AI Engineers T Cells To Fight Cancer

A computationally designed version of a human T-cell receptor improved receptor expression, reduced unwanted chain pairing, and made engineered T cells better at recognizing and killing tumor cells.

T-cell therapies can turn the immune system into a powerful tool against cancer. T cells are immune cells that help identify and destroy infected or abnormal cells. They recognize potential targets using proteins on their surface called T-cell receptors (TCRs). Cells display small fragments of proteins on their surface, and TCRs recognize specific fragments presented by other surface molecules. When a T cell recognizes its target, it receives signals that activate it to respond. Cancer cells can evade this process, so one cancer treatment involves genetically modifying a patient’s T cells to recognize a specific cancer-related target.

But engineering these receptors comes with a problem: a TCR is made from two chains that must pair correctly for the receptor to function. When an engineered TCR is introduced into a patient’s T cells, its chains can pair incorrectly with the cell’s original TCR chains, reducing the amount of functional receptor on the cell surface and potentially creating unwanted specificities.

A new study used AI to redesign the less visible part of the TCR. The resulting receptor, called structurally enhanced TCR (SET), improved T-cell function and increased the ability of engineered T cells to control tumors in mice.

Redesigning the Receptor

A TCR contains variable regions that recognize the target and constant regions that help the two TCR chains fit together and connect with the rest of the T-cell signaling machinery. For an engineered T cell to work, both chains have to assemble correctly before the completed receptor reaches the surface. However, the engineered chains must also compete with the cell’s natural TCR chains, which can further reduce the number of functional engineered receptors.