N.N. Semenov Federal Research Center for Chemical Physics, Moscow, Russia.
N.N. Semenov Federal Research Center for Chemical Physics, Moscow, Russia; Department of Chemistry, Lomonosov Moscow State University, Moscow Russia.
Mol Cell Proteomics. 2020 Jun;19(6):960-970. doi: 10.1074/mcp.RA120.001986. Epub 2020 Apr 6.
Glioblastoma (GBM) is one of the most aggressive human cancers with a median survival of less than two years. A distinguishing pathological feature of GBM is a high degree of inter- and intratumoral heterogeneity. Intertumoral heterogeneity of GBM has been extensively investigated on genomic, methylomic, transcriptomic, proteomic and metabolomics levels, however only a few studies describe intratumoral heterogeneity because of the lack of methods allowing to analyze GBM samples with high spatial resolution. Here, we applied TOF-SIMS (Time-of-flight secondary ion mass spectrometry) for the analysis of single cells and clinical samples such as paraffin and frozen tumor sections obtained from 57 patients. We developed a technique that allows us to simultaneously detect the distribution of proteins and metabolites in glioma tissue with 800 nm spatial resolution. Our results demonstrate that according to TOF-SIMS data glioma samples can be subdivided into clinically relevant groups and distinguished from the normal brain tissue. In addition, TOF-SIMS was able to elucidate differences between morphologically distinct regions of GBM within the same tumor. By staining GBM sections with gold-conjugated antibodies against Caveolin-1 we could visualize border between zones of necrotic and cellular tumor and subdivide glioma samples into groups characterized by different survival of the patients. Finally, we demonstrated that GBM contains cells that are characterized by high levels of Caveolin-1 protein and cholesterol. This population may partly represent a glioma stem cells. Collectively, our results show that the technique described here allows to analyze glioma tissues with a spatial resolution beyond reach of most of other omics approaches and the obtained data may be used to predict clinical behavior of the tumor.
胶质母细胞瘤(GBM)是最具侵袭性的人类癌症之一,中位生存期不到两年。GBM 的一个显著的病理学特征是高度的肿瘤内异质性和肿瘤间异质性。GBM 的肿瘤间异质性已经在基因组、甲基组、转录组、蛋白质组和代谢组学水平上进行了广泛研究,然而,由于缺乏允许以高空间分辨率分析 GBM 样本的方法,只有少数研究描述了肿瘤内异质性。在这里,我们应用飞行时间二次离子质谱(TOF-SIMS)分析了 57 名患者的单个细胞和临床样本,如石蜡和冷冻肿瘤切片。我们开发了一种技术,使我们能够以 800nm 的空间分辨率同时检测神经胶质瘤组织中蛋白质和代谢物的分布。我们的结果表明,根据 TOF-SIMS 数据,神经胶质瘤样本可以根据临床相关的分组进行细分,并与正常脑组织区分开来。此外,TOF-SIMS 能够阐明同一肿瘤内形态上不同的 GBM 区域之间的差异。通过用金标记的针对 Cav-1 的抗体对 GBM 切片进行染色,我们可以观察到坏死区和细胞肿瘤区之间的边界,并将神经胶质瘤样本细分为具有不同患者生存率的组。最后,我们证明 GBM 含有高水平 Cav-1 蛋白和胆固醇的细胞。这个群体可能部分代表神经胶质瘤干细胞。总之,我们的结果表明,这里描述的技术允许以大多数其他组学方法无法达到的空间分辨率分析神经胶质瘤组织,并且所获得的数据可用于预测肿瘤的临床行为。