Gastric cancers have recently been classified into several types on the basis of molecular characterization, and the new taxonomy has shown to have clinical relevance. However, the technology required for thorough molecular classification is complicated and expensive, currently preventing widespread use. We aimed to reproduce the results of molecular classification using only simple techniques, that is, immunohistochemical analysis and in situ hybridization. We classified a cohort of 349 successive gastric adenocarcinomas into 5 subtypes, on the basis of protein or mRNA expression of MLH1, E-cadherin, p53, and Epstein-Barr virus. We observed that the subtypes presented distinct clinicopathologic characteristics and corresponded to the molecular classifications previously reported. Epstein-Barr virus -positive tumors were more common in male individuals and in the body of the stomach. Microsatellite-unstable (MSI) tumors, which showed aberrant MLH1 expression, were correlated with increased age and intestinal histology. Both types showed better overall survival than the other types. Gastric cancers with reduced expression of E-cadherin, corresponding to the epithelial to mesenchymal transition or genome stable subtypes, showed the poorest overall survival, with a high prevalence of poorly cohesive carcinoma (ie, diffuse type, of the Lauren classification system). In conclusion, we were able to reproduce a previously reported molecular classification of gastric cancers using immunohistochemical analysis and in situ hybridization. We verified the effectiveness and applicability of this method, which shows promise for use in a clinical setting in the foreseeable future.

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BACKGROUND AND PURPOSE:Cystic pituitary adenomas may mimic Rathke cleft cysts when there is no solid enhancing component found on MR imaging, and preoperative differentiation may enable a more appropriate selection of treatment strategies. We investigated the diagnostic potential of MR imaging features to differentiate cystic pituitary adenomas from Rathke cleft cysts and to develop a diagnostic model.