Apoptotic qPCR gene expression array analysis demonstrates proof-of-concept for rapid blastocoel fluid-conditioned media molecular prediction

Purpose: Successful identification of transcriptomic biomarkers within human IVF embryos may enhance implantation prediction and provide insights not available through conventional embryo biopsy genomic analysis. We demonstrate proof-of-concept for a methodology to assess overall embryo gene expression using qPCR with blastocoel fluid-conditioned media by examining the comparative presence of apoptotic genes. Methods: Blastocoel fluid-conditioned media were collected from 19 embryos (11 euploid) following trophectoderm biopsy of day-5 ICSI-IVF blastocysts. Media were assessed for apoptotic gene expression via qPCR. Statistical analysis of gene expression was conducted via Wilcoxon Signed-Ranks test (overall expression), multivariate ANOVA (functional gene groups), and chi-square test of independence (gene level). Results: A significantly higher overall apoptotic gene expression within euploid versus aneuploid embryos (p = 0.001) was observed. There was significantly (p = 0.045) higher expression of pro-apoptotic genes between implanted and not implanted embryos. Pro- vs. anti-apoptotic gene expression from all euploid embryos approached significance (p = 0.053). The ploidy status-based claim is further substantiated at the gene level with significantly higher expression of BBC3 (p = 0.012) and BCL2L13 (p = 0.003) in euploid embryos compared to aneuploid embryos. Conclusions: In this preliminary study, we demonstrate that (1) qualitative analysis of blastocoel fluid-conditioned media gene expression is possible, (2) global trends of expression are potentially related to clinical outcomes, and (3) gene-level expression trends exist and may be another viable metric for comparative expression between samples. The presence of statistical significance within analyses conducted with this sample size warrants a larger investigation of blastocoel fluid-conditioned media as an additional beneficial predictive tool for future IVF cases.