{
  "abstract": "Purpose\n\nBlood-based biomarkers for the early detection of gastric cancer remain limited. We conducted a systematic analysis of pre-treatment plasma proteomics profiled using the Olink Reveal panel and developed diagnostic prediction models within a leakage-controlled, outer out-of-fold (OOF) internal validation framework based on nested cross-validation. In parallel, pathway-level activity was summarized using a predefined exploratory suppressive burden index to support biological interpretation.Methods\n\nWe analysed plasma samples from 90 participants (30 healthy controls, 30 early-stage/localized gastric cancer, 30 advanced gastric cancer) using the Olink Reveal platform. Group E comprises stage T1 and T2 tumours; consequently, this group is operationally defined as early-stage/localized gastric cancer, rather than classic early gastric cancer in the strict sense. The advanced group comprised T3/T4 disease. Differential abundance was tested with age- and sex-adjusted limma models. Predictive models were developed using nested cross-validation, with preprocessing and tuning performed within training folds and performance evaluated through outer-loop OOF predicted probabilities. The suppressive burden index used predefined Reactome terms and explicit orientation signs.Results\n\nAge- and sex-adjusted analyses identified several proteins differentially abundant between early gastric cancer and healthy controls. Reactome term-set analyses indicated immune-related pathway variation across disease states, although these pathway-level findings should be interpreted as exploratory. OOF internal validation showed that proteomic models improved discrimination over age/sex covariates for the main early-detection task, while the relative performance of protein-only and full models varied across resampling analyses. Calibration slopes and decision-curve results were reported from OOF predictions and interpreted as internal-validation evidence only.Conclusion\n\nPlasma proteomics captures systemic immune alterations associated with early-stage/localized gastric cancer and may support minimally invasive risk modeling. Given the modest single-center cohort and absence of external validation, the diagnostic models and suppressive burden index should be considered exploratory and require independent validation before clinical use.",
  "abstract_shown": true,
  "affiliations": [
    "Medical Experiment Center, General Hospital of Ningxia Medical University, 804 Shengli South Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China.",
    "First Clinical Medical College, Ningxia Medical University, 1180 Shengli South Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China.",
    "Medical Experiment Center, General Hospital of Ningxia Medical University, 804 Shengli South Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China. chenping0420@nxmu.edu.cn."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Shao Rui Ding"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiang Li"
    },
    {
      "affs": [
        1
      ],
      "name": "Xiang Dong"
    },
    {
      "affs": [
        2
      ],
      "name": "Ping Chen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ddv7t7hecz5m6.bib",
  "cited_by": 0,
  "doi": "10.1186/s12885-026-16490-5",
  "fulltext_url": "https://europepmc.org/articles/PMC13700262",
  "id": "ddv7t7hecz5m6",
  "issns": [
    "1471-2407"
  ],
  "landing_url": "https://europepmc.org/article/MED/42928152",
  "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",
      "2740|Gastric Cancer Management and Outcomes"
    ]
  ],
  "openalex": "W7171647348",
  "pdf_url": "https://europepmc.org/articles/PMC13700262?pdf=render",
  "pmcid": "PMC13700262",
  "pmid": "42928152",
  "published": "2026-07-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ddv7t7hecz5m6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:20Z",
      "native_id": "MED:42928152",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42928152"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2740|Gastric Cancer Management and Outcomes",
      "subfield": "general"
    }
  ],
  "title": "Exploration of plasma proteomic landscapes using Olink Reveal technology to identify biomarkers for early-stage/localized gastric cancer.",
  "title_text": "Exploration of plasma proteomic landscapes using Olink Reveal technology to identify biomarkers for early-stage/localized gastric cancer.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:21:20Z",
  "url": "https://research.draconitic.com/paper/ddv7t7hecz5m6",
  "venue": "BMC cancer",
  "versions": []
}