Purpose The diagnosis of pancreatic cystic lesions has increased dramatically. Most are benign, whereas some, such as intraductal papillary mucinous neoplasms (IPMN), represent precursors of pancreatic adenocarcinoma. Therapeutic stratification of IPMNs is challenging without precise information on dysplasia grade and presence of invasion. We assessed the diagnostic benefit of using miRNAs as biomarkers in pancreatic cyst fluid, focusing on IPMNs because of their frequency and malignant potential. Experimental Design RNA was extracted from 55 microdissected formalin-fixed, paraffin-embedded (FFPE) IPMN specimens, and 65 cyst fluid specimens aspirated following surgical resection. Expression of 750 miRNAs was evaluated with TaqMan miRNA Arrays using 22 FFPE and 15 cyst fluid specimens. Differential expression of selected miRNA candidates was validated in 33 FFPE and 50 cyst fluid specimens using TaqMan miRNA Assays. Results We identified 26 and 37 candidate miRNAs that distinguish low-grade from high-grade IPMNs using FFPE and cyst fluid specimens, respectively. A subset of 18 miRNAs, selected from FFPE and cyst fluid data, separated high-grade IPMNs from low-grade IPMNs, serous cystadenomas (SCA) and uncommon cysts, such as solid pseudopapillary neoplasms (SPN) and cystic pancreatic neuroendocrine tumors (PanNET). A logistic regression model using nine miRNAs allowed prediction of cyst pathology implying resection (high-grade IPMNs, PanNETs, and SPNs) versus conservative management (low-grade IPMNs, SCAs), with a sensitivity of 89%, a specificity of 100%, and area under the curve of 1. Conclusions We found candidate miRNAs that helped identify patients with high-grade IPMN and exclude nonmucinous cysts. These classifiers will require validation in a prospective setting to ultimately confirm their clinical usefulness.

Pancreatic ductal adenocarcinoma (PDAC) is known for its poor prognosis resulting from being diagnosed at an advanced stage. Accurate early diagnosis and new therapeutic modalities are therefore urgently needed. MicroRNAs (miRNAs), considered a new class of biomarkers and therapeutic targets, may be able to fulfill those needs. Combining tissue microdissection with global miRNA array analyses, cell type-specific miRNA expression profiles were generated for normal pancreatic ductal cells, acinar cells, PDAC cells derived from xenografts and also from macrodissected chronic pancreatitis (CP) tissues. We identified 78 miRNAs differentially expressed between ND and PDAC cells providing new insights into the miRNA-driven pathophysiological mechanisms involved in PDAC development. Having filtered miRNAs which are upregulated in the three pairwise comparisons of PDAC vs. ND, PDAC vs. AZ and PDAC vs. CP, we identified 15 miRNA biomarker candidates including miR-135b. Using relative qRT-PCR to measure miR-135b normalized to miR-24 in 75 FFPE specimens (42 PDAC and 33 CP) covering a broad range of tumor content, we discriminated CP from PDAC with a sensitivity and specificity of 92.9% [95% CI5(80.5, 98.5)] and 93.4% [95% CI5(79.8, 99.3)], respectively. Furthermore, the area under the curve (AUC) value reached of 0.97 was accompanied by positive and negative predictive values of 95% and 91%, respectively. In conclusion, we report pancreatic cell-specific global miRNA profiles, which offer new candidate miRNAs to be exploited for functional studies in PDAC. Furthermore, we provide evidence that miRNAs are well-suited analytes for development of sensitive and specific aid-in-diagnosis tests for PDAC.Pancreatic ductal adenocarcinoma (PDAC) is characterized by its late clinical presentation, early and aggressive local invasion and high metastatic potential. The lack of sensitive early detection strategies and its strong resistance to chemotherapy and radiation therapy compounds the overall very poor prognosis of PDAC, which has a median survival time following diagnosis of 3-5 months. Surgery is still the only effective treatment option, improving the median survival time to 10-20 months; however, at the time of diagnosis, only 20% of PDACs are amenable to surgery and cure is rarely achieved. 1 Thus, improved early diagnosis modalities as well as new therapeutic targets for the development of effective treatment strategies are urgently needed to improve the dismal prognosis of PDAC. MicroRNAs (miRNAs), a class of 18-23 nt noncoding RNAs, have gained much attention as a new family of molecules involved in cancer development 2,3 and thus are under investigation for their suitability as diagnostic biomarkers and therapeutic targets.miRNAs as biomarkers offer a number of advantages. First, compared with mRNAs, which are very sensitive to degradation, miRNAs are more stable in compromised human specimens (e.g., formalin-fixed paraffin-embedded; FFPE). 4,5 Second, their expression levels can be measured reliably in FFPE tissue sampl...

OBJECTIVES:Current diagnostic tools for pancreatic cysts fail to reliably differentiate mucinous from nonmucinous cysts. Reliable biomarkers are needed. MicroRNAs (miRNA) may offer insights into pancreatic cysts. Our aims were to (1) identify miRNAs that distinguish benign from both premalignant cysts and malignant pancreatic lesions using formalin-fixed, paraffin-embedded (FFPE) pathology specimens; (2) identify miRNAs that distinguish mucinous cystic neoplasm (MCN) from branch duct-intraductal papillary mucinous neoplasm (BD-IPMN).METHODS:A total of 69 FFPE pancreatic specimens were identified: (1) benign (20 serous cystadenoma (SCA)), (2) premalignant (10 MCN, 10 BD-IPMN, 10 main duct IPMN (MD-IPMN)), and (3) malignant (19 pancreatic ductal adenocarcinoma (PDAC)). Total nucleic acid extraction was performed followed by miRNA expression profiling of 378 miRNAs interrogated using TaqMan MicroRNA Arrays Pool A and verification of candidate miRNAs. Bioinformatics was used to generate classifiers.RESULTS:MiRNA profiling of 69 FFPE specimens yielded 35 differentially expressed miRNA candidates. Four different 4-miRNA panels differentiated among the lesions: one panel separated SCA from MCN, BD-IPMN, MD-IPMN, and PDAC with sensitivity 85% (62, 97), specificity 100% (93, 100), a second panel distinguished MCN from SCA, BD-IPMN, MD-IPMN, and PDAC with sensitivity and specificity 100% (100, 100), a third panel differentiated PDAC from IPMN with sensitivity 95% (76, 100) and specificity 85% (72, 96), and the final panel diagnosed MCN from BD-IPMN with sensitivity and specificity approaching 100%.CONCLUSIONS:MiRNA profiling of surgical pathology specimens differentiates serous cystadenoma from both premalignant pancreatic cystic neoplasms and PDAC and MCN from BD-IPMN.

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Diagnosis of pancreatic cancer remains a clinical challenge. Both chronic pancreatitis and pancreatic cancer may present with similar symptoms and similar imaging features, often leading to incorrect interpretation. Thus, the use of an objective molecular test that can discriminate between chronic pancreatitis and pancreatic cancer will be a valuable asset in obtaining a definitive diagnosis of pancreatic cancer. Following Clinical Laboratory Improvement Amendments and College of American Pathologists guidelines, Asuragen Clinical Services Laboratory has developed and validated a laboratory-developed test, miRInform(®) Pancreas, to aid in the identification of pancreatic ductal adenocarcinoma. This molecular diagnostic tool uses reverse-transcription quantitative PCR to measure the expression difference between two miRNAs, miR-196a and miR-217, in fixed tissue specimens. This article describes the test validation process as well as determination of performance parameters of miRInform Pancreas.

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