PDF(Pubmed)
Abstract：
Brain glioma is one of the cancer types with worst prognosis, and LMO2 has been reported to play oncogenic functions in brain gliomas. Herein, analysis of datasets from The Cancer Genome Atlas (TCGA) indicated that higher LMO2 level in patient samples indicated worse prognosis in lower grade gliomas (LGG) but not glioblastoma multiforme (GBM). Further, in tumor tissues consisting of a variety of cell types, LMO2 level indicated intratumoral endothelium and pattern recognition receptor (PRR) response in both LGGs and GBMs, and additionally indicated cytotoxic T-lymphocyte, M2 macrophage infiltration and fibroblast specifically in LGGs. Moreover, only in LGGs these aspects were significantly associated with patient survival, in either risky or protective manner, and these dissected associations can give a better prediction on patient prognosis than LMO2 alone. This study not only provided more detailed understandings of LMO2 functional representatives in brain gliomas but also demonstrated that dealing with certain gene (LMO2 in this study) in transcriptome data with the Weighted Gene Co-Expression Network Analysis (WGCNA) method was a robust strategy for dissecting exact and reasonable gene functions/associations in a complicated tumor environment.
摘要：
脑胶质瘤是预后最差的癌症类型之一，据报道，LMO2在脑胶质瘤中发挥致癌功能。在这里，对来自癌症基因组图谱(TCGA)的数据集的分析显示,患者样本中较高的LMO2水平表明,在低级别神经胶质瘤(LGG)中预后较差,而在多形性胶质母细胞瘤(GBM)中不存在.Further,在由多种细胞类型组成的肿瘤组织中，LMO2水平表明LGG和GBM的肿瘤内内皮和模式识别受体（PRR）反应，并额外显示细胞毒性T淋巴细胞，M2巨噬细胞浸润和成纤维细胞特异性地存在于LGGs中。此外，仅在LGG中，这些方面与患者生存率显着相关，以危险或保护的方式，与单独使用LMO2相比，这些解剖的关联可以更好地预测患者的预后。这项研究不仅提供了对脑胶质瘤中LMO2功能代表的更详细了解，而且还证明了使用加权基因共表达网络分析（WGCNA）方法处理转录组数据中的某些基因（本研究中的LMO2）是一种强大的策略。在复杂的肿瘤环境中解剖准确合理的基因功能/关联。
