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S100A10, a novel biomarker in pancreatic ductal adenocarcinoma
Pancreatic cancer is arguably the deadliest cancer type. The efficacy of current therapies is often hindered by the inability to predict patient outcome. As such, the development of tools for early detection and risk prediction is key for improving outcome and quality of life. Here, we introduce the...
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Published in: | Molecular oncology 2018-11, Vol.12 (11), p.1895-1916 |
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Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Pancreatic cancer is arguably the deadliest cancer type. The efficacy of current therapies is often hindered by the inability to predict patient outcome. As such, the development of tools for early detection and risk prediction is key for improving outcome and quality of life. Here, we introduce the plasminogen receptor S100A10 as a novel predictive biomarker and a driver of pancreatic tumor growth and invasion. We demonstrated that S100A10 mRNA and protein are overexpressed in human pancreatic tumors compared to normal ducts and nonductal stroma. S100A10 mRNA and methylation status were predictive of overall survival and recurrence‐free survival across multiple patient cohorts. S100A10 expression was driven by promoter methylation and the oncogene KRAS. S100A10 knockdown reduced surface plasminogen activation, invasiveness, and in vivo growth of pancreatic cancer cell lines. These findings delineate the clinical and functional contribution of S100A10 as a biomarker in pancreatic cancer.
In this study, we perform a robust clinical and functional assessment of the plasminogen receptor S100A10 as a novel biomarker in pancreatic ductal adenocarcinoma patients. We demonstrated that S100A10 is overexpressed in pancreatic tumors and is modulated by oncogenic KRAS and DNA methylation. S100A10 also mediated in vivo tumor growth, plasminogen activation and invasion of pancreatic cancer cells. |
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ISSN: | 1574-7891 1878-0261 |
DOI: | 10.1002/1878-0261.12356 |