Transcriptomic Analysis and Finding of Potential Key mRNA Expression Profile in Human Cumulus Cells During in Vitro Culture and Different Passages Based on Integrated Bioinformatics Analysis

This study leveraged microarray datasets to investigate differentially expressed genes (DEGs) in cumulus cells and their relevance in predicting the successful implantation of embryos in human in-vitro fertilization procedures. The microarray data were obtained from the GEO database, encompassing samples of cumulus cells during in vitro culture and different passages. To ensure data consistency, inter-batch normalization was performed, and Principal Component Analysis (PCA) was applied to assess the impact of normalization on sample group clustering. The integrated dataset included samples from cumulus cells during in vitro culture, comprising 17,662 genes. Utilizing the "limma" software package, 1906 DEGs were identified, with 437 genes downregulated and 589 genes upregulated in the cumulus cells of infertility cases, while 748 genes were upregulated, and 1317 genes were downregulated in cumulus cells of successful implantation cases. Functional enrichment analysis utilized Gene Ontology, Metascape, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment tools. Biological processes and molecular functions were enriched, including protein targeting, mRNA processing, and molecular binding among the identified DEGs. Furthermore, target prediction and functional enrichment analysis of microRNAs (miRNAs) revealed 25 key genes and 13 relevant miRNAs were identified. Notably, hsa-miR-149, hsa-miR23b, hsa-miR-877, hsa-miR593, hsa-miR-18a, hsa-miR25, hsa-miR185, mmu-miR-207, hsa-miR425, hsa-miR214, hsa-miR-129, hsa-miR-629, and hsa-miR-194 emerged as the most prominent miRNAs with potential regulatory roles in successful embryo implantation. This comprehensive analysis provides valuable insights into the molecular mechanisms underlying embryo implantation, offering potential targets for further research and therapeutic interventions in assisted reproductive technologies.