Related Experiment Video
Updated: Oct 24, 2025

Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting
Published on: March 25, 2019
Label-free determination of liver cancer stages using surface-enhanced Raman scattering coupled with preferential
Siqi Gao1, Yamin Lin1, Mengmeng Zheng1
1MOE Key Laboratory of OptoElectronic Science and Technology for Medicine, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, Fujian, China. jqlin@fjnu.edu.cn.
Abstract:
Here, we explored a label-free albumin targeted analysis method by utilizing hydroxyapatite (HAp) to adsorb-release serum albumin, in conjunction with surface-enhanced Raman scattering (SERS) for screening liver cancer (LC) at different tumor (T) stages. Excitingly, albumin can be preferentially adsorbed by HAp as compared with other serum proteins. Moreover, we developed a novel strategy using a high concentration of PO43- solution as the albumin-release agent. This method overcomes the shortcomings of the traditional purification technology of serum albumin, which requires acid to release protein, and ensures that the structure and properties of albumin are not damaged. The SERS spectra of serum albumin obtained from three sample groups were analyzed to verify the feasibility of this new method: healthy volunteers (n = 35), LC patients with T1 stage (n = 25) and LC patients with T2-T4 stage (n = 23). Furthermore, principal component analysis (PCA) combined with linear discriminant analysis (LDA) was employed to classify the early T (T1) stage LC vs. normal group and advanced T (T2-T4) stage LC vs. normal group, yielding high diagnostic accuracies of 90.00% and 96.55%, respectively, which showed a 10% improvement in diagnostic accuracy for the early stage detection of cancer as compared with previous studies. The results of this exploratory work demonstrated that HAp-adsorbed-released serum albumin combined with SERS analysis has great potential for label-free, noninvasive and sensitive detection of different T stages of liver cancer.
More Related Videos
08:05Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
Published on: June 10, 2025
13:01Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
Published on: June 3, 2022