Infertility affects approximately 48 million couples globally. Despite the enormous progress of the methods of reproductive medicine that has been made since the first test-tube baby was born in 1978, the implantation rate of day-3 embryos is only around 15-20 % and 30 % of day-5 embryos. Numerous strategies aim to improve implantation rates and prevent repeated implantation failure. However, there is no specific general recommendation leading to satisfying results. One of the many risk factors relevant in this regard is the uterine immunological make-up, mainly the uterine Natural Killer (uNK) cells. They orchestrate the overall immune response during implantation by influencing trophoblast invasion and vascular remodeling and throughout pregnancy, uNK cells are also the main immune cells at the maternal–fetal interface. Previously, uNK count has been correlated with various fertility issues including idiopathic recurrent miscarriage. The present study used endometrial samples collected from 256 patients with recurrent implantation failure (RIF), habitual abortion (HA) and idiopathic sterility. Samples were collected between day 19 and 21 of the menstrual cycle mainly by Pipelle endometrial sampling. The samples were fixed in formalin for 24 hours and further processed for immunohistochemistry using anti-CD56 to visualize this antigen marker of uNK cells. Immunohistochemical counting was performed to assess the low, normal, or elevated count of uNK cells. According to the one-way ANOVA test, the age of our patients did not have any influence on the count of uNK cells. With Spearman correlation analysis, we found statistically significant correlation (p-value 0.05) of -0.133 between prior miscarriage and lower uNK cell count. Using the same analysis we found statistically significant correlation (correlation 0.233 with p-value 0.01) between number of uNK cells and activation status. Patients with higher uNK cells were more frequenty diagnosed with endometriosis (p-value 0.05, correlation 0.130). Patients with an immunological factor of sterility (defined by a clinical immunologist) had a lower chance of gravidity (-0.203 with p-value 0.01). Based on our results, we can confirm that there is a correlation between RIF, HA, idiopathic sterility, endometriosis, and immunological factor of sterility (uNK cell count). The true predictive value with regard to fertility outcomes needs to be addressed in future research.
Despite recent advancements in reproductive medicine, recurrent implantation failure and habitual abortion remain ongoing issues. One of the most important aspects of successful implantation is the intricate immune response and regulation necessary for the acceptance of the hemiallogenic embryo. The most numerous immune cells in the decidua are uterine natural killer cells (uNK). Studies suggest that changes in the uNK count and physiology may be responsible for the aforementioned pathological conditions. Thus, testing for uNK may provide valuable insights into their pathogenesis. The study compared Pipelle endometrial sampling with conventional curettage to find out whether the less invasive Pipelle method is a viable alternative of tissue collection. Tissue samples from 14 patients obtained by both methods were examined. The average size of tissue samples obtained with Pipelle was 17 mm2 , samples obtained with curettage had on average 34 mm2 . Using immunohistochemical visualization of CD56 (NK cells) and granzyme B antigens (serine protease-expressing activation state of NK cells), it was found that the average total count of CD56 / mm2 was 115 for Pipelle and 120 for curettage, respectively. The study also proved a correlation between granzyme B positivity and identification of NK cells clusters. The results indicated that Pipelle endometrial sampling seems a suitable method of tissue harvesting for the purpose of uNK cells examination. Pipelle endometrial sampling is safe, cost-effective and can be performed on an outpatient basis without the need of anesthesia or analgesia. Several issues remain yet to be solved: how to standardize the subsequent uNK testing, how to interpret the results and finally yet importantly, how to use this knowledge in personalized treatment protocols.