Involvement of WNT2 in trophoblast cell behavior in preeclampsia development.

This study aimed to determine the WNT2 expression in patients with severe preeclampsia and to explore the function of WNT2 dysregulation on the biological behaviors of trophoblast cells. The WNT2 and ß-catenin expression in the patients with early-onset and late-onset severe preeclampsia and normal controls was determined. Subsequently, WNT2 was overexpressed and knocked down in HTR8 cells and WNT2 signaling pathway in regulating trophoblast cell proliferation, migration, invasion, and apoptosis were evaluated in vitro. The mRNA and protein expression levels of WNT2 and ß-catenin were decreased in patients with preeclampsia, especially early-onset severe preeclampsia. Overexpression of WNT2 promoted trophoblast cell proliferation, migration, and invasion and inhibited apoptosis in vitro, whereas knockdown of WNT2 had opposite effects. The findings of this study reveal that WNT2 and ß-catenin were decreased expressed in patients with preeclampsia. Decreased expression of WNT2 may inhibit trophoblast cell proliferation, migration, and invasion but induced apoptosis. WNT2 may serve as a promising biomarker for early detection of preeclampsia.

Predicting the target genes of miRNAs in preterm via targetscore algorithm.

Compared with normal neonates, preterm infants have an immature immune system which causes them to have a higher morbidity rate and even death. In order to reduce the mortality of newborns, we need to find the target genes which affect the preterm and understand their mechanism. It has been verified that microRNA (miRNA)-200 and miRNA-182 are closely related to the incidence of preterm. Therefore, it is significant to predict the target genes which are regulated by them for further understanding the mechanism of preterm. We chose the targetscore method for calculating the variational Bayesian-Gaussian mixture model (VB-GMM) as the target genes prediction method. It is designed for condition-specific target predictions and not limited to predict conserved genes, so the results are more accurate than previous sequence-based target prediction algorithms. In this study, our major contribution is to predict the target mRNAs of the chosen miRNAs with the gene expression profiles and a new method, which can effectively improve the accuracy of the prediction.