Abstract
BackgroundTreatment strategy for early gastric cancer depends on the probability of lymph node metastasis. The aim of this study is to develop a nomogram predicting lymph node metastasis in early gastric cancer using clinicopathological factors and biomarkers.MethodsA literature review was performed to identify biomarkers related to lymph node metastasis in gastric cancer. Seven markers were selected and immunohistochemistry was performed in 336 early gastric cancer tissues. Based on the multivariable analysis, a prediction model including clinicopatholgical factors and biomarkers was developed, and benefit of adding biomarkers was evaluated using the area under the receiver operating curve and net reclassification improvement. Functional study in gastric cancer cell line was performed to evaluate mechanism of biomarker.ResultsOf the seven biomarkers studied, α1 catenin and CD44v6 were significantly associated with lymph node metastasis. A conventional prediction model, including tumor size, histological type, lymphatic blood vessel invasion, and depth of invasion, was developed. Then, a new prediction model including both clinicopathological factors and CD44v6 was developed. Net reclassification improvement analysis revealed a significant improvement of predictive performance by the addition of CD44v6, and a similar result was shown in the internal validation using bootstrapping. Prediction nomograms were then constructed based on these models. In the functional study, CD44v6 was revealed to affect cell proliferation, migration and invasion.ConclusionsOverexpression of CD44v6 was a significant predictor of lymph node metastasis in early gastric cancer. The prediction nomograms incorporating CD44v6 can be useful to determine treatment plans in patients with early gastric cancer.
Highlights
Treatment strategy for early gastric cancer depends on the probability of lymph node metastasis
Of the seven biomarkers studied, α1 catenin and CD44v6 were significantly associated with lymph node metastasis
Net reclassification improvement analysis revealed a significant improvement of predictive performance by the addition of CD44v6, and a similar result was shown in the internal validation using bootstrapping
Summary
Treatment strategy for early gastric cancer depends on the probability of lymph node metastasis. Endoscopic resection is considered for tumors with a very low risk of lymph node metastasis. [3] recent studies reported considerable incidences of lymph node metastasis in tumors meeting the expanded criteria, and oncological safety of endoscopic treatment is still debated. Most studies have been undertaken in cases of advanced gastric cancer tissues, and few studies have reported significant association between biomarkers and lymph node metastasis in early gastric cancer tissues. The aim of this study is to develop a nomogram predicting lymph node metastasis in early gastric cancer using clinicopathological factors and biomarkers
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