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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 T, Vrtacnik Bokal E, Lovrecic L, Kopitar AN, Maver A - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Human Reproduction, Division of Gynaecology, University Medical Centre Ljubljana, Slajmerjeva 3, SI-1000 Ljubljana, Slovenia.

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.

No MeSH data available.


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.
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pone.0115865.g001: 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.

Mentions: We first performed genome wide gene expression analysis using microarrays on 64 individual GC and CC samples, derived from 21 women: 13 GC and 10 CC samples surrounding non-fertilized (non-F) oocytes, 11 GC and 10 CC samples surrounding fertilized oocytes, which did not lead to pregnancy after SET (non-P) and 10 GC and 10 CC samples surrounding fertilized oocytes, which led to pregnancy after SET (P). Samples of GC and CC surrounding non-F oocytes were derived from non-P and P groups; 6 GC and 5 CC samples from non-P group, 7 GC and 5 CC from P group. In the next step, quantitative real-time PCR (qPCR) validation of microarray data was performed. We have used 25 CC samples (6 non-F, 9 non-P, 10 P) that were previously included in the microarray analysis, followed by a validation on a new set of 30 CC samples (10 non-F, 10 non-P, 10 P), derived from 20 women (Fig. 1).


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

Burnik Papler T, Vrtacnik Bokal E, Lovrecic L, Kopitar AN, Maver A - PLoS ONE (2015)

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.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4359149&req=5

pone.0115865.g001: 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.
Mentions: We first performed genome wide gene expression analysis using microarrays on 64 individual GC and CC samples, derived from 21 women: 13 GC and 10 CC samples surrounding non-fertilized (non-F) oocytes, 11 GC and 10 CC samples surrounding fertilized oocytes, which did not lead to pregnancy after SET (non-P) and 10 GC and 10 CC samples surrounding fertilized oocytes, which led to pregnancy after SET (P). Samples of GC and CC surrounding non-F oocytes were derived from non-P and P groups; 6 GC and 5 CC samples from non-P group, 7 GC and 5 CC from P group. In the next step, quantitative real-time PCR (qPCR) validation of microarray data was performed. We have used 25 CC samples (6 non-F, 9 non-P, 10 P) that were previously included in the microarray analysis, followed by a validation on a new set of 30 CC samples (10 non-F, 10 non-P, 10 P), derived from 20 women (Fig. 1).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Human Reproduction, Division of Gynaecology, University Medical Centre Ljubljana, Slajmerjeva 3, SI-1000 Ljubljana, Slovenia.

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.

No MeSH data available.