Franceschi Sara, Lessi Francesca, Morelli Mariangela, Menicagli Michele, Aretini Paolo, Gambacciani Carlo, Pieri Francesco, Grimod Gianluca, Trapanese Maria Grazia, Valenti Silvia, Paiar Fabiola, Di Stefano Anna Luisa, Santonocito Orazio Santo, Pasqualetti Francesco, Mazzanti Chiara Maria
Fondazione Pisana per la Scienza, 56017 Pisa, Italy.
Department of Neurosurgery, Spedali Riuniti di Livorno, 57124 Livorno, Italy.
Cancers (Basel). 2024 Nov 6;16(22):3748. doi: 10.3390/cancers16223748.
BACKGROUND/OBJECTIVES: Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options. Extracellular vesicles (EVs) derived from GBM cells contain important biomarkers, such as microRNAs, proteins, and DNA mutations, which are involved in tumor progression, invasion, and resistance to treatment. Identifying surface markers on these EVs is crucial for their isolation and potential use in noninvasive diagnosis. This study aimed to use tumor-derived explants to investigate the surface markers of EVs and explore their role as diagnostic biomarkers for GBM.
Tumor explants from nine GBM patients without IDH1/IDH2 mutations or 1p-19q co-deletion were cultured to preserve both tumor viability and cytoarchitecture. EVs were collected from the tumor microenvironment using differential centrifugation, filtration, and membrane affinity binding. Their surface protein composition was analyzed through multiplex protein assays. RNA-Seq data from TCGA and GTEx datasets, along with in silico single-cell RNA-seq data, were used to assess EV surface biomarker expression across large GBM patient cohorts.
The in vitro model successfully replicated the tumor microenvironment and produced EVs with distinct surface markers. Biomarker analysis in large datasets revealed specific expression patterns unique to GBM patients compared with healthy controls. These markers demonstrated potential as a GBM-specific signature and were correlated with clinical data. Furthermore, in silico single-cell RNA-seq provided detailed insights into biomarker distribution across different cell types within the tumor.
This study underscores the efficacy of the tumor-derived explant model and its potential to advance the understanding of GBM biology and EV production. A key innovation is the isolation of EVs from a model that faithfully mimics the tumor's original cytoarchitecture, offering a deeper understanding of the cells involved in EV release. The identified EV surface markers represent promising targets for enhancing EV isolation and optimizing their use as diagnostic tools. Moreover, further investigation into their molecular cargo may provide crucial insights into tumor characteristics and evolution.
背景/目的：胶质母细胞瘤（GBM）是一种侵袭性脑癌，治疗选择有限。源自GBM细胞的细胞外囊泡（EVs）含有重要的生物标志物，如微小RNA、蛋白质和DNA突变，这些都参与肿瘤进展、侵袭及对治疗的抗性。识别这些EVs上的表面标志物对于其分离及在无创诊断中的潜在应用至关重要。本研究旨在利用肿瘤来源的外植体来研究EVs的表面标志物，并探索其作为GBM诊断生物标志物的作用。
对9例无异柠檬酸脱氢酶1/异柠檬酸脱氢酶2（IDH1/IDH2）突变或1p-19q共缺失的GBM患者的肿瘤外植体进行培养，以保持肿瘤活力和细胞结构。通过差速离心、过滤和膜亲和结合从肿瘤微环境中收集EVs。通过多重蛋白质分析对其表面蛋白质组成进行分析。来自癌症基因组图谱（TCGA）和基因型组织表达（GTEx）数据集的RNA测序（RNA-Seq）数据，以及计算机模拟单细胞RNA测序数据，用于评估大样本GBM患者队列中EV表面生物标志物的表达情况。
体外模型成功复制了肿瘤微环境，并产生了具有独特表面标志物的EVs。大型数据集中的生物标志物分析显示，与健康对照相比，GBM患者具有独特的特异性表达模式。这些标志物显示出作为GBM特异性特征的潜力，并与临床数据相关。此外，计算机模拟单细胞RNA测序提供了关于肿瘤内不同细胞类型中生物标志物分布的详细见解。
本研究强调了肿瘤来源外植体模型的有效性及其在推进对GBM生物学和EV产生理解方面的潜力。一项关键创新是从忠实地模拟肿瘤原始细胞结构的模型中分离出EVs，从而更深入地了解参与EV释放的细胞。所鉴定的EV表面标志物是增强EV分离及优化其作为诊断工具应用的有前景的靶点。此外，对其分子货物的进一步研究可能为肿瘤特征和演变提供关键见解。
