SIRPB1 regulates inflammatory factor expression in the glioma microenvironment via SYK: functional and bioinformatics insights
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Background

SIRPB1 expression is upregulated in various tumor types, including gliomas, and is known to contribute to tumor progression; nevertheless, its function in the immune milieu of gliomas is still mainly unknown.

Methods

This study, we analyzed 1152 normal samples from the GTEx database and 670 glioma samples from the TCGA database to investigate the relationship between the expression of SIRPB1 and clinicopathological features. Moreover, SIRPB1 gene knockout THP-1 cell lines were constructed using CRISPR/Cas9 and were induced into a co-culture of macrophages and glioma cells in vitro to learn more about the role of SIRPB1 in the glioma immune milieu. Lastly, we established a prognostic model to predict the effect of SIRPB1 on prognosis.

Results

Significantly higher levels of SIRPB1 expression were found in gliomas, which had an adverse effect on the immune milieu and correlated poorly with patient survival. SIRPB1 activation with certain antibodies results in SYK phosphorylation and the subsequent activation of calcium, MAPK, and NF-κB signaling pathways. This phenomenon is primarily observed in myeloid-derived cells as opposed to glioma cells. In vitro co-culture demonstrated that macrophages with SIRPB1 knockout showed decreased IL1RA, CCL2, and IL-8, which were recovered upon ectopic expression of SIRPB1 but reduced again following treatment with SYK inhibitor GS9973. Critically, a lower overall survival rate was linked to increased SIRPB1 expression. Making use of SIRPB1 expression along with additional clinicopathological variables, we established a nomogram that showed a high degree of prediction accuracy.

Conclusions

Our study demonstrates that glioma cells can be activated by macrophages via SIRPB1, subsequently reprogramming the TME, suggesting that SIRPB1 could serve as a promising therapeutic target for gliomas.

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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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