Gene Expression Profile of Primary Gastric Cancer: Towards the Prediction of Lymph Node Status

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The identification of gastric tumors associated with a higher risk of lymph node metastasis could help surgeons select patients who may benefit from extended lymph node dissection. The aim of this study was to screen the genome in the search of primary gastric cancer gene expression profiles that might predict lymph node status.


The gene expression profile was evaluated in frozen tumor samples obtained from 32 patients with primary gastric adenocarcinomas. The array consisted of a duplicated spot panel of 5,541 human genes. To classify node-positive (N+) and node-negative (N-) cases, a logistic regression model was fitted optimizing the Akaike Information Criteria after a stepwise gene selection. The accuracy was evaluated by means of leave-one-out cross validation.


All patients underwent radical gastrectomy and extended lymphadenectomy. Of all the cases, 21 were N+ and 11 demonstrated no lymph node involvement (N-). After quality filtering, the analysis of variance selected a set of 136 genes potentially correlated with nodal involvement (P value <.05). Of these 136 genes, 5 were differentially expressed (adjusted P value <.05). After a stepwise gene selection, only three genes (Bik, aurora kinase B, eIF5A2) were retained in the logistic model, which could correctly predict lymph node status in 30 of 32 cases.


If our findings were confirmed, the identified gene pattern might be used to tailor the extent of lymph node dissection on a single patient basis.

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