Surface-Enhanced Raman Spectroscopic (SERS) Characterization of Low Molecular Weight Fraction of the Serum of Breast Cancer Patients with Principal Component Analysis (PCA) and Partial Least Square-Discriminant Analysis (PLS-DA)

Abstract

Vibrational spectroscopic techniques including Raman spectroscopy have been increasingly used for the analysis of body fluids particularly blood serum. Low molecular weight protein fractions (LMWFs) present in blood serum are usually associated with pathological condition related to disease. However, human serum analysis is challenging because these LMWFs are dominated by high molecular weight proteins, making analysis by Raman spectroscopy difficult. In the current study, in order to overcome this limitation, the separation of the high molecular weight fraction (HMWF) was done by centrifugal filtration of the sera from breast cancer patients using 50 kDa filters. The filtrate was analyzed by surface-enhanced Raman spectroscopy (SERS). Comparison of the SERS spectral features of the whole serum and their filtrate fraction obtained by ultra-centrifugation indicate that this approach is capable of potentially targeting small circulating biomarkers dominated by the HMWF in unmodified serum. SERS spectra of the filtrate fractions of modified disease samples contain prominent peaks at 477, 684, 743, 859, 1263, 1275 and 1512 cm⁻¹ in comparison to unmodified serum. The SERS peaks at 573, 594, 730, 743, 859, 963, 1103 and 1453 cm⁻¹ in spectra collected from cancerous serum filtrate fractions distinguished them from healthy samples. The spectra were further analyzed by principal component analysis (PCA) and partial least squares – discriminant analysis (PLS-DA). The validated PLS-DA model yielded classification of the cancerous and healthy samples with the sensitivity and specificity of 99% each.

Keywords:

• Breast cancer
• blood serum
• surface-enhanced Raman spectroscopy (SERS)
• principal component analysis (PCA)
• partial least squares – discriminant analysis (PLS-DA)

Disclosure statement

The authors have no competing financial or personal interests to declare regarding this work.

Additional information

Funding

The authors are highly thankful to Higher Education Commission (HEC) of Pakistan for providing financial support for this research work through grant # HEC-NRPU/8494..