Comparison of surface enhanced Raman spectroscopy and Raman spectroscopy for the detection of breast cancer based on serum samples.

In this study, surface enhanced Raman spectroscopy (SERS) and Raman spectroscopy (RS), are employed for the classification of different stages of breast cancer using clinically diagnosed serum samples from breast cancer patients and healthy individuals. These serum samples are compared for their spectral features acquired by SERS and RS to establish spectral features that can be considered as spectral markers of breast cancer diagnosis and classification. SERS features related to DNA, proteins and lipids were observed which are solely observed in the serum samples of patients at different stages of breast cancer as compared to healthy samples. In order to explore the capability of SERS and RS and their comparison as an analytical tool for the efficient understanding of the progression of breast cancer, Principal Component Analysis (PCA) is done for the SERS and RS spectra of control, stage 2, stage 3 and stage 4. Furthermore, the Partial Least Squares-Discriminant Analysis (PLS-DA) was performed to compare the diagnostic performance of SERS and Raman spectroscopy for the classification of disease positive samples and healthy ones. The sensitivity and specificity and area under receiver operating characteristic (AUROC) curve values for SERS data were 90%, 98.4%, and 94% respectively which were higher as compared to Raman spectral data for which these values were found to be 88.2%, 97.7%, and 83.4% respectively.

Raman spectroscopy of blood plasma samples from breast cancer patients at different stages.

Raman spectroscopy was employed for the characterization of blood plasma samples from patients at different stages of breast cancer. Blood plasma samples taken from clinically diagnosed breast cancer patients were compared with healthy controls using multivariate data analysis techniques (principal components analysis - PCA) to establish Raman spectral features which can be considered spectral markers of breast cancer development. All the stages of the disease can be differentiated from normal samples. It is also found that stage 2 and 3 are biochemically similar, but can be differentiated from each other by PCA. The Raman spectral data of the stage 4 is found to be biochemically distinct, but very variable between patients. Raman spectral features associated with DNA and proteins were identified, which are exclusive to patient plasma samples. Moreover, there are several other spectral features which are strikingly different in the blood plasma samples of different stages of breast cancer. In order to further explore the potential of Raman spectroscopy as the basis of a minimally invasive screening technique for breast cancer diagnosis and staging, PCA-Factorial Discriminant Analysis (FDA) was employed to classify the Raman spectral datasets of the blood plasma samples of the breast cancer patients, according to different stages of the disease, yielding promisingly high values of sensitivity and specificity for all stages.

Raman spectral analysis for rapid screening of dengue infection.

Infection with the dengue virus is currently clinically detected according to different biomarkers in human blood plasma, commonly measured by enzyme linked immunosorbent assays, including non-structural proteins (Ns1), immunoglobulin M (IgM) and immunoglobulin G (IgG). However, there is little or no mutual correlation between the biomarkers, as demonstrated in this study by a comparison of their levels in samples from 17 patients. As an alternative, the label free, rapid screening technique, Raman spectroscopy has been used for the characterisation/diagnosis of healthy and dengue infected human blood plasma samples. In dengue positive samples, changes in specific Raman spectral bands associated with lipidic and amino acid/protein content are observed and assigned based on literature and these features can be considered as markers associated with dengue development. Based on the spectroscopic analysis of the current, albeit limited, cohort of samples, Principal Components Analysis (PCA) coupled Factorial Discriminant Analysis, yielded values of 97.95% sensitivity and 95.40% specificity for identification of dengue infection. Furthermore, in a comparison of the normal samples to the patient samples which scored low for only one of the biomarker tests, but high or medium for either or both of the other two, PCA-FDA demonstrated a sensitivity of 97.38% and specificity of 86.18%, thus providing an unambiguous screening technology.