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Evaluation of prognostic significance of granulocyte-related factors in cancer patients undergoing personalized peptide vaccination
- Publication Year :
- 2015
-
Abstract
- Since cancer vaccines do not always elicit beneficial effects in treated patients, identification of biomarkers for predicting clinical outcomes would be highly desirable. We previously reported that abnormal granulocytes present in peripheral blood mononuclear cells (PBMC) may contribute to poor prognosis in advanced prostate cancer patients receiving personalized peptide vaccination (PPV). In the current study, we examined whether soluble factors derived from granulocytes, such as matrix metalloproteinase 9 (MMP-9), myeloperoxidase (MPO), and arginase 1 (ARG1), and inhibitory cytokine TGFβ in pre-vaccination plasma were useful for predicting prognosis after PPV in advanced cancer patients. In biliary tract cancer (n=25), multivariate Cox regression analysis demonstrated that patients with higher plasma MMP-9 levels had a significantly worse overall survival (OS) [hazard ratio (HR) = 4.637, 95% confidence interval (CI) = 1.670 - 12.877, P = 0.003], whereas MPO, ARG1, or TGFβ levels were not correlated with OS. Similarly, patients with higher MMP-9 levels showed worse prognosis than those with lower MMP-9 levels in other types of advanced cancers, including non-small cell lung cancer (n=32, P = 0.037 by log-rank test), and pancreatic cancer (n=41, P = 0.042 by log-rank test). Taken together, plasma MMP-9 levels before vaccination might be potentially useful as a biomarker for selecting advanced cancer patients who would benefit from PPV.<br />This study was supported by a research program of the Project for Development of Innovative Research on Cancer Therapeutics (P-Direct), Ministry of Education, Culture, Sports, Science and Technology of Japan; a research program of the Regional Innovation Cluster Program of the Ministry of Education, Culture, Sports, Science and Technology of Japan; and Kurozumi Medical Foundation.
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1181856486
- Document Type :
- Electronic Resource