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. 2014 Sep 16;5(8):696-705.
doi: 10.7150/jca.10094. eCollection 2014.

Circulating microRNAs in Pancreatic Juice as Candidate Biomarkers of Pancreatic Cancer

Jin Wang  1 , Massimo Raimondo  2 , Sushovan Guha  3 , Jinyun Chen  4 , Lixia Diao  5 , Xiaoqun Dong  6 , Michael B Wallace  2 , Ann M Killary  7 , Marsha L Frazier  8 , Timothy A Woodward  2 , Jing Wang  5 , Subrata Sen  7
Affiliations

Circulating microRNAs in Pancreatic Juice as Candidate Biomarkers of Pancreatic Cancer

Jin Wang et al. J Cancer. .

Abstract

Development of sensitive and specific biomarkers, preferably those circulating in body fluids is critical for early diagnosis of cancer. This study performed profiling of microRNAs (miRNAs) in exocrine pancreatic secretions (pancreatic juice) by microarray analysis utilizing pancreatic juice from 6 pancreatic ductal adenocarcinoma (PDAC) patients and two pooled samples from 6 non-pancreatic, non-healthy (NPNH) as controls. Differentially circulating miRNAs were subsequently validated in 88 pancreatic juice samples from 50 PDAC, 19 chronic pancreatitis (CP) patients and 19 NPNH controls. A marked difference in the profiles of four circulating miRNAs (miR-205, miR-210, miR-492, and miR-1427) was observed in pancreatic juice collected from patients with PDAC and those without pancreatic disease. Elevated levels of the four miRNAs together predicted PDAC with a specificity of 88% and sensitivity of 87%. Inclusion of serum CA19-9 level increased the sensitivity to 91% and the specificity to 100%. Enrichment of the four miRNAs in pancreatic juice was associated with decreased OS, as was the combination of miR-205 and miR-210. Higher contents of miR-205 and miR-210 were also associated with lymph node metastasis. Elevated levels of circulating miR-205, miR-210, miR-492, and miR-1247 in pancreatic juice are, therefore, promising candidate biomarkers of disease and poor prognosis in patients with PDAC.

Keywords: biomarker; circulating; miRNA; pancreatic cancer.; pancreatic juice.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
Hierarchical clustering analysis of microRNA microarray expression profile. (A) Clusters of patients with pancreatic ductal adenocarcinoma (PDAC) and non-pancreatic, non-healthy controls (NPNH). (B) Hierarchical clustering of microRNA expression in PDAC pancreatic juice samples with similar miRNA profiles were grouped together, which showed that miR-492, miR-1247, miR-205 and miR-210 were in the same cluster.
Figure 2
Figure 2
Quantitative real-time polymerase chain reaction (qRT-PCR) and Locked nucleic acid in situ hybridization (LNA-ISH) analysis of expression levels of microRNAs. (A) qRT-PCR analysis of relative expression levels of 4 microRNAs (miR-205, miR-210, miR-492, and miR-1247) in pancreatic juice samples from patients with pancreatic ductal adenocarcinoma (PDAC), patients with chronic pancreatitis (CP), and non-pancreatic, non-healthy (NPNH) controls. The relative abundance of four miRNAs, normalized to the level of RNU6B, significantly varied in pancreatic juice samples from patients with PDAC, CP and NPNH. (B) LNA-ISH-IHC images showing miR-492 expression in 3 (J101, J16, J39) pancreatic ductal adenocarcinoma tissue samples (magnification ×100). (C) The graph shows qRT-PCR results for miR-492 in pancreatic juice samples from the same patients.
Figure 3
Figure 3
Receiver operating characteristic curves (ROC) and Kaplan-Meier plots showing association of pancreatic juice miRNA profiles in PDAC patients and their clinical outcome. (A) Receiver operating characteristic curves showing expression levels of individual microRNAs (miR-205, miR-210, miR-492, and miR-1247), CA19-9, and a combination. (B) Kaplan-Meier overall survival curves for patients with pancreatic ductal adenocarcinoma with high levels of both miR-205 and miR-210 at or above the median (shown in green); either miR-205 or miR-210, or neither upregulated in pancreatic juice samples (shown in blue). The curves were compared using univariate (log-rank) analysis.
See this image and copyright information in PMC

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