Transfer learning between preclinical models and human tumors identifies a conserved NK cell activation signature in anti-CTLA-4 responsive tumors.

These data demonstrate a novel application of our transfer learning approach, which was able to identify cell state transitions conserved in preclinical models and human tumors. This approach can be adapted to explore many questions in cancer therapeutics, enhance translational research, and enable better understanding and treatment of disease.