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Updated: May 8, 2026
Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos
Published on: February 22, 2016
Beyond morphology: a multi-protein analysis of single blastocyst conditioned medium to predict pregnancy potential of
Peilin Chen1, Chunyu Huang1, Hongzhan Zhang1
1Shenzhen Key Laboratory of Reproductive Immunology for Peri-implantation, Guangdong Engineering Technology Research Centre of Reproductive Immunology for Peri-implantation, Shenzhen Zhongshan Institute for Reproductive Medicine and Genetics, Shenzhen Zhongshan Obstetrics and Gynaecology Hospital, Shenzhen, China.
Research Question:
Can a non-invasive approach predicting embryonic pregnancy potential be developed by analysing proteins in single blastocyst conditioned medium (SBCM)?
Design:
Patients with infertility who underwent vitrified-warmed single blastocyst transfer (January 2021-December 2023) were included in this study. SBCM corresponding to transferred blastocysts was collected and analysed using highly sensitive single-molecule array technology to quantify the concentrations of 12 candidate proteins (n = 1390). Key proteins were selected for model development for prediction of clinical pregnancy using a training set (n = 240), and subsequently validated with a test set (n = 60). Performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curves.
Results:
Among the 12 proteins examined, elevated concentrations of interleukin-8 (IL-8) (P < 0.001) and beta-human chorionic gonadotrophin (B-HCG) (P = 0.009) were associated with a significantly higher clinical pregnancy rate, whereas elevated C-C motif chemokine 5 (RANTES, 'regulated on activation, normal T cell expressed and secreted') was associated with a significantly lower pregnancy rate (P < 0.001). Individual biomarkers demonstrated modest discriminatory capacity for predicting clinical pregnancy for IL-8 (AUC = 0.600; P = 0.03), B-HCG (AUC = 0.588; P = 0.002) and RANTES (AUC = 0.397; P = 0.001). A multi-protein prediction model integrating these three biomarkers exhibited superior discriminatory performance (AUC = 0.722), and significantly outperformed each individual protein marker (P ≤ 0.005). The combined model incorporating both the multi-protein signature and morphological grading parameters achieved optimal predictive accuracy (AUC = 0.744). These findings were validated in an independent test set (AUC = 0.724).
Conclusions:
This study establishes a novel multi-protein model for predicting clinical pregnancy. The combination of IL-8, B-HCG and RANTES in SBCM provides a promising non-invasive approach for embryo selection, particularly when integrated with morphological assessment.
