Predictive biomarkers may allow precision therapy of endometriosis.

Introduction: Endometriosis is a chronic inflammatory gynecological disorder that causes pelvic pain. Due to the heterogeneity of the disease, response to any treatment in an individual is variable. We aimed to develop in vitro testing that could be adapted for use in precision therapy for endometriosis. We piloted a personalized medicine approach by identifying predictive biomarkers while determining the effect of bazedoxifene (BZA) and medroxyprogesterone acetate (MPA) on the gene expression of a progesterone receptor (PR), an estrogen receptor (ER), and an aromatase (CYP19A1) enzyme in cells cultured from biopsies of endometriosis patients. The differential expression of the most common molecular targets in endometriosis therapy correlated with cellular response. Methods: Primary eutopic endometrial stromal cells were cultured from endometrial biopsies obtained in secretory phase from women between 24 and 42 years old with moderate-to-severe endometriosis (stages III and IV). Exclusion criteria included use of hormonal treatments and intrauterine contraception in the 6 months prior to surgery. Cells were treated either with BZA, MPA, or vehicle control. Total RNA was extracted from the treated and untreated cells. Differential expression of genes that are involved in the pathogenesis of endometriosis was determined by quantitative reverse transcriptase-polymerase chain reaction analysis. Results: After determining the baseline expression levels of PRA/B, ERα and CYP19A1, response to treatment was monitored using Ki-67 as a marker of cell proliferation. MPA was effective in blocking proliferation in the group expressing high levels of PRA/B. Endometrium expressing high levels of CYP19A1 preferentially responded to BZA, a selective estrogen receptor modulator known to block estrogen action in endometrium. Conclusions: PR expression may predict progestin resistance in endometriosis while CYP19A1 expression may indicate the need to block estrogen signaling.