Background: Disturbances in immunological responses and modulation lead to implantation and pregnancy failure and might be involved in the pathogenesis of infertility. This project aimed to screen and identify immune-related genes as potential biomarkers for treatment.Methods: Gene expression profiles were obtained from Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were screened using GEO 2R to explore potential biomarkers. Protein-protein interaction (PPI) network analysis and functional enrichment analysis were applied to explore possible mechanisms. The deconvolution algorithm [referred to as Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)] was employed to assess tissue-infiltrating immune cells. Western blot analysis and immunohistochemistry (IHC) were conducted for determination of protein levels.Results: In this research, we identified 24 candidate immune-related DEGs via combined DEGs and functional analysis. We also found that the ratio of M0 macrophages and resting mast cells was higher in infertile group (P<0.05), whereas the amounts of activated natural killer (NK) cells was significantly lower compared with the control group (P<0.05). Furthermore, we evaluated the relationship between immune cells and candidate genes and found that 17 genes were related to M0 macrophages, resting mast cells, or activated NK cells. The genes CD40, PRF1, and EDN3 were chosen based on validation from independent datasets. Finally, our clinical samples confirmed the expression of the 3 genes.Conclusions: The study recognized 3 genes that are signatures and could be potential biomarkers for unexplained infertility. These genes might guide the immunotherapy of these patients and become new treatment targets.

For patients with recurrent implantation failure (RIF), immune system imbalances have become the focus of research. The effects of different classes of immunotherapies on improving pregnancy outcomes have not been fully established. This network meta-analysis was performed to assess the impact of popular immunotherapies in women with RIF. We systematically searched the Cochrane Central Register of Controlled Trials, PubMed, Embase, and Web of Science databases as well as clinical trial registration websites. Randomized controlled trials comparing immunotherapeutic outcomes were included. We performed the random-effects network metaanalysis to compare efficacy measures. A total of 21 trials involving 2277 participants and 8 immunotherapies were eligible for this study. Patients that had been administered with PBMCs, G-CSF, PRP, and sirolimus exhibited higher CPR than those administered with the placebo (2.63, 1.71-4.06; 2.03, 1.35-3.05; 1.98, 1.02-3.84; 2.55, 1.36-4.79; and 3.95, 1.33-11.72, respectively). For IR, only PBMCs and G-CSF were significantly more effective than the placebo (2.92, 1.39-6.12; 2.66, 1.16-6.06, respectively). In terms of LBR, PBMCs (2.96, 1.67-5.27) and sirolimus (3.55, 1.18-10.64) were effective. However, r-hLIF (0.25, 0.10-0.62) had a reduced risk of LBR. No therapeutic regimen was found to have significantly decreased MR, but PBMCs exhibited the lowest rank among all interventions (0.28, 0.06-1.44). To improve clinical pregnancy while reducing miscarriage outcomes, PBMCs might be a beneficent therapeutic option for RIF in the future.

Hepatocellular carcinoma (HCC) is a malignant primary liver cancer with poor prognosis. Most previous studies on anti-HCC effects of traditional Chinese medicines (TCM) have focused on the mechanism of direct action and few researchers considered that TCM can inhibit tumor progression and improve prognosis of HCC patients through regulating tumor microenvironment (TME). In this study, network pharmacology combined bioinformatics methods were employed to analysis mechanism of Bombyx batryticatus (B. batryticatus, one of the most frequently used traditional Chinese animal medicines, has been used in some Asian countries for centuries as an anticancer agent, anti-inflammatory agent, and antioxidant.) in regulating TME of HCC. The results showed that 24 core targets and 2 compounds were identified from overlapping between differential expression genes related to HCC in the cancer genome atlas (TCGA) database and targets of B. batryticatus in TCMSP database. For further analyzing the role of TME heterogeneity of HCC on anti-HCC mechanism of B. batryticatus, the correlation of core targets related with overall survival of HCC with TME cells in hepatitis C or hepatitis B virus-associated hepatocellular carcinoma (VIR) and non-hepatitis C or hepatitis B virus-associated hepatocellular carcinoma (NVIR) were calculated, respectively. The results showed that AKR1C3, SPP1 were significantly related with macrophages in VIR and other targets including NR1I2, CYP1A2 and CYP3A4 were significantly associated with macrophages in NVIR; the target protein AKR1C3 was significantly negative correlated with macrophages M1 in VIR (cor=-0.35, P-value0.05). In conclusion, the molecular mechanism of anti-HCC of B. batryticatus can be related to the tumor microenvironment to some extent. B. batryticatus may exert its anti-cancer effects and improve prognosis of patients by regulating macrophages M1 in VIR and NVIR through acting on different targets.