RESUMEN
The natural flavonoid compound chrysin has promising anti-tumor effects. In this study, we aimed to investigate the mechanism by which chrysin inhibits the growth of non-small cell lung cancer (NSCLC). Through in vitro cell culture and animal models, we explored the impact of chrysin on the growth of NSCLC cells and the pro-cancer effects of tumor-associated macrophages (TAMs) and their mechanisms. We observed that M2-TAMs significantly promoted the growth and migration of NSCLC cells, while also markedly activating the autophagy level of these cells. Chrysin displayed a significant inhibitory effect on the growth of NSCLC cells, and it could also suppress the pro-cancer effects of M2-TAMs and inhibit their mediated autophagy. Furthermore, combining network pharmacology, we found that chrysin inhibited TAMs-mediated autophagy activation in NSCLC cells through the regulation of the CDK1/ULK1 signaling pathway, rather than the classical mTOR/ULK1 signaling pathway. Our study reveals a novel mechanism by which chrysin inhibits TAMs-mediated autophagy activation in NSCLC cells through the regulation of the CDK1/ULK1 pathway, thereby suppressing NSCLC growth. This discovery not only provides new therapeutic strategies for NSCLC but also opens up new avenues for further research on chrysin.
RESUMEN
Gamma radiation is progressively emerging as an effective method to enhance the sterilization efficiency of medical plastics including Polyvinyl chloride (PVC). The parameters of the radiation facility will affect the efficiency of radiation sterilization. To investigate these effects, we simulate the gamma radiation sterilization performance of PVC material sample using Monte Carlo Method. The simulation results indicated that compared with the sterilization time of 20-90 min from high-temperature steam sterilization of medical waste, by optimizing the parameters of the model radiation facility, the radiation sterilization time can be reduced to 6.61 min. The optimized model facility parameters are as follows: the gamma photon energy is 1.25 MeV, the model space is 300 × 300 × 300 cm3, the reflective layer material is concrete and its thickness is 8 cm, the PVC sample layer area is 100 × 100 cm2, the distance between the radiation source and the PVC sample layer is 150 cm, the energy deposition in the bottom layer of the PVC sample layer is 1.31315 × 10-6 MeV/g. This study offers a potentially feasible way for PVC sterilization, while also providing a crucial reference for the further promotion and application of radiation sterilization technology.
RESUMEN
Purpose: Pyroptosis exerts an undesirable impact on the clinical outcome of breast cancer. Since any single gene is insufficient to be an appropriate marker for pyroptosis, our aim is to develop a pyroptosis-related gene (PRG) signature to predict the survival status and immunological landscape for breast cancer patients. Methods: The information of breast cancer patients was retrieved from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the gene expressions of this signature in breast cancer. Its prognostic value was evaluated by univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, receiver operating characteristics (ROCs), univariate/multivariate analysis, and nomogram. Analyses of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to explore its potential biological function in breast cancer. The potential correlation between this signature and tumor immunity was revealed based on single sample gene set enrichment analysis (ssGSEA), ESTIMATE and CIBERSORT algorithms. Results: A PRG signature containing GSDMC, GZMB, IL18, and TP63 was created in a TCGA training cohort and validated in two validation GEO cohorts GSE58812 and GSE37751. Compared with a human mammary epithelial cell line MCF-10A, the expression levels of GSDMC, GZMB and IL18 were upregulated, while TP63 was found with lower expression level in breast cancer cells SK-BR-3, BT-549, MCF-7, and MDA-MB-231 using RT-qPCR assay. Based on univariate and multivariate Cox models, ROC curve, nomogram as well as calibration curve, it was revealed that this signature with high-risk score could independently predict poor clinical outcomes in breast cancer. Enrichment analyses demonstrated that the involved mechanism was tightly linked to immune-related processes. SsGSEA, ESTIMATE and CIBERSORT algorithms further pointed out that the established model might exert an impact on immune cell abundance, immune cell types and immune-checkpoint markers. Furthermore, individuals with breast cancer responded differently to these therapeutic agents based on this signature. Conclusions: Our data suggested that this PRG signature with high risk was tightly associated with impaired immune function, possibly resulting in an unfavorable outcome for breast cancer patients.