Quantitative and direct serum albumin detection by label-free SERS using tunable hydroxyapatite nanostructure for prostate cancer detection.

With the aid of good biocompatibility and stability with hydroxyapatite (HAp) in protein separation and adsorption fields, we developed a novel extraction-isolation albumin analysis method by relying on the specific adsorption capacity of HAp, combining with surface-enhanced Raman spectroscopy (SERS) for prostate cancer screening. Two different nanostructures of HAp particles, including the HAp flower and HAp sphere, were synthesized with a hydrothermal method, and the targeted binding and extraction abilities of serum albumin of these two HAp particles were compared. By changing the morphology of the nanostructure, the albumin-adsorption capacity of HAp varied significantly. Compared with spherical HAp particles, HAp flower particles have more albumin binding sites per unit area. Thus, the HAp flower displayed the superior capacity for adsorption-release of albumin, which was further employed for clinical prostate cancer screening. Based on the superior adsorption-extraction ability of albumin of HAp flower, serum albumin was adsorbed and extracted by HAp flower from serum samples of prostate cancer patients (n = 30) and healthy volunteers (n = 30), and mixed with silver colloids to perform SERS spectral analysis. The partial least square-support vector machines (PLS-SVM) model is used to analyze the obtained serum albumin SERS spectra and establish the diagnostic model, the diagnostic accuracy was up to 95.00% for differentiating the normal volunteer from prostate patient groups. The results demonstrate that the PLS-SVM model provides superior performance in the classification of a prostate cancer diagnosis. Due to the advantages of simplicity and rapidness, the HAp flower-adsorbed-released albumin combined with SERS was expected to become a promising tool for prostate cancer detection.