Endometriosis is a refractory estrogen-dependent gynecological disease in which ovarian endometriosis(OE) is the most common, and the main cell components are endometrial epithelial cells and stromal cells. However, constructing ectopic endometrial epithelial cell models in basic studies is still challenging. In this study, we explored the feasibility and influencing factors of constructing and validating eutopic and ectopic endometrial organoid models of OE as in-vitro models. Eutopic and ectopic endometrial tissues of OE patients were selected to establish organoids. Morphologically, the organoids showed a three-dimensional glandular structure with vacuoles or cystic irregularities, and the histological features of the epithelial organoids in endometriosis were well preserved. Immunofluorescence showed positive expression of epithelial markers and estrogen/progesterone receptors. Genetic identification revealed a 100% match between endometriosis epithelial organoids and endometrial tissue, indicating a common origin. The effects of estrogen and progesterone on the proliferation and secretion of organoids differed with the change in concentration. The successful construction of ectopic endometrial organoids provides a new in vitro model for drug intervention and mechanism study of ovarian endometriosis.

Human endometrial epithelia undergo injury repair and regeneration with the menstrual cycle; however, mechanisms underpinning the roles of endometrial epithelial cells in endometrial lesions and regeneration remain incompletely understood, mainly owing to the difficulty in the isolation and expansion of primary endometrial epithelial cells and the lack of reliable models for in vitro and in vivo studies. In this report, we sought to improve methods for the isolation and expansion of human endometrial epithelial cells with a Rho-associated protein kinase (ROCK) inhibitor–modified medium and subsequently characterize endometrial epithelium generated with primary cells cultured in an air–liquid interface (ALI) state. Immunocytochemistry staining revealed the expression of epithelial cellular adhesion molecule (EpCam) and stage-specific embryonic antigen-1 (SSEA-1) but a lack of CD13 in endometrial epithelial cells. Meanwhile, a large number of proliferative Ki67+ cells were observed in isolated epithelial cells. Importantly, the EpCam+/CD13− cells were capable of forming spheroids, a characteristic of epithelial stem/progenitor cells. Interestingly, these cells also exhibited a capacity to reconstitute epithelial layers in an ALI state. Morphological analysis revealed mucosal secretion of differentiated epithelial cells with cilia and microvilli in ALI epithelial cells as determined by electronic microscopy. Immunoblotting assay further demonstrated the expression of endometrial epithelial cell markers keratin 17/19 and EpCam and stem cell marker OCT3/4 but not stromal cell marker Vimentin protein and CD13 in cell expansions. Furthermore, molecular analysis also showed that the exposure of cells to estrogen elevated the expression of estrogen receptor and progesterone receptors in ALI cultures. Our results shed light on the possibility of expanding sufficient numbers of endometrial epithelial cells for stem cell biology studies, and they provide a feasible and alternative model that can recapitulate the characteristics and physiology of endometrial epithelium in vivo.

Background: High grade serous ovarian cancer (HGSOC) is the most common subtype of ovarian cancer. Although platinum-based chemotherapy has been the cornerstone for HGSOC treatment, nearly 25% of patients would have less than 6 months of interval since the last platinum chemotherapy, referred to as platinum-resistance. Currently, no precise tools to predict platinum resistance have been developed yet.Methods: Ninety-nine HGSOC patients, who have finished cytoreductive surgery and platinum-based chemotherapy in Peking University Third Hospital from 2018 to 2019, were enrolled. Whole-genome sequencing (WGS) and whole-exome sequencing (WES) were performed on the collected tumor tissue samples to establish a platinum-resistance predictor in a discovery cohort of 57 patients, and further validated in another 42 HGSOC patients.Results: A high prevalence of alterations in DNA damage repair (DDR) pathway, including BRCA1/2, was identified both in the platinum-sensitive and resistant HGSOC patients. Compared with the resistant subgroup, there was a trend of higher prevalence of homologous recombination deficiency (HRD) in the platinum-sensitive subgroup (78.95% vs. 47.37%, p=0.0646). Based on the HRD score, microhomology insertions and deletions (MHID), copy number changes load, duplication load of 1–100 kb, single nucleotide variants load, and eight other mutational signatures, a combined predictor of platinum-resistance, named as DRDscore, was established. DRDscore outperformed in predicting the platinum-sensitivity than the previously reported biomarkers with a predictive accuracy of 0.860 at a threshold of 0.7584. The predictive performance of DRDscore was validated in an independent cohort of 42 HGSOC patients with a sensitivity of 90.9%.Conclusions: A multi-genomic signature-based analysis enabled the prediction of initial platinum resistance in advanced HGSOC patients, which may serve as a novel assessment of platinum resistance, provide therapeutic guidance, and merit further validation.

