Center for Genomic Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos 62210, Mexico.
Medical Research Unit in Human Genetics, Hospital of Pediatrics, National Medical Center XXI Century, Mexican Social Security Institute, Mexico City 06720, Mexico.
Oncol Rep. 2020 Aug;44(2):661-673. doi: 10.3892/or.2020.7625. Epub 2020 May 27.
Glioblastoma is a difficult disease to diagnose. Proteomic techniques are commonly applied in biomedical research, and can be useful for early detection, making an accurate diagnosis and reducing mortality. The relevance of mitochondria in brain development and function is well known; therefore, mitochondria may influence the development of glioblastoma. The T98G (with oxidative metabolism) and U87MG (with glycolytic metabolism) cell lines are considered to be useful glioblastoma models for studying these tumors and the role of mitochondria in key aspects of this disease, such as prognosis, metastasis and apoptosis. In the present study, principal component analysis of protein abundance data identified by liquid chromatography coupled to tandem mass spectrometry (LC‑MS/MS) and matrix‑assisted laser desorption/ionization‑time of flight mass spectrometry (MALDI‑TOF) from 2D gels indicated that representative mitochondrial proteins were associated with glioblastoma. The selected proteins were organized into T98G‑ and U87MG‑specific protein‑protein interaction networks to demonstrate the representativeness of both proteomic techniques. Gene Ontology overrepresentation analysis based on the relevant proteins revealed that mitochondrial processes were associated with metabolic changes, invasion and metastasis in glioblastoma, along with other non‑mitochondrial processes, such as DNA translation, chaperone responses and autophagy. Despite the lower resolution of 2D electrophoresis, principal component analysis yielded information of comparable quality to that of LC‑MS/MS. The present analysis pipeline described a specific and more complete metabolic status for each cell line, defined a clear mitochondrial performance for distinct glioblastoma tumors, and introduced a useful strategy to understand the heterogeneity of glioblastoma.
胶质母细胞瘤是一种难以诊断的疾病。蛋白质组学技术常用于生物医学研究,可用于早期检测、准确诊断和降低死亡率。线粒体在脑发育和功能中的相关性是众所周知的;因此,线粒体可能会影响胶质母细胞瘤的发展。T98G(具有氧化代谢)和 U87MG(具有糖酵解代谢)细胞系被认为是研究这些肿瘤和线粒体在该疾病关键方面(如预后、转移和细胞凋亡)作用的有用胶质母细胞瘤模型。在本研究中,通过液相色谱-串联质谱(LC-MS/MS)和基质辅助激光解吸/电离-飞行时间质谱(MALDI-TOF)对二维凝胶进行蛋白质丰度数据的主成分分析表明,代表性线粒体蛋白与胶质母细胞瘤相关。选择的蛋白质被组织成 T98G 和 U87MG 特异性蛋白质-蛋白质相互作用网络,以证明两种蛋白质组学技术的代表性。基于相关蛋白质的基因本体论过表达分析表明,线粒体过程与胶质母细胞瘤中的代谢变化、侵袭和转移有关,以及其他非线粒体过程,如 DNA 翻译、伴侣反应和自噬。尽管二维电泳的分辨率较低,但主成分分析仍能提供与 LC-MS/MS 相当的高质量信息。本分析流程描述了每个细胞系的特定且更完整的代谢状态,为不同的胶质母细胞瘤肿瘤定义了明确的线粒体功能,并引入了一种理解胶质母细胞瘤异质性的有用策略。