Body Mass Index and Risk of Female Reproductive System Tumors Subtypes: A Meta-Analysis Using Mendelian Randomization.

Introduction: A strong association was previously established between body mass index (BMI) and female reproductive system tumors; however, the causal relationship is unclear. We conducted a Mendelian randomization (MR) study to further explore this association. Methods: Genetic information for BMI was retrieved from a published genome-wide association study involving 339,224 participants. Genetic associations with five common female reproductive system tumors were obtained from the FinnGen, UK Biobank studies, and other large consortia. Results: Genetic predisposition towards BMI exhibits a significant association with multiple tumors of the female reproductive system. Specifically, for every 1-unit increase in BMI log-transformed odds ratio (OR). The OR fluctuations overall for patients with breast cancer ranged from 0.661 to 0.996 (95% confidence interval [CI],0.544-1.000, P < 0.05). When stratified by estrogen receptor (ER) status, the OR for patients with ER (+) breast cancer ranged from 0.782 to 0.844 (95% CI, 0.616-0.994, P < 0.05) and that for those with ER (-) breast cancer ranged from 0.663 to 0.789 (95% CI, 0.498-0.991, P < 0.05). Additionally, ORs were as follows for cancer types: 1.577-1.908 (95% CI, 1.049-2.371, P < 0.05) for endometrial carcinoma; 1.216-1.303 (95% CI, 1.021-1.591, P < 0.05) for high-grade serous ovarian cancer; 1.217 (95% CI, 1.034-1.432, P < 0.05) for low-grade malignant serous ovarian cancer; and 1.502 (95% CI, 1.112-2.029, P < 0.05) for endometrioid ovarian carcinoma. Furthermore, our findings indicated that genetic predisposition towards BMI did not exhibit a causal association with uterine fibroids, cervical precancerous lesions, or cervical cancer itself. Conclusion: A genetic association was established between a high BMI and high risk of developing multiple tumors of the female reproductive system and their associated subtypes. This underscores the significance of taking measures to prevent reproductive system tumors in women who have a high BMI.

Gliotoxin elicits immunotoxicity in the early innate immune system of ducks.

Gliotoxin (GT) belongs to the epipolythiodioxopiperazine (ETP) family, which is considered a crucial virulence determinant among the secondary metabolites produced by Aspergillus fumigatus. The metabolites are commonly found in food and feed, contributing to the invasion and immune escape of Aspergillus fumigatus, thereby posing a significant threat to the health of livestock, poultry, and humans. Heterophil extracellular traps (HETs), a novel form of innate immune defense, have been documented in the chicken's innate immune systems for capturing and eliminating invading microbes. However, the effects and mechanisms of GT on the production of duck HETs in vitro remain unknown. In this study, we first confirmed the presence of HETs in duck innate immune systems and further investigated the molecular mechanism underlying GT-induced HETs release. Our results demonstrate that GT can trigger typical release of HETs in duck. The structures of GT-induced HETs structures were characterized by DNA decoration, citrullinated histones 3, and elastase. Furthermore, NADPH oxidase, glycolysis, ERK1/2 and p38 signaling pathway were found to regulate GT-induced HETs. In summary, our findings reveal that gliotoxin activates HETs release in the early innate immune system of duck while providing new insights into the immunotoxicity of GT towards ducks.

Cuproptosis-Associated lncRNA Gene Signature Establishes New Prognostic Profile and Predicts Immunotherapy Response in Endometrial Carcinoma.

Uterine corpus endometrial carcinoma (UCEC), a prevalent kind of cancerous tumor in female reproductive system that has a dismal prognosis in women worldwide. Given the very limited studies of cuproptosis-related lncRNAs (CRLs) in UCEC. Our purpose was to construct a prognostic profile based on CRLs and explore its assess prognostic value in UCEC victims and its correlation with the immunological microenvironment. METHODS: 554 UCEC tumor samples and 23 normal samples' RNA-seq statistics and clinical details were compiled from data in the TCGA database. CRLs were obtained using Pearson correlation analysis. Using LASSO Cox regression, multivariate Cox regression, and univariate Cox regression analysis, six CRLs are confirmed to develop a risk prediction model at last.We identified two main molecular subtypes and observed that multilayer CRLs modifications were related to patient clinicopathological features, prognosis, and tumor microenvironment (TME) cell infiltration characteristics, and then we verified the prognostic hallmark of UCEC and examined its immunological landscape.Finally, using qRT-PCR, model hub genes' expression patterns were confirmed. RESULTS: A unique CRL signature was established by the combination of six differently expressed CRLs that were highly linked with the prognosis of UCEC patients. According to their CRLs signatures, the patients were divided into two groups: the low-risk and the high-risk groups. Compared to individuals at high risk, patients at low risk had higher survival rates (p < 0.001). Additionally, Cox regression reveals that the profiles of lncRNAs linked to cuproptosis may independently predict prognosis in UCEC patients. The 1-, 3-, and 5-year risks' respective receiver operating characteristics (ROC) exhibited AUC values of 0.778, 0.810, and 0.854. Likewise, the signature could predict survival in different groups based on factors like stage, age, and grade, among others. Further investigation revealed differences between the different risk score groups in terms of drug sensitivity,immune cell infiltration,tumor mutation burden (TMB) score and microsatellite instability (MSI) score. Compared to the group of high risk, the low-risk group had greater rates of TMB and MSI. Results from qRT-PCR revealed that in UCEC vs normal tissues, AC026202.2, NRAV, AC079466.2, and AC090617.5 were upregulated,while LINC01545 and AL450384.1 were downregulated. CONCLUSIONS: Our research clarified the relationship between CRLs signature and the immunological profile and prognosis of UCEC.This signature will establish the framework for future investigations into the endometrial cancer CRLs mechanism as well as the exploitation of new diagnostic tools and new therapeutic.

Polo-like kinase 1 as a biomarker predicts the prognosis and immunotherapy of breast invasive carcinoma patients.

Background: Invasive breast carcinoma (BRCA) is associated with poor prognosis and high risk of mortality. Therefore, it is critical to identify novel biomarkers for the prognostic assessment of BRCA. Methods: The expression data of polo-like kinase 1 (PLK1) in BRCA and the corresponding clinical information were extracted from TCGA and GEO databases. PLK1 expression was validated in diverse breast cancer cell lines by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. Single sample gene set enrichment analysis (ssGSEA) was performed to evaluate immune infiltration in the BRCA microenvironment, and the random forest (RF) and support vector machine (SVM) algorithms were used to screen for the hub infiltrating cells and calculate the immunophenoscore (IPS). The RF algorithm and COX regression model were applied to calculate survival risk scores based on the PLK1 expression and immune cell infiltration. Finally, a prognostic nomogram was constructed with the risk score and pathological stage, and its clinical potential was evaluated by plotting calibration charts and DCA curves. The application of the nomogram was further validated in an immunotherapy cohort. Results: PLK1 expression was significantly higher in the tumor samples in TCGA-BRCA cohort. Furthermore, PLK1 expression level, age and stage were identified as independent prognostic factors of BRCA. While the IPS was unaffected by PLK1 expression, the TMB and MATH scores were higher in the PLK1-high group, and the TIDE scores were higher for the PLK1-low patients. We also identified 6 immune cell types with high infiltration, along with 11 immune cell types with low infiltration in the PLK1-high tumors. A risk score was devised using PLK1 expression and hub immune cells, which predicted the prognosis of BRCA patients. In addition, a nomogram was constructed based on the risk score and pathological staging, and showed good predictive performance. Conclusions: PLK1 expression and immune cell infiltration can predict post-immunotherapy prognosis of BRCA patients.