OUP accepted manuscript

Time-series single-cell transcriptomic profiling of luteal-phase endometrium uncovers dynamic characteristics and its dysregulation in recurrent implantation failures

Understanding human endometrial dynamics in the establishment of endometrial receptivity remains a challenge, which limits early diagnosis and treatment of endometrial-factor infertility. Here, we decode the endometrial dynamics of fertile women across the window of implantation and characterize the endometrial deficiency in women with recurrent implantation failure. A computational model capable of both temporal prediction and pattern discovery is used to analyze single-cell transcriptomic data from over 220,000 endometrial cells. The time-series atlas highlights a two-stage stromal decidualization process and a gradual transitional process of the luminal epithelial cells across the window of implantation. In addition, a time-varying gene set regulating epithelium receptivity is identified, based on which the recurrent implantation failure endometria are stratified into two classes of deficiencies. Further investigation uncovers a hyper-inflammatory microenvironment for the dysfunctional endometrial epithelial cells of recurrent implantation failure. The holistic characterization of the physiological and pathophysiological window of implantation and a computational tool trained on this temporal atlas provide a platform for future therapeutic developments.

The Role of the Endometrium in Implantation: A Modern View

According to the current data, the endometrium acts as a "sensor" of embryo quality, which promotes the implantation of euploid embryos and prevents the implantation and/or subsequent development of genetically abnormal embryos. The present review addresses the nature of the "sensory function" of the endometrium and highlights the necessity for assessing its functional status. The first section examines the evolutionary origin of the "sensory" ability of the endometrium as a consequence of spontaneous decidualization that occurred in placental animals. The second section details the mechanisms for implementing this function at the cellular level. In particular, the recent findings of the appearance of different cell subpopulations during decidualization are described, and their role in implantation is discussed. The pathological consequences of an imbalance among these subpopulations are also discussed. Finally, the third section summarizes information on currently available clinical tools to assess endometrial functional status. The advantages and disadvantages of the approaches are emphasized, and possible options for developing more advanced technologies for assessing the "sensory" function of the endometrium are proposed.

Predicting risk of endometrial failure: a biomarker signature that identifies a novel disruption independent of endometrial timing in patients undergoing hormonal replacement cycles

OBJECTIVE

To propose a new gene expression signature that identifies endometrial disruptions independent of endometrial luteal phase timing and predicts if patients are at risk of endometrial failure.

DESIGN

Multicentric, prospective study.

SETTING

Reproductive medicine research department in a public hospital affiliated with private fertility clinics and a reproductive genetics laboratory.

PATIENTS

Caucasian women (n = 281; 39.4 ± 4.8 years old with a body mass index of 22.9 ± 3.5 kg/m2) undergoing hormone replacement therapy between July 2018 and July 2021. Endometrial samples from 217 patients met RNA quality criteria for signature discovery and analysis.

INTERVENTION(S)

Endometrial biopsies collected in the mid-secretory phase.

MAIN OUTCOME MEASURE(S)

Endometrial luteal phase timing-corrected expression of 404 genes and reproductive outcomes of the first single embryo transfer (SET) after biopsy collection to identify prognostic biomarkers of endometrial failure.

RESULTS

Removal of endometrial timing variation from gene expression data allowed patients to be stratified into poor (n = 137) or good (n = 49) endometrial prognosis groups on the basis of their clinical and transcriptomic profiles. Significant differences were found between endometrial prognosis groups in terms of reproductive rates: pregnancy (44.6% vs. 79.6%), live birth (25.6% vs. 77.6%), clinical miscarriage (22.2% vs. 2.6%), and biochemical miscarriage (20.4% vs. 0%). The relative risk of endometrial failure for patients predicted as a poor endometrial prognosis was 3.3 times higher than those with a good prognosis. The differences in gene expression between both profiles were proposed as a biomarker, coined the endometrial failure risk (EFR) signature. Poor prognosis profiles were characterized by 59 upregulated and 63 downregulated genes mainly involved in regulation (17.0%), metabolism (8.4%), immune response, and inflammation (7.8%). This EFR signature had a median accuracy of 0.92 (min = 0.88, max = 0.94), median sensitivity of 0.96 (min = 0.91, max = 0.98), and median specificity of 0.84 (min = 0.77, max = 0.88), positioning itself as a promising biomarker for endometrial evaluation.

