Using artificial intelligence, Ludwig Cancer Research scientists have developed a powerful predictive model for identifying the most potent cancer killing immune cells for use in cancer immunotherapies., can be applied to personalized cancer treatments that tailor therapy to the unique cellular makeup of each patient's tumors.
T cells that penetrate solid tumors are known as tumor-infiltrating lymphocytes, or TILs. However, not all TILs are effective at recognizing and attacking tumor cells."Only a fraction is in fact tumor reactive -- the majority are bystanders," Harari explained."The challenge we set for ourselves was to identify the few TILs that are equipped with T cell receptors able to recognize antigens on the tumor.
The TRTpred model analyzed TILs from 42 patients with melanoma and gastrointestinal, lung and breast cancer and identified tumor-reactive TCRs with about 90 percent accuracy. The researchers further refined their TIL selection process by applying a secondary algorithmic filter to screen for only those tumor-reactive T-cells with"high avidity" -- that is, those that bind strongly to tumor antigens.
The team then introduced a third filter to maximize recognition of diverse tumor antigens."What we want is to maximize the chances the TILs will target as many different antigens as possible," Harari said. Alexandre Harari is a PI in the Hi-TIDe team at Ludwig Lausanne and an associate professor at the University of Lausanne.Rémy Pétremand, Johanna Chiffelle, Sara Bobisse, Marta A. S. Perez, Julien Schmidt, Marion Arnaud, David Barras, Maria Lozano-Rabella, Raphael Genolet, Christophe Sauvage, Damien Saugy, Alexandra Michel, Anne-Laure Huguenin-Bergenat, Charlotte Capt, Jonathan S. Moore, Claudio De Vito, S. Intidhar Labidi-Galy, Lana E.
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