Computational design of synthetic receptors with programmable signalling activity for enhanced cancer T cell therapy

Area of Science:

• Immunology
• Biotechnology
• Computational Biology

Background:

• The tumor microenvironment (TME) significantly influences tumor progression and can impede the effectiveness of chimeric antigen receptor T-cell (CAR-T) therapies.
• Current strategies for enhancing CAR-T cell function by targeting soluble TME factors are limited due to the complex signaling of synthetic receptors.

Purpose of the Study:

• To develop a novel computational protein design platform for creating allosteric receptors with programmable responses to TME factors.
• To engineer TME-sensing switch receptors (T-SenSERs) that provide co-stimulation and cytokine signals to T cells.
• To enhance the anti-tumor efficacy of CAR-T cells by overcoming TME-mediated suppression.

Main Methods:

• Utilized a computational protein design platform for de novo assembly of allosteric receptors.
• Developed T-SenSERs designed to specifically target tumor-associated factors vascular endothelial growth factor (VEGF) and colony-stimulating factor 1 (CSF1).
• Integrated T-SenSERs with CARs in human T cells for testing in preclinical cancer models.

Main Results:

• Successfully designed and assembled T-SenSERs with programmable input-output functions.
• Demonstrated that T-SenSERs can selectively respond to VEGF or CSF1, factors commonly found in tumors.
• Combination of CAR and T-SenSER significantly enhanced anti-tumor responses in lung cancer and multiple myeloma models in a factor-dependent manner.

Conclusions:

• The developed T-SenSER platform enables the creation of synthetic biosensors for cell engineering.
• This approach enhances CAR-T cell function by enabling them to sense and respond to the TME.
• Paves the way for accelerated development of engineered T cells for improved cancer immunotherapy and other cell-based applications.