Stratifying Cumulus Cell Samples Based on Molecular Profiling to Help Resolve Biomarker Discrepancies and to Predict Oocyte Developmental Competence.

To increase the efficiency of assisted reproductive techniques (ART), molecular studies have been performed to identify the best predictive biomarkers for selecting the most suitable germ cells for fertilization and the best embryo for intra-uterine transfer. However, across different studies, no universal markers have been found. In this study, we addressed this issue by generating gene expression and CpG methylation profiles of outer cumulus cells obtained during intra-cytoplasmic sperm injection (ICSI). We also studied the association of the generated genomic data with the clinical parameters (spindle presence, zona pellucida birefringence, pronuclear pattern, estrogen level, endometrium size and lead follicle size) and the pregnancy result. Our data highlighted the presence of several parameters that affect analysis, such as inter-individual differences, inter-treatment differences, and, above all, specific treatment protocol differences. When comparing the pregnancy outcome following the long protocol (GnRH agonist) of ovarian stimulation, we identified the single gene markers ( and , FDR < 5%) which were also correlated with endometrium size, upstream regulators (e.g., , , , , and ) and several bio-functions related to cell death (apoptosis) and cellular growth and proliferation. In conclusion, our study highlighted the need to stratify samples that are very heterogeneous and to use pathway analysis as a more reliable and universal method for identifying markers that can predict oocyte development potential.

PMID: 34203623