity: 100%; specificity: 99%) based on globulin SERS spectroscopy, respectively. A partial least squares (PLS) approach was introduced to develop diagnostic models. An albumin PLS model successfully predicted the unidentified subjects with a diagnostic accuracy of 93.5% (sensitivity: 95.6%; specificity: 91.3%) and the globulin PLS model gave a diagnostic accuracy of 93.5% (sensitivity: 91.3%; specificity: 95.6%). These results suggest that serum protein SERS spectroscopy can be a sensitive and clinically powerful means for colorectal cancer detection.

Surface-enhanced Raman spectroscopy for differentiation between benign and malignant thyroid tissues

The aim of this study was to evaluate the potential of applying silver nano-particle based surface-enhanced Raman scattering (SERS) to discriminate different types of human thyroid tissues. SERS measurements were performed on three groups of tissue samples including thyroid cancers (n = 32), nodular goiters (n = 20) and normal thyroid tissues (n = 25). Tentative assignments of the measured tissue SERS spectra suggest interesting cancer specific biomolecular differences. The principal component analysis (PCA) and linear discriminate analysis (LDA) together with the leave-one-out, cross-validated technique yielded diagnostic sensitivities of 92%, 75% and 87.5%; and specificities of 82.6%, 89.4% and 84.4%, respectively, for differentiation among normal, nodular and malignant thyroid tissue samples. This work demonstrates that tissue SERS spectroscopy associated with multivariate analysis diagnostic algorithms has great potential for detection of thyroid cancer at the molecular level.

Gold nanoaggregates for probing single-living cell based on surface-enhanced Raman spectroscopy

Abstract. Gold nanoparticles are delivered into living cells by transient electroporation method to obtain intracellular surface-enhanced Raman spectroscopy (SERS). The subcellular localization of gold nanoparticles is characterized by transmission electron microscopy, and the forming large gold nanoaggregates are mostly found in the cytoplasm. The SERS detection of cells indicates that this kind of gold nanostructures induces a high signal enhancement of cellular chemical compositions, in addition to less cellular toxicity than that of silver nanoparticles. These results demonstrate that rapid incorporation of gold nanoparticles by electroporation into cells has great potential applications in the studies of cell biology and biomedicine.

Multiphoton microscopic imaging of human normal and cancerous oesophagus tissue

In this paper, microstructures of human oesophageal submucosa are evaluated using multiphoton microscopy, based on two‐photon excited fluorescence and second harmonic generation. The content and distribution of collagen, elastic fibers and cancer cells in normal and cancerous submucosa layer have been distinctly obtained and briefly discussed. The variation of these components is very relevant to the pathology in oesophagus, especially in early oesophageal cancer. Our results further indicate that the multiphoton microscopy technique has the potential application in vivo in clinical diagnosis and monitoring of early oesophageal cancer.

Detection of human serum proteins using Raman and SERS spectroscopy

The use of normal Raman (NR) spectroscopy and surface enhanced Raman scattering (SERS) spectroscopy to analyze the biochemical information of human serum proteins and hence distinguish between normal and primary hepatic carcinoma (PHC) serum samples was investigated. The serum samples were obtained from patients who were clinically diagnosed with PHC (n=20) and healthy volunteers (n=20). All spectra were collected in the spectral range of 400-1800 cm-1 and analyzed through the multivariate statistical methods of principal component analysis (PCA). The results showed that both NR and SERS combined with PCA had good performance in distinguishing the human serum proteins between PHC patients and healthy volunteers with high sensitivity and specificity of 100%. And we can get more detail information of component and conformation of human serum proteins by considering NR and SERS spectrum. Our results support the concept again that serum protein Raman and SERS spectroscopy combined with PCA analysis both can become noninvasive and rapid diagnostic tools to detect the primary hepatic carcinoma.

Serum albumin analysis for type II diabetes detection using surface-enhanced Raman spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy combined with membrane electrophoresis (ME) was firstly employed to detect albumin variation in type II diabetic development. Albumin was first purified from human serum by ME and then mixed with silver nanoparticles to perform SERS spectral analysis. SERS spectra were obtained from blood albumin samples of 20 diabetic patients and 19 healthy volunteers. Subtle but discernible changes in the acquired mean spectra of the two groups were observed. Tentative assignment of albumin SERS bands indicated specific structural changes of albumin molecule with diabetic development. Meanwhile, PCA-LDA diagnostic algorithms were employed to classify the two kinds of albumin SERS spectra, yielding the diagnostic sensitivity of 90% and specificity of 94.7%. The results from this exploratory study demonstrated that the EM-SERS method in combination with multivariate statistical analysis has great potential for the label-free detection of albumin variation for improving type II diabetes screening.

