Raman spectroscopy and multivariate analysis of serum samples from breast cancer patients
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Serum samples were studied using Raman spectroscopy and analyzed through the multivariate statistical methods of principal component analysis (PCA) and linear discriminant analysis (LDA). The blood samples were obtained from 11 patients who were clinically diagnosed with breast cancer and 12 healthy volunteer controls. The PCA allowed us to define the wavelength differences between the spectral bands of the control and patient groups. However, since the differences in the involved molecules were in their tertiary or quaternary structure, it was not possible to determine what molecule caused the observed differences in the spectra. The ratio of the corresponding band intensities were analyzed by calculating the p values and it was found that only seven of these band ratios were significant and corresponded to proteins, phospholipids, and polysaccharides. These specific bands might be helpful during screening for breast cancer using Raman Spectroscopy of serum samples. It is also shown that serum samples from patients with breast cancer and from the control group can be discriminated when the LDA is applied to their Raman spectra.
KeywordsBreast Cancer Multivariate Raman Serum Spectroscopy
The authors wish to thank CONACYT and CONCyTEG for financial support under grant numbers 42891-F, C02-44058, 03-02-K118-039-A01, and 06-04-K117-90-Anexo1. We want to thank the editor and the referees for their valuable comments to improve this work. Also, we thank Q. F. B. Yolanda Pérez Valentín and Martin Olmos.
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