How AI Found the Words to Kill Cancer Cells

Predictive Model Allows Researchers to Encode Commands for Cells to Carry Out

By Robin Marks | | December 08, 2022

Acute Lymphoblastic Leukemia

Using new machine learning techniques, researchers at UC San Francisco, in collaboration with a team at IBM Research, have developed a virtual molecular library of thousands of “command sentences” for cells, based on combinations of “words” that guided engineered immune cells to seek out and tirelessly kill cancer cells.

The work, published online Dec. 8, 2022, in Science, represents the first time such sophisticated computational approaches have been applied to a field that, until now, has progressed largely through ad hoc tinkering and engineering cells with existing, rather than synthesized, molecules.

The advance allows scientists to predict which elements – natural or synthesized – they should include in a cell to give it the precise behaviors required to respond effectively to complex diseases.

“This is a vital shift for the field,” said Wendell Lim, PhD, the Byers Distinguished Professor of Cellular and Molecular Pharmacology, who directs the UCSF Cell Design Institute and led the study. “Only by having that power of prediction can we get to a place where we can rapidly design new cellular therapies that carry out the desired activities.”

Meet the Molecular Words That Make Cellular Command Sentences

Much of therapeutic cell engineering involves choosing or creating receptors that, when added to the cell, will enable it to carry out a new function. Receptors are molecules that bridge the cell membrane to sense the outside environment and provide the cell with instructions on how to respond to environmental conditions.

Putting the right receptor into a type of immune cell called a T cell can reprogram it to recognize and kill cancer cells. These so-called chimeric antigen receptors (CARs) have been effective against some cancers but not others.

Lim and lead author Kyle Daniels, PhD, a researcher in Lim’s lab, focused on the part of a receptor located inside the cell, containing strings of amino acids, referred to as motifs. Each motif acts as a command “word,” directing an action inside the cell. How these words are strung together into a “sentence” determines what commands the cell will execute.