These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Accurate discrimination of pancreatic ductal adenocarcinoma and chronic pancreatitis using multimarker expression data and samples obtained by minimally invasive fine needle aspiration. Author: Chen Y, Zheng B, Robbins DH, Lewin DN, Mikhitarian K, Graham A, Rumpp L, Glenn T, Gillanders WE, Cole DJ, Lu X, Hoffman BJ, Mitas M. Journal: Int J Cancer; 2007 Apr 01; 120(7):1511-7. PubMed ID: 17192896. Abstract: To augment cytological diagnosis of pancreatic ductal adenocarcinoma (PDAC) in tissue samples obtained by minimally invasive endoscopic ultrasound-guided fine needle aspiration, we investigated whether a small set of molecular markers could accurately distinguish PDAC from chronic pancreatitis (CP). Expression levels of 29 genes were first determined by quantitative real-time RT-PCR in a training set of tissues in which the final diagnosis was PDAC (n=20) or CP (n=10). Using receiver operator characteristic curve analysis, we determined that the single gene with the highest diagnostic accuracy for discrimination of CP vs. PDAC in the training study was urokinase plasminogen activator receptor (UPAR; AUC value = 0.895, 95% CI=0.728-0.976). In the set of test tissues (n=14), the accuracy of UPAR decreased to 79%. However, we observed that the addition of 6 genes (EPCAM2, MAL2, CEA5, CEA6, MSLN and TRIM29; referred to as the 6-gene classifier) to UPAR resulted in high accuracy in both training and testing sets. Excluding 3 samples (out of 44; 7%) for which results of the UPAR/6-gene classifier were "undefined," the accuracy of the UPAR/6-gene classifier was 100% in training samples (n=29), 92% in 12 test samples (p=0.004 that results were randomly generated; p=0.046 that the UPAR/6-gene classifier was comparable to UPAR alone; chi2 test), 100% in 3 samples for which the initial cytological diagnosis was "suspicious" and 98% (40/41) overall. Our results provide evidence that molecular marker expression data can be used to augment cytological analysis.[Abstract] [Full Text] [Related] [New Search]