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

Megha Mete1, Amiya Ojha1, Priyanka Dhar2

  • 1Department of Bioengineering, National Institute of Technology Agartala, Agartala, Tripura, 799046, India.

PubMed

Insights

Ferroptosis, an iron-dependent cell death, impacts cancer, aging, and diseases. Understanding its mechanisms and developing biomarkers are key to unlocking new therapeutic strategies.

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.