Science China Life Sciences

, Volume 54, Issue 9, pp 828–834

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

  • ShangYuan Feng
  • JianJi Pan
  • YanAn Wu
  • Duo Lin
  • YanPing Chen
  • GangQin Xi
  • JuQiang Lin
  • Rong Chen
Open Access
Research Papers

DOI: 10.1007/s11427-011-4212-8

Cite this article as:
Feng, S., Pan, J., Wu, Y. et al. Sci. China Life Sci. (2011) 54: 828. doi:10.1007/s11427-011-4212-8
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Abstract

A surface-enhanced Raman spectroscopy (SERS) method combined with multivariate analysis was developed for non-invasive gastric cancer detection. SERS measurements were performed on two groups of blood plasma samples: one group from 32 gastric patients and the other group from 33 healthy volunteers. Tentative assignments of the Raman bands in the measured SERS spectra suggest interesting cancer-specific biomolecular changes, including an increase in the relative amounts of nucleic acid, collagen, phospholipids and phenylalanine and a decrease in the percentage of amino acids and saccharide in the blood plasma of gastric cancer patients as compared with those of healthy subjects. Principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and cancer plasma with high sensitivity (79.5%) and specificity (91%). A receiver operating characteristic (ROC) curve was employed to assess the accuracy of diagnostic algorithms based on PCA-LDA. The results from this exploratory study demonstrate that SERS plasma analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of gastric cancers.

Keywords

surface-enhanced Raman spectroscopy (SERS) blood plasma gastric cancer detection 
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Copyright information

© The Author(s) 2011

This article is published under license to BioMed Central Ltd. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  • ShangYuan Feng
    • 1
  • JianJi Pan
    • 2
  • YanAn Wu
    • 3
  • Duo Lin
    • 1
  • YanPing Chen
    • 2
  • GangQin Xi
    • 1
  • JuQiang Lin
    • 1
  • Rong Chen
    • 1
  1. 1.Key Laboratory of OptoElectronic Science and Technology for MedicineMinistry of Education of China, Fujian Normal UniversityFuzhouChina
  2. 2.Fujian Provincial Tumor HospitalFuzhouChina
  3. 3.Fujian Provincial HospitalFuzhouChina

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