Charting the tumor antigen landscape of breast cancer by high-throughput antigen screening 2580
Year: 2025
Type: article
Abstract: Description Tumor infiltrating lymphocytes (TILs) that mediate tumor regression through recognition of cancer-specific antigens by their T-cell receptors (TCRs) are of great clinical value in the treatment of cancer. However, it is unclear what these antigens are and whether they contribute to anti-tumor immunity. Based on our previous antigen discovery platform, TCR-MAP, we have developed a rapid screening method to isolate cells carrying the cognate antigen from a library of hundreds of thousands of antigen-presenting cells. Our screening strategy is highly effective in identifying antigenic targets recognized by TCRs of known specificity and can allow us to identify the cognate antigens of therapeutically relevant TCRs from cancer patient TILs. Using a cohort of triple negative breast cancer patients who have undergone radiation and anti-PD-1 combination therapy, we conducted single-cell sequencing analyses of tumor biopsies to obtain TCR sequences from the top expanded CD8 T cell clones. These TCRs are being screened against a human peptidome library for self and aberrantly expressed antigens to map the antigen landscape of breast cancer and characterize the contribution of the identified antigens to anti-tumor immunity. Initial screens reveal a few unique self-antigens but show that most patient TCRs do not recognize non-mutated antigens. With additional TCR antigens being screened, our eventual antigen landscape will help guide the development of future TCR-based therapies. Funding Sources Ge Zhu is a Damon Runyon Fellow supported by the Damon Runyon Cancer Research Foundation (DRG-2473-22). Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)
Source: The Journal of Immunology
Authors: Ge Zhu, Charlotte Wang, Terence Martin, Aiquan Chang, Simon Knott, Steve Elledge
Language: English
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4416446437
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