Purpose: This study was designed to evaluate molecular markers for the detection of micrometastasis in esophageal adenocarcinoma, define algorithms to distinguish positive from benign lymph nodes and to validate these findings in an independent tissue set and in patients with p(N0) esophageal adenocarcinoma.
Experimental design: Potential markers were identified through literature and database searches. All markers were analyzed by quantitative reverse transcription (QRT)-PCR on a limited set of primary tumors and benign lymph nodes. Selected markers were further evaluated on a larger tissue set and classification algorithms were generated for individual markers and combinations. Algorithms were statistically validated internally as well as externally on an independent set of lymph nodes. Selected markers were then used to identify occult disease in lymph nodes from 34 patients with p(N0) esophageal adenocarcinoma.
Results: Thirty-nine markers were evaluated, six underwent further analysis and five were analyzed in the external validation study. Two markers provided perfect classification in both the screening and validation sets, although parametric bootstrap analysis estimated 2% to 3% optimism in the observed classification accuracy. Several marker combinations also gave perfect classification in the observed data sets, and estimates of optimism were lower, implying more robust classification than with individual markers alone. Five of thirty-four patients with esophageal adenocarcinoma had positive nodes by multimarker QRT-PCR analysis and disease-free survival was significantly worse in these patients (P = 0.0023).
Conclusions: We have identified novel QRT-PCR markers for the detection of occult lymph node disease in patients with esophageal adenocarcinoma. The objective nature of QRT-PCR results, and the ability to detect occult metastases, make this an attractive alternative to routine pathology.