Expert review of hematology · 2025
SYK identified by bioinformatics analysis promotes the proliferation of multiple myeloma.
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Deng Ju, Li Peichun, Li Shuo, Liang Fengting, Hong Minglin, Zhang Ting, Tan Yanhong, Ren Fanggang, Zhang Yaofang, Xu Zhifang, Wang Hongwei
Аннотация
BACKGROUND: Despite recent advancements, the pathogenesis of multiple myeloma (MM) remains incompletely elucidated, with relapse and therapy resistance persisting as major clinical challenges, underscoring the imperative to identify novel therapeutic targets.
RESEARCH DESIGN AND METHODS: Differentially expressed genes were initially screened from the GSE6477 and GSE6691 datasets. Subsequent functional annotation and pathway enrichment analyses were conducted utilizing the DAVID bioinformatics platform. A protein-protein interaction network was constructed via the STRING database, followed by module analysis and hub genes identification through CytoHubba plugin. The biological significance of candidate genes was ultimately validated through ex vivo cellular functional assays and in vivo xenograft tumorigenesis experiments in murine models.
RESULTS: Bioinformatics analysis identified spleen tyrosine kinase (SYK) as the most prognostically significant candidate gene (p = 0.027). The SYK-specific inhibitor BAY61-3606 demonstrated time- (p < 0.05) and dose- (p < 0.01) dependent inhibition of MM cell viability, concomitant induction of G2/M phase cell cycle arrest (p < 0.001), and significant promotion of apoptosis (p < 0.05). In vivo experiments utilizing MM xenograft models demonstrated that BAY61-3606 administration significantly attenuated tumor growth kinetics (p < 0.05).
CONCLUSIONS: Our findings establish SYK as a therapeutic target in MM, thereby facilitating the development of innovative treatment strategies.
RESEARCH DESIGN AND METHODS: Differentially expressed genes were initially screened from the GSE6477 and GSE6691 datasets. Subsequent functional annotation and pathway enrichment analyses were conducted utilizing the DAVID bioinformatics platform. A protein-protein interaction network was constructed via the STRING database, followed by module analysis and hub genes identification through CytoHubba plugin. The biological significance of candidate genes was ultimately validated through ex vivo cellular functional assays and in vivo xenograft tumorigenesis experiments in murine models.
RESULTS: Bioinformatics analysis identified spleen tyrosine kinase (SYK) as the most prognostically significant candidate gene (p = 0.027). The SYK-specific inhibitor BAY61-3606 demonstrated time- (p < 0.05) and dose- (p < 0.01) dependent inhibition of MM cell viability, concomitant induction of G2/M phase cell cycle arrest (p < 0.001), and significant promotion of apoptosis (p < 0.05). In vivo experiments utilizing MM xenograft models demonstrated that BAY61-3606 administration significantly attenuated tumor growth kinetics (p < 0.05).
CONCLUSIONS: Our findings establish SYK as a therapeutic target in MM, thereby facilitating the development of innovative treatment strategies.