{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T18:02:25Z","timestamp":1790359345822,"version":"4.1.0"},"reference-count":35,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013076","name":"National Major Science and Technology Projects of China","doi-asserted-by":"publisher","award":["2024ZD0527200"],"award-info":[{"award-number":["2024ZD0527200"]}],"id":[{"id":"10.13039\/501100013076","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The Random Forest model showed robust performance on the independent test set (AUC\u2009=\u20090.864). 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\u201310%), 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\n                      <jats:italic>PTGS2<\/jats:italic>\n                      (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 (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.055), consistent with its proposed role as an early event marker. Pseudotime trajectory inference was insensitive to root node assignment.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0358259","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T17:49:42Z","timestamp":1790358582000},"page":"e0358259","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"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"],"prefix":"10.1371","volume":"21","author":[{"given":"Bing","family":"Tang","sequence":"first","affiliation":[{"name":"Sichuan University","place":["Chengdu, China"],"department":["Division of Surgery, Institute of Integrated Traditional Chinese and Western Medicine, West China 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