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DOI 10.3389/fgene.2021.832627

Медицинская библиотека · Frontiers in genetics · 2022

A Computational Framework to Identify Biomarkers for Glioma Recurrence and Potential Drugs Targeting Them.

Ma Shuzhi, Guo Zhen, Wang Bo, Yang Min, Yuan Xuelian, Ji Binbin, Wu Yan, Chen Size

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Аннотация

Background

Recurrence is still a major obstacle to the successful treatment of gliomas. Understanding the underlying mechanisms of recurrence may help for developing new drugs to combat gliomas recurrence. This study provides a strategy to discover new drugs for recurrent gliomas based on drug perturbation induced gene expression changes.

Methods

The RNA-seq data of 511 low grade gliomas primary tumor samples (LGG-P), 18 low grade gliomas recurrent tumor samples (LGG-R), 155 glioblastoma multiforme primary tumor samples (GBM-P), and 13 glioblastoma multiforme recurrent tumor samples (GBM-R) were downloaded from TCGA database. DESeq2, key driver analysis and weighted gene correlation network analysis (WGCNA) were conducted to identify differentially expressed genes (DEGs), key driver genes and coexpression networks between LGG-P vs LGG-R, GBM-P vs GBM-R pairs. Then, the CREEDS database was used to find potential drugs that could reverse the DEGs and key drivers.

Results

We identified 75 upregulated and 130 downregulated genes between LGG-P and LGG-R samples, which were mainly enriched in human papillomavirus (HPV) infection, PI3K-Akt signaling pathway, Wnt signaling pathway, and ECM-receptor interaction. A total of 262 key driver genes were obtained with frizzled class receptor 8 (FZD8), guanine nucleotide-binding protein subunit gamma-12 (GNG12), and G protein subunit β2 (GNB2) as the top hub genes. By screening the CREEDS database, we got 4 drugs (Paclitaxel, 6-benzyladenine, Erlotinib, Cidofovir) that could downregulate the expression of up-regulated genes and 5 drugs (Fenofibrate, Oxaliplatin, Bilirubin, Nutlins, Valproic acid) that could upregulate the expression of down-regulated genes. These drugs may have a potential in combating recurrence of gliomas.

Conclusion

We proposed a time-saving strategy based on drug perturbation induced gene expression changes to find new drugs that may have a potential to treat recurrent gliomas.

Для цитирования: Ma Shuzhi, Guo Zhen, Wang Bo, Yang Min, Yuan Xuelian, Ji Binbin, Wu Yan, Chen Size. A Computational Framework to Identify Biomarkers for Glioma Recurrence and Potential Drugs Targeting Them.. Frontiers in genetics. 2022. DOI: 10.3389/fgene.2021.832627.
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