Abstract
Biomarkers for the early diagnosis of pancreatic cancer (PC) are urgent needed. Plasma microRNAs (miRNAs) might be used as biomarkers for the diagnosis of cancer. We analyzed 361 plasma samples from 6 surgical centers in China and performed machine learning approach. We gain insight of the association between the aberrant plasma miRNA expression and pancreatic disease. 671 microRNAs were screened in the discovery phase and 33 microRNAs in the training phase and 13 microRNAs in the validation phase. After the discovery phase and training phase, 2 diagnostic panels were constructed comprising 3 microRNAs in panel I (miR-486-5p, miR-126-3p, miR-106b-3p) and 6 microRNAs in panel II (miR-486-5p, miR-126-3p, miR-106b-3p, miR-938, miR-26b-3p, miR-1285). Panel I and panel II had high accuracy for distinguishing pancreatic cancer from chronic pancreatitis (CP) with area under the curve (AUC) values of 0.891 (Standard Error (SE): 0.097) and 0.889 (SE: 0.097) respectively, in the validation phase. Additionally, we demonstrated that the diagnostic value of the panels in discriminating PC from CP were comparable to that of carbohydrate antigen 19–9 (CA 19–9) 0.775 (SE: 0.053) (P = 0.1 for both). This study identified 2 diagnostic panels based on microRNA expression in plasma with the potential to distinguish PC from CP. These patterns might be developed as biomarkers for pancreatic cancer.
Highlights
Pancreatic cancer is a very lethal disease with the 5-year survival rate less than 5% [1]
Multivariable analysis demonstrated that 15 microRNAs had the potential to separate patients with pancreatic cancer from healthy controls
Compared with patients with chronic pancreatitis, 19 miRNAs were significantly dysregulated in patients with pancreatic cancer [16]
Summary
Pancreatic cancer is a very lethal disease with the 5-year survival rate less than 5% [1]. Diagnosis is the key strategy for improving the long-term outcome of pancreatic cancer. Current methods for the diagnosis of PC can be divided into two main categories: imaging techniques and serological markers [3]. The diagnostic performance of these tests is unsatisfactory, www.impactjournals.com/oncotarget for the diagnosis of early-stage PC [4]. Carbohydrate antigen 19-9 (CA 19-9) has been used for many years as a serum marker for PC diagnosis[5]. To improve the prognosis of PC, it is urgent to develop specific and noninvasive biomarkers for PC diagnosis, especially for early-stage tumors
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