细胞滋养层
滋养层
子痫前期
生物
表型
上皮-间质转换
胎盘
男科
基因
内分泌学
怀孕
胎儿
遗传学
过渡(遗传学)
医学
作者
Anna Natenzon,Patrick McFadden,Sonia C. DaSilva‐Arnold,Stacy Zamudio,Nicholas P. Illsley
出处
期刊:Placenta
[Elsevier BV]
日期:2022-02-10
卷期号:120: 25-31
被引量:32
标识
DOI:10.1016/j.placenta.2022.02.004
摘要
The mechanism by which human cytotrophoblast cells (CTB) differentiate into extravillous trophoblast cells (EVT) is an epithelial-mesenchymal transition (EMT). Polarized CTB, anchored in an epithelial layer, are transformed into motile, non-polar EVT which invade the uterus. Our previous research has shown that over gestation, invasive first trimester EVT are converted to a non-invasive phenotype showing a reduced degree of EMT. We hypothesized that in an under-invasion pathology, such as early onset preeclampsia, third trimester EVT would display a less advanced EMT profile than controls. The goal of this study was to determine whether expression of EMT-associated genes in the EVT of early onset preeclamptics shows a less mesenchymal, more epithelial phenotype compared to control pregnancies. Measures of preeclamptic CTB and EVT gene expression, using highly purified cells from third trimester, early onset preeclamptics and gestational-age matched controls, showed clear evidence of a phenotypic pattern characteristic of an EMT. Comparison of preeclamptic EVT to gestational-age matched, control EVT demonstrated multiple changes in gene expression, including changes in well-known EMT gene markers, indicative of a more limited EMT. These changes are not explained by differences in the preeclamptic CTB precursors. In this first study of purified third trimester EVT, we show that the pattern of gene expression corresponding to EMT-associated differentiation is diminished in early onset preeclampsia. This provides a mechanistic framework for many of the molecular changes observed in preeclampsia and presents an opportunity for detailed studies of the pathways regulating the aberrant EMT and for potential biomarkers of the process.
科研通智能强力驱动
Strongly Powered by AbleSci AI