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Mol Hum Reprod. 2003 May;9(5):253-64.

Gene expression profiling of human endometrial receptivity on days LH+2 versus LH+7 by microarray technology.

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NV Organon, Department of Target Discovery, Oss, The Netherlands.


In humans, embryonic implantation and reproduction depends on the interaction of the embryo with the receptive endometrium. To gain a global molecular understanding of human endometrial receptivity, we compared gene expression profiles of pre-receptive (day LH+2) versus receptive (LH+7) endometria obtained from the same fertile woman (n = 5) in the same menstrual cycle in five independent experiments. Biopsies were analysed using the Affymetrix HG-U95A array, a DNA chip containing approximately 12,000 genes. Using the pre-defined criteria of a fold change >/=3 in at least four out of five women, we identified 211 regulated genes. Of these, 153 were up-regulated at LH+7 versus LH+2, whereas 58 were down-regulated. Amongst these 211 regulated genes, we identified genes that were known to play a role in the development of a receptive endometrium, and genes for which a role in endometrial receptivity, or even endometrial expression, has not been previously described. Validation of array data was accomplished by mRNA quantification by real time quantitative fluorescent PCR (Q-PCR) of three up-regulated [glutathione peroxidase 3 (GPx-3), claudin 4 (claudin-4) and solute carrier family 1 member 1 (SLC1A1)] genes in independent LH+2 versus LH+7 endometrial samples from fertile women (n = 3) and the three up-regulated genes throughout the menstrual cycle (n = 15). Human claudin-4 peaks specifically during the implantation window, whereas GPx-3 and SLC1A1 showed highest expression in the late secretory phase. In-situ hybridization (ISH) experiments showed that GPx-3 and SLC1A1 expression was restricted to glandular and luminal epithelial cells during the mid- and late luteal phase. The present work adds new and important data in this field, and highlights the complexity of studying endometrial receptivity even using global gene-expression analysis.

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