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.
May 7 2024Ludwig Institute for Cancer Research
Cellular immunotherapy involves extracting immune cells from a patient's tumor, optionally engineering them to enhance their natural abilities to combat cancer and reintroducing them to the body after they've been expanded in culture. T cells are one of the two main types of white blood cells, or lymphocytes, that circulate in the blood and patrol for virally infected or cancerous cells.
TRTpred can learn from one T cell population and create a rule which can then be applied to a new population. So, when faced with a new TCR, the model can read its transcriptomic profile and predict whether it is tumor reactive or not." Related StoriesThe 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 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.
Antigen Artificial Intelligence Biotechnology Blood Cancer Cell Immunotherapy Melanoma Research
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AI predicts tumor-killing cells with high accuracy, study showsUsing 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.
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