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Atypical protein kinase C signaling and placentation

Atypical protein kinase C signaling and placentation
非典型蛋白激酶 C 信号转导和胎盘
批准号:
9903417
负责人:
Soumen Paul
金额:
$22.95万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2022-03-31

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Abstract Early pregnancy loss is a serious health concern. Defective development of the syncytiotrophoblast (SynT)- lineage, which assures placentation and establishes the fetal/maternal exchange surface, is one of the leading causes for early pregnancy loss. Furthermore, in an established pregnancy, defective development and function of SynT-lineage could lead to pregnancy-associated complications like IUGR and preeclampsia or serve as developmental causes for postnatal or adult diseases. Despite of the critical importance of SynTs, we have a poor understanding of signaling mechanisms that regulate SynT development. Especially very little is known about early human placentation process. Our studies with mouse model provide genetic evidence that loss-of atypical protein kinase C isoform, PKCλ/ι, function in trophoblast progenitors could lead to early pregnancy due to defective development of SynTs within the placental labyrinth zone. These observations led us to the central hypothesis of this proposal that PKCλ/ι)-signaling mediates a conserved function in establishing SynT development across mammalian species. The goal of this proposal is to test this hypothesis by using both transgenic mouse and human trophoblast stem cells (human TSCs) as experimental models. Two specific aims are proposed. In aim 1, using conditional PKCλ/ι knockout mouse models, we will test the hypothesis that cell-autonomous function of PKCλ/ι in trophoblast progenitors is essential for SynT development and placentation. In aim 2, using human TSCs as a model system, we will test the hypothesis that PKCλ/ι signaling is essential for both maintenance of the stem/progenitor state in hTSCs and their differentiation towards SynT lineage.
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Modeling Human Placentation via Single Cell RNA-Sequencing
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Modeling Human Placentation via Single Cell RNA-Sequencing
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