Predicting risk of endometrial failure: a biomarker signature that identifies a novel disruption independent of endometrial timing in patients undergoing hormonal replacement cycles.

To propose a new gene expression signature that identifies endometrial disruptions independent of endometrial luteal phase timing and predicts if patients are at risk of endometrial failure. Multicentric, prospective study. Reproductive medicine research department in a public hospital affiliated with private fertility clinics and a reproductive genetics laboratory. Caucasian women (n=281; 39.4±4.8 years old with a BMI of 22.9±3.5 kg/m Endometrial biopsies collected in the mid-secretory phase. Endometrial luteal phase timing-corrected expression of 404 genes and reproductive outcomes of the first single embryo transfer (SET) following biopsy collection to identify prognostic biomarkers of endometrial failure. (s): Removal of endometrial timing variation from gene expression data allowed patients to be stratified into poor (n=137) or good (n=49) endometrial prognosis groups based on their clinical and transcriptomic profiles. Significant differences were found between endometrial prognosis groups in terms of reproductive rates: pregnancy (44.6% vs. 79.6%, p-value=3.8E-5), live birth (25.6% vs. 77.6%, p-value=5E-10), clinical miscarriage (22.2% vs. 2.6%, p-value=0.0066), and biochemical miscarriage (20.4% vs. 0%, p-value=0.0023). The relative risk of endometrial failure for patients predicted as a poor endometrial prognosis was 3.3-times higher than those with a good prognosis. The differences in gene expression between both profiles were proposed as a biomarker, coined the Endometrial Failure Risk (EFR) signature. Poor prognosis profiles were characterized by 59 up-regulated and 63 down-regulated genes mainly involved in regulation (17.0%), metabolism (8.4%), immune response and inflammation (7.8%). This EFR signature had a median accuracy of 0.92 (min=0.88, max=0.94), median sensitivity of 0.96 (min=0.91, max=0.98), and median specificity of 0.84 (min=0.77, max=0.88), positioning itself as a promising biomarker for endometrial evaluation. (s): The EFR signature revealed a novel endometrial disruption, independent of endometrial luteal phase timing, present in 73.7% of patients. This EFR signature stratified patients into two significantly distinct and clinically relevant prognosis profiles providing opportunities for personalized therapy. Nevertheless, further validations are needed prior to implementing this gene signature as an artificial intelligence (AI)-based tool to reduce the risk of patients experiencing endometrial failure.

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