CONCLUSION(S)

The EFR signature revealed a novel endometrial disruption, independent of endometrial luteal phase timing, present in 73.7% of patients. This EFR signature stratified patients into 2 significantly distinct and clinically relevant prognosis profiles providing opportunities for personalized therapy. Nevertheless, further validations are needed before implementing this gene signature as an artificial intelligence (AI)-based tool to reduce the risk of patients experiencing endometrial failure.

Dynamic chromatin remodeling in cycling human endometrium at single-cell level

Estrogen-dependent proliferation followed by progesterone-dependent differentiation of the endometrium culminates in a short implantation window. We performed single-cell assay for transposase-accessible chromatin with sequencing on endometrial samples obtained across the menstrual cycle to investigate the regulation of temporal gene networks that control embryo implantation. We identify uniquely accessible chromatin regions in all major cellular constituents of the endometrium, delineate temporal patterns of coordinated chromatin remodeling in epithelial and stromal cells, and gain mechanistic insights into the emergence of a receptive state through integrated analysis of enriched transcription factor (TF) binding sites in dynamic chromatin regions, chromatin immunoprecipitation sequencing analyses, and gene expression data. We demonstrate that the implantation window coincides with pervasive cooption of transposable elements (TEs) into the regulatory chromatin landscape of decidualizing cells and expression of TE-derived transcripts in a spatially defined manner. Our data constitute a comprehensive map of the chromatin changes that control TF activities in a cycling endometrium at cellular resolution.

A molecular staging model for accurately dating the endometrial biopsy

Natural variability in menstrual cycle length, coupled with rapid changes in endometrial gene expression, makes it difficult to accurately define and compare different stages of the endometrial cycle. Here we develop and validate a method for precisely determining endometrial cycle stage based on global gene expression. Our 'molecular staging model' reveals significant and remarkably synchronised daily changes in expression for over 3400 endometrial genes throughout the cycle, with the most dramatic changes occurring during the secretory phase. Our study significantly extends existing data on the endometrial transcriptome, and for the first time enables identification of differentially expressed endometrial genes with increasing age and different ethnicities. It also allows reinterpretation of all endometrial RNA-seq and array data that has been published to date. Our molecular staging model will significantly advance understanding of endometrial-related disorders that affect nearly all women at some stage of their lives, such as heavy menstrual bleeding, endometriosis, adenomyosis, and recurrent implantation failure.

Microbial Communities in Gynecological Cancers and Their Association with Tumor Somatic Variation

There are strong correlations between the microbiome and human disease, including cancer. However, very little is known about potential mechanisms associated with malignant transformation in microbiome-associated gynecological cancer, except for HPV-induced cervical cancer. Our hypothesis is that differences in bacterial communities in upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. We first assessed differences in the taxonomic composition of microbial communities and genomic variation between gynecologic cancers and normal samples. Then, we performed a correlation analysis to assess whether differences in microbial communities selected for specific single nucleotide variation (SNV) between normal and gynecological cancers. We validated these results in independent datasets. This is a retrospective nested case-control study that used clinical and genomic information to perform all analyses. Our present study confirms a changing landscape in microbial communities as we progress into the upper genital tract, with more diversity in lower levels of the tract. Some of the different genomic variations between cancer and controls strongly correlated with the changing microbial communities. Pathway analyses including these correlated genes may help understand the basis for how changing bacterial landscapes may lead to these cancers. However, one of the most important implications of our findings is the possibility of cancer prevention in women at risk by detecting altered bacterial communities in the upper genital tract epithelium.

Designing Effective Multi-Target Drugs and Identifying Biomarkers in Recurrent Pregnancy Loss (RPL) Using In Vivo, In Vitro, and In Silico Approaches

