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Researchers at USC developed a machine learning method to identify specific molecules, called cell fate determinants, that can convert GBM cells into cells that function similarly to dendritic cells (DCs), which are important for activating an anti-tumor immune response. The machine learning technique can analyze tens of thousands of genes and millions of gene connections within GBM cells to find those that can be transformed using CFDs. Once the GBM cells are treated with the CFDs, they acquire characteristics and functions of natural dendritic cells, including the ability to capture and present antigens, which are pieces of the tumor that T cells need to recognize in order to mount an attack. In mouse models, this new approach led to a reduction in tumor growth and improved survival rates. When combined with other immunotherapies, the treatment worked even better. While further development is needed and human trials are still likely a few years away, this is an exciting and innovative approach.