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Related Experiment Video

Updated: Jan 8, 2026

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Published on: October 4, 2019

A Cuproptosis-Related lncRNA Signature Predicts Prognosis and Shapes the Immune Landscape in Primary Lower-Grade

Mengyang Wang¹, Jianmei Yang², Lei Shen³

¹Department of Neurosurgery, Wuhan No. 1 Hospital, Wuhan, 430022, Hubei, China, whyyy.com.

Genetics Research

|December 24, 2025

Summary

This summary is machine-generated.

This study identifies four cuproptosis-related long noncoding RNAs (CRLs) that predict lower-grade glioma (LGG) patient prognosis and immune profiles. These findings offer potential new therapeutic strategies for LGG.

Keywords:

cuproptosis immune infiltration immune microenvironment lncRNA primary lower-grade glioma

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Last Updated: Jan 8, 2026

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Published on: October 4, 2019

Area of Science:

Oncology
Molecular Biology
Genetics

Background:

Lower-grade gliomas (LGGs) are common brain tumors with unclear risk stratification.
Cuproptosis, a programmed cell death pathway linked to metabolism, and long noncoding RNAs (lncRNAs) are implicated in glioma progression.
The role of cuproptosis-related lncRNAs (CRLs) in LGG development requires further elucidation.

Purpose of the Study:

To identify CRLs associated with LGG prognosis and immune characteristics.
To develop a prognostic signature based on CRLs for LGG risk stratification.
To explore potential therapeutic targets and predict drug efficacy in LGG.

Main Methods:

Correlation analysis to identify 963 CRLs.
LASSO and multivariate Cox regression to construct a prognostic signature of four CRLs.
Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), ESTIMATE, and TIDE to analyze biological processes and immune landscapes.
Validation of drug efficacy and lncRNA function in vitro.

Main Results:

A four-gene prognostic signature (AC002456.1, TPRG1-AS1, AC098851.1, LYRM4-AS1) was developed, classifying LGG patients into distinct risk groups.
Significant differences in biological processes and immune landscapes were observed between risk groups.
The CRL signature correlated with immunotherapy effectiveness, and drugs like MG-132 showed anti-glioma effects in vitro.
Knockdown of TPRG1-AS1 and LYRM4-AS1 impaired glioma cell migration and proliferation.

Conclusions:

CRLs are significantly associated with prognosis and immune characteristics in LGG.
The developed CRL-based signature provides a novel tool for LGG risk stratification.
CRLs and identified drugs represent potential therapeutic strategies for LGG patients.