Live birth in patients stimulated with r-hFSH or r-hFSH: r-hLH is strongly associated with cumulus cell derived gene...

Morphological embryo assessment, time-lapse imaging or PGT-A can prioritize an embryo for transfer in IVF/ICSI cycles. Nevertheless, there remains potential to enhance the efficiency of ART cycles and reduce the time-to-pregnancy. Previously, a pregnancy predictive non-invasive cumulus cell (CC) test was developed and clinically validated for HP-hMG stimulated patients. In this study, CC gene expression profiles from r-hFSH and r-hFSH:r-hLH stimulated ICSI patients were evaluated for their potential to predict the most competent oocyte/embryo, resulting in live birth.

This observational cohort study comprises 113 patients allocated to the two study groups stimulated with either r-hFSH (n = 47) or r-hFSH:r-hLH (n = 66). RT-qPCR analysis was performed on 1135 CC samples for 11 predefined biomarkers (CAMK1D, EFNB2, SASH1, GOT1, SLC6A9, HAS2, PTGS2, HSPH1, VCAN, GSTA4, STC2) and 2 endogenous controls (UBC, B2M). Univariate (95%CI) and multivariable analyses (leave-one-out cross-validation and stepwise linear regression) were performed.

The two study groups were first compared to verify if one prediction model could fit the two patient groups. While patient characteristics and stimulation were comparable, the biomarker expression for EFNB2 (e.g.: CC of all oocytes n = 1123, 95%CI: 0.27, 0.49) and GOT1 (CC of all oocytes n = 1123, 95%CI: -0.25, -0.11) significantly differed between the two groups. Stepwise linear regression models were therefore built for the two study groups. The biomarker expression in CC of oocytes developing into transferred blastocysts was compared based on transfer outcomes (live birth or not) and models contained only gene expression data. The strongest live birth predictive biomarkers were GOT1, HAS2, SASH1 and PTGS2 for r-hFSH patients (AUC 0.7284; 70% accuracy) and GOT1 with HAS2 (AUC 0.9529; 88% accuracy) for r-hFSH:r-hLH stimulated patients.

These findings merit further validation in an interventional prospective study. Predictive CC biomarkers are a promising non-invasive technology to shorten the time-to-pregnancy in ICSI patients stimulated with different types of recombinant gonadotropins.

Ethical approval was obtained from the Ethical Committee of Vrije Universiteit Brussel - UZ Brussel (IEC: 2020.335) and the study was registered at ClinicalTrials.gov (ID NCT04710264; registration date 14/1/2021).