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Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer
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; how...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038516/ https://www.ncbi.nlm.nih.gov/pubmed/27698806 http://dx.doi.org/10.3892/ol.2016.5013 |
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author | Xu, Jianting E, Changyong Yao, Yongfang Ren, Shuangchun Wang, Guoqing Jin, Haofan |
author_facet | Xu, Jianting E, Changyong Yao, Yongfang Ren, Shuangchun Wang, Guoqing Jin, Haofan |
author_sort | Xu, Jianting |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5038516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-50385162016-10-03 Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer Xu, Jianting E, Changyong Yao, Yongfang Ren, Shuangchun Wang, Guoqing Jin, Haofan Oncol Lett Articles 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. D.A. Spandidos 2016-10 2016-08-16 /pmc/articles/PMC5038516/ /pubmed/27698806 http://dx.doi.org/10.3892/ol.2016.5013 Text en Copyright: © Xu et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Xu, Jianting E, Changyong Yao, Yongfang Ren, Shuangchun Wang, Guoqing Jin, Haofan Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
title | Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
title_full | Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
title_fullStr | Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
title_full_unstemmed | Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
title_short | Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
title_sort | matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038516/ https://www.ncbi.nlm.nih.gov/pubmed/27698806 http://dx.doi.org/10.3892/ol.2016.5013 |
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