{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T13:52:22Z","timestamp":1782309142968,"version":"3.54.5"},"reference-count":59,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T00:00:00Z","timestamp":1782086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The link between metabolic syndrome (MetS) and cancer has been widely studied, but overall research patterns, shared mechanisms, and applications remain unclear. A bibliometric and bioinformatics analysis is needed to identify trends and clarify the molecular pathways connecting MetS to cancer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A bibliometric analysis using Web of Science and PubMed assessed publication trends, collaboration, key authors\/journals, and research topics from 2000 to 2024. Visualization and analysis used VOSviewer, CiteSpace, and Bibliometrix. Also included bioinformatics for protein interaction networks, hub genes, and enrichment analysis via R pipelines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Research output grew mainly driven by China and the US, with Europe showing high collaborative centrality. Thematic analysis shifted from isolated metabolic issues to integrated MetS phenotypes, cancer prognosis, and interventions. Bioinformatics found hub genes and pathways linking metabolic dysregulation with tumor development, especially involving inflammation, insulin signaling, and metabolic reprogramming.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This analysis supports a bidirectional MetS-cancer link and shifts focus from tumor-centric to a holistic view of the tumor-host metabolic system. Targeting metabolic dysfunction may improve cancer prognosis, treatment tolerance, and outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1799202","type":"journal-article","created":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T04:35:24Z","timestamp":1782102924000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The metabolic syndrome-cancer axis: global research trends and clinical landscapes"],"prefix":"10.3389","volume":"17","author":[{"given":"Dianzhe","family":"Tian","sequence":"first","affiliation":[{"name":"Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College","place":["Beijing, China"]},{"name":"Eight-year Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College","place":["Beijing, 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