Author
Listed:
- Jungho Yang
- Kyueng-Whan Min
- Dong-Hoon Kim
- Byoung Kwan Son
- Kyoung Min Moon
- Young Chan Wi
- Seong Sik Bang
- Young Ha Oh
- Sung-Im Do
- Seoung Wan Chae
- Sukjoong Oh
- Young Hwan Kim
- Mi Jung Kwon
Abstract
Background: Matrix metalloproteinase-9 (MMP-9) is associated with remodelling of the extracellular matrix and invasion in various cancers. Identifying proteins connected to high MMP-9 expression is important in explaining its mechanisms. Our study aims to shed light on genes associated with high MMP-9 expression and to discuss their clinical impact in breast cancer. Methods: We evaluated 173 breast cancer cases from the Kangbuk Samsung Hospital, with 1964 cases from the Molecular Taxonomy of Breast Cancer International Consortium database serving as a validation cohort. We investigated relationships between MMP-9 expression and clinicopathological characteristics. We then used gene set enrichment analyses to detect the association of genes with MMP-9 overexpression, and performed survival analyses to determine the significance of the gene in three independent cohorts. Results: High MMP-9 expression correlated with poor prognosis in univariate and multivariate analyses. Using gene set enrichment analysis, we found that tumour necrosis factor receptor superfamily member 12A (TNFRSF12A) was linked to high MMP-9 expression. In the survival analysis of three published data sets (METABRIC, GSE1456, GSE20685), high TNFRSF12A was relevant to a poor survival rate. Conclusions: High levels of TNFRSF12A associated with MMP-9 overexpression may be important to explain the progression of breast cancer, and survival could be improved using therapy targeting TNFRSF12A.
Suggested Citation
Jungho Yang & Kyueng-Whan Min & Dong-Hoon Kim & Byoung Kwan Son & Kyoung Min Moon & Young Chan Wi & Seong Sik Bang & Young Ha Oh & Sung-Im Do & Seoung Wan Chae & Sukjoong Oh & Young Hwan Kim & Mi Jung, 2018.
"High TNFRSF12A level associated with MMP-9 overexpression is linked to poor prognosis in breast cancer: Gene set enrichment analysis and validation in large-scale cohorts,"
PLOS ONE, Public Library of Science, vol. 13(8), pages 1-13, August.
Handle:
RePEc:plo:pone00:0202113
DOI: 10.1371/journal.pone.0202113
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