BMC Cancer (Aug 2024)

Results from a real-world study: a novel glycosyltransferase risk score for prognosis, tumor microenvironment phenotypes and immunotherapy in bladder cancer

  • Renyu Liu,
  • Ting Yang,
  • Jinyu Huang,
  • Zicheng Xiao,
  • Jinhui Liu,
  • Zhenghao Li,
  • Shiyu Tong

DOI
https://doi.org/10.1186/s12885-024-12712-w
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 13

Abstract

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Abstract Background Although immunotherapy shows tremendous potential in the treatment of bladder cancer (BLCA), the overall prognosis and response rates to immunotherapy in BLCA remain suboptimal. Methods We performed an extensive evaluation of glycosyltransferase expression patterns in BLCA patients by analyzing 210 glycosyltransferase-related genes. Subsequently, we established correlations between these glycosyltransferase patterns, prognosis, and tumor microenvironment (TME) phenotypes. To offer personalized patient assessments, we developed a glycosyltransferase risk score that accurately predicts prognosis, TME phenotypes, and molecular subtypes. Importantly, we developed a RNA-seq cohort, named Xiangya cohort, to validate our results. Results Two distinct patterns of glycosyltransferase expression were identified, corresponding to inflamed and noninflamed TME phenotypes, and demonstrated the potential to predict prognosis. We developed and validated a comprehensive risk score that accurately predicted individual patient prognosis in the TCGA-BLCA cohort. Additionally, we constructed a nomogram that integrated the risk score with several key clinical factors. Importantly, this risk score was successfully validated in external cohorts, including the Xiangya cohort and GSE48075. Furthermore, we discovered a positive correlation between this risk score and tumor-infiltrating lymphocytes in both the TCGA-BLCA and Xiangya cohorts, suggesting that patients with a higher risk score exhibited an inflamed TME phenotype and were more responsive to immunotherapy. Finally, we observed that the high and low risk score groups were consistent with the luminal and basal subtypes of BLCA, respectively, providing further validation of the risk score’s role in the TME in terms of molecular subtypes. Conclusions Glycosyltransferase patterns exhibit distinct TME phenotypes in BLCA. Our comprehensive risk score provides a promising approach for prognostic prediction and assessment of immunotherapy efficacy, offering valuable guidance for precision medicine.

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