Pregnancy Prediction in Single Embryo Transfer Cycles after ICSI Using QPCR: Validation in Oocytes from the Same Cohort

Abstract

Cumulus cell (CC) gene expression is being explored as an additional method to morphological scoring to choose the embryo with the highest chance to pregnancy. In 47 ICSI patients with single embryo transfer (SET), from which individual CC samples had been stored, 12 genes using QPCR were retrospectively analyzed. The CC samples were at the same occasion also used to validate a previously obtained pregnancy prediction model comprising three genes (ephrin-B2 (EFNB2), calcium/calmodulin-dependent protein kinase ID, stanniocalcin 1). Latter validation yielded a correct pregnant/non-pregnant classification in 72% of the samples. Subsequently, 9 new genes were analyzed on the same samples and new prediction models were built. Out of the 12 genes analyzed a combination of the best predictive genes was obtained by stepwise multiple regression. One model retained EFNB2 in combination with glutathione S-transferase alpha 3 and 4, progesterone receptor and glutathione peroxidase 3, resulting in 93% correct predictions when 3 patient and treatment cycle characteristics were included into the model. This large patient group allowed to do an intra-patient analysis for 7 patients, an analysis mimicking the methodology that would ultimately be used in clinical routine. CC related to a SET that did not give pregnancy and CC related to their subsequent frozen/thawed embryos which ended in pregnancy were analyzed. The models obtained in the between-patient analysis were used to rank the oocytes within-patients for their chance to pregnancy and resulted in 86% of correct predictions. In conclusion, prediction models built on selected quantified transcripts in CC might help in the decision making process which is currently only based on subjective embryo morphology scoring. The validity of our current models for routine application still need prospective assessment in a larger and more diverse patient population allowing intra-patient analysis.

The transcriptome of corona radiata cells from individual MІІ oocytes that after ICSI developed to embryos selected for transfer: PCOS women compared to healthy women

“…However, the apparent inconsistency between the present study and the study by Haouzi et al [ 5 ] could be explained by the different study designs and experimental approaches: Firstly, we used enzymatically isolated CRCs, which constitute the innermost cells closest to the oocyte, whereas Haouzi et al [ 5 ] used mechanically cut cumulus cells. Several previous studies have successfully used enzymatically isolated cumulus cells [ 24 – 29 ] and CRCs [ 30 , 31 ] to investigate gene expression differences according to e.g. oocyte quality.…”

“…The strict use of CRCs from MІІ oocytes developing into top quality embryos in the present microarray study might explain why there were no individual genes with significant differential expression between PCOS and controls. Previous studies have shown that the transcriptome of cumulus cells from MІІ oocytes of poor developmental competence differed from cumulus cells of MІІ oocytes with high developmental competence [ 24 , 26 , 29 , 31 – 36 ]. These previous findings underlined the importance of oocyte selection, when comparing cumulus cells or CRCs in relation to a certain condition, such as PCOS.…”

Oocyte environment: follicular fluid and cumulus cells are critical for oocyte health

“…Additional cumulus cell genes involving signaling, homeostasis, and metabolism have been variably reported as higher (VCAN, PTGS2, EFNB2, SPSB2, UBQLN1, DPP8, HIST1H4C, CALM1, NRP1, PSMD6, BCL2L11, PCK1, and RGS2) or lower (TOM1, NFIB) in association with embryos yielding pregnancy or live births compared with embryos failing to implant (110)(111)(112)(113)(114)(115)(116). In addition, cumulus cell gene expression of HAS2 and FSH receptor has been used to select up to three metaphase II oocytes within a cohort of oocytes, from which one selected oocyte (vs. a randomly selected metaphase II oocyte) has a 60% (vs. a 38%) chance of developing to a live birth (111).…”

Making IVF more effective through the evolution of prediction models: is prognosis the missing piece of the puzzle?

“…Exploring a different concept and introducing the value of the genetic factor in model development, Wathlet et al (2013) folded 'genomics' into a prediction model on a successful embryo transfer and live birth. They initially compared the RNA levels of 12 genes derived from cumulus cells of pregnant and non-pregnant women.…”