Plasma microRNA panels to diagnose pancreatic cancer: Results from a multicenter study
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Zhe Cao1,*, Chang Liu2,*, Jianwei Xu3,*, Lei You1, Chunyou Wang4, Wenhui Lou5, Bei Sun6, Yi Miao7, Xubao Liu8, Xiaowo Wang2, Taiping Zhang1, Yupei Zhao1
1Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
2MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST/Department of Automation, Tsinghua University, Beijing, 100084, China
3Department of General Surgery, Qilu Hospital, Shandong University, Jinan, 250012, China
4Department of General Surgery, Pancreatic Disease Institute, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430022, China
5Department of Pancreatic Surgery, Zhong Shan Hospital, Fudan University, Shanghai, 200032, China
6Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Harbin Medical University, Harbin, 150001, China
7Department of General Surgery, The First Affiliated Hospital, Nanjing Medical University, Nanjing, 210029, China
8Department of Hepatopancreatobiliary Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China
*These authors contributed equally to this work and are co-first authors
Xiaowo Wang, email: firstname.lastname@example.org
Taiping Zhang, email: email@example.com
Yupei Zhao, email: firstname.lastname@example.org
Keywords: pancreatic cancer, microRNA panels, multicenter study, diagnosis
Received: February 15, 2016 Accepted: May 04, 2016 Published: May 19, 2016
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.
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