Recurrent pregnancy loss (RPL) occurs in approximately 5% of women. Despite an abundance of evidence, the molecular mechanism of RPL’s pathology remains unclear. Here, we report the protective role of polo-like kinase 1 (PLK1) during RPL. We aimed to construct an RPL network utilizing GEO datasets and identified hub high-traffic genes. We also investigated whether the expressions of PLK1 were altered in the chorionic villi collected from women with RPL compared to those from healthy early pregnant women. Gene expression differences were evaluated using both pathway and gene ontology (GO) analyses. The identified genes were validated using in vivo and in vitro models. Mice with PLK1-overexpression and PLK1-knockdown in vitro models were produced by transfecting certain plasmids and si-RNA, respectively. The apoptosis in the chorionic villi, mitochondrial function, and NF-κB signaling activity was evaluated. To suppress the activation of PLK1, the PLK1 inhibitor BI2536 was administered. The HTR-8/SVneo and JEG-3 cell lines were chosen to establish an RPL model in vitro. The NF-κB signaling, Foxo signaling, PI3K/AKT, and endometrial cancer signaling pathways were identified via the RPL regulatory network. The following genes were identified: PLK1 as hub high-traffic gene and MMP2, MMP9, BAX, MFN1, MFN2, FOXO1, OPA1, COX15, BCL2, DRP1, FIS1, TRAF2, and TOP2A. Clinical samples were examined, and the results demonstrated that RPL patients had tissues with decreased PLK1 expression in comparison to women with normal pregnancies (p < 0.01). In vitro, PLK1 knockdown induced the NF-κB signaling pathway and apoptosis activation while decreasing cell invasion, migration, and proliferation (p < 0.05). Furthermore, the in vivo model proved that cell mitochondrial function and chorionic villi development are both hampered by PLK1 suppression. Our findings revealed that the PLK1/TRAF2/NF-κB axis plays a crucial role in RPL-induced chorionic villi dysfunction by regulating mitochondrial dynamics and apoptosis and might be a potential therapeutic target in the clinic.

The Human Early Maternal–Embryonic Interactome

Background: Single cell transcriptomics offers an avenue for predicting, with improved accuracy, the gene networks that are involved in the establishment of the first direct cell–cell interactions between the blastocyst and the maternal luminal epithelium. We hypothesised that in silico modelling of the maternal–embryonic interface may provide a causal model of these interactions, leading to the identification of genes associated with a successful initiation of implantation. Methods: Bulk and single cell RNA-sequencing of endometrial epithelium and scRNAseq of day 6 and 7 trophectoderm (TE) were used to model the initial encounter between the blastocyst and the maternal uterine lining epithelium in silico. In silico modelling of the maternal–embryonic interface was performed using hypernetwork (HN) analysis of genes mediating endometrial–TE interactions and the wider endometrial epithelial transcriptome. A hypernetwork analysis identifies genes that co-ordinate the expression of many other genes to derive a higher order interaction likely to be causally linked to the function. Potential interactions of TE with non-ciliated luminal cells, ciliated cells, and glandular cells were examined. Results: Prominent epithelial activities include secretion, endocytosis, ion transport, adhesion, and immune modulation. Three highly correlated clusters of 25, 22 and 26 TE-interacting epithelial surface genes were identified, each with distinct properties. Genes in both ciliated and non-ciliated luminal epithelial cells and glandular cells exhibit significant functional associations. Ciliated cells are predicted to bind to TE via galectin–glycan interaction. Day 6 and day 7 embryonic–epithelial interactomes are largely similar. The removal of aneuploid TE-derived mRNA invoked only subtle differences. No direct interaction with the maternal gland epithelial cell surface is predicted. These functional differences validate the in silico segregation of phenotypes. Single cell analysis of the epithelium revealed significant change with the cycle phase, but differences in the cell phenotype between individual donors were also present. Conclusions: A hypernetwork analysis can identify epithelial gene clusters that show correlated change during the menstrual cycle and can be interfaced with TE genes to predict pathways and processes occurring during the initiation of embryo–epithelial interaction in the mid-secretory phase. The data are on a scale that is realistic for functional dissection using current ex vivo human implantation models. A focus on luminal epithelial cells may allow a resolution to the current bottleneck of endometrial receptivity testing based on tissue lysates, which is confounded by noise from multiple diverse cell populations.

Use of 'omics for endometrial timing: the cycle moves on

For some years, the prospect of precise and personalized timing of the endometrial cycle for optimal embryo replacement has been held out as a potential solution to low implantation rates. It is envisaged that a receptive state can be defined and reached at a predictable time, and embryo replacement performed in synchrony. In the last century, morphological changes characteristic of the mid secretory phase were defined in precisely timed cycles in women of proven fertility, but when deviations from this standardized schedule occur, their significance for implantation has remained uncertain. ‘Omics technologies have been widely advocated for staging the endometrial cycle and defining a set of biochemical requirements for implantation, but after two decades of research, improvements to pregnancy rates have not followed, and there is a striking lack of agreement regarding the molecular characterization of the receptive state. Some of the rationale underlying these problems is now emerging with the application of higher-level computational and biological methodology. Here, we consider the challenges of defining an endometrial phenotype that can support implantation and continuing pregnancy. Receptivity may be an emergent trait depending on contributions from multiple proteins that have low pathway connectivity. We recommend that authors choose language which rigorously avoids the implication that protocols for molecular staging of the mid secretory phase inherently identify a state of receptivity to the implanting blastocyst.