{
  "abstract": "Background Neoadjuvant chemo-immunotherapy improves outcomes in resectable non-small cell lung cancer (NSCLC), but predicting postoperative recurrence remains challenging. While the precursor exhausted T cell (Texp) index offers prognostic value, the broader tumor immune microenvironment (TIME) contains untapped predictive potential. Methods A secondary analysis was conducted based on single-cell RNA and TCR sequencing data from 138 NSCLC patients treated with neoadjuvant chemo-immunotherapy. Following collinearity filtering of 51 immune cell subtypes and the Texp index, LASSO-Cox regression was applied to develop a prognostic Risk Score for recurrence-free survival (RFS). Results A four-feature Risk Score was identified, incorporating the Texp index, CXCL13+ Th1-like CD4+ T cells, KLRB1+ MAIT CD8+ T cells, and terminally exhausted T cells. This score robustly stratified patients into distinct RFS groups and demonstrated independent prognostic value in multivariate analysis (HR = 6.090, p = 0.004). Compared to the baseline Texp index alone, the expanded Risk Score model yielded significantly improved predictive discrimination (mean ΔC-index = 0.096) and demonstrated superior net clinical benefit in decision curve analysis at 12 and 24 months. Conclusion This integrated single-cell immune Risk Score provides enhanced prognostic accuracy over single-metric biomarkers, offering a refined tool for postoperative risk stratification and personalized adjuvant management in NSCLC.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China",
    "Criminal Science and Technology Office, Criminal Police Brigade of Pidu Branch of Chengdu Public Security Bureau",
    "Department of Neurology, The Affiliated Hospital, Southwest Medical University",
    "Department of Comprehensive Inpatient Ward, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jun Ge"
    },
    {
      "affs": [
        1
      ],
      "name": "Xuesong Tong"
    },
    {
      "affs": [
        2
      ],
      "name": "Xingxia Wang"
    },
    {
      "affs": [
        3
      ],
      "name": "Jian Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5h63w8p00aszg.bib",
  "cited_by": 0,
  "doi": "10.1186/s12885-026-16565-3",
  "fulltext_url": "https://doi.org/10.1186/s12885-026-16565-3",
  "id": "5h63w8p00aszg",
  "issns": [
    "1471-2407"
  ],
  "landing_url": "https://doi.org/10.1186/s12885-026-16565-3",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "RC254-282"
    ],
    [
      "openalex",
      "2730|Cancer Immunotherapy and Biomarkers"
    ]
  ],
  "openalex": "W7169876092",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-07-01",
  "publisher": "BMC",
  "ris": "https://research.draconitic.com/paper/5h63w8p00aszg.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:46:03Z",
      "native_id": "7cd66b4a6eba46178e4e79737058adae",
      "source": "doaj",
      "url": "https://doi.org/10.1186/s12885-026-16565-3"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2730|Cancer Immunotherapy and Biomarkers",
      "subfield": "oncology"
    }
  ],
  "title": "A single-cell derived immune risk score predicts recurrence in NSCLC following neoadjuvant chemo-immunotherapy",
  "title_text": "A single-cell derived immune risk score predicts recurrence in NSCLC following neoadjuvant chemo-immunotherapy",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:46:03Z",
  "url": "https://research.draconitic.com/paper/5h63w8p00aszg",
  "venue": "BMC Cancer",
  "versions": []
}