AIM: Gene expression profiling provides an unique opportunity to gain insight into the development of different types of gastric cancer. Tumor sample heterogeneity is thought to decrease the sensitivity and tumor specificity of microarray analysis. Thus, microdissection and preamp-lification of RNA is frequently performed. However, this technique may also induce considerable changes to the expression profile. To assess the effect of gastric tumor heterogeneity on expression profiling results, we measured the variation in gene expression within the same gastric cancer sample by performing a gene chip analysis with two RNA preparations extracted from the same tumor specimen. METHODS: Tumor samples from six intestinal T2 gastric tumors were dissected under liquid nitrogen and RNA was prepared from two separate tumor fragments. Each extraction was individually processed and hybridized to an Affymetrix U133A gene chip covering approximately 18 000 human gene transcripts. Expression profiles were analyzed using Microarray Suite 5.0 (Affymetrix) and GeneSpring 6.0 (Silicon Genetics). RESULTS: All gastric cancers showed little variance in expression profiles between different regions of the same tumor sample. In this case, gene chips displayed mean pair wise correlation coefficients of 0.94±0.02 (mean±SD), compared to values of 0.61±0.1 for different tumor samples. Expression of the variance between the two expression profiles as a percentage of “total change” (Affymetrix) revealed a remarkably low average value of 1.18±0.78 for comparing fragments of the same tumor sample. In contrast, comparison of fragments from different tumors revealed a percentage of 24.4±4.5. CONCLUSION: Our study indicates a low degree of expression profile variability within gastric tumor samples isolated from one patient. These data suggest that tumor tissue heterogeneity is not a dominant source of error for microarray analysis of larger tumor samples, making total RNA extraction an appropriate strategy for performing gene chip expression profiling of gastric cancer. AIM: Gene expression profiling provides an unique opportunity to gain insight into the development of different types of gastric cancer. Tumor sample heterogeneity is thought to decrease the sensitivity and tumor specificity of microarray analysis. Thus, microdissection and preamplification of RNA is frequently performed However, this technique may also induce influence changes in expression profiling results, we measured the variation in gene expression within the same gastric cancer sample by performing a gene chip analysis with two RNA METHODS extracted from the same tumor specimen. METHODS: Tumor samples from six intestinal T2 gastric tumors were dissected under liquid nitrogen and RNA was prepared from two separate tumor fragments. Each extraction was individually processed and hybridized to an Affymetrix U133A gene chip covering approximately 18 000 human gene transcripts. Expression profiles were analyzed using Microarray Suite 5.0 (Affymetrix) and GeneSpring 6.0 (Silicon Genetics). RESULTS: All gastric cancers showed little variance in expression profiles between different regions of the same tumor sample. In this case, gene chips displayed mean pair wise correlation coefficients of 0.94 ± 0.02 (mean ± SD), compared to values ​​of 0.61 ± 0.1 for different tumor samples. Expression of the variance between the two expression profiles as a percentage of “total change” (Affymetrix) revealed a remarkably low average value of In contrast, comparison of fragments from different tumors revealed a percentage of 24.4 ± 4.5. CONCLUSION: Our study indicates a low degree of expression profile variability within gastric tumor samples isolated from one patient. These data suggest that tumor tissue heterogeneity is not a dominant source of error for microarray analysis of larger tumor samples, making total RNA extraction an approp riatestrategy for performing gene chip expression profiling of gastric cancer.