{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T03:34:53Z","timestamp":1769052893110,"version":"3.49.0"},"reference-count":46,"publisher":"Public Library of Science (PLoS)","issue":"5","license":[{"start":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T00:00:00Z","timestamp":1747180800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Joint Development Program for Early Gastrointestinal Cancer Physicians","award":["GTCZ-2023-SC-06 and GTCZ-2020-SC-51-0003"],"award-info":[{"award-number":["GTCZ-2023-SC-06 and GTCZ-2020-SC-51-0003"]}]},{"name":"the Hospital-level project of Mianyang Third People's Hospital","award":["202206"],"award-info":[{"award-number":["202206"]}]}],"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>Cuproposis is a new-found mechanism of cell death, and the role of cuproposis-related genes (CRGs) in pancreatic cancer prognosis remains uncertain.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>DECRGs were identified from TCGA and GTEx databases. Five OS-associated hub genes were screened using Cox regression and LASSO analyses. A prognostic model was constructed and validated by survival analysis. GSEA, gene mutation, small-molecule drugs, immune-infiltrating and TF\/miRNA\/mRNA network were investigated to determine the underlying mechanism of 5-CRGs. In addition, RT-qPCR, and WB were applied to validate the expression of 5-CRGs. CCK8, colony formation and transwell assays were used to prove the function of LIPT1 in PC.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>PDP1, DLAT, DBT, LIAS, and LIPT1 were screened as hub genes. 5-CRGs prognostic model established the low-risk population has a longer OS. There was a high the risk score value for the prediction in clinicopathological features. The forest plots showed that age, N stage and the RiskScore were the significant independent risk indicators. T cells CD4 memory resting and Mast cells are the amplest immune cell subpopulations in the high-score individuals. The expression of 5 CRGs exhibited significant differences in PC cell lines and tissues, LIPT1-knockdowning inhibited proliferation and invasion of pancreatic cancer cell lines.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>Five CRGs relevant to pancreatic cancer prognosis were identified. Meanwhile, a new and accurate five CRGs prognostic model of pancreatic cancer was constructed. In addition, LIPT1 may promote proliferation, invasion and migration of pancreatic cancer cell lines. This may have a specific guiding value for future development of precise anti-cancer treatment strategies.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0323458","type":"journal-article","created":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T18:02:20Z","timestamp":1747245740000},"page":"e0323458","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Comprehensive analysis and experiment validation of five cuproptosis-related genes in prognosis, immune infiltration and metabolic characterization of pancreatic cancer"],"prefix":"10.1371","volume":"20","author":[{"given":"Qianxi","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaoling","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueli","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Honglin","family":"Quan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guojun","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xia","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4233-7864","authenticated-orcid":true,"given":"Linju","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,5,14]]},"reference":[{"issue":"1","key":"pone.0323458.ref001","first-page":"17","article-title":"Cancer statistics, 2023. 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