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.
Early detection of hepatocellular carcinoma is difficult due to the absence of recognizable physical symptoms. In this study, Raman spectra of liver normal tissues and hepatocellular carcinoma tissues were measured by using silver nanoparticles based surface enhanced Raman spectroscopy (SERS), respectively. The mean Raman spectra of two groups are roughly similar. But the peaks intensity of hepatocellular carcinoma tissues at 722 cm-1 and 1049 cm-1 are obviously higher than those of normal tissues. Some peaks of hepatocellular carcinoma tissues have shifted by different degree. Besides, Raman peaks at 1004cm-1 had disappeared in normal tissue. The result suggested that SERS spectra can feature liver normal tissue and hepatocellular carcinoma tissue. Principal component analysis (PCA) coupled with linear discriminant analysis (LDA) was performed on the measured spectra. There were three most diagnostically significant PCs (PC3, PC9, and PC15, p<0.05) for discriminating these two groups. The diagnostic sensitivity and specificity both were 84.6%. The whole analysis of each sample needs less time-consumed and cost than other traditional methods in detecting and diagnosing HCC. The preliminary result suggests that SERS spectra can be a potential medical technology to detect and diagnose HCC.
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.
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.
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.
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