Expert review of hematology · 2025
Exploring shared pathogenesis of multiple myeloma and osteoporosis via bioinformatic analysis.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Wang Yajie, Liu Chengdi, Tang Kegong, Zhang Jiyun, Liu Xinran, Ma Yiming, Li Xiaofei
Аннотация
BACKGROUND: The purpose of this study is to explore the common differentially expressed genes (DEGs) between multiple myeloma (MM) and osteoporosis and the associated molecular mechanisms.
RESEARCH DESIGN AND METHODS: We obtained the overlapping DEGs between MM and osteoporosis with the GEO2R online tool. Then, the DEGs were clustered on the MetaCore website to identify the biological process and pathway. In addition, the STRING database and Cytoscape were used to construct the protein-protein interaction (PPI) network and identify hub genes. Finally, miRNA-gene and transcriptional factor (TF)-gene interaction networks were constructed.
RESULTS: A total of 252 genes were identified as DEGs in the overlapping two datasets. Functional analysis emphasizes the crucial role of the cell cycle in these two diseases. 10 hub genes were identified using cytoHubba, including CCNA2, ASPM, MKI67, FN1, FEN1, STAT1, DEPDC1, ITGB8, DYNC2LI1, HBEGF. In addition, according to the miRNA-gene and TF-gene interaction networks, part of TFs (RELA, TP53), and miRNAs (miR-26b-5p, miR-192-5p) may be identified as key regulators in MM and osteoporosis at the same time.
CONCLUSIONS: The present study reveals the common pathogenesis of MM and osteoporosis. These shared pathways may provide new targets for further mechanistic studies of the pathogenesis and treatment of MM and osteoporosis.
RESEARCH DESIGN AND METHODS: We obtained the overlapping DEGs between MM and osteoporosis with the GEO2R online tool. Then, the DEGs were clustered on the MetaCore website to identify the biological process and pathway. In addition, the STRING database and Cytoscape were used to construct the protein-protein interaction (PPI) network and identify hub genes. Finally, miRNA-gene and transcriptional factor (TF)-gene interaction networks were constructed.
RESULTS: A total of 252 genes were identified as DEGs in the overlapping two datasets. Functional analysis emphasizes the crucial role of the cell cycle in these two diseases. 10 hub genes were identified using cytoHubba, including CCNA2, ASPM, MKI67, FN1, FEN1, STAT1, DEPDC1, ITGB8, DYNC2LI1, HBEGF. In addition, according to the miRNA-gene and TF-gene interaction networks, part of TFs (RELA, TP53), and miRNAs (miR-26b-5p, miR-192-5p) may be identified as key regulators in MM and osteoporosis at the same time.
CONCLUSIONS: The present study reveals the common pathogenesis of MM and osteoporosis. These shared pathways may provide new targets for further mechanistic studies of the pathogenesis and treatment of MM and osteoporosis.