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Tammy Glenn

Publications and source records attributed to Tammy Glenn.

3 recordsLinked to original sources

Accurate discrimination of pancreatic ductal adenocarcinoma and chronic pancreatitis using multimarker expression data and samples obtained by minimally invasive fine needle aspiration.

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.

Adult↗

Accurate discrimination of Barrett's esophagus and esophageal adenocarcinoma using a quantitative three-tiered algorithm and multimarker real-time reverse transcription-PCR.

Esophageal adenocarcinoma (EA) is increasing faster than any other cancer in the U.S. In this report, we first show that EA can be distinguished from normal esophagus (NE) and esophageal squamous cell carcinoma by plotting expression values for EpCam, TFF1, and SBEM in three-dimensional Euclidean space. For monitoring progression of Barrett's esophagus (BE) to EA, we developed a highly sensitive assay for limited quantities of tissue whereby 50 ng of RNA are first converted to cDNA using 16 gene-specific primers. Using a set of training tissues, we developed a novel quantitative three-tiered algorithm that allows for accurate (overall accuracy = 61/63, 97%) discrimination of BE versus EA tissues using only three genes. The gene used in the first tier of the algorithm is TSPAN: samples not diagnosed as BE or EA by TSPAN in the first tier are then subjected to a second-tier analysis using ECGF1, followed by a third-tier analysis using SPARC. Addition of TFF1 and SBEM to the first tier (i.e., a five-gene marker panel) increases the overall accuracy of the assay to 98% (62/63) and results in mean molecular diagnostic scores (+/- SD) that are significantly different between EA and BE samples (3.19 +/- 1.07 versus -2.74 +/- 1.73, respectively). Our results suggest that relatively few genes can be used to monitor progression of BE to EA.

Adenocarcinoma↗