Modeling human endometrial decidualization from the interaction between proteome and secretome.

CONTEXT Decidualization of the human endometrium, which involves morphological and biochemical modifications of the endometrial stromal cells (ESCs), is a prerequisite for adequate trophoblast invasion and placenta formation. OBJECTIVE This study aims to investigate the proteome and secretome of in vitro decidualized ESCs. These data were combined with published genomic information and integrated to model the human decidualization interactome. DESIGN Prospective experimental case-control study. SETTING A private research foundation. PATIENTS Sixteen healthy volunteer ovum donors. INTERVENTION Endometrial samples were obtained, and ESCs were isolated and decidualized in vitro. MAIN OUTCOME MEASURES Two-dimensional difference in-gel electrophoresis, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry, Western blot, human protein cytokine array, ELISA, and bioinformatics analysis were performed. RESULTS The proteomic analysis revealed 60 differentially expressed proteins (36 over- and 24 underexpressed) in decidualized versus control ESCs, including known decidualization markers (cathepsin B) and new biomarkers (transglutaminase 2, peroxiredoxin 4, and the ACTB protein). In the secretomic analysis, a total of 13 secreted proteins (11 up- and 2 down-regulated) were identified, including well-recognized markers (IGF binding protein-1 and prolactin) and novel ones (myeloid progenitor inhibitory factor-1 and platelet endothelial cell adhesion molecule-1). These proteome/secretome profiles have been integrated into a decidualization interactome model. CONCLUSIONS Proteomic and secretomic have been used as hypothesis-free approaches together with complex bioinformatics to model the human decidual interactome for the first time. We confirm previous knowledge, describe new molecules, and we have built up a model for human in vitro decidualization as invaluable tool for the diagnosis, therapy, and interpretation of biological phenomena.