Identification of necroptosis-related genes and immune infiltration analysis on the pathogenesis of recurrent implantation failure through integrated bioinformatics analysis

Abstract

Abstract Purpose This study aimed to elucidate the role of necroptosis, a cell death process, in the pathogenesis of Recurrent Implantation Failure (RIF), a significant hurdle in Assisted Reproductive Technology. Methods Using the Gene Expression Omnibus database, we isolated RIF-related RNA-seq data and identified differentially expressed necroptosis-related genes (DENRGs). Functional enrichment analysis, Protein-Protein Interaction (PPI) networks, transcription factors (TFs) regulatory network, and Single sample gene set enrichment analysis (ssGSEA) were employed to understand the role of these genes in RIF. Results Twenty DENRGs were filtered, and six key genes (MLKL, FASLG, XIAP, CASP1, BIRC3, and TLR3) were identified at the hub of the PPI network. A predictive model for RIF, based on these genes, displayed good performance. A positive correlation of TLR3 with PER2, RORC, and FOXO1, and a negative correlation with UHRF1, BRCA2, and GLI1 was observed in the TFs network. The RIF group demonstrated significantly lower infiltration levels of 16 immune cells. Expression levels of key genes, except for XIAP, differed significantly between RIF and control groups. Potential therapeutic drugs modulating CASP1 were also predicted. Conclusion The investigation highlights the crucial role of necroptosis-related genes, especially MLKL, FASLG, XIAP, CASP1, BIRC3, and TLR3 in RIF pathogenesis. The identified genes can contribute to an effective RIF predictive model and suggest potential therapeutic targets for novel RIF treatments.