{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T05:03:05Z","timestamp":1789448585741,"version":"build-2803163510"},"reference-count":55,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"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. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Duchenne muscular dystrophy (DMD) is a hereditary neuromuscular disease characterized by progressive myofiber injury, chronic inflammatory response, and persistent fibrotic remodeling, for which no universal clinical treatment is currently available. The inflammatory-fibrotic microenvironment is regarded as a critical driver of DMD progression; nevertheless, the key molecules governing extracellular matrix (ECM) remodeling and immune imbalance remain incompletely elucidated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Two transcriptomic datasets were integrated to construct an expression matrix containing DMD patients and healthy controls. Extracellular matrix (ECM) activation scores were calculated based on three representative ECM gene sets. Differential analysis combined with weighted gene co-expression network analysis (WGCNA) was performed to identify core modules related to DMD and ECM activation. A protein\u2013protein interaction (PPI) network was built for the intersecting genes, and hub genes were screened by integrating five network topology algorithms. Immune cell infiltration characteristics were analyzed in protein tyrosine phosphatase receptor type C (PTPRC) high- and low-expression groups, followed by gene set enrichment analysis (GSEA). A PTPRC knockdown cell model was established, and quantitative real-time PCR (qRT-PCR), Western blotting (WB), and immunofluorescence (IF) were applied to verify the effect of PTPRC on C2C12 myoblast differentiation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      ECM activation scores were elevated in the DMD group and showed favorable diagnostic efficacy. After stratification by ECM score, the ECM-High group exhibited activation of fibrosis\/epithelial\u2013mesenchymal transition (EMT) and immune\/inflammatory pathways, accompanied by metabolic dysfunction and aberrant activation of myogenesis-related programs. WGCNA further identified the MEturquoise module, which was positively correlated with both DMD status and ECM score. Intersection of this module with DMD and ECM differential genes yielded PTPRC. Immune infiltration analysis showed increased proportions of M2 macrophages and regulatory T cells (Tregs) in the PTPRC_High group. GSEA confirmed significant activation of 12 inflammatory pathways.\n                      <jats:italic>In vitro<\/jats:italic>\n                      experiments demonstrated that PTPRC knockdown markedly promoted myogenic differentiation and alleviated fibrotic phenotypes in myoblasts.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>PTPRC serves as a candidate biomarker for DMD. Its high expression participates in DMD-associated fibrosis, likely linked to an immunosuppressive microenvironment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1905030","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T04:28:08Z","timestamp":1789446488000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Transcriptomics-based analysis of muscle injury mechanism mediated by inflammatory imbalance in the Duchenne muscular dystrophy muscle microenvironment"],"prefix":"10.3389","volume":"17","author":[{"given":"Chunhui","family":"Shan","sequence":"first","affiliation":[{"name":"Department of Medical Imaging, Hebei General Hospital","place":["Shijiazhuang, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Li","sequence":"additional","affiliation":[{"name":"Department 1 of Cardiovascular Medicine, Hebei General Hospital","place":["Shijiazhuang, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Neurology, Hebei Medical University Third Hospital","place":["Shijiazhuang, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhe","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Neurology, Hebei Medical University Third Hospital","place":["Shijiazhuang, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinhong","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Neurology, Hebei Medical University Third Hospital","place":["Shijiazhuang, Hebei, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Bing","sequence":"additional","affiliation":[{"name":"Department of Neurology, Hebei Medical University Third Hospital","place":["Shijiazhuang, Hebei, 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