Tian Yixin, Ke Yiquan, Ma Yanxia
Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, The Neurosurgery Institute of Guangdong Province, Guangzhou 510282, China.
Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China.
PeerJ. 2020 May 20;8:e9038. doi: 10.7717/peerj.9038. eCollection 2020.
Glioma is one of the most fatal tumors in central nervous system. Previous studies gradually revealed the association between tumor microenvironment and the prognosis of gliomas patients. However, the correlation between tumor-infiltrating immune cell and stromal signatures are unknown. In our study, we obtained gliomas samples from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). The landscape of tumor infiltrating immune cell subtypes in gliomas was calculated by CIBERSORT. As a result, we found high infiltration of macrophages was correlated with poor outcome ( < 0.05). Then functional enrichment analysis of high/low macrophage-infiltrating groups was performed by GSEA. The results showed three gene sets includes 102 core genes about angiogenesis were detected in high macrophage-infiltrating group. Next, we constructed PPI network and analyzed prognostic value of 102 core genes. We found that five stromal signatures indicated poor prognosis which including HSPG2, FOXF1, KDR, COL3A1, SRPX2 ( < 0.05). Five stromal signatures were adopted to construct a classifier. The classifier showed powerful predictive ability (AUC = 0.748). Patients with a high risk score showed poor survival. Finally, we validated this classifier in TCGA and the result was consistent with CGGA. Our investigation of tumor microenvironment in gliomas may stimulate the new strategy in immunotherapy. Five stromal signature correlated with poor prognosis also provide a strong predator of gliomas patient outcome.
胶质瘤是中枢神经系统中最致命的肿瘤之一。先前的研究逐渐揭示了肿瘤微环境与胶质瘤患者预后之间的关联。然而,肿瘤浸润免疫细胞与基质特征之间的相关性尚不清楚。在我们的研究中,我们从中国胶质瘤基因组图谱(CGGA)和癌症基因组图谱(TCGA)获得了胶质瘤样本。通过CIBERSORT计算胶质瘤中肿瘤浸润免疫细胞亚型的情况。结果,我们发现巨噬细胞的高浸润与不良预后相关(<0.05)。然后通过基因集富集分析(GSEA)对高/低巨噬细胞浸润组进行功能富集分析。结果显示在高巨噬细胞浸润组中检测到三个包含102个关于血管生成的核心基因的基因集。接下来,我们构建了蛋白质-蛋白质相互作用(PPI)网络并分析了102个核心基因的预后价值。我们发现五个基质特征表明预后不良,包括硫酸乙酰肝素蛋白聚糖2(HSPG2)、叉头框蛋白F1(FOXF1)、激酶插入结构域受体(KDR)、Ⅲ型胶原蛋白α1链(COL3A1)、短链px2蛋白(SRPX2)(<0.05)。采用这五个基质特征构建了一个分类器。该分类器显示出强大的预测能力(曲线下面积[AUC]=0.748)。高风险评分的患者生存情况较差。最后,我们在TCGA中验证了这个分类器,结果与CGGA一致。我们对胶质瘤肿瘤微环境的研究可能会推动免疫治疗的新策略。与预后不良相关的五个基质特征也为胶质瘤患者的预后提供了有力的预测指标。