Cao Kangxi, Jiang Xingyu, Wang Baishun, Ni Zhaohui, Chen Yan
Department of Neurosurgery, The Second Hospital of Jilin University, Changchun, China.
Department of Pathogenobiology, The Key Laboratory of Zoonosis, Chinese Ministry of Education, College of Basic Medical Sciences, Jilin University, Changchun, China.
Front Neurol. 2022 Jun 10;13:905561. doi: 10.3389/fneur.2022.905561. eCollection 2022.
Glioblastoma (GBM) is the most common primary brain malignant tumor, and patients with GBM have a poor prognosis. The tumor microenvironment (TME) is connected to tumorigenesis and prognosis. However, the TME-related genes and therapeutic targets in GBM are yet to be identified. Thus, the presented study aimed to identify TME-related biomarkers in GBM and develop a novel target for the treatment of the disease.
ESTIMATE computational methods were utilized to estimate the amounts of stromal and immune components in 697 patients with glioma from the Cancer Genome Atlas database. Then, the protein-protein interaction network and univariate Cox regression analyzed the differentially expressed genes. Serum amyloid A1 (SAA1) was determined to be a predictive factor. SAA1 expression was statistically significant in GBM compared to the normal samples and other glioma subtypes and negatively associated with survival. Independent prognostic analysis identified SAA1 as a TME-related prognostic factor. Furthermore, Western blot analysis showed that SAA1 is upregulated in GBM, which was confirmed by the external validation in the Chinese Glioma Genome Atlas. The gene set enrichment analysis in GBM revealed enrichment of immune-related activities in the SAA1 high-expression group, while mitosis and cell cycle were enriched in the low-expression group. CIBERSORT analysis of the tumor-infiltrating immune cell proportion revealed that M2 macrophages, neutrophils, activated mast cells, resting mast cells, and regulatory T cells were correlated with SAA1 expression. Finally, immune checkpoint genes, tumor mutation burden, and drug sensitivity were also analyzed between the high- and low-expression groups.
SAA1 could be a distinctive gene between GBM and other subtype gliomas, and thus a novel biomarker for estimating the survival and TME status. The altered expression level shifts the primary function of SAA1 from cell cycle and mitosis to immune activity. High expression of SAA1 is associated with poor survival and upregulates the expression of LAIR1 and TNFSF14, thereby deeming it as the drug sensitivity indicator for XAV939, TGX-221, and lapatinib in GBM immune therapy.
胶质母细胞瘤（GBM）是最常见的原发性脑恶性肿瘤，GBM患者预后较差。肿瘤微环境（TME）与肿瘤发生和预后相关。然而，GBM中与TME相关的基因和治疗靶点尚未确定。因此，本研究旨在鉴定GBM中与TME相关的生物标志物，并开发该疾病治疗的新靶点。
利用ESTIMATE计算方法估计来自癌症基因组图谱数据库的697例胶质瘤患者的基质和免疫成分数量。然后，蛋白质-蛋白质相互作用网络和单变量Cox回归分析差异表达基因。血清淀粉样蛋白A1（SAA1）被确定为一个预测因子。与正常样本和其他胶质瘤亚型相比，SAA1在GBM中的表达具有统计学意义，且与生存率呈负相关。独立预后分析确定SAA1为与TME相关的预后因子。此外，蛋白质印迹分析表明SAA1在GBM中上调，这在中国胶质瘤基因组图谱的外部验证中得到证实。GBM中的基因集富集分析显示，SAA1高表达组中免疫相关活动富集，而低表达组中有丝分裂和细胞周期富集。对肿瘤浸润免疫细胞比例的CIBERSORT分析显示，M2巨噬细胞、中性粒细胞、活化肥大细胞、静息肥大细胞和调节性T细胞与SAA1表达相关。最后，还分析了高表达组和低表达组之间的免疫检查点基因、肿瘤突变负荷和药物敏感性。
SAA1可能是GBM与其他亚型胶质瘤之间的一个独特基因，因此是评估生存和TME状态的新型生物标志物。表达水平的改变将SAA1的主要功能从细胞周期和有丝分裂转变为免疫活性。SAA1的高表达与较差的生存率相关，并上调LAIR1和TNFSF14的表达，从而使其成为GBM免疫治疗中XAV939、TGX-221和拉帕替尼的药物敏感性指标。
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