Identification of potential serum biomarkers for gastric cancer by a novel computational method, multiple normal tissues corrected differential analysis

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Title
Identification of potential serum biomarkers for gastric cancer by a novel computational method, multiple normal tissues corrected differential analysis
Author(s)
Mirang Kim; H J Kim; B Y Choi; Jeong Hwan Kim; K S Song; S M Noh; J C Kim; D S Han; Seon-Young Kim; Yong Sung Kim
Bibliographic Citation
Clinica Chimica Acta, vol. 413, no. 3, pp. 428-433
Publication Year
2012
Abstract
Background: Genes specifically expressed in one or a few tissues and upregulated in tumors are potentially good serum biomarkers. Methods: By applying a recently developed computational method, called multiple normal tissues corrected differential analysis (MNTDA), we identified genes that are likely to be upregulated in the blood of gastric cancer patients as compared to normal controls. Results: We identified four genes (MMP-1, MMP-3, MMP-12, and CXCL5) as potential serum biomarkers for gastric cancer. Of these four genes, only MMP-1 was significantly upregulated in the sera of 40 gastric cancer patients, as compared to 40 control sera. The same pattern was observed in the second cohort of 80 gastric cancer patients and 80 controls. In a combined analysis, the level of serum MMP-1 in gastric cancer patients was significantly higher than the level in control samples (P< 0.0001). The use of MMP-1 was 62.5% sensitive and 62.5% specific in detecting gastric cancer patients. Patients with high serum levels of MMP-1 had a significantly worse outcome than patients with low serum MMP-1 levels. Finally, we determined that preoperative serum MMP-1 levels were prognostic, independent of tumor stage. Conclusions: MMP-1 is a potential prognostic marker for gastric cancer patients after gastrectomy.
Keyword
Gastric cancerMMP-1Prognostic biomarker
ISSN
0009-8981
Publisher
Elsevier
DOI
http://dx.doi.org/10.1016/j.cca.2011.10.026
Type
Article
Appears in Collections:
Aging Convergence Research Center > 1. Journal Articles
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