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.