Differential diagnosis of pancreatic tumors by molecular analysis of clinical specimens

Feasibility of fecal microRNAs as novel biomarkers for pancreatic cancer

Introduction

Pancreatic cancer (PCA) is an aggressive tumor that associates with high mortality rates. Majority of PCA patients are diagnosed usually at late tumor stages when the therapeutic options are limited. MicroRNAs (miRNA) are involved in tumor development and are commonly dysregulated in PCA. As a proof-of-principle study, we aimed to evaluate the potential of fecal miRNAs as biomarkers for pancreatic cancer.

Materials and Methods

Total RNA was extracted from feces using Qiagen's miRNA Mini Kit. For miRNA expression analyses we selected a subset of 7 miRNAs that are frequently dysregulated in PCA (miR-21, -143, -155, -196a, -210, -216a, -375). Subsequently, expression levels of these miRNAs were determined in fecal samples from controls (n = 15), chronic pancreatitis (n = 15) and PCA patients (n = 15) using quantitative TaqMan-PCR assays.

Results

All selected miRNAs were detectable in fecal samples with high reproducibility. Four of seven miRNAs (miR-216a, -196a, -143 und -155) were detected at lower concentrations in feces of PCA patients when compared to controls (p<0.05). Analysis of fecal miRNA expression in controls and patients with chronic pancreatitis and PCA revealed that the expression of miR-216a, -196a, -143 und -155 were highest in controls and lowest in PCA. The expression of the remaining three miRNAs (miR-21, -210 and -375) remained unchanged among controls and the patients with either chronic pancreatitis or PCA.

Conclusion

Our data provide novel evidence for the differential expression of miRNAs in feces of patients with PCA. If successfully validated in large-scale prospective studies, the fecal miRNA biomarkers may offer novel tools for PCA screening research.

Differentiation of multiple types of pancreatico-biliary tumors by molecular analysis of clinical specimens

Timely and accurate diagnosis of pancreatic ductal adenocarcinoma (PDAC) is critical in order to provide adequate treatment to patients. However, the clinical signs and symptoms of PDAC are shared by several types of malignant or benign tumors which may be difficult to differentiate from PDAC with conventional diagnostic procedures. Among others, these include ampullary cancers, solid pseudopapillary tumors, and adenocarcinomas of the distant bile duct, as well as inflammatory masses developing in chronic pancreatitis. Here, we report an approach to accurately differentiate between these different types of pancreatic masses based on molecular analysis of biopsy material. A total of 156 bulk tissue and fine needle aspiration biopsy samples were analyzed using a dedicated diagnostic cDNA array and a composite classification algorithm developed based on linear support vector machines. All five histological subtypes of pancreatic masses were clearly separable with 100% accuracy when using all 156 individual samples for classification. Generalized performance of the classification system was tested by 10 × 10-fold cross validation (100 test runs). Correct classification into the five diagnostic groups was demonstrated for 81.5% of 1,560 test set predictions. Performance increased to 85.3% accuracy when PDAC and distant bile duct carcinomas were combined in a single diagnostic class. Importantly, overall sensitivity of detection of malignant disease was 92.2%. The molecular diagnostic approach presented here is suitable to significantly aid in the differential diagnosis of undetermined pancreatic masses. To our knowledge, this is the first study reporting accurate differentiation between several types of pancreatico-biliary tumors in a single molecular analytical procedure.

Global microRNA expression profiling of microdissected tissues identifies miR-135b as a novel biomarker for pancreatic ductal adenocarcinoma

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% CI=(80.5, 98.5)] and 93.4% [95% CI=(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.

Advances in pancreatic cancer detection

Pancreatic cancer represents a major challenge for research studies and clinical management. No specific tumor marker for the diagnosis of pancreatic cancer exists. Therefore, extensive genomic, transcriptomic, and proteomic studies are being developed to identify candidate markers for use in high-throughput systems capable of large cohort screening. Understandably, the complex pathophysiology of pancreatic cancer requires sensitive and specific biomarkers that can improve both early diagnosis and therapeutic monitoring. The lack of a single diagnostic marker makes it likely that only a panel of biomarkers is capable of providing the appropriate combination of high sensitivity and specificity. Biomarker discovery using novel technology can improve prognostic upgrading and pinpoint new molecular targets for innovative therapy.

S100A4 mRNA is a diagnostic and prognostic marker in pancreatic carcinoma

OBJECTIVE

The aim of this study is to evaluate the clinical significance of S100A4 mRNA expression in pancreatic cancer.

MATERIALS AND METHODS

We obtained invasive ductal carcinoma (IDC) cells from ten lesions, intraductal papillary mucinous neoplasm (IPMN) cells from 20 lesions, and normal ductal cells from 20 normal pancreatic tissues by laser microdissection of frozen tissues. S100A4 expression was examined in the microdissected cells and in formalin-fixed paraffin-embedded (FFPE) samples of 87 pancreatic cancers by quantitative reverse transcription-polymerase chain reaction.

RESULTS

IDC cells expressed higher levels of S100A4 than IPMN cells (P = 0.002) and normal ductal cells (P < 0.001), although the difference between IPMN cells and normal ductal cells was not statistically significant (P = 0.070). Analysis of FFPE samples revealed that high S100A4 expression was significantly associated with a shorter overall survival (P = 0.023). In immunohistochemical analysis, the extent of S100A4 mRNA expression was significantly correlated with the expression of S100A4 protein (P = 0.028).

CONCLUSION

S100A4 could be a marker for malignancy in pancreatic tumors and for poor prognosis in patients with pancreatic cancer.

Biomarkers in the diagnosis and early detection of pancreatic cancer

BACKGROUND

Pancreatic cancer, owing to its raising incidence and aggressiveness, is a major challenge, both for research and for clinical management. As pancreatic cancer has a complex pathophysiology, in addition to improving the methods of early diagnosis, sensitive and specific biomarkers are a prerequisite.

OBJECTIVE

As there is no specific tumor marker for pancreatic cancer diagnosis, extensive genomics/transcriptomics and proteomics studies have been developed with the aim of finding candidate markers and contributing to high-throughput systems for large cohort screening.

METHODS

A literature review was done to study these biomarkers in relation to diagnosis, prognosis and therapy targets in pancreatic cancer.

RESULTS/CONCLUSION

For early diagnosis improvement, only a panel of soluble biomarkers could provide the appropriate combination between high sensitivity and specificity. Prognostic upgrading would benefit from biomarker discovery and validation performed on tumor tissue. New technology could delineate molecular targets for innovative therapy in pancreatic cancer.