AUTHOR=Zhao Xiaoxuan , Zhao Yang , Jiang Yuepeng , Zhang Qin 

TITLE=Deciphering the endometrial immune landscape of RIF during the window of implantation from cellular senescence by integrated bioinformatics analysis and machine learning

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.952708

DOI=10.3389/fimmu.2022.952708

ISSN=1664-3224

ABSTRACT=Recurrent implantation failure (RIF) is an extremely thorny issue in in vitro fertilization (IVF)-Embryo transfer (ET). However, its intricate etiology and pathological mechanisms are still unclear. Nowadays, there has been extensive interest in cellular senescence and endometrial immune characteristics during the window of implantation (WOI). This study aims to probe into the pathological mechanism of RIF from cellular senescence and investigate the correlation between cellular senescence and endometrial immune characteristics during WOI based on a bioinformatics combined with machine learning strategy, so as to elucidate the underlying pathological mechanisms of RIF and to explore novel treatment strategies for RIF. Firstly, gene sets of GSE26787 and GSE111974 from the Gene Expression Omnibus (GEO) database were included for the weighted gene correlation network analysis (WGCNA), from which we concluded that the genes of the core module were closely related to cell fate decision and immune regulation. Subsequently, we identified 25 cellular senescence associated differentially expressed genes (DEGs) in RIF by intersecting DEGs with cellular senescence associated genes from Cell Senescence database. And functional enrichment analysis were conducted to further reveal the specific molecular mechanisms by which these molecules regulate cellular senescence and immune pathways. Succeedingly, eight signature genes were determined by machine learning method of support vector machine-recursive feature elimination (SVM-RFE), random forest (RF) and artificial neural network (ANN), comprising LATS1, EHF, DUSP16, ADCK5, PATZ1, DEK, MAP2K1 and ETS2, which were also validated in gene set of GSE106602. Furthermore, distinct immune microenvironment abnormalities in the RIF endometrium during WOI were comprehensively explored and validated in GSE106602, including infiltrating immunocytes, immune function, as well as the expression profiling of human leukocyte antigen genes and immune checkpoint genes. Moreover, the correlation between the eight signature genes with the endometrial immune landscape of RIF were also evaluated. After that, two distinct subtypes with significantly distinct immune infiltration characteristics were identified by consensus clustering analysis base on the eight signature genes. In conclusion, this study demonstrated that celluar senescence might play a pushing role in the pathological mechanism of RIF, which might be closely related to its impact on the immune microenvironment during WOI phase