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New AI method could aid the development of T cell-based cancer therapies

2021
MD Anderson Cancer Center, Houston, USA(1)
University of Texas Southwestern Medical Center, Dallas, USA(2)
In this study, the researchers have developed an artificial intelligence (AI) technique that can identify which cell surface peptides produced by neoantigens are recognized by the immune system. By applying this method, called pMTnet, to human tumour genomics data, the authors discovered that neoantigens were generally more immunogenic than self-antigens, but human endogenous retrovirus E (a special type of self-antigen that is reactivated in kidney cancer) is more immunogenic than neoantigens. They further discovered that patients with more clonally expanded T cells that exhibit better affinity against truncal rather than subclonal neoantigens had a more favourable prognosis and treatment response to immunotherapy in melanoma and lung cancer but not in kidney cancer. Thus, pMTnet could lead to new ways to predict cancer prognosis and potential responsiveness to immunotherapies which may help develop treatments such as cancer vaccines and T-cell based therapies.
Deep learning-based prediction of the T cell receptor–antigen binding specificity
Alexandre Reuben(1), Tao Wang(2)
#1348
Added on: 02-23-2022
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