{
  "abstract": "Background: The fecal lipidomic changes underlying the colorectal adenoma-carcinoma sequence remain incompletely characterized, particularly regarding the continuous metabolic trajectory and heterogeneity of precancerous adenomas. We aimed to use publicly available multi-omics data and an integrative computational framework to identify candidate lipidomic features associated with a CRC-like metabolic state in adenomas. Methods: We developed an extreme-phenotype machine learning strategy using fecal lipidomics from healthy controls and colorectal cancer (CRC) patients (Study ID: ST003798) to build a diagnostic model, which was then blindly applied to adenoma patients to compute a Fecal Lipidomic Malignancy Risk Score (FL-MRS), interpreted here as a CRC-like lipidomic similarity score. SHAP analysis prioritized influential lipid features, and cross-sectional pseudotime trajectory inference reconstructed the metabolic continuum. Transcriptomic data from TCGA-COAD and single-cell RNA-seq (Broad Institute) were integrated to explore potential tissue-level correlates. Targeted single-molecule trend verification of the top lipid candidate was performed in an independent cohort (ST002787), as full model replication was not feasible due to limited inter-cohort feature overlap. Multiple sensitivity analyses were conducted to assess the robustness of the computational pipeline. Results: The Random Forest model showed robust performance on the independent test set (AUC = 0.864). When applied to adenomas, 51.7% of patients exceeded the FL-MRS threshold derived from extreme phenotypes; however, this proportion far exceeds the known clinical adenoma-carcinoma progression rate (approximately 5–10%), indicating that FL-MRS should be interpreted as a metabolic similarity metric rather than a direct cancer risk probability. SHAP analysis prioritized arachidonic acid-derived cholesterol ester CE(20:4) as the top predictive feature, with 100% bootstrap selection frequency. Integrative analysis of independent transcriptomic datasets identified upregulation of PTGS2 (COX-2) in tumor tissue and its predominant expression in stromal cells. External single-molecule targeted verification confirmed an accumulation trend of CE(20:4) and an early adenoma-phase peak of eicosanoid mediators (including oxidative stress and LOX-pathway metabolites). Notably, CE(20:4) levels did not differ significantly between adenoma and CRC (P = 0.055), consistent with its proposed role as an early event marker. Pseudotime trajectory inference was insensitive to root node assignment. Conclusions: This computational study suggests that fecal CE(20:4) and the associated COX-2 pathway may represent candidate features of a CRC-like metabolic state in colorectal adenomas. FL-MRS is not proposed as a clinical diagnostic or risk-prediction tool; rather, it serves as a research instrument for quantifying CRC-like metabolic similarity and guiding future validation studies. All findings are derived from publicly available retrospective data without independent experimental validation and should be regarded as hypothesis-generating. The complete analysis code is publicly archived to ensure reproducibility and facilitate future validation.",
  "abstract_shown": true,
  "affiliations": [
    "Division of Surgery, Institute of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, China",
    "Department of Rehabilitation, The People’s Hospital of Jianyang City, Jianyang, China"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Bing Tang"
    },
    {
      "affs": [
        1
      ],
      "name": "Yanru Chen"
    },
    {
      "name": "Xia Yang"
    },
    {
      "name": "Hanlin Gong"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fwk7nyyjfmr16.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0358259",
  "fulltext_url": null,
  "id": "fwk7nyyjfmr16",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0358259",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Metabolomics and Mass Spectrometry Studies"
    ],
    [
      "plos",
      "/Biology and life sciences/Biochemistry/Lipids"
    ],
    [
      "plos",
      "/Biology and life sciences/Biochemistry/Lipids/Lipid metabolism"
    ],
    [
      "plos",
      "/Biology and life sciences/Biochemistry/Metabolism/Lipid metabolism"
    ],
    [
      "plos",
      "/Biology and life sciences/Cell biology/Oxidative stress"
    ],
    [
      "plos",
      "/Biology and life sciences/Computational biology/Genome analysis/Transcriptome analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics/Genomics/Genome analysis/Transcriptome analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Molecular biology/Macromolecular structure analysis/Lipid analysis"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology/Medical risk factors/Cancer risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancer risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancers and neoplasms/Adenomas"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancers and neoplasms/Colorectal cancer"
    ]
  ],
  "openalex": "W7214304351",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0358259&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-25",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/fwk7nyyjfmr16.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:43Z",
      "native_id": "10.1371/journal.pone.0358259",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0358259"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "plos:oncology",
      "subfield": "oncology"
    }
  ],
  "title": "Integrative computational analysis of public fecal lipidomics and transcriptomics datasets suggests a candidate association between the COX-2 pathway and CE(20:4) in colorectal adenoma-carcinoma progression",
  "title_text": "Integrative computational analysis of public fecal lipidomics and transcriptomics datasets suggests a candidate association between the COX-2 pathway and CE(20:4) in colorectal adenoma-carcinoma progression",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:43Z",
  "url": "https://research.draconitic.com/paper/fwk7nyyjfmr16",
  "venue": "PLOS One",
  "versions": []
}