<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Since the introduction of <italic>in vitro</italic> fertilization (IVF) in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC) have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR)] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC) for two prediction models were calculated. Among tested genes, <italic>AMHR2</italic> and <italic>LIF</italic> showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.</p></abstract>

Since the introduction of in vitro fertilization (IVF) in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC) have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR)] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC) for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

Embryo quality predictive models based on cumulus cells gene expression

Division of Medical Oncology, Institute of Oncology, Ljubljana,

Reproductive Unit, Department of Obstetrics and Gynaecology, University Medical Centre Ljubljana, Ljubljana,

Faculty of Medicine, University of Ljubljana, Ljubljana,

Balkan Journal of Medical Genetics

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

{"article-title":"Embryo quality predictive models based on cumulus cells gene expression"}

Since the introduction of in vitro fertilization (IVF) in clinical practice of infertility treatment, the indicators for high quality embryos were...

Gene	Mann-Whitney U (significance)a Significance expressed as a p value.	AMHR2 High Group (significance)a Significance expressed as a p value.	AMHR2 Low Group (significance)a Significance expressed as a p value.
AMHR2	0.03	–	–
FSHR	0.44	0.52	0.09
LIF	0.11	0.03	0.59
SERPINE2	0.74	0.72	0.37
0.72VEGFC	0.72	0.34	0.75

Parameters	Significancea Significance in the model expressed as a p value.	Exp(B)	95% CI for Exp(B)
			Lower	Upper
Age	0.26	1.10	0.93	1.28
Body mass index	0.82	0.98	0.79	1.21
Patient	0.25	0.93	0.82	1.05
Constant	0.67

Embryo quality predictive models based on cumulus cells gene expression

Article Category: Original Article

Published Online: Aug 02, 2016

Page range: 5 - 12

DOI: https://doi.org/10.1515/bjmg-2016-0001

Keywords
gene, Cumulus cells (CC), Embryo prediction, gene, fertilization (IVF)

© 2016 Walter de Gruyter GmbH, Berlin/Boston

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Binary logistic model for embryo outcome where age, body mass index and patient distribution were tested between high quality and low quality embryo groups. None of the tested variables were shown to be significant in our data.

Embryo quality predictive models based on cumulus cells gene expression

Article Category: Original Article

Published Online: Aug 02, 2016

Page range: 5 - 12

DOI: https://doi.org/10.1515/bjmg-2016-0001

Keywordsgene, Cumulus cells (CC), Embryo prediction, gene, fertilization (IVF)

© 2016 Walter de Gruyter GmbH, Berlin/Boston

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Binary logistic model for embryo outcome where age, body mass index and patient distribution were tested between high quality and low quality embryo groups. None of the tested variables were shown to be significant in our data.

Keywords
gene, Cumulus cells (CC), Embryo prediction, gene, fertilization (IVF)