Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2009 Feb 21;15(7):865-70.
doi: 10.3748/wjg.15.865.

Diagnostic model of saliva protein finger print analysis of patients with gastric cancer

Zheng-Zhi Wu  1 , Ji-Guo Wang, Xiao-Li Zhang
Affiliations

Diagnostic model of saliva protein finger print analysis of patients with gastric cancer

Zheng-Zhi Wu et al. World J Gastroenterol. .

Abstract

Aim: To explore the method for early diagnosis of gastric cancer by screening the expression spectrum of saliva protein in gastric cancer patients using mass spectrometry for proteomics.

Methods: Proportional peptide mass fingerprints were obtained by analysis based on proteomics matrix-assisted laser desorption ionization time-of-flight/mass spectrometry. A diagnosis model was established using weak cation exchange magnetic beads to test saliva specimens from gastric cancer patients and healthy subjects.

Results: Significant differences were observed in the mass to charge ratio (m/z) peaks of four proteins (1472.78 Da, 2936.49 Da, 6556.81 Da and 7081.17 Da) between gastric cancer patients and healthy subjects.

Conclusion: The finger print mass spectrum of saliva protein in patients with gastric cancer can be established using gastric cancer proteomics. A diagnostic model for distinguishing protein expression mass spectra of gastric cancer from non-gastric-cancer saliva can be established according to the different expression of proteins 1472.78 Da, 2936.49 Da, 6556.81 Da and 7081.17 Da. The method for early diagnosis of gastric cancer is of certain value for screening special biological markers.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Sample spectrum showing a lower average peak value for proteins 1472.78 Da (A) and 2936.49 Da (B) in the normal group than in the gastric cancer group, and a higher value for proteins 6556.81 Da (C) and 7081.17 Da (D) in the normal group than in the gastric cancer group. Red line: Normal group; Green line: Gastric cancer group.
Figure 2
Figure 2
Three-dimensional map showing a lower average peak value for proteins 1472.78 Da (A) and 2936.49 Da (B) in normal group than in gastric cancer group, and a higher value for proteins 6556.81 Da (C) and 7081.17 Da (D) in normal group in gastric cancer group. Red line: Normal group; Green line: Gastric cancer group.
Figure 3
Figure 3
Complete mass spectrum of proteins 1472.78 Da, 2936.49 Da, 6556.81 Da and 7081.17 Da, respectively.
Figure 4
Figure 4
Complete three-dimensional mass spectrum of proteins 1472.78 Da, 2936.49 Da, 6556.81 Da and 7081.17 Da, respectively. Red line: Normal group; Green line: Gastric cancer group.
See this image and copyright information in PMC

References

    1. Vitzthum F, Behrens F, Anderson NL, Shaw JH. Proteomics: from basic research to diagnostic application. A review of requirements & needs. J Proteome Res. 2005;4:1086–1097. - PubMed
    1. Liao AJ, Su Q, Wang X, Zeng B, Shi W. Isolation and bioinformatics analysis of differentially methylated genomic fragments in human gastric cancer. World J Gastroenterol. 2008;14:1333–1338. - PMC - PubMed
    1. Hofman LF. Human saliva as a diagnostic specimen. J Nutr. 2001;131:1621S–1625S. - PubMed
    1. Hu S, Loo JA, Wong DT. Human saliva proteome analysis and disease biomarker discovery. Expert Rev Proteomics. 2007;4:531–538. - PubMed
    1. Papale M, Pedicillo MC, Di Paolo S, Thatcher BJ, Lo Muzio L, Bufo P, Rocchetti MT, Centra M, Ranieri E, Gesualdo L. Saliva analysis by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF/MS): from sample collection to data analysis. Clin Chem Lab Med. 2008;46:89–99. - PubMed

Publication types

MeSH terms

Substances