胶质瘤预后生物标志物SYK及其与免疫浸润的相关性。

Experimental and therapeutic medicine Pub Date : 2023-09-07 eCollection Date: 2023-10-01 DOI:10.3892/etm.2023.12198
Changxin Wang, Pei Liu, Yu Sun, Ting Liu, Xiaoxiao Xu, Jiamin Guo, Zheng Gong, Haixin Sun, Rui Xu
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摘要

肿瘤微环境(TME)为胶质瘤的发展提供了良好的条件。本研究旨在确定神经胶质瘤的预后因素,这些因素可用于改善该疾病患者的预后。在本研究中,通过估计RNA转录相对亚群的细胞类型鉴定(CIBERSORT)和使用表达数据计算的恶性肿瘤组织中的基质细胞和免疫细胞的估计用于估计来自癌症基因组图谱数据库的698例神经胶质瘤病例中肿瘤浸润免疫细胞的比率以及免疫和基质成分的量。此外,通过基因本体论和京都基因和基因组百科全书分析研究了某些差异表达基因,并通过蛋白质-蛋白质相互作用(PPI)网络和Cox联合分析鉴定了与预后相关的单个基因。TME的免疫和基质细胞评分与胶质瘤患者的生存率显著相关。通过PPI网络和Cox回归分析,脾脏酪氨酸激酶(SYK)最终被确定为神经胶质瘤患者的最佳预后因素。此外,还采用了基因集富集分析和CIBERSORT分析。前者表明高表达SYK组基因主要富集于免疫相关活性。后者显示SYK的表达与分化的T细胞簇4记忆静息和单核细胞呈正相关。上述实验分析为SYK的生物学预测提供了理论依据。数据表明,SYK通过促进TME从免疫优势向代谢活性的转变,有助于神经胶质瘤患者的免疫预测。最后,采用逆转录定量PCR和蛋白质印迹法对胶质瘤细胞中的单基因表达进行了验证。这可能为神经胶质瘤的治疗提供预后价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Prognostic biomarker SYK and its correlation with immune infiltrates in glioma.

The tumor microenvironment (TME) provides excellent conditions for the development of glioma. The present study sought to identify the prognostic factors of glioma that could be used to improve the prognosis of patients with this disease. In the present study, Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data calculations were employed to estimate the ratio of tumor-infiltrating immune cells and the quantity of immune and stromal components in 698 glioma cases from the Cancer Genome Atlas database. In addition, certain differentially expressed genes were studied by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses and single genes associated with prognosis were identified by protein-protein interaction (PPI) network and Cox combined analysis. The immune and stromal scores of the TME were significantly associated with glioma patient survival. By using the PPI network and Cox regression analyses, spleen tyrosine kinase (SYK) was eventually identified as the best prognostic factor for patients with glioma. In addition, Gene Set Enrichment Analysis and CIBERSORT analyses were employed. The former indicated that the high-expression SYK group genes were mainly enriched in immune-related activities. The latter revealed that SYK expression was positively associated with T cell cluster of differentiation 4 memory resting and monocytes. The aforementioned experimental analyses provided the theoretical basis for the biological prediction of SYK. The data indicated that SYK contributed to immune predictors in patients with glioma by facilitating the shift of the TME from immune dominance to metabolic activity. Finally, reverse transcription-quantitative PCR and western blotting were used to verify the single gene expression in glioma cells. This may provide prognostic value for the treatment of glioma.

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