Int J Med Sci 2020; 17(11):1550-1560. doi:10.7150/ijms.46780 This issue
Department of Urology, The First Affiliated Hospital of Soochow University, 215006, Suzhou, Jiangsu, China.
#These authors contribute equally to the current work.
Background: Matrix Metalloproteinases (MMPs) play an indispensable role in the initial alteration and development of PCa. We tried to generate an MMP-related prognostic signature (MMPS) in prostate cancer (PCa).
Methods: TCGA-PRAD, MSKCC/GSE21032, GSE116918, GSE70769 cohorts were enrolled to assess the prognostic value of MMPs. The least absolute shrinkage and selection operator (LASSO) Cox regression was employed to generate the MMPS signature. The log-rank test and Kaplan-Meier (K-M) survival curve were applied to show the difference RFS, The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) was plotted to predict the accuracy of signature. CIBERSORT was conducted to analyze the different immune infiltration in MMPS-H and MMPS-L groups. Potential signaling pathways activated in the MMPS-H groups by Metascape.
Results: MMP1, MMP7, MMP11, MMP24 and MMP26 were selected by LASSO regression and established the MMPS predict signature. The MMPS showed the high prognostic value in TCGA-PRAD training cohort (AUC=0.714) and validation cohorts (GSE116918: AUC=0.976, GSE70769: AUC=0.738, MSKCC: AUC=0.793). Pid integrin1 pathway, G2M checkpoint, and response to growth factor signaling pathways were activated in MMPS-H group, patients with the high MMPS risk score and low M2 macrophage showed the worst recurrence-free survival (RFS).
Conclusion: MMPs involved and played an essential role in the tumorigenesis and biochemical recurrence in PCa patients. The MMPS signature could accurately predict the recurrence of PCa patients and validated in several cohorts.
Keywords: prostate cancer, matrix metalloproteinases, prognostic signature, LASSO regressio