Using AI Technology to Chart Immune Cell Receptor

Using AI Technology to Chart Immune Cell Receptor
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Johns Hopkins Medicine

Johns Hopkins Medicine (click to view)

Johns Hopkins Medicine


Johns Hopkins scientists have used a form of artificial intelligence to create a map that compares types of cellular receptors, the chemical “antennas” on the surface of immune system T-cells. Their experiments with lab-grown mouse and human T-cells suggest that people with cancer who have a greater variety of such receptors may respond better to immunotherapy drugs and vaccines.

A report on how the scientists created and tested what they call “ImmunoMap” appeared Dec. 20 in Cancer Immunology Research.

“ImmunoMap gives scientists a picture of the wide diversity of the immune system’s responses to cellular antigens,” says Jonathan Schneck, M.D., Ph.D., professor of pathology, medicine and oncology at the Johns Hopkins University School of Medicine, and a member of the Johns Hopkins Kimmel Cancer Center.

Receptors on T-cells recognize antigens, or pieces of other cells that trigger an immune response, particularly antibodies. If the antigens are foreign, T-cells raise the alarm within the immune system, which can distribute an “all-points bulletin” to be on the lookout for the unfamiliar antigens.

Because diseases such as cancer tend to evade detection by T-cells’ receptors, allowing a tumor to grow unchecked, scientists have long sought “intel” on this process as a means of developing therapies that target malignant cells, but leave healthy cells alone.

“Much of immunotherapy today is built on the premise that we know these antigens,” says Johns Hopkins biomedical engineering M.D./Ph.D. student John-William Sidhom. “But we actually don’t know as much as we need to about them and the T-cells that recognize them.”

Click here to read more about this study.

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