Author:
Hu Jia-Li,Yierfulati Gulinazi,Wang Lu-Lu,Yang Bing-Yi,Lv Qiao-Ying,Chen Xiao-Jun
Abstract
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.
Funder
Science and Technology Commission of Shanghai Municipality
National Natural Science Foundation of China
Shanghai Rising-Star Program
Subject
Genetics (clinical),Genetics,Molecular Medicine
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献