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<p>Glioma classification is crucial for effective diagnosis and treatment. Heat Shock Proteins (HSPs) have been associated with tumor development and progression. In this study, we established a prognostic model for glioma based on Heat Shock Proteins-associated genes (HSPGs). Using the Cancer Genome Atlas (TCGA) cohorts and the Chinese Glioma Genome Atlas (CGGA), we identified a signature of 4 HSPGs as an independent prognostic factor for glioma. The risk model demonstrated excellent performance in both training and validation sets. Additionally, we developed a nomogram incorporating clinical parameters and the HSPGs signature to enhance prognostic prediction. Immunoenrichment analysis revealed a correlation between the risk score and the immunosuppressive status of glioma. In the functional assays, HSPA5 was identified as a key participant in several critical biological processes associated with glioma. Silencing HSPA5 expression may lead to the inhibition of glioma cell proliferation, migration, invasion and resistance to apoptosis. These findings present a novel classification for glioma prognosis with enhanced accuracy and offer valuable insights into the potential use of HSPGs as prognostic indicators for gliomas.</p>

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Heat shock proteins related signature characterizes immune status and predicts prognosis of gliomas

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月5日

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  • Zhiyan Sun,
  • Haibin Wan,
  • Minghui Du,
  • Yiding Guo,
  • Rui Tao,
  • Xuzhe Zhao,
  • Yutao Zhang,
  • Pei Yang,
  • Dabiao Zhou

摘要

Glioma classification is crucial for effective diagnosis and treatment. Heat Shock Proteins (HSPs) have been associated with tumor development and progression. In this study, we established a prognostic model for glioma based on Heat Shock Proteins-associated genes (HSPGs). Using the Cancer Genome Atlas (TCGA) cohorts and the Chinese Glioma Genome Atlas (CGGA), we identified a signature of 4 HSPGs as an independent prognostic factor for glioma. The risk model demonstrated excellent performance in both training and validation sets. Additionally, we developed a nomogram incorporating clinical parameters and the HSPGs signature to enhance prognostic prediction. Immunoenrichment analysis revealed a correlation between the risk score and the immunosuppressive status of glioma. In the functional assays, HSPA5 was identified as a key participant in several critical biological processes associated with glioma. Silencing HSPA5 expression may lead to the inhibition of glioma cell proliferation, migration, invasion and resistance to apoptosis. These findings present a novel classification for glioma prognosis with enhanced accuracy and offer valuable insights into the potential use of HSPGs as prognostic indicators for gliomas.