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Identification of FCER1G as a key gene in multiple myeloma based on weighted gene co-expression network analysis
Xiao Qiu1, Jia-He Zhang1, Ying Xu1
1Department of Hematology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University; The First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, People's Republic of China.
Purpose:
Although the prognosis of multiple myeloma (MM) has remarkably improved with the emerge of novel agents, it remains incurable and relapses inevitably. The molecular mechanisms of MM have not been well-studied. Herein, this study aimed to identify key genes in MM.
Materials And Methods:
The GSE39754 dataset was used to screen differentially expressed genes (DEGs) and construct a co-expression network. Hub nodes were identified in the protein and protein interaction (PPI) network. Datasets GSE13591 and GSE2658 were used to validate hub genes. Moreover, function and gene set enrichment analyses were performed to elucidate the molecular pathogenesis of MM.
Results:
In this study, 11 genes were found to be hub genes in the co-expression network, among which four genes (CD68, FCER1G, PLAUR and LCP2) were also identified as hub nodes. In the test dataset GSE13591, CD68 and FCER1G were significantly downregulated in MM. Besides, the areas under the curve (AUCs) of CD68 and FCER1G were greater than 0.8 in both the training dataset and the test dataset. Our results also confirmed that FCER1G highly expressed patients had remarkably longer survival times in MM. Function and pathway enrichment analyses suggested that hub genes were associated with epithelial mesenchymal transition, TNF-α signaling via NF-κB and inflammatory response. GSEA in our study indicated that FCER1G participated in NK cell mediated cytotoxicity and the NOD-like receptor signaling pathway.
Conclusion:
Our study identified FCER1G as a key gene in MM, providing a novel biomarker and potential molecular mechanisms of MM for further studies.
Insights
This study identified FCER1G as a key gene in multiple myeloma (MM). Lower FCER1G expression correlates with poorer prognosis, suggesting its potential as a biomarker for MM.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Multiple myeloma (MM) remains incurable despite advances in novel agents.
- The underlying molecular mechanisms of MM require further investigation.
- Identifying key genes is crucial for understanding MM pathogenesis and developing new therapies.
Purpose of the Study:
- To identify key genes involved in the molecular mechanisms of multiple myeloma (MM).
- To discover potential biomarkers for MM prognosis and treatment.
Main Methods:
- Utilized the GSE39754 dataset to screen for differentially expressed genes (DEGs) and construct a co-expression network.
- Identified hub nodes in the protein-protein interaction (PPI) network.
- Validated hub genes using datasets GSE13591 and GSE2658.
- Performed function and gene set enrichment analyses (GSEA) to elucidate molecular pathogenesis.
Main Results:
- Identified 11 hub genes, with CD68, FCER1G, PLAUR, and LCP2 confirmed as significant.
- FCER1G and CD68 were found to be significantly downregulated in MM patients.
- FCER1G expression levels correlated with longer survival times in MM.
- Enrichment analyses linked hub genes to pathways such as epithelial mesenchymal transition and TNF-α signaling.
Conclusions:
- FCER1G is identified as a key gene in multiple myeloma (MM).
- FCER1G serves as a potential novel biomarker for MM.
- This study provides insights into the molecular mechanisms of MM, particularly FCER1G's role in immune-related pathways.
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