Background <p>Adenosine-related RNA modifications, including N6-methyladenosine (m<sup>6</sup>A), N1-methyladenosine (m<sup>1</sup>A), alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) editing, critically regulate transcriptional programs in cancer. However, their coordinated contribution to bladder cancer biology and response to immunotherapy remains poorly understood.</p> Methods <p>We systematically characterized four classes of RNA modification “writer” genes in bladder cancer, assessing somatic mutations, copy-number variations, and mRNA expression patterns across seven independent cohorts, including TCGA-BLCA, E-MTAB-4321, and GEO datasets (GSE32894, GSE13507, GSE48276, GSE70691, and GSE69795). Unsupervised consensus clustering identified RNA modification-based molecular subtypes, which were used to construct an RNA modification-based prognostic and immunotherapy response score (RMP_Score). This score was validated across multiple external cohorts, including the IMvigor210 anti-PD-L1 dataset. Differentially expressed genes (DEGs) between subtypes were assessed and integrated through Kaplan-Meier survival analysis and Cox proportional hazards regression to construct the RMP_Score. Bulk and single-cell transcriptomic analyses, complemented by in vitro functional assays, were performed to investigate the role of carboxylesterase 1 (CES1), a key component of the RMP_Score. Tumor microenvironment (TME) composition was quantified using single-sample gene set enrichment analysis (ssGSEA).</p> Results <p>RNA modification “writer” genes exhibited frequent somatic mutations and copy-number amplifications, which were strongly associated with transcriptional dysregulation and inferior overall survival. Unsupervised clustering revealed two distinct subtypes: a metabolism-enriched cluster associated with favorable prognosis, and an immune- and stroma-enriched cluster characterized by abundant regulatory T-cell infiltration and adverse clinical outcomes. The RMP_Score robustly stratified patient survival across six independent cohorts, correlated with differential sensitivity to inhibitors targeting the JNK/p38, PI3K/mTOR, and WNT pathways, and accurately predicted clinical responses to anti-PD-L1 immunotherapy, with low RMP_Scores demonstrating superior responses. CES1 emerged as a robust predictor of poor survival and immunotherapy resistance, closely associated with tumor progression, extracellular matrix remodeling, and an immunosuppressive, fibroblast-rich TME. Functionally, CES1 silencing significantly attenuated bladder cancer cell viability, invasive capacity, and migratory potential in vitro.</p> Conclusions <p>These findings established an RNA modification-based framework for molecular classification and risk stratification in bladder cancer, and identified CES1 as a metabolically driven regulator of the TME with potential utility as a prognostic and predictive biomarker for immune checkpoint blockade.</p>

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Integrative analysis of adenosine-related RNA modifications defines molecular subtypes of bladder cancer and identifies CES1 as a driver of tumor progression and immunotherapy resistance

  • Xingxing Huo,
  • Jian Qi,
  • Yongfu Zhu,
  • Hang Song,
  • Wei Han,
  • Shujie Wang

摘要

Background

Adenosine-related RNA modifications, including N6-methyladenosine (m6A), N1-methyladenosine (m1A), alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) editing, critically regulate transcriptional programs in cancer. However, their coordinated contribution to bladder cancer biology and response to immunotherapy remains poorly understood.

Methods

We systematically characterized four classes of RNA modification “writer” genes in bladder cancer, assessing somatic mutations, copy-number variations, and mRNA expression patterns across seven independent cohorts, including TCGA-BLCA, E-MTAB-4321, and GEO datasets (GSE32894, GSE13507, GSE48276, GSE70691, and GSE69795). Unsupervised consensus clustering identified RNA modification-based molecular subtypes, which were used to construct an RNA modification-based prognostic and immunotherapy response score (RMP_Score). This score was validated across multiple external cohorts, including the IMvigor210 anti-PD-L1 dataset. Differentially expressed genes (DEGs) between subtypes were assessed and integrated through Kaplan-Meier survival analysis and Cox proportional hazards regression to construct the RMP_Score. Bulk and single-cell transcriptomic analyses, complemented by in vitro functional assays, were performed to investigate the role of carboxylesterase 1 (CES1), a key component of the RMP_Score. Tumor microenvironment (TME) composition was quantified using single-sample gene set enrichment analysis (ssGSEA).

Results

RNA modification “writer” genes exhibited frequent somatic mutations and copy-number amplifications, which were strongly associated with transcriptional dysregulation and inferior overall survival. Unsupervised clustering revealed two distinct subtypes: a metabolism-enriched cluster associated with favorable prognosis, and an immune- and stroma-enriched cluster characterized by abundant regulatory T-cell infiltration and adverse clinical outcomes. The RMP_Score robustly stratified patient survival across six independent cohorts, correlated with differential sensitivity to inhibitors targeting the JNK/p38, PI3K/mTOR, and WNT pathways, and accurately predicted clinical responses to anti-PD-L1 immunotherapy, with low RMP_Scores demonstrating superior responses. CES1 emerged as a robust predictor of poor survival and immunotherapy resistance, closely associated with tumor progression, extracellular matrix remodeling, and an immunosuppressive, fibroblast-rich TME. Functionally, CES1 silencing significantly attenuated bladder cancer cell viability, invasive capacity, and migratory potential in vitro.

Conclusions

These findings established an RNA modification-based framework for molecular classification and risk stratification in bladder cancer, and identified CES1 as a metabolically driven regulator of the TME with potential utility as a prognostic and predictive biomarker for immune checkpoint blockade.