Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning

Our HRD Index model based on these seven genes significantly correlated with clinical prognosis in glioma patients and holds promise for guiding clinical management.

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Publication Details

Journal
PLoS ONE
Published
2025-12-19
DOI
https://doi.org/10.1371/journal.pone.0337731
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning

Zhouqing Chen, Zheng Zhan, Jiaxuan Li, Zhong Wang et al.
PLoS ONE
Glioma Diagnosis and Treatment
article

Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning

Zhouqing Chen, Zheng Zhan, Jiaxuan Li, Zhong Wang, Xin Wu, Long‐Yuan Li, Mei Chang
article en

Abstract

Our HRD Index model based on these seven genes significantly correlated with clinical prognosis in glioma patients and holds promise for guiding clinical management.

PLoS ONEVol. 20(12)
Soochow University (CN), First Affiliated Hospital of Soochow University (CN)
Openalex Percentile: Top 38%
Glioma Diagnosis and Treatment
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