A serum albumin analysis technique combining hydroxyapatite (HAp) and surface-enhanced Raman scattering for noninvasive breast cancer screening

Combining serum albumin via adsorption-exfoliation on hydroxyapatite particles (HAp) with surface-enhanced Raman scattering (SERS), we developed a novel quantitative analysis of albumin method from blood serum for breast cancer screening applications. For adults, the normal range of serum albumin is defined as 3.5-5.0 g/dL, and the levels <3.5 g/dL is called hypoalbuminemia. The quantitatively analysis obtained by our HAp method had a good linear relationship from 1 to 10 g/dL. More importantly, the lower limit of detection was less than the albumin prognostic factor for disease (3.5 g/dL). Serum albumin was adsorbed and exfoliated by HAp from serum samples of breast cancer patients and healthy volunteers, and then mixed with silver colloids to perform SERS spectral analysis. Subtle changes in the SERS spectra of serum proteins indicated that some specific biomolecular contents and albumin secondary structures change with cancer progression. Principal component analysis (PCA), as a spectral dimensionality reduction method, combining with a linear discriminant analysis (LDA) was employed to screen and classify breast cancer. Based on the PCA-LDA algorithm, yielding the diagnostic sensitivity and specificity of breast cancer patients were 95% and 90%, respectively. This exploratory work demonstrated that HAp adsorbed-exfoliated serum proteins combined with SERS spectroscopy has great potential for label-free and non-invasive screening of breast cancer.