Meta-signature of human endometrial receptivity: a meta-analysis and validation study of transcriptomic biomarkers.
Signe AltmäeMariann KoelUrmo VõsaPriit AdlerMarina SuhorutšenkoTriin Laisk-PodarViktorija KukushkinaMerli SaareAgne Velthut-MeikasKaarel KrjutškovLusine AghajanovaParameswaran G LalitkumarKristina Gemzell-DanielssonLinda GiudiceCarlos SimónAndres SalumetsPublished in: Scientific reports (2017)
Previous transcriptome studies of the human endometrium have revealed hundreds of simultaneously up- and down-regulated genes that are involved in endometrial receptivity. However, the overlap between the studies is relatively small, and we are still searching for potential diagnostic biomarkers. Here we perform a meta-analysis of endometrial-receptivity associated genes on 164 endometrial samples (76 from 'pre-receptive' and 88 from mid-secretory, 'receptive' phase endometria) using a robust rank aggregation (RRA) method, followed by enrichment analysis, and regulatory microRNA prediction. We identify a meta-signature of endometrial receptivity involving 57 mRNA genes as putative receptivity markers, where 39 of these we confirm experimentally using RNA-sequencing method in two separate datasets. The meta-signature genes highlight the importance of immune responses, the complement cascade pathway and the involvement of exosomes in mid-secretory endometrial functions. Bioinformatic prediction identifies 348 microRNAs that could regulate 30 endometrial-receptivity associated genes, and we confirm experimentally the decreased expression of 19 microRNAs with 11 corresponding up-regulated meta-signature genes in our validation experiments. The 57 identified meta-signature genes and involved pathways, together with their regulatory microRNAs could serve as promising and sought-after biomarkers of endometrial receptivity, fertility and infertility.
Keyphrases
- genome wide
- endometrial cancer
- bioinformatics analysis
- genome wide identification
- transcription factor
- single cell
- immune response
- endothelial cells
- dna methylation
- genome wide analysis
- rna seq
- poor prognosis
- mesenchymal stem cells
- gene expression
- binding protein
- dendritic cells
- inflammatory response
- long non coding rna
- polycystic ovary syndrome