Cucurbitacin B targets STAT3 to induce ferroptosis in non-small cell lung cancer.

Cucurbitacin B (CuB) is a compound found in plants like Cucurbitaceae that has shown promise in fighting cancer, particularly in lung cancer. However, the specific impact of CuB on ferroptosis and how it works in lung cancer cells has not been fully understood. Our research has discovered that CuB can effectively slow down the growth of non-small cell lung cancer (NSCLC) cells. Even in small amounts, it was able to inhibit the growth of various NSCLC cell lines. This inhibitory effect was reversed when ferroptosis inhibitors DFO, Lip-1 and Fer-1 were introduced. CuB was found to increase the levels of reactive oxygen species (ROS), lipid ROS, MDA, and ferrous ions within H358 lung cancer cells, leading to a decrease in GSH, mitochondrial membrane potential (MMP) and changes in ferroptosis-related proteins in a dose-dependent manner. These findings were also confirmed in A549 lung cancer cells. In A549 cells, different concentrations of CuB induced the accumulation of intracellular lipid ROS, ferrous ions and changes in ferroptosis-related indicators in a concentration-dependent manner. Meanwhile, the cytotoxic effect induced by CuB in A549 cells was counteracted by ferroptosis inhibitors DFO and Fer-1. Through network pharmacology, we identified potential targets related to ferroptosis in NSCLC cells treated with CuB, with STAT3 targets showing high scores. Further experiments using molecular docking and cell thermal shift assay (CETSA) revealed that CuB interacts with the STAT3 protein. Western blot and immunofluorescence staining demonstrated that CuB inhibits the phosphorylation of STAT3 (P-STAT3) in H358 cells. Silencing STAT3 enhanced CuB-induced accumulation of lipid ROS and iron ions, as well as the expression of ferroptosis-related proteins. On the other hand, overexpression of STAT3 reversed the effects of CuB-induced ferroptosis. The results indicate that CuB has the capability to suppress STAT3 activation, resulting in ferroptosis, and could be a promising treatment choice for NSCLC.

Machine learning identifies ferroptosis-related gene ANXA2 as potential diagnostic biomarkers for NAFLD.

Introduction: Non-alcoholic fatty liver disease (NAFLD), a major cause of chronic liver disease, still lacks effective therapeutic targets today. Ferroptosis, a type of cell death characterized by lipid peroxidation, has been linked to NAFLD in certain preclinical trials, yet the exact molecular mechanism remains unclear. Thus, we analyzed the relationship between ferroptosis genes and NAFLD using high-throughput data. Method: We utilized a total of 282 samples from five datasets, including two mouse ones, one human one, one single nucleus dataset and one single cell dataset from Gene Expression Omnibus (GEO), as the data basis of our study. To filter robust treatment targets, we employed four machine learning methods (LASSO, SVM, RF and Boruta). In addition, we used an unsupervised consensus clustering algorithm to establish a typing scheme for NAFLD based on the expression of ferroptosis related genes (FRGs). Our study is also the first to investigate the dynamics of FRGs throughout the disease process by time series analysis. Finally, we validated the relationship between core gene and ferroptosis by in vitro experiments on HepG2 cells. Results: We discovered ANXA2 as a central focus in NAFLD and indicated its potential to boost ferroptosis in HepG2 cells. Additionally, based on the results obtained from time series analysis, ANXA2 was observed to significantly define the disease course of NAFLD. Our results demonstrate that implementing a ferroptosis-based staging method may hold promise for the diagnosis and treatment of NAFLD. Conclusion: Our findings suggest that ANXA2 may be a useful biomarker for the diagnosis and characterization of NAFLD.