Dataset Information

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.

SUBMITTER: Burnik Papler T

PROVIDER: S-EPMC4359149 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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

Burnik Papler Tanja T Vrtacnik Bokal Eda E Lovrecic Luca L Kopitar Andreja Natasa AN Maver Ales A

PloS one 20150313 3

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 express ...[more]

PMID: 25769026

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Project description:Currently, in vitro fertilization (IVF) is one of the most common approaches towards treating infertility. However, the success of this approach is still relatively low an the outcome of the IVF procedure is challenging to predict. At present, there is no highly successful marker that could reliably predict the pregnancy outcome in the process of assisted reproduction (AR). Currently, multiple embryo transfers are performed to warrant a successful pregnancy outcome, but this commonly results in multiple pregnancies, narrowing the feasibility of this method for a subset of couples affected by infertility. Recently IVF cycles with single-embryo transfers have become an option of interest in AR approaches. Such cycles, however, are significantly less successful and for this reason, there is an incentive to improve the pregnancy chance per IVF cycle by incorporating more criteria for selection of the embryo with the highest implantation potential. Gene expression in follicular cells, including granulosa cells (GC) and cumulus cells (CC) has previously been considered as a tool to predict the quality of the oocytes in several studies in addition to assessing the morphologic criteria of the embryos. Gene expression estimation in these cells, especially of the CC population, carries along several benefits as their harvesting is non-invasive, they are in direct contact with the oocyte and are usually discarded during the process of intracytoplasmatic sperm injection procedure (ICSI), making them any easily accessible surrogate tissue for gene expression analyses. Considering that several studies reporting various rates of success in prediction of AR cycle outcome with expression as a biomarker have been published, we attempted to perform the largest study of global gene expression alterations in finding novel biomarkers to outcome of in- vitro fertilization, which would encompass discovery of new biomarker genes and subsequent confirmational study of the selected biomarker set on an independent validation group. In this experiments 4 samples were hybridized twice, to allow for inspection of technical validity of microarray experiments.

Dataset Information

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

Publications

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

Similar Datasets

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