Ovarian cancer (OV) is a common malignant tumor of the female reproductive system with a 5-year survival rate of ∼30 %. Inefficient early diagnosis and prognosis leads to poor survival in most patients. G protein-coupled receptors (GPCRs, the largest family of human cell surface receptors) are associated with OV. We aimed to identify GPCR-related gene (GPCRRG) signatures and develop a novel model to predict OV prognosis. We downloaded data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Prognostic GPCRRGs were screened using least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and a prognostic model was constructed. The predictive ability of the model was evaluated by Kaplan-Meier (K-M) survival analysis. The levels of GPCRRGs were examined in normal and OV cell lines using quantitative reverse-Etranscription polymerase chain reaction. The immunological characteristics of the high- and low-risk groups were analyzed using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Based on the risks scores, 17 GPCRRGs were associated with OV prognosis. CXCR4, GPR34, LGR6, LPAR3, and RGS2 were significantly expressed in three OV datasets and enabled accurate OV diagnosis. K-M analysis of the prognostic model showed that it could differentiate high- and low-risk patients, which correspond to poorer and better prognoses, respectively. GPCRRG expression was correlated with immune infiltration rates. Our prognostic model elaborates on the roles of GPCRRGs in OV and provides a new tool for prognosis and immune response prediction in patients with OV.

Backgrounds: Ovarian cancer (OC) is still the leading aggressive and lethal disease of gynecological cancers, and platinum-based regimes are the standard treatments. However, nearly 20%–30% of patients with OC are initial platinum resistant (IPR), and there is a lack of valid tools to predict whether they will be primary platinum resistant or not prior to chemotherapy.Methods: Transcriptome data from The Cancer Genome Atlas (TCGA) was downloaded as the training data, and transcriptome data of GSE15622, GSE102073, GSE19829, and GSE26712 were retrieved from Gene Expression Omnibus (GEO) as the validation cohorts. Differentially expressed genes (DEGs) were selected between platinum-sensitive and platinum-resistant patients from the training cohort, and multiple machine-learning algorithms [including random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] were utilized to determine the candidate genes from DEGs. Then, we applied logistic regression to establish the IPR signature based on the expression. Finally, comprehensive clinical, genomic, and survival feature were analyzed to understand the application value of the established IPR signature.Results: A total of 532 DEGs were identified between platinum-resistant and platinum-sensitive samples, and 11 of them were shared by these three-machine learning algorithms and utilized to construct an IPR prediction signature. The area under receiver operating characteristic curve (AUC) was 0.841 and 0.796 in the training and validation cohorts, respectively. Notably, the prediction capacity of this signature was stable and robust regardless of the patients’ homologous recombination deficiency (HRD) and mutation burden status. Meanwhile, the genomic feature was concordant between samples with high- or low-IPR signature, except a significantly higher prevalence of gain at Chr19q.12 (regions including CCNE1) in the high-IPR signature samples. The efficacy of prediction of platinum resistance of IPR signature successfully transferred to the precise survival prediction, with the AUC of 0.71, 0.72, and 0.66 to predict 1-, 3-, and 5-year survival, respectively. At last, we found a significantly different tumor-infiltrated lymphocytes feature, including lower abundance of CD4+ naive T cells in the samples with high-IPR signature. A relatively lower tumor immune dysfunction and exclusion (TIDE) value and more sensitivity to multiple therapies including Gefitinib may suggest the potency to transfer from platinum-based therapy to immunotherapy or target therapies in patients with high-IPR signature.Conclusion: Our study established an IPR signature based on the expression of 11 genes that could stably and robustly distinguish OC patients with IPR and/or poor outcomes, which may guide therapeutic regimes tailoring.

Endometriosis is an aggressive disease. It is the main cause of chronic pelvic pain, dysmenorrhea, and infertility, affecting the well-being of women. This study aimed to explore the role of U0126 and BAY11-7082 in endometriosis (EMs) treatment in rats by targeting the MEK/ERK/NF-κB pathway. The EMs model was generated and the rats were divided into model, dimethyl sulfoxide, U0126, BAY11-708, and control groups (Sham operation group). After 4 weeks of treatment, the rats were sacrificed. Compared with model group, U0126 and BAY11-7082 treatment significantly inhibited ectopic lesion growth, glandular hyperplasia, and interstitial inflammation. Compared to control group, PCNA and MMP9 levels were significantly increased in the eutopic and ectopic endometrial tissues of model group; the levels of MEK/ERK/NF-κB pathway proteins also increased significantly. Compared with model group, MEK, ERK, and NF-κB levels decreased significantly after U0126 treatment and NF-κB protein expression decreased significantly after BAY11-7082 treatment, with no significant difference in MEK and ERK levels. The proliferation and invasion activities of eutopic and ectopic endometrial cells also significantly decreased after U0126 and BAY11-7082 treatment. In summary, our results showed that U0126 and BAY11-7082 inhibited ectopic lesion growth, glandular hyperplasia, and interstitial inflammatory response in EMs rats by inhibiting the MEK/ERK/NF-κB signaling pathway.