Research Papers:

Clinically relevant circulating microRNA profiling studies in pancreatic cancer using meta-analysis

Zenglin Pei, Song-Mei Liu, Jing-Tao Huang, Xuan Zhang, Dong Yan, Qianlin Xia, Chunxia Ji, Weiping Chen, Xiaoyan Zhang, Jianqing Xu and Jin Wang _

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Oncotarget. 2017; 8:22616-22624. https://doi.org/10.18632/oncotarget.15148

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Zenglin Pei1, Song-Mei Liu2, Jing-Tao Huang2, Xuan Zhang1, Dong Yan3, Qianlin Xia1, Chunxia Ji1, Weiping Chen4, Xiaoyan Zhang1, Jianqing Xu1, Jin Wang1

1Scientific Research Center, Shanghai Public Health Clinical Center, Fudan University, Jinshan District, Shanghai 201508, P.R. China

2Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China

3Department of Medical Oncology, Beijing Chaoyang Hospital affiliated to Capital Medical University, Beijing, China

4Genomics Core, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA

Correspondence to:

Jin Wang, email: [email protected]

Keywords: pancreatic cancer, meta-analysis, diagnostics, multiple miRNA, SROC

Received: October 24, 2016     Accepted: January 25, 2017     Published: February 07, 2017


Background: Pancreatic cancer (PaCa) is the most lethal gastrointestinal (GI) tumor. Although many studies on differentially expressed miRNAs as candidate biomarkers of pancreatic cancer have been published, reliability of these findings generated from investigations performed in single laboratory settings remain unclear.

Results: There were 29 articles with a total of 2,225 patients and 1,618 controls included in this meta-analysis. The pooled sensitivity was 82% (95% CI, 79–85%); the specificity was 85% (95% CI, 79–89%); and area under the curve (AUC) was 0.89 (95% CI, 0.86–0.92). Subgroup analyses indicated that there were significant divergences between Caucasian and Asian subgroups for circulating miRNA analysis.

Materials And Methods: To comprehensively investigate the potential utility of miRNAs as biomarkers of the disease, we searched publications diagnosing PaCa using miRNAs from PubMed, Medline, Embase, Google Scholar and Chinese National Knowledge Infrastructure (CNKI) databases. The sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic (SROC) curve were used to examine the overall test performance, and heterogeneity was analyzed with the I2 test.

Conclusions: Our analysis demonstrated that multiple miRNAs (SEN: 85%; SPE: 89%; AUC: 0.93) were more accurate for diagnosing PaCa than a single miRNA (SEN: 78%; SPE: 79%; AUC: 0.84), and future studies are still needed to confirm the diagnostic value of these pooled miRNAs for PaCa.

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