Department of Medical, Oral and Biotechnological Sciences, 'G. D'Annunzio' University of Chieti-Pescara, Via Vestini 31, 66100 Chieti, Italy.
Center for Advanced Studies and Technology (CAST), 'G. D'Annunzio' University of Chieti-Pescara, Via L Polacchi 13, 66100 Chieti, Italy.
Int J Mol Sci. 2024 Sep 10;25(18):9778. doi: 10.3390/ijms25189778.
Like most tumors, glioblastoma multiforme (GBM), the deadliest brain tumor in human adulthood, releases extracellular vesicles (EVs). Their content, reflecting that of the tumor of origin, can be donated to nearby and distant cells which, by acquiring it, become more aggressive. Therefore, the study of EV-transported molecules has become very important. Particular attention has been paid to EV proteins to uncover new GBM biomarkers and potential druggable targets. Proteomic studies have mainly been performed by "bottom-up" mass spectrometry (MS) analysis of EVs isolated by different procedures from conditioned media of cultured GBM cells and biological fluids from GBM patients. Although a great number of dysregulated proteins have been identified, the translation of these findings into clinics remains elusive, probably due to multiple factors, including the lack of standardized procedures for isolation/characterization of EVs and analysis of their proteome. Thus, it is time to change research strategies by adopting, in addition to harmonized EV selection techniques, different MS methods aimed at identifying selected tumoral protein mutations and/or isoforms due to post-translational modifications, which more deeply influence the tumor behavior. Hopefully, these data integrated with those from other "omics" disciplines will lead to the discovery of druggable pathways for novel GBM therapies.
与大多数肿瘤一样,胶质母细胞瘤(GBM)是成年人中最致命的脑肿瘤,会释放细胞外囊泡(EVs)。其内容反映了肿瘤的起源,可以捐赠给附近和远处的细胞,这些细胞通过获得 EV 内容而变得更具侵袭性。因此,对 EV 转运分子的研究变得非常重要。人们特别关注 EV 蛋白,以发现新的 GBM 生物标志物和潜在的可成药靶点。蛋白质组学研究主要通过“自上而下”的质谱(MS)分析,从培养的 GBM 细胞的条件培养基和 GBM 患者的生物体液中通过不同程序分离 EV 进行。尽管已经鉴定出大量失调蛋白,但这些发现转化为临床实践仍然难以捉摸,可能是由于多种因素造成的,包括缺乏用于 EV 分离/表征和分析其蛋白质组的标准化程序。因此,是时候通过采用除了协调一致的 EV 选择技术外,还采用不同的 MS 方法来识别选定的肿瘤蛋白突变体和/或由于翻译后修饰而导致的同工型,从而改变研究策略,这些修饰更深入地影响肿瘤行为。希望这些数据与来自其他“组学”学科的数据相结合,将为新型 GBM 治疗方法发现可成药途径。