Identification of therapeutic targets and immune landscape in glioblastoma through crosstalk with glioma-associated mesenchymal stem cells

被引:0
|
作者
Zheng, Haoyang [1 ]
Wang, Haofei [1 ]
Zhang, Duo [2 ]
Gan, Yong [3 ]
Wu, Yuyi [1 ]
Xiang, Wei [1 ]
Fu, Peng [1 ]
机构
[1] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Neurosurg, Wuhan 430022, Peoples R China
[2] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Nursing, Wuhan 430030, Peoples R China
[3] Huazhong Univ Sci & Technol, Tongji Med Coll, Sch Publ Hlth, Dept Social Med & Hlth Management, 13 Hangkong Rd, Wuhan 430030, Peoples R China
基金
中国国家自然科学基金;
关键词
Glioblastoma; Mesenchymal Stem Cells; Bioinformatics Analysis; Therapeutic Targets; Molecular Dynamics Simulation; STAUROSPORINE; EXPRESSION; INHIBITOR; INVASION;
D O I
10.1016/j.intimp.2025.114228
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: Glioma-associated mesenchymal stem cells (GA-MSCs) are one of the key factors limiting the effectiveness of glioblastoma (GBM) treatment and contributing to poor patient prognosis, making them a potential therapeutic target for GBM. In-depth research into the complex crosstalk between GA-MSCs and GBM cells not only aids in understanding the mechanisms of GBM progression but also provides valuable insights for developing new potential drugs. Methods: We conducted a comprehensive bioinformatics analysis aimed at identifying shared dysregulated genes between GBM and GA-MSCs. Through hub gene enrichment and immune infiltration analyses, we explored key molecular pathways and the immune landscape. Additionally, Cox regression analysis was employed to identify key factors influencing overall survival in GBM. The expression patterns and functional roles of hub genes were validated across various cancer types and datasets. Finally, dynamic simulations were used to assess the binding affinity of potential drugs to the targets, further supporting their potential as therapeutic candidates. Results: We identified 32 candidate genes primarily involved in the 1-kappa-B kinase/NF-kappa-B and MAPK signaling pathways, both of which played critical roles in tumor survival, proliferation, and invasion. Notable hub genes included DUSP1, FYN, FLNC, FN1, G3BP1, MYO1B, and WLS, each contributing uniquely to GBM progression. Among them, FLNC was highlighted as a key regulatory factor in GBM progression. Molecular dynamics simulations further revealed its potential as a therapeutic target, particularly demonstrating a high binding affinity with staurosporine. Additionally, a high proportion of dendritic cells contributed to the formation of the GBM immune microenvironment. Conclusions: This study revealed the co-expression patterns and metabolic pathways between GA-MSCs and GBM, providing new insights into the molecular mechanisms of GBM progression. Targeting FLNC with staurosporine presents a promising therapeutic strategy for GBM. Aditionally, targeting the shared pathways of both may offer a valuable approach for treating malignant brain tumors.
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页数:20
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