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Unraveling the Interplay of D-2-HG in Glioblastoma Tumorigenesis via Integrated Machine Learning and Molecular
Yangfan Zou1,2, Xuefei Yu1,3, Qinglin Li3
1Faculty of Chinese Medicine, Macau University of Science and Technology, 999078 Macau, China.
Background:
Glioblastoma (GBM) is an exceptionally aggressive type of brain tumor with a poor prognosis, underscoring the urgent need to identify new molecular targets for therapeutic development. The objective of this research is to clarify the molecular interactions affected by the oncometabolite D-2-hydroxyglutarate (D-2-HG) within the framework of GBM.
Methods:
Differential expression analysis of multi-omics data identified potential target genes linked to GBM pathogenesis. To enhance our understanding of the binding interactions between D-2-HG and the identified target proteins, we utilized an integrated methodology encompassing various machine learning algorithms, network pharmacology techniques, and molecular docking.
Results:
A sum of 135 genes was recognized as possible targets through which D-2-HG exerts its effects in GBM. The ensuing analysis, utilizing machine learning techniques, identified six crucial genes [eukaryotic translation initiation factor 4E binding protein 1 (EIF4EBP1), fatty acid binding protein 3 (FABP3), potassium voltage-gated channel subfamily Q member 2 (KCNQ2), epithelial cell adhesion molecule (EPCAM), sphingosine-1-phosphate receptor 5 (S1PR5), and metabotropic glutamate receptor 3 (GRM3)] as key regulators. Among these, FABP3, KCNQ2, EPCAM, S1PR5, and GRM3 were significantly downregulated, whereas EIF4EBP1 was markedly upregulated (p < 0.05). Molecular docking simulations indicated a strong binding affinity of D-2-HG towards the target proteins.
Conclusions:
Our study suggests that D-2-HG plays a significant role in the pathogenesis of GBM by modulating specific genes and signaling pathways. Utilizing machine learning techniques, we identified six essential regulatory genes, and further molecular docking simulations revealed a strong affinity of D-2-HG for these critical targets. Collectively, these results establish a substantial basis for future investigations into the mechanistic role of D-2-HG in GBM oncogenesis.
Insights
This study reveals how the oncometabolite D-2-hydroxyglutarate (D-2-HG) impacts glioblastoma (GBM) by identifying key regulatory genes. Findings show D-2-HG strongly binds to these targets, offering new therapeutic avenues for aggressive brain tumors.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Glioblastoma (GBM) is a highly aggressive brain tumor with limited treatment options.
- Identifying novel molecular targets is crucial for developing effective GBM therapies.
- The oncometabolite D-2-hydroxyglutarate (D-2-HG) is implicated in GBM pathogenesis.
Purpose of the Study:
- To elucidate the molecular interactions influenced by D-2-HG in glioblastoma.
- To identify potential therapeutic targets modulated by D-2-HG in GBM.
Main Methods:
- Differential expression analysis of multi-omics data to identify GBM-associated genes.
- Application of machine learning algorithms and network pharmacology for target identification.
- Molecular docking simulations to assess binding affinity between D-2-HG and target proteins.
Main Results:
- 135 potential D-2-HG target genes were identified in GBM.
- Six key regulatory genes were pinpointed: EIF4EBP1, FABP3, KCNQ2, EPCAM, S1PR5, and GRM3.
- D-2-HG demonstrated strong binding affinity to these identified target proteins.
Conclusions:
- D-2-HG significantly contributes to GBM pathogenesis by regulating specific genes and pathways.
- The identified regulatory genes (EIF4EBP1, FABP3, KCNQ2, EPCAM, S1PR5, GRM3) are critical targets for D-2-HG action.
- These findings provide a foundation for further research into D-2-HG's role in GBM oncogenesis and potential therapeutic strategies.
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