Endometriosis, a chronic disease characterized by recurrent pelvic pain and infertility, severely impacts the health and life quality of many women worldwide. Since phytoestrogens are commonly found in a variety of foods, and estrogen is a major pathological factor for the pathogenesis of endometriosis, their possible involvement cannot be ignored. This review summarizes data on the relationship between phytoestrogen intake and endometriosis risk, and analyzes the findings from in vitro experiments, rodent endometriotic models, and human intervention trials. While favorable results were often obtained from endometrial primary cultures and animal models for resveratrol, isoflavones and puerarin, only resveratrol showed promising results in human intervention trials. Critical issues concerning the current study efforts are discussed: the possible reasons beneath the discrepant observations of estrogenic/anti-estrogenic effects by phytoestrogens; the complicated interplays between phytoestrogens and endogenous estrogens; the shortage of currently used animal models; the necessity to apply reasonable doses of phytoestrogens in experiments. It is expected that the analyses would help to more properly assess the phytoestrogens’ effects on the endometriosis pathogenesis and their potential values for preventive or therapeutic applications.

Osthole (OST) is a plant-derived compound that can inhibit the proliferation of tumor cells and has a tumor-suppressive effect in multiple types of cancers. However, the mechanisms of OST-mediated breast cancer (BrCa) inhibition were still largely unknown. In this study, we made full use of the GSE85871 dataset to identify potential targets of OST in BrCa via multiple bioinformatics analysis. Next, a series of in vitro experiments were conducted to check the role of GNG7 in BrCa and the relationship between OST and GNG7. Through a series of bioinformatics analyses, GNG7 was identified as a potential target of OST, which could be significant upregulated by OST exposure in BrCa cells. Besides, GNG7 was lowly expressed in BrCa tissues compared with normal breast tissues, and BrCa patients with low GNG7 expression had shorter overall survival (OS) and relapse-free survival (RFS) compared with those with high GNG7 expression. Moreover, GNG7 silencing significantly enhanced cell proliferation and inhibited apoptosis, and exogenous overexpression of GNG7 showed reverse effects on BrCa cells. Last but not least, GNG7 inhibition could notably rescue OST-mediated cytotoxic effects. In summary, we identified GNG7 as a novel target for OST in BrCa and a potential tumor suppressor. Thus, OST could be therapeutically beneficial for BrCa through a GNG7-dependent mechanism.

Background: C-X-C motif chemokine ligand 9 (CXCL9), which is involved in the pathological processes of various human cancers, has become a hot topic in recent years. We developed a radiomic model to identify CXCL9 status in ovarian cancer (OC) and evaluated its prognostic significance. Methods: We analyzed enhanced CT scans, transcriptome sequencing data, and corresponding clinical characteristics of CXCL9 in OC using the TCIA and TCGA databases. We used the repeat least absolute shrinkage (LASSO) and recursive feature elimination(RFE) methods to determine radiomic features after extraction and normalization. We constructed a radiomic model for CXCL9 prediction based on logistic regression and internal tenfold cross-validation. Finally, a 60-month overall survival (OS) nomogram was established to analyze survival data based on Cox regression. Results: CXCL9 mRNA levels and several other genes involving in T-cell infiltration were significantly relevant to OS in OC patients. The radiomic score (rad_score) of our radiomic model was calculated based on the five features for CXCL9 prediction. The areas under receiver operating characteristic (ROC) curves (AUC-ROC) for the training cohort was 0.781, while that for the validation cohort was 0.743. Patients with a high rad_score had better overall survival (P < 0.001). In addition, calibration curves and decision curve analysis (DCA) showed good consistency between the prediction and actual observations, demonstrating the clinical utility of our model. Conclusion: In patients with OC, the radiomics signature(RS) of CT scans can distinguish the level of CXCL9 expression and predict prognosis, potentially fulfilling the ultimate purpose of precision medicine.

