Genomic assessment of follicular marker genes as pregnancy predictors for human IVF

Abstract

Embryo selection efficiency in human IVF procedure is still suboptimal as shown by low pregnancy rates with single embryo transfer (SET). Bidirectional communication between the oocyte and follicular cells (FC) is essential to achieve developmental competence of the oocyte. Differences in the gene expression profile of FCs from follicles leading to pregnancy could provide useful markers of oocyte developmental competence. FCs were recovered by individual follicle puncture. FC expression levels of potential markers were assessed by Q-PCR with an intra-patient and an inter-patient analysis approach. Using gene expression, a predictive model of ongoing pregnancy was investigated. Using intra-patient analysis, four candidate genes, phosphoglycerate kinase 1 (PGK1), regulator of G-protein signalling 2 (RGS2), regulator of G-protein signalling 3 (RGS3) and cell division cycle 42 (CDC42) showed a difference between FCs from follicles leading to a pregnancy or developmental failure. The best predictors for ongoing pregnancy were PGK1 and RGS2. Additionally, inter-patient analysis revealed differences in FC expression for PGK1 and CDC42 between follicles leading to a transferred embryo with positive pregnancy results and those with negative results. Both inter-patient and intra-patient approaches must be taken into consideration to delineate gene expression variations in the context of follicular competence. A predictor model using biomarkers could improve the efficiency of predicting developmental competence of oocytes. These new approaches provide useful tools in the context of embryo selection and in the improvement of pregnancy rates with SET.

Protein expression in human cumulus cells as an indicator of blastocyst formation and pregnancy success

“…Therefore, the majority of investigations have focused on the analysis of CC gene expression to identify non-invasive predictors of embryo development and treatment outcome [14,[24][25][26][27][28]. However, few experiments have focused on protein expression [37], which is a more reliable indicator of the cellular phenotype.…”

“…In fact, although it is known that prolonging the embryo culture period allows for a better selection of embryos for transfer leading to increased implantation rates and reduced risk of twin and higher order pregnancies [38], there is concern that a strategy of blastocyst culture may result in higher cycle cancellation rates [39]. Potential CC biomarkers correlated to oocyte quality, embryo competence, or pregnancy outcome have been identified by microarray analysis [14,24,26,40], RT-PCR [41,42], or quantitative RT-PCR [25,43,44]. Although genomics can supply valuable information regarding expected functions, the proteome is the entire complement of proteins expressed by a genome, and therefore, it is more indicative of the phenotype and can provide important information that is complementary to the data obtained from gene expression studies.…”

“…Although many studies have focused on the analysis of CC gene expression in the search for novel markers of oocyte competence and pregnancy outcome [14,[24][25][26][27][28], this approach does not actually reflect the cell phenotype. In fact, protein synthesis is the major outcome of gene expression and is directly associated with the observed phenotype, which is not always the case with RNA.…”

Biomarkers of human oocyte developmental competence expressed in cumulus cells before ICSI: a preliminary study

“…Each PC is therefore a linear combination of the levels of expression of the measured genes. Based on the maximal Euclidean distance between the positive and negative samples, PCA was used to determine the true positive sample associated with successful pregnancy among the two transferred embryos as described elsewhere [39].…”

Granulosa cell biomarkers to predict pregnancy in ART: pieces to solve the puzzle

“…Validation of 10 genes was performed using qRT-PCR and showed UDP-glucose pyrophosphorylase 2 (UGP2) and pleckstrin homology-like domain family A member 1 (PHLDA1) gene expression was significantly higher in the pregnant group. In addition, the same lab performed a slightly different study and performed logistical regression analysis to determine which genes would best predict pregnancy (Hamel et al 2010a). Included in these analyses were 9 patients for intrapatient analysis with successful pregnancies vs arrested embryos, and 38 patients for inter-patient analysis that included a third group with unsuccessful pregnancies.…”