MI2026 – WenZhen Li

Title:
CROSSTCR: a curated database of experimentally validated TCR cross-reactivity for molecular mimicry assessment and safer TCR therapy design

Abstract:
T cell receptor (TCR) cross-reactivity—the ability of one TCR to recognize multiple peptide–MHC (pMHC) complexes—is essential for immune adaptability but poses major safety risks for TCR-engineered cancer therapies, as molecular mimicry between tumor and self-peptides has led to severe off-target toxicities. We developed CROSSTCR, a comprehensive and manually curated database integrating experimentally validated evidence of TCR cross-reactivity. Bidirectional TCR–antigen relationships are annotated, and data reliability is ensured through rule-based filtering, expert curation, and multi-level verification using sequence alignment, ESM-2 embedding similarity, and structural comparison. The current release contains >20,000 TCR–pMHC interactions across ~1,500 cross-reactive groups. Despite low sequence similarity, peptides recognized by the same TCR share embedding proximity and convergent 3D conformations, revealing conserved features underlying cross-reactivity. A case study of the MAGE-A3/Titin mimicry event reproduced clinically observed off-target cardiotoxicity. The web platform provides interactive visualization and downloadable datasets. CROSSTCR offers the first systematic, validated resource for TCR cross-reactivity, supporting molecular mimicry assessment and safer design of TCR-based cancer immunotherapies.

Biography:
My research focuses on TCR-based immunotherapy and cancer treatment, with particular interest in TCR cross-reactivity, molecular mimicry, and the development of computational resources to support safer and more precise cancer immunotherapies.