Characterization of secreted proteins in HepG2 and LO2 cells by Raman spectroscopy

Secreted proteins, the promising source of biomarkers for early detection and diagnosis of cancer, have received considerable attention. Raman spectroscopy and principal component analysis (PCA) were used to characterize the secreted proteins collected from the cell cultures of human hepatoma cell line HepG2 and normal human liver cell line LO2 in this paper. We found the major difference of secreted proteins Raman spectra between HepG2 and LO2 cells were in the range of 1200cm-1-1800cm-1. Compared with LO2 cells, some significant changes based on secondary structure of secreted proteins in HepG2 cells were observed, including the increase in the relative intensity of the band at 1004cm-1, 1445cm-1, 1674cm-1 and the decrease at 1074cm-1. These variations of Raman bands indicated that the species and conformation of secreted proteins in HepG2 cells changed. The measured Raman spectra of the two groups were separated into two distinct clusters with no overlap and high specificity and sensitivity by PCA. These results show that the combination of Raman spectroscopy and PCA analysis may be a powerful tool for distinguishing the secreted proteins between human hepatoma cells and normal human liver cells, provide a new thought to analyze the secreted proteins from cancer cells and find a novel cancer biomarker.

Diagnosis of Esophageal Tissue Based on Surface-Enhanced Raman Spectroscopy

Gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) was first applied to analyze esophageal cancer tissue and normal tissue in this paper. SERS measurements were performed on 62 tissue samples (31 esophageal carcinoma tissues and 31 normal tissues) obtained from 31 patients. Principal components analysis (PCA) combined with linear discriminant analysis (LDA) were employed to analyze and classify the tissue SERS spectra acquired from esophageal cancer and normal tissues. The diagnostic algorithms based on PCA-LDA yielded high diagnostic sensitivity (90.3%) and specificity (90.3%). Receiver operating characteristic (ROC) curve was employed to confirm the effectiveness of PCA-LDA multivariate analysis. Tentative assignments of the tissue SERS spectra suggested some changes in protein structure, a decrease in the relative amounts of phospholipids, an increase in the percentage of tryptophan, histone, tyrosine and phenylalanine contents in tumor tissue as compared to that of normal subject. The results from our exploratory study demonstrated that gold nanoparticle based tissue SERS spectroscopy in conjunction with PCA-LDA analysis can differentiate esophageal cancer from normal esophageal tissue samples with high accuracy. Tissue SERS spectroscopy may be a potentially clinically useful tool for the early diagnosis of esophageal cancer.

Esophageal cancer detection based on two-photon excitation fluorescence combined with membrane electrophoresis of blood serum

Nonlinear optical spectroscopy has wide applications in the medical field with special advantages. Through combining nonlinear optical spectroscopy with membrane electrophoresis, we endeavored to develop a novel method for blood serum analysis for cancer detection applications. In this method, albumin and globin are isolated from blood serum by membrane electrophoresis to perform two-photon excitation fluorescences (TPEF) spectral analysis. The obtained spectra present rich signatures of the biochemical constituents of whole proteins. We evaluated the utility of this method by analyzing albumin and globin samples of blood serum from esophageal cancer patients and healthy volunteers. Twophoton excitation fluorescences revealed that esophageal cancer group can be unambiguously discriminated from the normal group, and I457/I639, I511/I639, and I543/I639 ratios can be used as indicators to diagnose early esophageal cancer. These results are very promising for developing a label-free, non-invasive clinical tool for early cancer detection and screening.

Based on surface-enhanced Raman spectroscopy analysis of serum albumin in different stages of liver disease for early screening primary liver cancer

Despite the introduction of high-technology methods of detection and diagnosis, screening of primary liver cancer (PLC) remains imperfect. To diagnosis PLC earlier, Surface-enhanced Raman spectroscopy (SERS) coupled with cellulose-acetate membrane electrophoresis were introduced to separate human serum albumin and SERS spectra. Three groups (15 normal persons’ samples, 17 hepatitis/cirrhosis samples, 15 cases of PLC) of serum albumin were tested. Silver colloid was used to obtain SERS spectra of human serum albumin. Principal component analysis (PCA) and linear discriminant analysis (LDA) were also employed for statistical analysis. The mean Raman spectra of three groups and the difference spectra of any two suggested that the albumin has changed in liver patients. Compared to normal groups, some Raman peaks have shifted or even disappeared in hepatitis/cirrhosis and PLCs groups. The sensitivity and specificity between PLCs and normal groups is 80% and 93.3%. Among hepatitis/cirrhosis and normal groups, the sensitivity is 88.2% and specificity is also 93.3%. Besides, the sensitivity and specificity between PLCs and hepatitis/cirrhosis groups is 86.7% and 76.5%. All the above data and results indicated that early screening of PLC is potential by SERS in different stages of liver disease before cancer occurs.