Molecular classification of human endometrial cycle stages by transcriptional profiling

Endometrium is a dynamic tissue that undergoes cyclic changes each month, under the overall control of estrogen and progesterone. The aims of this study were to investigate the changing global gene expression profile of human endometrium during the menstrual cycle using microarray technology and to determine the correlation between histopathological evaluation and molecular profile of the samples. Standard two-colour cDNA microarrays were performed on the 43 samples against a common reference, using a 10.5 K cDNA glass slide microarray. The results were validated using real-time PCR. Analysis of expression data was carried out using parametric analysis of variance with Benjamini–Hochberg correction. Hierarchical clustering reveals a strong relationship between histopathology and transcriptional profile of the samples. The study identified 1452 genes that showed significant changes in expression (P≤0.05) across the menstrual cycle, with 425 genes having changes that are at least 2-fold. The data were also independently analysed by a CSIRO algorithm called GeneRaVETM that identified a small subset of genes whose expression profiles could be used to classify nearly all the biopsies into their correct cycle stage. We also identified and validated three genes [(natural cytotoxicity triggering receptor (NCR)3, fucosyl transferase (FUT)4 and Fyn-binding protein (FYB)] that had not been shown to have significant cyclic changes in the human endometrium, previously. We have shown for the first time that endometrial cycle stage prediction is possible based on global gene expression profile.