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A Novel Insight into Paraptosis-Related Classification and Signature in Lower-Grade Gliomas.

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This study introduces a new model for lower-grade gliomas (LGG) using paraptosis-related genes. This model effectively predicts patient survival and identifies potential drug sensitivities, offering new directions for LGG treatment.

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Lower-grade gliomas (LGG) are common brain tumors that can progress to aggressive forms and develop drug resistance.
  • Paraptosis, a non-apoptotic programmed cell death, is emerging as a therapeutic target in gliomas, but its role in LGG remains unclear.

Purpose of the Study:

  • To develop a novel prognostic model for lower-grade gliomas (LGG) based on paraptosis-related genes (PRGs).
  • To identify key PRGs that can predict overall survival (OS) and guide treatment strategies for LGG patients.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) database for consensus clustering and identified 10 PRG signatures using LASSO and Cox regression analyses.
  • Validated the prognostic model using the Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) databases.
  • Performed Kaplan-Meier analysis, time-dependent ROC analysis, and nomogram construction to assess predictive performance and independent prognostic value.

Main Results:

  • Identified 10 PRG signatures (CDK4, TNK2, DSTYK, CDKN3, CCR4, CASP9, HSPA5, RGR, LPAR1, PDCD6IP) that successfully stratify LGG patients into high- and low-risk subgroups.
  • The developed risk score was an independent predictor of overall survival (OS) in LGG patients.
  • Enrichment analysis revealed enriched immune-related processes and distinct immune infiltration patterns in the high-risk group, alongside potential correlations between PRG signatures and drug sensitivity.

Conclusions:

  • The novel paraptosis-based prognostic model provides a valuable tool for predicting OS in LGG patients.
  • The identified PRG signatures offer insights into the biological mechanisms underlying LGG progression and immune evasion.
  • This study highlights the therapeutic potential of targeting paraptosis and PRGs for improved LGG treatment strategies.