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February 12, 2026Discover Oncology0 citationsOpen Access

Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction

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HLHaobin LiuWeifang Medical UniversityYWYuxiao WuWeifang Medical UniversityHSHaoyu SunWeifang Medical University

Key Points

  • The aim is to develop and validate a prognostic model for low-grade gliomas (LGGs) based on metabolic gene scoring and immune interactions.
  • Constructed a metabolism-driven prognostic model for LGG patients.
  • Performed multi-omics analysis to evaluate metabolic dysregulation and immune microenvironment.
  • Conducted computational analysis to assess drug sensitivity differences between risk groups.
  • High-risk scores correlate with metabolic dysregulation and an immunosuppressive microenvironment.
  • Enhanced presence of M2 macrophages is observed in high-risk patients.
  • Identified potential therapeutic compounds that may effectively target metabolic-immune interactions.

Abstract

This study constructed and validated a metabolism-driven prognostic model. The model enables prognostic stratification of LGG patients and links high-risk scores to metabolic dysregulation and an immunosuppressive microenvironment characterized by M2 macrophage enrichment, based on multi-omics data. Mechanistic exploration indicates this association is particularly pronounced in myeloid cells, predominantly within metabolism-related M2 macrophage subpopulations. Furthermore, computational analysis suggests differences in drug sensitivity between risk groups and identifies potential therapeutic compounds, providing clues for future exploration of therapeutic strategies targeting metabolic-immune interactions.

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Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/698d6d9f5be6419ac0d52b39https://doi.org/10.1007/s12672-026-04635-8
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