Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer

Xu,Jianting; E,Changyong; Yao,Yongfang; Ren,Shuangchun; Wang,Guoqing; Jin,Haofan

doi:10.3892/ol.2016.5013

Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer

Authors:
- Jianting Xu
- Changyong E
- Yongfang Yao
- Shuangchun Ren
- Guoqing Wang
- Haofan Jin
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Affiliations: Cancer Centre, First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, Department of Hepatobiliary and Pancreatic Surgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Pathogenobiology, Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, Changchun, Jilin 130021, P.R. China
Published online on: August 16, 2016 https://doi.org/10.3892/ol.2016.5013
Pages: 2403-2408
Copyright: © Xu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Gastric cancer (GC) is one of the most common types of cancer of the digestive tract. Invasion of tumor cells into surrounding tissue and metastasis are among the most significant checkpoints in tumor progression. It is known that matrix metalloproteinases (MMPs) are involved in these processes; however, knowledge of their molecular interaction networks is still limited. Investigation of these networks could provide a more comprehensive picture of the function of MMPs in tumorigenesis. Furthermore, it could be used to develop new approaches to targeted anticancer therapy. In this study, we performed microarray analysis, and 1666 genes that were aberrantly expressed in GC tissues were identified (fold change >2, P<0.05). In addition, quantitative polymerase chain reaction analysis has confirmed that MMP1, MMP3, MMP7, MMP10, MMP11 and MMP12 expression is upregulated in GC. In addition, the MMP3 expression level was negatively correlated with GC differentiation (P<0.05). By integrating the microarray information and BioGRID and STRING databases, we constructed an MMP‑related molecular interaction network and observed that 18 genes (including MMPs) were highly expressed in GC tissues. The most enriched of these 18 genes in the Gene Oncology (GO) and pathway analysis were in extracellular matrix disassembly (GO biological process) and extracellular matrix‑receptor interaction (KEGG pathway), which are closely correlated with cancer invasion and metastasis. Collectively, our results suggest that the MMP‑related interaction network has a role in GC progression, and therefore further studies are required in order to investigate these network interactions in tumorigenesis.

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