Cumulus Cell Transcriptome Signatures as Predictive Biomarkers in ART: A Cross-Sectional Prospective Study of Molecular Determinants for Embryo Competence and Pregnancy Outcomes
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background In ART, embryo selection traditionally relies on morphological assessment, which has limited predictive value for developmental potential. Cumulus cells offer a non-invasive source of biomarkers for oocyte quality. This study investigated whether three candidate genes, CALM1 , PSMD6 , and AK124742 , could serve as predictive biomarkers for pregnancy outcomes, particularly in the context of PCOS. Methods This cross-sectional prospective study included 66 patients (33 PCOS and 33 controls) undergoing IVF or ICSI treatment. Gene expression in cumulus cells was analyzed using qRT-PCR with GAPDH as reference. Pregnancy outcomes were monitored through β-hCG testing and confirmed by ultrasound imaging of fetal cardiac activity. Results All three genes showed elevated expression in the pregnant versus non-pregnant group, with PSMD6 (p < 0.001) and AK124742 (p < 0.05) reaching statistical significance. Independent of pregnancy status, PCOS patients exhibited significantly higher CALM1 and AK124742 expression (p = 0.003, p < 0.001) and lower PSMD6 expression (p = 0.002) compared to controls. Age-adjusted analysis revealed CALM1 was significantly elevated in pregnant patients (p < 0.05). PCOS patients yielded significantly more oocytes (14.15 vs. 9.03, p = 0.005), but this did not correlate with higher pregnancy rates. IVF achieved significantly higher success rates than ICSI (85.7% vs. 43.3%, p = 0.007). Sperm morphology showed a significant correlation with fertilization rates (r²=0.337, p < 0.001). Conclusion In PCOS patients, three genes showed potential as embryo competence biomarkers, but their expression was significantly altered. PCOS had a stronger impact on gene expression than pregnancy outcome, indicating that ovarian pathophysiology affects cumulus cell molecular signatures. This underscores the need to consider ovarian health for personalized fertility treatments.