Deciphering Ferroptosis: From Molecular Pathways to Machine Learning-Guided Therapeutic Innovation

Area of Science:

• Biochemistry
• Cell Biology
• Oncology

Background:

• Ferroptosis is a regulated cell death pathway crucial in various biological processes.
• It involves iron accumulation and lipid peroxidation, leading to plasma membrane damage.
• Ferroptosis dysregulation is implicated in cancer, aging, metabolic disorders, and neurodegenerative diseases.

Purpose of the Study:

• To review recent advancements in ferroptosis research.
• To highlight the therapeutic potential of targeting ferroptosis in diverse diseases.
• To discuss challenges and future directions in ferroptosis research and application.

Main Methods:

• Comprehensive literature review of ferroptosis mechanisms, genes, and pathways.
• Analysis of ferroptosis inducers, inhibitors, and regulators.
• Exploration of machine learning applications for biomarker and therapeutic target discovery.

Main Results:

• Ferroptosis is intricately linked to cellular signaling and metabolic networks.
• Targeting ferroptosis pathways shows promise for treating cancer and other diseases.
• Machine learning can identify complex patterns for biomarker and therapeutic target discovery.

Conclusions:

• Ferroptosis represents a significant therapeutic target across a spectrum of diseases.
• Overcoming challenges in ferroptosis detection and regulation is crucial for clinical translation.
• Continued research, including AI-driven approaches, is essential to harness ferroptosis's full potential.