Background: Shikonin (SK), a naphthoquinone with anti-tumor effects, has been found to decrease production of tumor-associated exosomes (exo). This study aims to verify the treatment effect of SK on ovarian cancer (OC) cells, especially on the production of exo and their subsequent effect on macrophage polarization. Methods: OC cells SKOV3 and A2780 were treated with SK. The exo were isolated from OC cells with or without SK treatment, termed OC exo and SK OC exo, respectively. These exo were used to treat PMA-induced THP-1 cells (M0 macrophages). M2 polarization of macrophages was determined by measuring the M2 specific cell surface markers CD163 and CD206 as well as the secretion of M2 cytokine IL-10. The functions of galectin 3 (LGALS3/GAL3) and β-catenin in macrophage polarization were determined by gain- or loss-of-function assays. CB-17 SCID mice were subcutaneously injected with SKOV3 cells to generate xenograft tumors, followed by OC exo or SK OC exo treatment for in vivo experiments. Results: SK suppressed viability, migration and invasion, and apoptosis resistance of OC cells in vitro. Compared to OC exo, SK OC exo reduced the M2 polarization of macrophages. Regarding the mechanism, SK reduced exo production in cancer cells, and it decreased the protein level of GAL3 in exo and recipient macrophages, leading to decreased β-catenin activation. M2 polarization of macrophages was restored by LGALS3 overexpression but decreased again by the β-catenin inhibitor FH535. Compared to OC exo, the SK OC exo treatment reduced the xenograft tumor growth in mice, and it decreased the M2 macrophage infiltration within tumor tissues. Conclusion: This study suggests that SK reduces M2 macrophage population in OC by repressing exo production and blocking exosomal GAL3-mediated β-catenin activation.

Background: Endometrial cancer (EC) is one of the most common gynecological malignancies worldwide. However, the molecular mechanisms and the prognostic prediction for EC patients remain unclear.Methods: In the current study, we performed an in-depth analysis of over 500 patients which were obtained from the Cancer Genome Atlas (TCGA) database. The bioinformatics analysis included gene set enrichment analysis (GSEA) and Cox and lasso regression analyses to ensure overall survival (OS)-related genes, moreover, to construct a prognostic model and a nomogram for EC patients.Results: GSEA identified 4 gene sets significantly associated with EC, which are DNA repair, unfolded protein response, reactive oxygen species pathway and UV response up. Twenty-five OS-related DNA repair genes were screened out, after that, a 9-mRNA signature was constructed to measure the risk scores of patients with different outcomes. In addition, a nomogram contained the 9-mRNA model and clinical parameters was also presented to assess the prognosis. Patients with low risk were more likely to have sensitivity to paclitaxel, vinblastine, rapamycin, metformin, imatinib, Akt inhibitor and lapatinib.Conclusions: The identified highly enriched gene sets may offer a novel insight into the tumorigenesis and treatment of EC. Additionally, the constructed 9-mRNA model and the nomogram have prominent clinical implications for prognosis evaluation and specific therapy guidance for EC patients.

With a high global incidence of over three million new cases in 2020 and a high mortality of over two million fatalities, ovarian cancer is one of the most common malignant tumors in gynecology. Exosomes can control the immunological condition of the tumor microenvironment (TME) by participating in intercellular interactions. Therefore, we aimed to construct an exosome-related prognostic model to predict the clinical outcomes of ovarian cancer patients. In this research, expression patterns of exosome-related genes were examined in multiple single-cell RNA-sequencing and bulk RNA-sequencing datasets. In addition, a novel exosome-related prognostic model was established by the least absolute shrinkage and selection operator (LASSO) regression method. Then, the correlations between risk score and immunological characteristics of the TME were explored. Moreover, SERPINB1, a gene in the prognostic signature, was further analyzed to reveal its value as a novel biomarker. In the current study, combined with single-cell and bulk omics datasets, we constructed an exosome-related prognostic model of four genes (LGALS3BP, SAT1, SERPINB1, and SH3BGRL3). Moreover, the risk score was associated with worse overall survival (OS) in ovarian cancer patients. Further analysis found that patients with high-risk score tended to shape a desert TME with hardly infiltration of immune cells. Then, SERPINB1, positively correlated with the favorable OS and negatively with the risk score, was chosen as the representative biomarker of the model. Moreover, SERPINB1 was positively correlated with the infiltration of immune subpopulations in both public and in-house cohort. In addition, the high-resolution analysis found that SERPINB1+ tumor cells communicated with microenvironment cells frequently, further explaining the potential reason for shaping an inflamed TME. To sum up, we established a novel exosome-related prognostic model (LGALS3BP, SAT1, SERPINB1, and SH3BGRL3) to predict the prognosis of patients with ovarian cancer and identify the immunological characteristics of the TME. In addition, SERPINB1 was identified as a promising biomarker for prognostic prediction in ovarian cancer.