Human cumulus cells as biomarkers for embryo and pregnancy outcomes

Abstract

Single-embryo transfer is becoming increasingly common in in vitro fertilization (IVF) treatment as a means of reducing multiple pregnancy rates leading to a higher incidence of medical, perinatal and neonatal complications. Consequently, selecting embryos with the highest implantation potential is of great importance in assisted reproductive technology. To date, the choice of the best embryos to transfer is based on subjective morphological parameters. However, as judged by their subjective aspect, movement towards more sophisticated technologies to select the most competent oocytes and/or embryos with the greatest implantation potential have become available, including emerging 'omics' sciences, such as genomics, transcriptomics, proteomics and metabolomics. In this way, the study of the cumulus cells (CCs) transcriptomic profile offers the opportunity, by a non-invasive method, to predict oocyte and embryo competence because bidirectional traffic between CCs and the oocyte is very important for the acquisition of this competence. Using either RT-PCR or DNA microarrays, some studies have provided evidence for the genes expressed in CCs presenting potential biomarkers to predict embryo quality and pregnancy outcomes. This review provides an overview of the current knowledge about CCs as biomarkers for oocyte and embryo selection under an IVF program.

Single-cell expression analysis of BMP15 and GDF9 in mature oocytes and BMPR2 in cumulus cells of women with polycystic ovary syndrome undergoing controlled ovarian hyperstimulation

“…The synergistic process of folliculogenesis is regulated mainly by GDF9 and BMP15 as well as their receptors (e.g., BMPR2, TR1, and BMPR1B) [14][15][16][17]. These two members of the TGF-β superfamily are coexpressed in human oocytes and play a fundamental role in granulosa cells steroidogenesis, ovulation, oocyte maturation, and embryo development in mammals [11,18,19].…”

Sequential (hFSH + recFSH) vs homogenous (hFSH or recFSH alone) stimulation: clinical and biochemical (cumulus cell gene expression) aspects

“…In IVF the yield per oocyte collected is well below 10 % [31], and it is hard to believe that the oocyte is the primary reason for this. Transcriptome analysis of cumulus cells has been proposed as a non-invasive tool for determining the quality of the corresponding oocyte, but this raises a few questions [18,19,32].…”

“…that there is a positive correlation between CC gene expression and oocyte quality. Moreover, there are large variations in the number of "sensible" specific gene markers for ongoing pregnancy, from four [21] to 630, and then 45 for the same group, the majority being up-regulated [18,19]. It is not clear that a high level of expression in CC at this stage is a sign of quality: the cumulus cells have reached the end of their life's journey, especially after cumulus expansion.…”

“…The impact on clinical data has been recorded. Cumulus cell transcript analyses were studied, as they are thought to represent a non-invasive approach for assessment of oocyte quality and molecular events triggered by FSH-based stimulation protocols [18][19][20][21]. Microarray technology offers a throughput transcript analysis tool to evaluate the effect of different FSH isoform mixes on biological and molecular pathways during ovarian stimulation.…”

Gene expression profiling of granulosa cells from PCOS patients following varying doses of human chorionic gonadotropin

“…Similarly, quantitative real-time RT-PCR analysis of genes from human cumulus cells was predictive of the quality of their enclosed oocytes [12,29,46]. These observations were further supported by subsequent studies that measured global gene expression of cumulus cells, which was concluded to be a non-invasive test for oocyte/embryo quality [2,3,15,41]. Granulosa and cumulus cell gene expression profiling has also been used to compare the effects of recombinant FSH vs. human menopausal gonadotrophin (hMG) [6,14], floating vs. cumulus granulosa cells [22], cumulus cells from lean vs. overweight-obese PCOS patients [21], and ovarian reserve status in young women with diminished ovarian reserve [39].…”