Ferroptosis-disease perils and therapeutic promise

Identification of imidazo[1,2-a]pyridine-3-amine as a novel drug-like scaffold for efficious ferroptosis inhibition in vivo

Ferroptosis has emerged as a promising therapeutic approach for a wide range of diseases. However, limited chemical diversity and poor drug-like profiles have hindered the development of effective ferroptosis inhibitors for clinical use. Herein, we identified drug-like imidazo[1,2-a]pyridine-3-amine derivatives as innovative ferroptosis inhibitors for injury-related diseases by drug scaffold repositioning strategy. Our findings established that the selected compounds exhibited high radical scavenging and effective membrane retention, thereby leading to significant suppression of lipid peroxidation and ferroptosis at nanomolar concentrations. Notably, compound C18, with low cytotoxicity and favorable pharmacokinetics properties, demonstrated remarkable in vivo neuroprotection against ischemic brain injury in mice. In conclusion, our investigations not only engender potent ferroptosis inhibitors with novel structural characteristics that warrant further development, but also serve as a valuable case study for drug repurposing in the discovery of additional ferroptosis inhibitors.

The Ways to Die: Cell Death in Liver Pathophysiology

Liver diseases are closely associated with various cell death mechanisms, including apoptosis, necroptosis, autophagy, pyroptosis, and ferroptosis. Each process contributes uniquely to the pathophysiology of liver injury and repair. Importantly, these mechanisms are not limited to hepatocytes; they also significantly involve nonparenchymal cells. This review examines the molecular pathways and regulatory mechanisms underlying these forms of cell death in hepatocytes, emphasizing their roles in several liver diseases, such as ischemia-reperfusion injury, metabolic dysfunction-associated steatotic liver disease, drug-induced liver injury, and alcohol-associated liver disease. Recent insights into ferroptosis and pyroptosis may reveal novel therapeutic targets for managing liver diseases. This review aims to provide a comprehensive overview of these cell death mechanisms in the context of liver diseases, detailing their molecular signaling pathways and implications for potential treatment strategies.

Clone-Resolved Chemical Depletion of T cells via Cellular Proximity Chemistry

T cells play a pivotal role in the development of autoimmune diseases. To mitigate autoimmune inflammation without inducing global immunosuppression, it is crucial to selectively eliminate autoreactive T cell clones while preserving the normal T cell repertoire. In this study, we applied cellular proximity chemistry to develop a T-cell depletion method with clonal precision. Using engineered dendritic cells (DCs) with surface-bound photosensitizers, we generated reactive oxygen species (ROS) at immune synapses, leading to the targeted death of antigen-specific T cells in close proximity. This process induces lipid oxidation in T cell membranes, triggering ferroptosis-like cell death. The method enables the selective elimination of specific T cell clones without affecting others, in which the clonal resolution was demonstrated by TCR sequencing. Finally, we demonstrated the efficacy of this approach in a type 1 diabetes model by selectively depleting the pathogenic 8.3 T cell clone, thereby protecting islet β cells and preserving overall T cell function. This strategy offers a promising avenue for immunosuppressive therapy that targets pathogenic T cells while maintaining overall immune integrity.

Biomarkers in glioblastoma and degenerative CNS diseases: defining new advances in clinical usefulness and therapeutic molecular target

Background

Discovering biomarkers is central to the research and treatment of degenerative central nervous system (CNS) diseases, playing a crucial role in early diagnosis, disease monitoring, and the development of new treatments, particularly for challenging conditions like degenerative CNS diseases and glioblastoma (GBM).

Methods

This study analyzed gene expression data from a public database, employing differential expression analyses and Gene Co-expression Network Analysis (WGCNA) to identify gene modules associated with degenerative CNS diseases and GBM. Machine learning methods, including Random Forest, Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine - Recursive Feature Elimination (SVM-RFE), were used for case-control differentiation, complemented by functional enrichment analysis and external validation of key genes.

Results

Ninety-five commonly altered genes related to degenerative CNS diseases and GBM were identified, with RELN and GSTO2 emerging as significant through machine learning screening. Receiver operating characteristic (ROC) analysis confirmed their diagnostic value, which was further validated externally, indicating their elevated expression in controls.

Conclusion

The study's integration of WGCNA and machine learning uncovered RELN and GSTO2 as potential biomarkers for degenerative CNS diseases and GBM, suggesting their utility in diagnostics and as therapeutic targets. This contributes new perspectives on the pathogenesis and treatment of these complex conditions.