Researchers have developed a computer model to help scientists identify tumor-fighting immune cells in patients with lung cancer treated with immune checkpoint inhibitors.
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., the team, including first author Zhen Zeng, Ph.D.
"Tumor-active T cells are very important to a patient's response to therapy, but they are difficult to find," Zeng says. The team also found key differences in the T cells activated in the tumors of patients who respond to immune checkpoint therapy compared with those who don't. Responding patients exhibit a higher proportion of stem-like memory T cells, which act as a reservoir for new cells and can develop into many effective anti-tumor cells, Zeng says.
"We hope to translate our three-gene signature into a biomarker that clinicians can use to guide cancer care," Smith says. She is also collaborating with other laboratories across the country to determine if MANAscore can be used in patients with different types of cancer. They've created a database of single-cell sequencing data across cancer types and will use the score to help identify cancer-type-specific responder T cell characteristics.
America, the Commonwealth Foundation, Bristol Myers Squibb, the National Institutes of Health, Kelsey Dickson Team Science Courage Research Award: Advancing New Therapies for Merkel Cell Carcinoma, the MCC Patient Gift Fund and the National Foundation for Cancer Research.
Lymphoma Lung Cancer Cancer Computer Modeling Mathematical Modeling Mathematics Information Technology
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