FerroScore: a statistical approach for quantifying tumor-related ferroptosis based on omics data.

Area of Science:

• Biochemistry
• Cell Biology
• Computational Biology

Background:

• Ferroptosis is programmed cell death driven by iron-dependent lipid peroxidation.
• It plays a role in complex diseases like cancer.
• Current detection methods are low-throughput and costly, limiting clinical use.

Purpose of the Study:

• To develop an effective statistical method, FerroScore, to quantify ferroptosis.
• To integrate activities of iron, glutathione, and lipid metabolism pathways.
• To enable cross-resolution assessment and provide mechanistic insights into diseases.

Main Methods:

• Developed FerroScore, a statistical method.
• Integrated three core metabolic pathways: iron, glutathione, and lipid metabolism.
• Applied FerroScore to pancreatic cancer transcriptomic data.

Main Results:

• FerroScore quantifies ferroptosis by integrating key pathway activities.
• Revealed a U-shaped relationship between ferroptosis and pancreatic cancer patient survival.
• Identified heterogeneous ferroptosis activity across tumor microenvironment cell types, including macrophages and CD8 Tcm cells.
• Showed ferroptosis-active cells reshape the immunosuppressive and pro-metastatic microenvironment via intercellular communication.

Conclusions:

• FerroScore offers a novel, high-throughput method for assessing ferroptosis.
• Provides mechanistic insights into tumor, immune, and neurodegenerative diseases.
• Has potential applications in targeted therapy and drug discovery for diseases like pancreatic cancer.