Integrated computational analysis identifies therapeutic targets with dual action in cancer cells and T cells

Area of Science:

• Immunology
• Computational Biology
• Oncology

Background:

• Cancer therapies targeting tumor cells often suppress the immune system.
• Identifying therapeutic targets that simultaneously enhance anti-tumor immunity is crucial for effective immuno-oncology.

Purpose of the Study:

• To develop a computational platform, ICRAFT, for discovering therapeutic targets that modulate both cancer cells and immune cells.
• To identify novel pathways that restrain tumor progression and potentiate anti-tumor immune responses.

Main Methods:

• Integrated immune-related CRISPR screen datasets, single-cell RNA sequencing (scRNA-seq), and clinical trial RNA-seq data.
• Utilized a systems-level approach for therapeutic target discovery by analyzing cancer and immune cell interactions.
• Employed the Immune-related CRISPR screen analyzer of functional targets (ICRAFT) platform.

Main Results:

• Identified TNFAIP3, PTPN2, and SOCS1 as targets enhancing cancer cell susceptibility to immune attack and T cell activation.
• Demonstrated that TNFAIP3 inactivation in cancer cells activates the TNF-NF-κB pathway, increasing chemokine expression and T cell recruitment.
• Showed that TNFAIP3 inactivation in T cells enhances anti-tumor efficacy through TNF-induced apoptosis.

Conclusions:

• ICRAFT provides a valuable resource for understanding anti-tumor immunity and advancing immuno-oncology drug development.
• Targeting pathways like TNFAIP3 offers a dual approach to cancer treatment by enhancing both tumor cell vulnerability and immune response.
• The integration of diverse datasets in ICRAFT facilitates a comprehensive systems-level understanding of cancer-immune interactions.