Background: The placenta is an important organ for fetal and maternal health during pregnancy and impacts offspring health late in life. Defects in placental vasculature and trophoblast have been identified in several pregnancy complications. Thus, the detailed molecular profile and heterogeneity of endothelial cells and trophoblasts in placentas will aid us in better understanding placental behaviors and improving pregnancy outcomes. Methods: Single-cell RNA sequencing (scRNA-seq) was performed to profile the transcriptomics of human placental villous tissues from eleven patients with normal pregnancies in the first and second trimesters (6–16 weeks of gestation). Results: The transcriptomic landscape of 52,179 single cells was obtained, and the cells were classified as trophoblasts, fibroblasts, endothelial cells, erythroid cells, Hofbauer cells, and macrophages. Our analysis further revealed the three subtypes of placental endothelial cells, with distinct metabolic signatures and transcription factor regulatory networks. We also determined the transcriptomic features of the trophoblast subpopulations and characterized two distinct populations of progenitor cells in cytotrophoblasts, which were capable of differentiating to extravillous trophoblasts and syncytiotrophoblasts, respectively. Conclusions: Our study provided a high-resolution molecular profile of the human placenta between 6 and 16 weeks of gestation. Our data revealed the placental cell complexity and demonstrated the transcriptional networks and signaling involved in placental endothelial and trophoblast differentiation during early pregnancy, which will be a resource for future studies of the human placental development.

Mitochondria are highly dynamic organelles capable of altering their sizes and shapes to maintain metabolic balance through coordinated fission and fusion processes. In various cancer types, mitochondrial hyperfragmentation has been frequently observed, contributing to the progression of cancer toward metastasis. Inverted formin 2 (INF2), which resides in the endoplasmic reticulum (ER), has been found to accelerate actin polymerization and drive mitochondrial fission. In this study, we demonstrate that INF2 expression is significantly upregulated in endometrial cancer (EC) and is associated with a poor prognosis in EC patients. INF2 promotes anchorage-dependent and independent EC cell growth in part by facilitating mitochondrial fission. Furthermore, in conditions of energy stress, AMP-activated protein kinase (AMPK) phosphorylates INF2 at Ser1077, leading to increased localization of INF2 to the ER and enhanced recruitment of the dynamin-related protein 1 (DRP1) to mitochondria. This AMPK-mediated phosphorylation of INF2 at Ser1077 facilitates mitochondrial division and promotes EC cell growth. Pathological examination using immunohistochemical analyses revealed a positive correlation between AMPK activity and phosphorylated INF2 (Ser1077) in EC specimens. Collectively, our findings uncover novel molecular mechanisms involving the AMPK-INF2 axis, which regulates mitochondrial dynamics and malignant cell growth in EC.

Purpose: Microsatellite instability (MSI) and mismatch repair deficiency (dMMR) are important biomarkers for predicting responses to immune checkpoint inhibitor (ICI) therapies. Although PCR-based tests for high MSI (MSI-H) and dMMR yield highly concordant results in endometrial cancer (EC), it is unclear whether this is true for MSI-H and MMR detected by next-generation sequencing (NGS) and immunohistochemistry (IHC), respectively. This study investigated whether EC with MSI-H identified by NGS and dMMR identified by IHC have similar tumor immune microenvironments. Patients and Methods: EC tissue and corresponding peripheral blood lymphocyte samples were collected from 99 randomly selected patients. MSI status and tumor mutation burden (TMB) were examined by NGS. MMR protein and programmed death ligand (PD-L)1 expression and tumor-infiltrating lymphocyte (TIL) abundance were evaluated by IHC. Results: Of the 99 EC samples, 29 (29%) had dMMR by IHC, while 18 (18%) had MSI-H by NGS. MSI and MMR status identified by the two methods were discordant in the 99 EC patients, and 2/18 NGS-identified MSI-H patients (11%) retained MMR protein expression. MSI-H and dMMR endometrial tumors had similar numbers of cluster of differentiation (CD)3+ TILs (T cells) and CD8+ TILs (cytotoxic T cells) in the tumor center and periphery, which differed from those in microsatellite stable (MSS) and mismatch repair-proficient (pMMR) EC; they also showed similar TMB, PD-L1 expression, and TIL counts with higher TMB and PD-L1 expression than MSS and pMMR ECs. The abundance of CD3+ and CD8+ TILs was increased in PD-L1-positive EC. Conclusion: NGS-identified MSI status and IHC-identified MMR status were inconsistent in EC, and 11% of NGS-identified MSI-H tumors retained MMR protein expression. Conversely, MSI and MMR status determined by the two methods provided similar data on TMB, PD-L1 expression, and TIL abundance, which can guide treatment decisions with ICIs.

Preeclampsia (PE) is a hypertensive disorder of pregnancy characterized by maternal endothelial dysfunction and end-organ damage. Our previous work demonstrated that PE patient-derived exosomes contained higher levels of soluble FMS-like tyrosine kinase-1 (sFlt-1) and significantly induced endothelial dysfunction and PE development. However, the mechanisms underlying the effect of sFlt-1-enriched exosomes (sFlt-1-Exo) on PE development are poorly characterized. Here, we revealed that trophoblast-derived sFlt-1-Exo treatment induced significant inhibition of human umbilical vein endothelial cell (HUVEC) migration and tube formation, as well as an increase in sFlt-1 secretion. Mechanistically, we found that the increased sFlt-1 secretion in the cell culture medium was attributed to enhanced transcription of sFlt-1 in HUVECs. Importantly, we observed that treating pregnant mice with sFlt-1-Exo or recombinant mouse sFlt-1 triggered a preeclampsia-like phenotype, characterized by elevated blood pressure, proteinuria, increased plasma sFlt-1 and adverse pregnancy outcomes. These results strongly suggested that sFlt-1-Exo-induced endothelial dysfunction could be partially attributed to the upregulation of sFlt-1 in endothelial cells, potentially leading to the development of a preeclampsia-like phenotype in mice.

Accurate molecular subtyping is essential for guiding precision treatment and prognostic stratification in endometrial cancer (EC). However, current methods, based on Sanger sequencing and immunohistochemistry (IHC), are costly, time-intensive, and difficult to implement widely in routine clinical practice, particularly in resource-limited settings. To overcome these challenges, we developed a deep-learning pipeline that directly infers EC molecular subtypes from routine hematoxylin-and-eosin (H&E) whole-slide images (WSIs). The framework integrates super-resolution enhancement (SRResGAN), transformer-based lesion segmentation (MedSAM), and a ResNet-101 classifier for molecular subtype prediction, with an LSTM module for survival modeling. This retrospective study included 393 Chinese patients diagnosed between 2010 and 2018, all with ≥ 5 years of follow-up. Molecular subtypes—POLE ^mut , mismatch repair-deficient (MMRd), p53abnormal (p53abn), and no specific molecular profile (NSMP)—were confirmed by Sanger sequencing and immunohistochemistry. The model achieved high classification accuracies (92% for POLE ^mut and MMRd, 91% for p53abn, and 90% for NSMP), with a strong correlation between predicted and observed survival (R2 = 0.9692; MAE = 123 days). External validation on two independent cohorts ( N = 35 and N = 83) confirmed robust generalizability across institutions. This study represents the first large-scale, multicenter, AI-based digital pathology model for EC molecular classification in China. The proposed workflow provides an automated, interpretable, and cost-efficient alternative to conventional molecular testing, supporting precision oncology, fertility-preserving management, and clinical decision-making in real-world practice.