{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T08:29:04Z","timestamp":1771921744248,"version":"3.50.1"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:00:00Z","timestamp":1768435200000},"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. Mol. Biosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Cancer-associated fibroblasts (CAFs) are key drivers of tumor progression in bladder cancer (BLCA), yet their molecular heterogeneity and prognostic utility remain incompletely characterized. Single-cell studies have revealed distinct CAF subpopulations with divergent clinical impacts, necessitating refined prognostic frameworks that capture CAF-mediated progression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We analyzed single-cell RNA sequencing data (GSE267718) from 8 BLCA patients to identify CAF populations and define progression-associated gene signatures. Using 359 TCGA-BLCA samples as the training cohort, we performed non-negative matrix factorization (NMF) consensus clustering on 85 prognostically significant CAF genes, identifying two molecular clusters with distinct survival outcomes. Through LASSO-Cox regression and stepwise selection, we constructed a four-gene Tumor-Progressing Fibroblast Riskscore model comprising\n                      <jats:italic>FOXA1<\/jats:italic>\n                      ,\n                      <jats:italic>TBX3<\/jats:italic>\n                      ,\n                      <jats:italic>LRIG1<\/jats:italic>\n                      , and\n                      <jats:italic>RNF11<\/jats:italic>\n                      . Model performance was validated in the E-MTAB-4321 cohort (n = 476). Functional validation of\n                      <jats:italic>RNF11<\/jats:italic>\n                      was performed using shRNA-mediated knockdown in T24 and 5637 bladder cancer cell lines, followed by proliferation, migration, invasion assays, and transcriptomic profiling.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Single-cell analysis identified 557 differentially expressed genes between non-muscle-invasive bladder cancer and muscle-invasive bladder cancer CAFs. NMF clustering stratified TCGA patients into 2 clusters with significantly different overall survival. The TPFR model showed consistent prognostic performance in both training and validation cohorts, with high-risk patients showing significantly worse survival. Functional enrichment analysis revealed that TPFR scores correlated with ECM-receptor interaction, focal adhesion, and cytoskeletal regulation pathways. Stratified analysis revealed superior model performance in elderly (&amp;gt;60 years), male, and early-stage patients. In particular,\n                      <jats:italic>RNF11<\/jats:italic>\n                      knockdown significantly reduced proliferation, migration, and invasion in 5637 and T24 cells, while transcriptomic analysis revealed alterations in tumors after\n                      <jats:italic>RNF11<\/jats:italic>\n                      knockdown including TNF and MAPK signaling pathway, indicating a potential mechanism by which RNF11 regulates bladder cancer progression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We established a CAF-based prognostic model that integrates single-cell insights with bulk transcriptomics for robust risk stratification in BLCA. The TPFR model shows clinical utility particularly in elderly and early-stage patients. Functional characterization showed that RNF11 regulates proliferation and migration of bladder cancer. These findings highlight the prognostic value of CAF signatures and provide a framework for precision medicine approaches in bladder cancer management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmolb.2025.1722809","type":"journal-article","created":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T05:17:34Z","timestamp":1768454254000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A novel tumor-progressing fibroblast signature derived from single-cell RNA sequencing enables prognostic stratification and reveals RNF11 as a functional regulator in bladder cancer"],"prefix":"10.3389","volume":"12","author":[{"given":"Miaoyu","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Urology, The Third People\u2019s Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, College of Medicine, Southwest Jiaotong University","place":["Chengdu, Sichuan, 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Affiliated Hospital of Southwest Jiaotong University, College of Medicine, Southwest Jiaotong University","place":["Chengdu, Sichuan, China"]},{"name":"Department of Urology, The Affiliated Hospital of Southwest Jiaotong University, The Third People\u2019s Hospital of Chengdu","place":["Chengdu, Sichuan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Su","sequence":"additional","affiliation":[{"name":"Medical Research Center, The Affiliated Hospital of Southwest Jiaotong University, The Third People\u2019s Hospital of Chengdu","place":["Chengdu, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kui","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Urology, The Third People\u2019s Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, College of Medicine, Southwest Jiaotong University","place":["Chengdu, Sichuan, 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