Systematic Analysis of the Molecular Mechanism Underlying Decidualization Using a Text Mining Approach.

Abstract

Decidualization is a crucial process for successful embryo implantation and pregnancy in humans. Defects in decidualization during early pregnancy are associated with several pregnancy complications, such as pre-eclampsia, intrauterine growth restriction and recurrent pregnancy loss. However, the mechanism underlying decidualization remains poorly understood. In the present study, we performed a systematic analysis of decidualization-related genes using text mining. We identified 286 genes for humans and 287 genes for mice respectively, with an overlap of 111 genes shared by both species. Through enrichment test, we demonstrated that although divergence was observed, the majority of enriched gene ontology terms and pathways were shared by both species, suggesting that functional categories were more conserved than individual genes. We further constructed a decidualization-related protein-protein interaction network consisted of 344 nodes connected via 1,541 edges. We prioritized genes in this network and identified 12 genes that may be key regulators of decidualization. These findings would provide some clues for further research on the mechanism underlying decidualization.