Surface Enhanced Raman Spectroscopy (SERS) for the Multiplex Detection of Braf, Kras, and Pik3ca Mutations in Plasma of Colorectal Cancer Patients.

In this paper, we discuss the use of a procedure based on polymerase chain reaction (PCR) and surface enhanced Raman spectroscopy (SERS) (PCR-SERS) to detect DNA mutations. Methods: This method was implemented by first amplifying DNA-containing target mutations, then by annealing probes, and finally by applying SERS detection. The obtained SERS spectra were from a mixture of fluorescence tags labeled to complementary sequences on the mutant DNA. Then, the SERS spectra of multiple tags were decomposed to component tag spectra by multiple linear regression (MLR). Results: The detection limit was 10-11 M with a coefficient of determination (R2) of 0.88. To demonstrate the applicability of this process on real samples, the PCR-SERS method was applied on blood plasma taken from 49 colorectal cancer patients to detect six mutations located at the BRAF, KRAS, and PIK3CA genes. The mutation rates obtained by the PCR-SERS method were in concordance with previous research. Fisher's exact test showed that only two detected mutations at BRAF (V600E) and PIK3CA (E542K) were significantly positively correlated with right-sided colon cancer. No other clinical feature such as gender, age, cancer stage, or differentiation was correlated with mutation (V600E at BRAF, G12C, G12D, G12V, G13D at KRAS, and E542K at PIK3CA). Visually, a dendrogram drawn through hierarchical clustering analysis (HCA) supported the results of Fisher's exact test. The clusters drawn by all six mutations did not conform to the distributions of cancer stages, differentiation or cancer positions. However, the cluster drawn by the two mutations of V600E and E542K showed that all samples with those mutations belonged to the right-sided colon cancer group. Conclusion: The suggested PCR-SERS method is multiplexed, flexible in probe design, easy to incorporate into existing PCR conditions, and was sensitive enough to detect mutations in blood plasma.

Detecting Esophageal Cancer Using Surface-Enhanced Raman Spectroscopy (SERS) of Serum Coupled with Hierarchical Cluster Analysis and Principal Component Analysis.

Serum samples taken from healthy individuals and pre- and post-operative esophageal cancer patients were analyzed using surface-enhanced Raman spectroscopy (SERS) to explore the feasibility of diagnosing esophageal cancer using the technique. The serum spectrum data were collected using a He-Ne laser of wavelength 632.8 nm. Differences in peaks assigned to nucleic acids, lipids, and proteins were found to be statistically significant between groups, which implies that corresponding serum alterations occur with the development of esophageal diseases. For quantitative analysis, the chemometric methods of hierarchical clustering analysis and principal component analysis were utilized on the obtained SERS spectra for classification with good results.

Noninvasive liver diseases detection based on serum surface enhanced Raman spectroscopy and statistical analysis.

In this paper, we investigated the feasibility of using surface enhanced Raman spectroscopy (SERS) of blood serum to discriminate liver cancer and liver cirrhosis patients from normal people. Serum taken from 44 healthy people, 45 liver cancer patients, 42 post-treatment liver cancer patients and 45 liver cirrhosis patients was measured. SERS peaks from these groups were compared and the assignments and biomedical meanings were analyzed and explained. In addition, support vector machine (SVM), partial least square-discriminant analysis (PLS-DA) and artificial neural networks (ANN) was used on the obtained SERS spectra to identify its diagnostic potential for liver diseases. PLS-SVM, PLS-DA and PLS-ANN indicated 91.5%, 89.2% and 90.3% accuracy, respectively. This preliminary study demonstrates that serum SERS can be used for liver cancer screening.

Different associations of CD45 isoforms with STAT3, PKC and ERK regulate IL-6-induced proliferation in myeloma.

In response to interleukin 6 (IL-6) stimulation, both CD45RO and CD45RB, but not CD45RA, translocate to lipid rafts. However, the significance of this distinct translocation and the downstream signals in CD45 isoforms-participated IL-6 signal are not well understood. Using sucrose fractionation, we found that phosphorylated signal transducer and activator of transcription (STAT)3 and STAT1 were mainly localized in lipid rafts in response to IL-6 stimulation, despite both STAT3 and STAT1 localizing in raft and non-raft fractions in the presence or absence of IL-6. On the other hand, extracellular signal-regulated kinase (ERK), and phosphorylated ERK were localized in non-raft fractions regardless of the existence of IL-6. The rafts inhibitor significantly impeded the phosphorylation of STAT3 and STAT1 and nuclear translocation, but had little effect on (and only postponing) the phosphorylation of ERK. This data suggests that lipid raft-dependent STAT3 and STAT1 pathways are dominant pathways of IL-6 signal in myeloma cells. Interestingly, the phosphorylation level of STAT3 but not STAT1 in CD45+ cells was significantly higher compared to that of CD45- cells, while the phosphorylation level of ERK in CD45+ myeloma cells was relatively low. Furthermore, exogenously expressed CD45RO/RB significantly enhanced STAT3, protein kinase C (PKC) and downstream NF-κB activation; however, CD45RA/RB inhibited IL-6-induced ERK phosphorylation. CD45 also enhanced the nuclear localization of STAT3 but not that of STAT1. In response to IL-6 stimulation, CD45RO moved into raft compartments and formed a complex with STAT3 and PKC in raft fraction, while CD45RA remained outside of lipid rafts and formed a complex with ERK in non-raft fraction. This data suggests a different role of CD45 isoforms in IL-6-induced signaling, indicating that while CD45RA/RB seems inhibit the rafts-unrelated ERK pathway, CD45RO/RB may actually work to enhance the rafts-related STAT3 and PKC/NF-κB pathways.