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Novel Prognostic Biomarkers of Gastric Cancer Based on Gene Expression Microarray: COL12A1, GSTA3, FGA and FGG

Overview
Journal Mol Med Rep
Specialty Molecular Biology
Date 2018 Aug 15
PMID 30106150
Citations 35
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Abstract

Gastric cancer (GC) is the fifth most common malignancy and the third leading cause of cancer‑associated mortality in the world. However, its mechanisms of occurrence and development have not been clearly elucidated. Furthermore, there is no effective tumor marker for GC. Using DNA microarray analysis, the present study revealed genetic alterations, screened out core genes as novel markers and discovered pathways for potential therapeutic targets. Differentially expressed genes (DEGs) between GC and adjacent normal tissues were identified, followed by pathway enrichment analysis of DEGs. Next, the protein‑protein interaction (PPI) network of DEGs was built and visualized. Analyses of modules in the PPI network were then performed to identify the functional core genes. Finally, survival analysis of core genes was conducted. A total of 256 genes were identified as DEGs between the GC samples and normal samples, including 169 downregulated and 87 upregulated genes. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, the present study identified a total of 143 GO terms and 21 pathways. Six clusters of functional modules were identified, and the genes associated with these modules were screened out as the functional core genes. Certain core genes, including collagen type 12 α1 chain (COL12A1), glutathione S‑transferase α3 (GSTA3), fibrinogen α chain (FGA) and fibrinogen γ chain (FGG), were the first reported to be associated with GC. Survival analysis suggested that these four genes, COL12A1 (P=0.002), GSTA3 (P=3.4x10‑6), FGA (P=0.00075) and FGG (P=1.4x10‑5), were significant poor prognostic factors and therefore, potential targets to improve diagnosis, optimize chemotherapy and predict prognostic outcomes.

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References
1.
Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M . Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2014; 136(5):E359-86. DOI: 10.1002/ijc.29210. View

2.
Allemani C, Weir H, Carreira H, Harewood R, Spika D, Wang X . Global surveillance of cancer survival 1995-2009: analysis of individual data for 25,676,887 patients from 279 population-based registries in 67 countries (CONCORD-2). Lancet. 2014; 385(9972):977-1010. PMC: 4588097. DOI: 10.1016/S0140-6736(14)62038-9. View

3.
Pinheiro D, Ferreira W, Leao Barros M, Araujo M, Rodrigues-Antunes S, Borges B . Perspectives on new biomarkers in gastric cancer: diagnostic and prognostic applications. World J Gastroenterol. 2014; 20(33):11574-85. PMC: 4155351. DOI: 10.3748/wjg.v20.i33.11574. View

4.
Uppal D, Powell S . Genetics/genomics/proteomics of gastric adenocarcinoma. Gastroenterol Clin North Am. 2013; 42(2):241-60. DOI: 10.1016/j.gtc.2013.01.005. View

5.
Takeno A, Takemasa I, Doki Y, Yamasaki M, Miyata H, Takiguchi S . Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis. Br J Cancer. 2008; 99(8):1307-15. PMC: 2570518. DOI: 10.1038/sj.bjc.6604682. View