{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T17:57:24Z","timestamp":1792000644763,"version":"4.4.0"},"reference-count":35,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T00:00:00Z","timestamp":1791936000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T00:00:00Z","timestamp":1791936000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Endocrinology"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Dopamine agonist resistance is observed in 10%\u201330% of patients with prolactinomas, resulting in therapeutic failure and tumour progression. The molecular mechanisms underlying this resistance are not yet fully understood, highlighting the need for the identification of novel biomarkers and therapeutic targets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We performed a comprehensive integrative analysis of bulk RNA sequencing and single\u2010cell RNA sequencing datasets obtained from dopamine agonist\u2010resistant and dopamine agonist\u2010sensitive prolactinomas. To substantiate the primary findings, we utilised a multifaceted methodological framework that integrated Weighted Gene Co\u2010expression Network Analysis with machine learning techniques, including Random Forest, Support Vector Machine, and Least Absolute Shrinkage and Selection Operator. This was complemented by functional assays, which encompassed in vitro experiments involving gene overexpression and knockdown in GH3 cell models, alongside in vivo investigations using nude mouse xenograft models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>LGALS3 has been identified as a pivotal factor in mediating resistance. Through single\u2010cell RNA sequencing analysis, a resistance\u2010specific subpopulation, termed Cluster 15, was discovered. This cluster is characterised by heightened genomic instability and stemness, as evidenced by increased expression of SOX2 and SOX9, with predominant expression of LGALS3. Mechanistically, LGALS3 activates the MAPK\/ERK signalling pathway, which in turn enhances cell viability, prolactin secretion, and migration, while simultaneously inhibiting apoptosis by modulating the Bax\/Bcl\u20102\/Caspase cascade. Functional validation studies demonstrated that silencing LGALS3 significantly reduced tumour growth both in vitro, as shown by decreased Ki67 proliferation and impaired migration, and in vivo, as indicated by reduced tumour weight and volume.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>LGALS3 functions as a candidate diagnostic biomarker and represents a promising therapeutic target. Targeting the LGALS3\u2010MAPK axis presents a viable strategy to restore therapeutic sensitivity in patients with refractory prolactinoma.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/cen.70220","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T17:41:59Z","timestamp":1791999719000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LGALS3 Drives Dopamine Agonist Resistance in Prolactinoma by Activating the MAPK\/ERK Pathway: A Multi\u2010Omics Study"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1923-4303","authenticated-orcid":false,"given":"Changjun","family":"Rao","sequence":"first","affiliation":[{"name":"Beijing Neurosurgical Institute Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang Street, Ouhai District Wenzhou Zhejiang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9056-6445","authenticated-orcid":false,"given":"Yangyu","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang Street, Ouhai District Wenzhou Zhejiang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0256-1261","authenticated-orcid":false,"given":"Chuzhong","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Neurosurgical Institute Capital Medical University Beijing China"},{"name":"Department of Neurosurgery Beijing Tiantan Hospital Affiliated with Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4769-2430","authenticated-orcid":false,"given":"Zerui","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery The First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang Street, Ouhai District Wenzhou Zhejiang China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,14]]},"reference":[{"issue":"10","key":"e_1_2_11_2_1","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1016\/S2213-8587(25)00227-X","article-title":"Prolactin\u2010Secreting Adenomas: Pathogenesis, Diagnosis, and Management","volume":"13","author":"Fleseriu M.","year":"2025","journal-title":"Lancet. 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