ArticleScience advances2023
Multi-tiered approach to detect autoimmune cross-reactivity of therapeutic T cell receptors.
Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- PepGen: conditional generation of peptides for MHC binding.Bioinformatics (Oxford, England) · 2026Article
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- Generation of T cells with reduced off-target cross-reactivities by engineering co-signalling receptors.Nature biomedical engineering · 2026Article
- Targeting solid tumors with TCR-T cells: mechanisms, progress, and challenges.Frontiers in oncology · 2026Review
- Endogenous retroviruses in aging and cancer: from genomic defense to oncogenic activation.Mobile DNA · 2025Review
- T cell receptor cross-reactivity prediction improved by a comprehensive mutational scan database.Cell systems · 2025Article
- CD22 TCR-engineered T cells exert antileukemia cytotoxicity without causing inflammatory responses.Science advances · 2025Article
- Comprehensive epitope mutational scan database enables accurate T cell receptor cross-reactivity prediction.bioRxiv : the preprint server for biology · 2025Article
- Identification of novel KRASJournal of translational medicine · 2025Article
- Natural TCRs targeting KRASG12V display fine specificity and sensitivity to human solid tumors.The Journal of clinical investigation · 2024Article
- Novel insights into TCR-T cell therapy in solid neoplasms: optimizing adoptive immunotherapy.Experimental hematology & oncology · 2024Review
- Exploring the therapeutic potential of precision T-Cell Receptors (TCRs) in targeting KRAS G12D cancer throughOncology research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 5 countries.
Funding
Abstract
T cell receptor (TCR)-engineered T cell therapy using high-affinity TCRs is a promising treatment modality for cancer. Discovery of high-affinity TCRs especially against self-antigens can require approaches that circumvent central tolerance, which may increase the risk of cross-reactivity. Despite the potential for toxicity, no standardized approach to screen cross-reactivity has been established in the context of preclinical safety evaluation. Here, we describe a practical framework to prospectively detect clinically prohibitive cross-reactivity of therapeutic TCR candidates. Cross-reactivity screening consisted of multifaceted series of assays including assessment of p-MHC tetramer binding, cell line recognition, and reactivity against candidate peptide libraries. Peptide libraries were generated using conventional contact residue motif-guided search, amino acid substitution matrix-based search unguided by motif information, and combinatorial peptide library scan-guided search. We demonstrate the additive nature of a layered approach, which efficiently identifies unsafe cross-reactivity including one undetected by conventional motif-guided search. These findings have important implications for the safe development of TCR-based therapies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.