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Abstract
Matrix metalloproteinases (MMPs) play an essential role in various physiological events. Recent studies have revealed its carcinogenic effect in malignancies. However, the different expression patterns, prognostic value, and immunological value of MMPs in pancreatic ductal adenocarcinoma (PDAC) are yet to be comprehensively explored. We utilized Gene Expression Profiling Interactive Analysis (GEPIA) and Gene Expression Omnibus databases to explore the abnormal expression of MMPs in PDAC. Then, Kaplan–Meier survival curve and Cox regression analysis were performed to assess the prognostic value of MMPs. Association between MMPs expression and clinicopathological features was analyzed through UALCAN website. Functional annotations and GSEA analysis were performed to excavate the possible signaling pathways involving prognostic-related MMP. TIMER and TISCH database were used to performed immune infiltration analysis. The expression of prognostic-related MMP in pancreatic cancer cell lines and normal pancreatic cells was detected by Real time quantitative PCR. We observed that 10 MMP genes were consistently up-regulated in GEPIA and GSE62452 dataset. Among them, five highly expressed MMPs (MMP1, MMP3, MMP11, MMP14, MMP28) were closely related to poor clinical outcomes of PDAC patients. Cox regression analysis indicated MMP28 was a risk factor influencing the overall survival of patients. In the clinicopathological analysis, up-regulated MMP28 was significantly associated with higher tumor grade and the mutation status of TP53. GSEA analysis demonstrated that high expression of MMP28 was involved in “interferon_alpha_response” and “P53_pathway”. Immune infiltration analysis showed that there was no correlation between MMP28 expression and immune cell infiltration. Single-cell sequencing analysis showed MMP28 has strong correlations with malignant cells and stromal cells infiltration in the tumor microenvironment. And MMP28 was highly expressed in various pancreatic cancer cell lines. In conclusion, MMP28 may represent a potential prognosis biomarker and novel therapeutic molecular targets for PDAC.
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Details
1 The First Hospital of China Medical University, Department of Laboratory Medicine, Shenyang, People’s Republic of China (GRID:grid.412636.4)
2 Sichuan University, West China Medical School, Chengdu, People’s Republic of China (GRID:grid.13291.38) (ISNI:0000 0001 0807 1581)
3 China Medical University, Department of Clinical Laboratory Diagnostics, Shenyang, People’s Republic of China (GRID:grid.412449.e) (ISNI:0000 0000 9678 1884)
4 The First Hospital of China Medical University, GCP Center, Shenyang, People’s Republic of China (GRID:grid.412636.4)