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Purpose <p>Exploring the expression of Mitochondrial Permeability Transition Dependent Necrosis lncRNA in bladder cancer and elucidate their precise function within the tumor microenvironment and impact on prognosis.</p> Methods <p>We employed a comprehensive bioinformatics approach to investigate the function and influence of lncRNA in bladder cancer. Gene expression data, clinical data, and mutation data of bladder cancer are obtained from TCGA database.</p> Results <p>We developed a new prognostic model incorporating 6 lncRNAs. The predictive efficacy of this model for bladder cancer prognosis was validated. Furthermore, we investigated the influence of model on the tumor microenvironment and drug sensitivity.</p> Conclusion <p>This study presents a novel prognostic framework for bladder cancer that holds great potential for enhancing prognostic prediction accuracy and optimizing treatment strategies for patients with this disease.</p>

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Constructing a prognostic model based on MPT-related genes and investigate the characteristics of immune infiltration in bladder cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月4日

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  • Lei Yang,
  • Zhiqiang Zhang,
  • Mengfan Xu,
  • Muhan Shang,
  • Haibing Wang,
  • Zhiqi Liu

摘要

Purpose

Exploring the expression of Mitochondrial Permeability Transition Dependent Necrosis lncRNA in bladder cancer and elucidate their precise function within the tumor microenvironment and impact on prognosis.

Methods

We employed a comprehensive bioinformatics approach to investigate the function and influence of lncRNA in bladder cancer. Gene expression data, clinical data, and mutation data of bladder cancer are obtained from TCGA database.

Results

We developed a new prognostic model incorporating 6 lncRNAs. The predictive efficacy of this model for bladder cancer prognosis was validated. Furthermore, we investigated the influence of model on the tumor microenvironment and drug sensitivity.

Conclusion

This study presents a novel prognostic framework for bladder cancer that holds great potential for enhancing prognostic prediction accuracy and optimizing treatment strategies for patients with this disease.