Breast cancer detection based on serum sample surface enhanced Raman spectroscopy.

Abstract

Raman spectroscopy is a vibrational technique which provides information about the chemical structure. Nevertheless, since many chemicals are present in a sample at very low concentration, the Raman signal observed is extremely weak. In surface enhanced Raman scattering (SERS), Raman signals can be enhanced by many orders of magnitude when nanoparticles are used. To the best of our knowledge, this is the first report in the breast cancer detection based on serum SERS. The serum samples were obtained from 12 patients who were clinically diagnosed with advanced breast cancer and 15 controls. In the same proportion, the serum samples were mixed with colloidal gold nanoparticles of 40 nm using sonication. At least 10 spectra were collected of each serum sample using a Jobin-Yvon LabRAM Raman Spectrometer with a laser of 830 nm. Raw spectra were processed by carrying baseline correction, smoothing, and normalization and then analyzed using principle component analysis (PCA) and linear discriminant analysis (LDA). Raman spectra showed strongly enhanced bands in the 600-1800 cm (-1) range due to the nanoparticle colloidal clusters observed. These Raman bands allowed identifying biomolecules present at low concentration as amide I and III, β carotene, glutathione, tryptophan, tyrosine, and phenylalanine. Preliminary results demonstrated that SERS and PCA-LDA can be used to discriminate between control and cancer samples with high sensitivity and specificity. SERS allowed short exposures and required a minimal sample preparation. The preliminary results suggest that SERS and PCA-LDA could be an excellent support technique for the breast cancer detection using serum samples.