{
  "abstract": "High-throughput screening of HLA class I epitopes underpins neoantigen vaccine design, T cell therapies, and pathogen immune monitoring, yet proteome-scale prioritization remains challenging under severe class imbalance. We present TriStageHLA, a compact three-stage framework that decomposes epitope discovery into peptide-only screening (PRE), allele-specific binding/presentation prediction (BIND), and immunogenicity prediction (IM). PRE performs early pruning via a LoRA-adapted ESM-2 classifier; BIND integrates quantitative binding affinity and eluted ligand data with a dual-branch architecture combining global cross-attention and local motif extraction; IM is fine-tuned on curated human T-cell assay data with a decoupled LoRA head. Trained on IEDB-derived datasets with per-allele balancing and allele-discordant supervision, TriStageHLA-BIND achieves AUROC of 96.2% and AUPRC of 95.2% on combined BA/EL evaluation, while TriStageHLA-IM reaches AUROC of 81.4\\% and AUPRC of 73.8\\% on held-out immunogenicity data, improving over the strongest immunogenicity baselines ImmuneApp (70.7% / 63.6%) and BigMHC-IM (60.1% / 51.5%). With substantially fewer trainable parameters than prior models, TriStageHLA enables efficient, calibrated epitope prioritization across binding, presentation, and immunogenicity. Code and pretrained weights are available at https://github.com/SkywalkerLuke/TriStageHLA.",
  "abstract_shown": true,
  "affiliations": [
    "City University of Hong Kong"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "name": "T. LU"
    },
    {
      "name": "Z. Wang"
    },
    {
      "name": "Y. Wang"
    },
    {
      "name": "Z. Li"
    },
    {
      "name": "T. Chen"
    },
    {
      "name": "K. Cho"
    },
    {
      "name": "Z. Yao"
    },
    {
      "name": "X. Li"
    },
    {
      "affs": [
        0
      ],
      "name": "K.-C. Wong"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e1s461yhdf9ya.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.29.762831",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762831v1.full",
  "id": "e1s461yhdf9ya",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762831v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762831v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/e1s461yhdf9ya.ris",
  "sources": [
    {
      "first_seen": "2026-11-10T00:24:51Z",
      "native_id": "10.64898/2026.10.29.762831",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762831v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Unveiling immune targets via TriStageHLA: high-throughput screening of peptide presentation, peptide-HLA binding, and immunogenicity",
  "title_text": "Unveiling immune targets via TriStageHLA: high-throughput screening of peptide presentation, peptide-HLA binding, and immunogenicity",
  "type": "preprint",
  "updated_at": "2026-11-10T00:24:51Z",
  "url": "https://research.draconitic.com/paper/e1s461yhdf9ya",
  "venue": "bioRxiv",
  "versions": []
}