Extracellular GPX4 impairs antitumor immunity via dendritic ZP3 receptors

Area of Science:

• Immunology
• Cancer Biology
• Cell Death

Background:

• Understanding the immunogenic properties of various cell death modalities is crucial for developing effective anti-cancer therapies.
• Ferroptosis, apoptosis, cuproptosis, and necroptosis are distinct forms of cell death with varying immunological consequences.

Purpose of the Study:

• To identify regulatory mechanisms that suppress the immunogenicity of ferroptosis.
• To investigate the role of glutathione peroxidase 4 (GPX4) in ferroptosis-induced immunosuppression.
• To explore therapeutic strategies targeting ferroptosis-mediated immune evasion.

Main Methods:

• Investigated the interaction between cancer cell-released GPX4 and dendritic cell (DC) surface protein zona pellucida glycoprotein 3 (ZP3).
• Analyzed the downstream signaling cascade involving cyclic adenosine monophosphate (cAMP) and protein kinase AMP-activated (PRKA).
• Assessed the impact on DC maturation, activation, and T cell priming in preclinical cancer models.

Main Results:

• Ferroptosis, but not other cell death types, leads to GPX4 release, which binds ZP3 on DCs.
• This interaction activates cAMP-PRKA signaling, inhibiting glycolysis and impairing DC function, resulting in T cell priming defects.
• Disrupting the GPX4-ZP3 interaction restored DC metabolic activity and enhanced anti-tumor immunity.
• Blockade of this pathway improved cancer immunosurveillance and potentiated T cell responses when combined with various cancer therapies.
• High ZP3 expression correlates with poor prognosis in solid tumors, and elevated GPX4/ZP3 levels indicate resistance to therapy.

Conclusions:

• A novel regulatory axis suppresses ferroptosis immunogenicity via GPX4-ZP3 interaction, leading to DC dysfunction and immune evasion.
• Targeting this pathway represents a promising strategy to enhance anti-tumor immunity and improve cancer treatment efficacy.
• GPX4 and ZP3 serve as potential biomarkers for predicting cancer prognosis and therapeutic response.