{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T05:49:55Z","timestamp":1791352195642,"version":"4.3.1"},"reference-count":54,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:00:00Z","timestamp":1791331200000},"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. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Keloids are fibroproliferative skin disorders characterized by persistent extracellular matrix deposition and limited treatment options. Ferroptosis has been implicated in fibrosis, but the molecular basis of ferroptosis-related changes in keloids remains unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Fibroblast-derived bulk transcriptomic datasets (GSE44270 and GSE145725) were integrated to identify differentially expressed ferroptosis-related genes. Weighted gene co-expression network analysis and machine-learning algorithms were used to identify candidate hub genes, which were evaluated in an external fibroblast dataset (GSE7890). Whole-tissue single-cell RNA-sequencing data (GSE191067) were used to characterize fibroblast and myeloid-cell states in keloid and normal-skin samples. Candidate regulatory relationships and potential ANKRD1-binding compounds were assessed in silico. Clinical tissue specimens were used for histological and protein-expression validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 163 differentially expressed genes were identified, and integration with 1,318 ferroptosis-related genes prioritized ANKRD1 as a candidate hub gene. ANKRD1 showed an area under the receiver operating characteristic curve above 0.80 in the external validation dataset and was positively associated with YAP1 expression in fibroblast-derived bulk transcriptomic data. Single-cell analysis identified a ECM-remodeling fibroblast state and three myeloid-cell states: inflammatory macrophages, resident-phagocytic macrophages, and DC-like myeloid cells. The ceRNA analysis identified a putative NEAT1\/MALAT1-miR-493-5p-ANKRD1 regulatory axis. Molecular docking, molecular-dynamics simulation, and ADMET profiling prioritized oleanolic acid and quercetin as candidate ANKRD1-binding compounds. Histological analyses showed excessive collagen deposition and increased ANKRD1 protein expression in keloid tissues.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ANKRD1 is a ferroptosis-related, fibroblast-associated candidate gene in keloids. The single-cell data describe fibroblast and myeloid-cell states in the keloid microenvironment. The proposed regulatory axis, candidate compounds, and potential role of ANKRD1 in fibroblast-myeloid interactions require further spatial and functional validation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1872427","type":"journal-article","created":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:49:51Z","timestamp":1791348591000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Deciphering fibroblast and myeloid-cell states in keloids: an integrative analysis identifies ANKRD1 as a ferroptosis-related candidate gene"],"prefix":"10.3389","volume":"17","author":[{"given":"Rongrong","family":"Xie","sequence":"first","affiliation":[{"name":"Department of Plastic Surgery, The Second Affiliated Hospital of Fujian Medical University","place":["Quanzhou, 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