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.

Gastric cancer is one of the most common malignancies, accounting for almost 10% of new cancer cases diagnosed worldwide[1,2]. However, knowledge about the molecular mechanisms underlying tumor development and progression is limited and molecular features of gastric cancer are not commonly used for diagnosis and treatment

cDNA and oligonucleotide microarrays are capable of profiling gene expression patterns of tens of thousands of genes in a single experiment. They are an ideal tool to study cancer progression and development and to identify new molecular markers for tumor classification and prognosis. Microarrays have been successfully applied to study various tumors, including gastric cancers[3-13].

Like most solid tumors, gastric cancer consists of many different cell types including endothelium, different types of stromal cells and inflammatory cells. Such tissue heterogeneity is thought to decrease the sensitivity and tumor specificity of the microarray analysis[14-16]. One strategy to overcome the problem of tissue heterogeneity is the use of laser capture microdissection (LCM) for isolation of a defined cell population[17,18] followed by amplification of the RNA for subsequent microarray analysis[19,20]. However, amplification-associated bias may induce considerable changes to the expression profile[15,21]. Depending on both the degree of tissue heterogeneity and the robustness of the microarray analysis protocol, it may therefore sometimes be advantageous to avoid RNA amplification and instead extract total RNA directly from a larger tumor sample.

To assess the influence of gastric tumor heterogeneity on the outcome of the microarray analysis, we measured the variation between gene expression profiles derived from two RNA preparations extracted from the same gastric tumor specimen.

Microarray studies on gastric cancer are currently based on two main methods of RNA preparation: the recently developed technique of LCM allows for the isolation of cancer cells and other subpopulations of interest from a heterogeneous piece of tumor tissue. The advantage of microdissection is that it directly focuses on the gastric cancer cells[5,10]. The disadvantage of LCM is at the level of resources and expertise. A certified pathologist is required to select the cells to be microdissected under the microscope, and microdissection itself requires an expensive technology and special training. Furthermore the amount of RNA obtained after LCM is not sufficient for microarray analysis and generally requires amplification. However, the amplification of small amounts of RNA from laser-captured samples is difficult and has been proved to be less reproducible than measurement of unamplified mRNA[15,21]. Even a minor degree of amplification bias might result in a substantial variation to the expression profile.

The approach we used here is based on total RNA extraction with RNA isolated directly from the gastric tumor tissue without the need for subsequent amplification. Hence, the microarray profile reflects all different tissue components present in the tumor. Most gastric cancer microarray studies are based on this method of RNA extraction[3,4,6-9,11-13]. This strategy is less laborious, because it does not require isolation of specific cell types. Moreover, there is usually a sufficient amount of high quality RNA obtained for microarray analysis. However, since the actual proportion of tumor cells in the gastric cancer tissue studied remains unknown, expression profiling based on this strategy may not reliably represent "true tumor changes. In other words, the level of intra-tumor variability is crucial for the sensitivity and tumor specificity of the microarray experiment. If there is a significant amount of intra-tumor variability, LCM becomes the strategy of choice.

In this study we found an unexpectedly low degree of expression profile variability within all gastric tumor samples studied. Randomly selected fragments from the same tumor sample displayed a striking similarity in expression profiles, while expression profiles derived from distinct tumor samples differed significantly. These data suggest that tissue heterogeneity is not a dominant source of error for microarray analysis of larger gastric tumor samples, making total RNA extraction an appropriate strategy for performing gene chip expression profiling of gastric cancer.

Our findings are in contrast to a recently published microarray study on human muscle biopsies[25], where tissue heterogeneity was a major source of expression profile variability. This indicates that our results may be exclusive for larger tumor samples and should not be generalized. It might also reflect the influence of study design and appropriate material selection on the outcome of any microarray experiment. We believe that an experienced pathologist who is able to carefully select an appropriate piece of gastric tumor for microarray experiments directly from a large tumor avoiding necrosis and infiltration by normal gastric mucosa is crucial for the quality of our results.

In our study, the degree of experimental variability was only minimal. In the early times of gene chip technology, Mills and Gordon[26] found a substantial level of experimental variability, with an average of 12% increase/decrease calls between the same RNA processed in parallel and hybridized on two Mu11k-A Affymetrix arrays. However, studies using newer, more robust Affymetrix array generations have achieved results consistent with our studies[25,27]. The low degree of experimental variability reflects the inherent advantage of the Affymetrix Gene Chip technology. Due to commercial mass production, they contain a robust series of controls designed to minimize chip-to-chip variation. The availability of standardized protocols together with the use of stringent laboratory quality control parameters also helps to reduce experimental variability.

In conclusion, we assume that gastric tumor expression profiling based on total RNA extraction reliably represents "true" tumor changes. Therefore, total RNA extraction may be the strategy of choice for microarray studies including large gastric cancer samples.