ArticleScience advances2025
Quantitative and large-scale investigation of human TCR-HLA cross-reactivity.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
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Who cites it
8 citing papers in PubMed.
- MHCXGraph: a graph-based approach to detecting T-cell receptor cross-reactivity.Briefings in bioinformatics · 2026Article
- Identifying expanding TCR clonotypes with a longitudinal Bayesian mixture model and their associations with cancer patient prognosis, metastasis-directed therapy, and VJ gene enrichment.Bioinformatics (Oxford, England) · 2026Article
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- TCR repertoire shaping of naïve T cell subsets in human ontogeny.Frontiers in immunology · 2026Article
- TCR2HLA: Calibrated inference of HLA genotypes from TCR repertoires enables identification of immunologically relevant metaclonotypes.PLoS computational biology · 2026Article
- ClareV: a contrastive learning framework for context-aware TRBV representations in TCR repertoires.Frontiers in immunology · 2026Article
- The Expanding Role of HLA-E in Host Defense: A Target for Broadly Applicable Vaccines and Immunotherapies.Cells · 2025Review
- TCR2HLA: calibrated inference of HLA genotypes from TCR repertoires enables identification of immunologically relevant metaclonotypes.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The interaction between human leukocyte antigens (HLAs) and T cell receptor (TCR) is essential for adaptive immune recognition. While it is known that one TCR can map to multiple HLA alleles, the extent of this cross-reactivity remains poorly understood. Here, we introduce THNet, a TCR-based HLA similarity network, and present a comprehensive analysis of HLA-TCR cross-reactivity, which is built upon more than 9 million significantly associated HLA-TCR pairs. We created similarity networks for both class I and class II HLA alleles, illustrating how peptide cross-presentation contributes to HLA-TCR cross-reactivity. Our analysis revealed disease susceptibilities missed by single-HLA enrichment analyses, especially in the Black population. Last, we demonstrated that THNet can prioritize optimal HLA mismatch candidates across different transplantation contexts, supporting its potential utility in donor selection strategies. In summary, our investigation of the HLA-TCR cross-reactive network provides useful insights into autoimmune risk prediction and improved transplantation outcomes.
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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.