Researchers at the Johns Hopkins Kimmel Cancer Center and Bloomberg~Kimmel Institute for Cancer Immunotherapy have developed a computer model to help scientists identify tumor-fighting immune cells in patients with lung cancer treated with immune checkpoint inhibitors.
In their study published Feb. 3 in Nature Communications, the team, including first author Zhen Zeng, Ph.D., a bioinformatics research associate at the Kimmel Cancer Center, demonstrated that their three-gene “MANAscore” computer model can identify the immune-cells targeted by immune checkpoint inhibitor therapies. It also helped the team identify differences associated with patient response to immunotherapy.
We have developed a way to identify the cells directly targeted by immune checkpoint inhibitors, and if we can identify them, we can study them. If we can study them, that means we can identify better biomarkers and better targets for combination immunotherapy.”
Kellie Smith, Ph.D., study’s senior author, associate professor of oncology at Johns Hopkins
Immune checkpoint inhibitors like PD-1 inhibitors are available to treat dozens of cancer types. These revolutionary therapies work by unleashing tumor-killing immune cells, called T cells, that are switched off by the protein PD-1. PD-1 inhibitors turn the patient’s T cells back on, allowing patients’ immune systems to fight cancer more effectively. But not all patients respond to these therapies, and scientists need to know why in order to develop improved therapies that help nonresponders.
“Tumor-active T cells are very important to a patient’s response to therapy, but they are difficult to find,” Zeng says.
Smith helped develop the MANAFEST technology (Mutation-Associated