Objective To assess the efficacy of metformin in megestrol acetate (MA)-based fertility-sparing treatment for patients with atypical endometrial hyperplasia (AEH) and endometrioid endometrial cancer (EEC).Design A randomised, single-centre, open-label, controlled trial conducted between October 2013 and December 2017.

Polycystic ovary syndrome (PCOS) is a frequent endocrine and metabolic syndrome in reproductive-age women. Recently, emerging evidence has shown that gut microbiota is closely related to metabolic diseases such as type 2 diabetes, obesity and PCOS. In the present study, we established dihydrotestosterone (DHT)-induced PCOS rats and used Illumina MiSeq sequencing (PE300) to examine the composition, diversity, and abundance of the gut microbiota in PCOS. We compared the effects of three PCOS treatments: Diane-35 (estrogen and progesterone), probiotics and berberine. The DHT-induced rats showed constant estrous cycles, the loss of mature ovarian follicles, insulin resistance and obesity. The reproductive and metabolic functions in the PCOS rats were improved by treatment with Diane-35 and probiotics. Diane-35 and probiotics could restore the diversity of the gut microbiota, and the recovery of gut microbiota disorders improved the reproductive function in PCOS-like rats. However, berberine drastically reduced the species diversity and amount of gut microbiota and showed no improvement in PCOS. The findings of this study will help us to better understand the influence of the gut microbiota in the metabolic and reproductive alterations in PCOS as well as suggest opportunities for future personal dietary guidance for PCOS.

Objective: The aim of this study was to establish predictive models based on the molecular profiles of endometrial lesions, which might help identify progestin-insensitive endometrial atypical hyperplasia (EAH) or endometrioid endometrial cancer (EEC) patients before progestin-based fertility-preserving treatment initiation.Methods: Endometrial lesions from progestin-sensitive (PS, n = 7) and progestin-insensitive (PIS, n = 7) patients were prospectively collected before progestin treatment and then analyzed by ATAC-Seq and RNA-Seq. Potential chromatin accessibility and expression profiles were compared between the PS and PIS groups. Candidate genes were identified by bioinformatics analyses and literature review. Then expanded samples (n = 35) were used for validating bioinformatics data and conducting model establishment.Results: ATAC-Seq and RNA-Seq data were separately analyzed and then integrated for the subsequent research. A total of 230 overlapping differentially expressed genes were acquired from ATAC-Seq and RNA-Seq integrated analysis. Further, based on GO analysis, REACTOME pathways, transcription factor prediction, motif enrichment, Cytoscape analysis and literature review, 25 candidate genes potentially associated with progestin insensitivity were identified. Finally, expanded samples were used for data verification, and based on these data, three predictive models comprising 9 genes (FOXO1, IRS2, PDGFC, DIO2, SOX9, BCL11A, APOE, FYN, and KLF4) were established with an overall predictive accuracy above 90%.Conclusion: This study provided potential predictive models that might help identify progestin-insensitive EAH and EEC patients before fertility-preserving treatment.

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