During placentation invasive extravillous trophoblasts (EVTs) migrate into the maternal uterus and modify its vessels. In particular, remodeling of the spiral arteries by EVTs is critical for adapting blood flow and nutrient transport to the developing fetus. Failures in this process have been noticed in different pregnancy complications such as preeclampsia, intrauterine growth restriction, stillbirth, or recurrent abortion. Upon invasion into the decidua, the endometrium of pregnancy, EVTs encounter different maternal cell types such as decidual macrophages, uterine NK (uNK) cells and stromal cells expressing a plethora of growth factors and cytokines. Here, we will summarize development of the EVT lineage, a process occurring independently of the uterine environment, and formation of its different subtypes. Further, we will discuss interactions of EVTs with arteries, veins and lymphatics and illustrate how the decidua and its different immune cells regulate EVT differentiation, invasion and survival. The present literature suggests that the decidual environment and its soluble factors critically modulate EVT function and reproductive success.

Background: DNA methylation (DNAm) profiling has emerged as a powerful tool for characterizing the placental methylome. However, previous studies have focused primarily on whole placental tissue, which is a mixture of epigenetically distinct cell populations. Here, we present the first methylome-wide analysis of first trimester (n = 9) and term (n = 19) human placental samples of four cell populations: trophoblasts, Hofbauer cells, endothelial cells, and stromal cells, using the Illumina EPIC methylation array, which quantifies DNAm at > 850,000 CpGs. Results: The most distinct DNAm profiles were those of placental trophoblasts, which are central to many pregnancy-essential functions, and Hofbauer cells, which are a rare fetal-derived macrophage population. Cell-specific DNAm occurs at functionally-relevant genes, including genes associated with placental development and preeclampsia. Known placental-specific methylation marks, such as those associated with genomic imprinting, repetitive element hypomethylation, and placental partially methylated domains, were found to be more pronounced in trophoblasts and often absent in Hofbauer cells. Lastly, we characterize the cell composition and cell-specific DNAm dynamics across gestation. Conclusions: Our results provide a comprehensive analysis of DNAm in human placental cell types from first trimester and term pregnancies. This data will serve as a useful DNAm reference for future placental studies, and we provide access to this data via download from GEO (GSE159526), through interactive exploration from the web browser (https://robinsonlab.shinyapps.io/Placental_Methylome_Browser/), and through the R package planet, which allows estimation of cell composition directly from placental DNAm data.

Some cancers have been stratified into subclasses based on their unique involvement of specific signaling pathways. The mapping of human cancer genomes is revealing a vast number of somatic alterations; however, the identification of clinically relevant molecular tumor subclasses and their respective driver genes presents challenges. This information is key to developing more targeted and personalized cancer therapies. Here, we generate a new mouse model of genomically unstable osteosarcoma (OSA) that phenocopies the human disease. Integrative oncogenomics pinpointed cAMP-dependent protein kinase type I, α regulatory subunit (Prkar1a) gene deletions at 11qE1 as a recurrent genetic trait for a molecularly distinct subclass of mouse OSA featuring RANKL overexpression. Using mouse genetics, we established that Prkar1a is a bone tumor suppressor gene capable of directing subclass development and driving RANKL overexpression during OSA tumorigenesis. Finally, we uncovered evidence for a PRKAR1A-low subset of human OSA with distinct clinical behavior. Thus, tumor subclasses develop in mice and can potentially provide information toward the molecular stratification of human cancers.