No specific gene expression signature in human granulosa and cumulus cells for prediction of oocyte fertilisation and embryo implantation

Abstract

In human IVF procedures objective and reliable biomarkers of oocyte and embryo quality are needed in order to increase the use of single embryo transfer (SET) and thus prevent multiple pregnancies. During folliculogenesis there is an intense bi-directional communication between oocyte and follicular cells. For this reason gene expression profile of follicular cells could be an important indicator and biomarker of oocyte and embryo quality. The objective of this study was to identify gene expression signature(s) in human granulosa (GC) and cumulus (CC) cells predictive of successful embryo implantation and oocyte fertilization. Forty-one patients were included in the study and individual GC and CC samples were collected; oocytes were cultivated separately, allowing a correlation with IVF outcome and elective SET was performed. Gene expression analysis was performed using microarrays, followed by a quantitative real-time PCR validation. After statistical analysis of microarray data, there were no significantly differentially expressed genes (FDR<0,05) between non-fertilized and fertilized oocytes and non-implanted and implanted embryos in either of the cell type. Furthermore, the results of quantitative real-time PCR were in consent with microarray data as there were no significant differences in gene expression of genes selected for validation. In conclusion, we did not find biomarkers for prediction of oocyte fertilization and embryo implantation in IVF procedures in the present study.

Fig 1. Study flowchart.

Microarray analysis was performed on 64 individual cumulus and granulosa cell samples derived from 21 women; the number of the samples in each group (non-F, non-P, P) is presented. In the second stage of the study, qPCR validation was performed on 55 samples derived from 41 women; 25 samples had previously been used for microarray analysis, 30 samples were newly added to the study and derived from 20 new women. 'newly added samples; Non-F—unfertilized; non-P—fertilized, but not pregnant; P—pregnant; GC- granulosa cells; CC- cumulus cells.

Fig 2. Number of genes surpassing a specified significance threshold (FDR = 0.05) in granulosa and cumulus cell lines when comparing pregnant versus non-pregnant samples.

Blue bars represent nominal P value, red bars represent adjusted P value.

Fig 3. Predictive performance of expression biomarkers in granulosa and cumulus cells according to microarray data.

AUC- area under the curve; GC- granulosa cells; CC- cumulus cells.

Fig 4. qPCR validation of microarray data.

Comparison of relative mRNA expression of the genes selected for validation of microarray data between non-P and P samples. A) qPCR performed on a set of cumulus cells samples that were previously used in microarray analysis. B) qPCR performed on a novel set of cumulus cells samples. Non-P: fertilized, but not pregnant; P- pregnant.