{
  "abstract": "Tumor-infiltrating lymphocytes (TILs) have been reported to be associated with prognosis in lung adenocarcinoma (LUAD). Effective prognostic models for LUAD remain limited, and more robust biomarkers for risk stratification are still needed. Effective TILs prognostic models for LUAD remain limited, and this study aims to construct an immune cell typing (ICT) score based on TILs to evaluate the survival risk of LUAD patients. Transcriptome data of LUAD were obtained from The Cancer Genome Atlas (TCGA) and seven Gene Expression Omnibus (GEO) datasets. The data were batch corrected before subsequent analysis. The ESTIMATE and CIBERSORT methods were used to calculate the tumor microenvironment-related score and the content of TILs, respectively. Differentially expressed genes were analyzed using the R software. Cluster analysis was performed using the k-means partition clustering method. The ICT score was calculated using principal components analysis. Survival analysis was performed using the Kaplan-Meier (KM) method with overall survival as the endpoint. The 5- and 10-year survival rates of patients in the high ICT score group were better than those in the low ICT score group (P<0.001). The expression levels of immune checkpoint-related genes, such as CD274, LAG3, CTLA4, and PDCD1, were lower in the high ICT score group. Patients with high ICT scores had lower tumor mutation burden (TMB) (P<0.001). The patients in the high TMB and ICT score group had the preferred survival (P<0.001). ICT scores can distinguish survival in different age, gender, and clinical stage groups (P<0.05), and the 5-year survival rates are better in the high ICT score groups. The ICT score model showed potential prognostic value in patients with LUAD. It may complement existing clinical indicators to improve prognostic stratification in LUAD.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Kang Tian"
    },
    {
      "affs": [
        0
      ],
      "name": "Xinjie Zhao",
      "orcid": "0009-0005-0833-9679"
    },
    {
      "affs": [
        0
      ],
      "name": "Jiajun Du"
    },
    {
      "affs": [
        0
      ],
      "name": "Fenglong Bie"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6yc3f1rfdyb0a.bib",
  "cited_by": 0,
  "doi": "10.21037/tcr-2026-2121",
  "fulltext_url": "https://europepmc.org/articles/PMC13743249",
  "id": "6yc3f1rfdyb0a",
  "issns": [
    "2218-676X",
    "2219-6803"
  ],
  "landing_url": "https://europepmc.org/article/MED/42997750",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2730|Cancer Immunotherapy and Biomarkers"
    ]
  ],
  "openalex": "W7224104848",
  "pdf_url": "https://europepmc.org/articles/PMC13743249?pdf=render",
  "pmcid": "PMC13743249",
  "pmid": "42997750",
  "published": "2026-10-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6yc3f1rfdyb0a.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T15:20:34Z",
      "native_id": "MED:42997750",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42997750"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2730|Cancer Immunotherapy and Biomarkers",
      "subfield": "oncology"
    }
  ],
  "title": "A tumor-infiltrating lymphocyte-related prognostic signature for lung adenocarcinoma.",
  "title_text": "A tumor-infiltrating lymphocyte-related prognostic signature for lung adenocarcinoma.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T15:20:34Z",
  "url": "https://research.draconitic.com/paper/6yc3f1rfdyb0a",
  "venue": "Translational cancer research",
  "versions": []
}