Expression of Matrix Metalloproteinase-7 Predicts Poor Prognosis in Gastric Cancer.


Journal

BioMed research international
ISSN: 2314-6141
Titre abrégé: Biomed Res Int
Pays: United States
ID NLM: 101600173

Informations de publication

Date de publication:
2022
Historique:
received: 05 12 2021
accepted: 31 03 2022
entrez: 2 5 2022
pubmed: 3 5 2022
medline: 4 5 2022
Statut: epublish

Résumé

To date, no potential markers have been established for predicting prognosis in gastric cancer. Matrix metalloproteinase-7 (MMP-7) has been suggested as a prognostic marker in several cancers. In this study, we aimed to determine the expression of the MMP-7 protein and its polymorphisms in gastric cancer tissues. The association between MMP-7 expression level and clinicopathological characteristics was also evaluated. MMP-7 protein expression and its polymorphisms were investigated in a total of 400 patients using immunohistochemistry and TaqMan SNP genotyping assays. The correlation of MMP-7 expression with clinicopathological characteristics, including tumor location, tumor size, histologic type, lymphatic invasion, vascular invasion, pathological T stage, pathological TNM stage, residual tumor, and CEA level, was investigated. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a multivariate Cox proportional hazards regression model. MMP-7 expression was found in 283 of 400 (70.75%) gastric cancer tissues. Expression of MMP-7 was significantly associated with poor clinicopathological characteristics, including vascular invasion (OR = 6.61, 95%CI = 4.26-9.89,

Identifiants

pubmed: 35496040
doi: 10.1155/2022/2300979
pmc: PMC9054443
doi:

Substances chimiques

Carcinoembryonic Antigen 0
MMP7 protein, human EC 3.4.24.23
Matrix Metalloproteinase 7 EC 3.4.24.23

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2300979

Informations de copyright

Copyright © 2022 Wareeporn Wattanawongdon et al.

Déclaration de conflit d'intérêts

The authors declare that there is no conflict of interest regarding the publication of this article.

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Auteurs

Wareeporn Wattanawongdon (W)

Suranaree University of Technology, Nakhon Ratchasima, Thailand.

Theeraya Simawaranon Bartpho (TS)

Suranaree University of Technology, Nakhon Ratchasima, Thailand.

Taweesak Tongtawee (T)

Suranaree University of Technology, Nakhon Ratchasima, Thailand.

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Classifications MeSH