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Title
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Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells
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Author
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Abstract
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| Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large amount of patient cells. To maximize information from and minimize the need of precious samples in cancer research, prediction models have been developed to identify in silico epitope-specific TCRs. In this chapter, we provide a step-by-step protocol to train a prediction model using the user-friendly TCRex webtool for the nearly universal tumor-associated antigen Wilms' tumor 1 (WT1)-specific TCR repertoire. WT1 is a self-antigen overexpressed in numerous solid and hematological malignancies with a high clinical relevance. Training of computational models starts from a list of known epitope-specific TCRs which is often not available for new cancer epitopes. Therefore, we describe a workflow to assemble a training data set consisting of TCR sequences obtained from WT137–45-reactive CD8 T cell clones expanded and sorted from healthy donor peripheral blood mononuclear cells |
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Language
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English
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Source (journal)
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Methods in cell biology. - New York
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Source (book)
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Methods in cell biology
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Publication
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New York
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Elsevier
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2024
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ISSN
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0091-679X
0091-679X
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DOI
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10.1016/BS.MCB.2023.08.001
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Volume/pages
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183
(2024)
, p. 143-160
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Full text (Publisher's DOI)
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