High incidence of gastric cancer-related death is mainly due to diagnosis at an advanced stage in addition to the lack of adequate neoadjuvant therapy. Hence, new tools aimed at early diagnosis would have a positive impact in the outcome of the disease. Using cDNA arrays having 376 genes either identified previously as altered in gastric tumors or known to be altered in human cancer, we determined expression signature of 99 tissue fragments representing normal gastric mucosa, gastritis, intestinal metaplasia, and adenocarcinomas. We first validated the array by identifying molecular markers that are associated with intestinal metaplasia, considered as a transition stage of gastric adenocarcinomas of the intestinal type as well as markers that are associated with diffuse type of gastric adenocarcinomas. Next, we applied Fisher's linear discriminant analysis in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Many classifiers could distinguish between normal and tumor samples, whereas, for the distinction of gastritis from tumor and for metaplasia from tumor, fewer classifiers were identified. Statistical validations showed that trios that discriminate between normal and tumor samples are powerful classifiers to distinguish between tumor and nontumor samples. More relevant, it was possible to identify samples of intestinal metaplasia that have expression signature resembling that of an adenocarcinoma and can now be used for follow-up of patients to determine their potential as a prognostic test for malignant transformation.

Adenocarcinomas of stomach and esophagus are frequently associated with preceding inflammatory alterations of the normal mucosa. Whereas intestinal metaplasia of the gastric mucosa is associated with higher risk of malignization, Barrett's disease is a risk factor for adenocarcinoma of the esophagus. Barrett's disease is characterized by the substitution of the squamous mucosa of the esophagus by a columnar tissue classified histopathologically as intestinal metaplasia. Using cDNA microarrays, we determined the expression profile of normal gastric and esophageal mucosa as well as intestinal metaplasia and adenocarcinomas from both organs. Data were explored to define functional alterations related to the transformation from squamous to columnar epithelium and the malignant transformation from intestinal metaplasia to adenocarcinomas. Based on their expression profile, adenocarcinomas of the esophagus showed stronger correlation with intestinal metaplasia of the stomach than with Barrett's mucosa. Second, we identified two functional modules, lipid metabolism and cytokine, as being altered with higher statistical significance. Whereas the lipid metabolism module is active in samples representing intestinal metaplasia and inactive in adenocarcinomas, the cytokine module is inactive in samples representing normal esophagus and esophagitis. Using the concept of relevance networks, we determined the changes in linear correlation of genes pertaining to these two functional modules. Exploitation of the data presented herein will help in the precise molecular characterization of adenocarcinoma from the distal esophagus, avoiding the topographical and descriptive classification that is currently adopted, and help with the proper management of patients with Barrett's disease. (Cancer Res 2005; 65(16): 7127-36)

Whereas cancer patients have benefited from liquid biopsies, the scenario for gastric adenocarcinoma (GAC) is still dismal. We used next‐generation deep sequencing of TP53—a highly mutated and informative gene in GAC—to assess mutations in tumor biopsies, plasma (PL) and stomach fluids (gastric wash—GW). We evaluated their potential to reveal tumor‐derived mutations, useful for monitoring mutational dynamics at diagnosis, progression and treatment. Exon‐capture libraries were constructed from 46 patients including tumor biopsies, GW and PL pre and post‐treatment (196 samples), with high vertical coverage >8,000×. At diagnosis, we detected TP53 mutations in 15/46 biopsies (32.6%), 7/46 GW‐ (15.2%) and 6/46 PL‐samples (13%). Biopsies and GW were concordant in 38/46 cases (82.6%) for the presence/absence of mutations and, furthermore, four GW‐exclusive mutations were identified, suggesting tumor heterogeneity. Considering the combined analysis of GW and PL, TP53 mutations found in biopsies were also identified in 9/15 (60%) of cases, the highest detection level reported for GAC. Our study indicates that GW could be useful to track DNA alterations, especially if anchored to a comprehensive gene‐panel designed for this malignancy.

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Biological markers of cellular adhesion and gastric differentiation were differently expressed in young and older patients. Our findings support the hypothesis that young patients develop carcinomas with a different genetic pathway compared to the pathway of tumors occurring at a later age, and we suggest further investigations to assess the prognostic relevance of the markers to specific subgroups.