Identification of potential diagnostic biomarkers in MMPs for pancreatic carcinoma

Pancreatic cancer (PC) is a malignant tumor which ranks fourth in cancer-related death. However, the specificity and sensitivity of traditional biomarkers such as carbohydrate antigen 19-9 no longer meet the clinical requirements. Tools as ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA) were used to analyze the differential expression of matrix metalloproteinases (MMPs) in PC and adjacent tissues. For further analysis, we adopted database for annotation, visualization and integrated discovery (DAVID 6.8), transcriptional regulatory relationships unraveled by sentence-based text (TRRUST) and other tools. We also identified drugs targeted the selected MMPs. Eight MMPs (MMP1, MMP2, MMP7, MMP9, MMP11, MMP12, MMP14, and MMP28) were differentially expressed in PC and adjacent tissue. MMP1 (P = .0189), MMP7 (P = .000216), MMP11 (P = .0209), MMP14 (P = .00611) were correlated with the pathological stages of PC. Patients with higher expression of MMP1 (P = .0011), MMP2 (P = .011), MMP7 (P = .0081), MMP9 (P = .046), MMP11 (P = .0019), MMP12 (P = .0011), MMP14 (P = .0011), and MMP28 (P = 6.3e-06) showed poor prognosis. Ten transcription factors were associated with the up-regulation of selected MMPs. Marimastat (DB00786) was found to target selected MMPs. Our research revealed that selected MMPs played an important role in the early diagnosis and prognosis of PC.