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Differential Gene Expression Analysis of Pure Cell Populations from Frozen UterineTissue Using Laser Capture Microdissection (LCM) and cDNA Microarrays

olated by LCM analysis (Fig. 1). Total RNA from the captured luminal epithelium was amplified and the differential gene expression between IM and INTER sites was examined by cDNA microarray analysis. Hybridizations were done in quadruplicate in a dye-swap manner, and the data were analyzed by using the significance analysis of microarrays (SAM). Figure 2 shows an identification of the genes with significant changes in expression. The graph shows the scatter plot of the observed relative difference d(i) versus the expected relative difference dE(i). The red spots (right upper area) indicate the genes with higher expression at IM, while the green spots (left lower area) indicate the genes with higher expression at INTER sites.

SAM is a statistical technique for the finding of significant genes in a set of microarray experiments. SAM uses repeated permutations of the data to determine if the expression of any gene is significantly related to the response variable (in this case, the difference between IM and INTER). In SAM, the relative difference d(i) for gene i is defined as:

where ri is a fold difference (or M value), si is a standard deviation, and s0 is a fudge factor. The expected relative difference dE(i) is the average of d(i)s from the data set generated by permutations. SAM calls a gene significant if the difference between d(i) and dE(i) is larger than user-provided threshold (delta value). For genes identified as significant, SAM estimates the percentage of genes identified by chance, the false discovery rate (FDR). For example, if 100 genes with 5% of FDR were selected, five genes among 100 genes are likely to be false positive.

In Figure 2, 88 genes were selected as significant in regard to gene expression changes with a FDR of 10%. Among them, 12 genes were negatively significant (green spots) and the rest were positively significant (red spot
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