大小很重要:胶质母细胞瘤患者尿液中大小细胞外囊泡的生物分子组成

Susannah M. Hallal, Liam A. Sida, Csilla Ágota Tűzesi, Brindha Shivalingam, Hao-Wen Sim, Michael E. Buckland, Laveniya Satgunaseelan, Kimberley L. Alexander
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摘要

尿液细胞外囊泡(uEVs)在生物标记物发现方面的前景正在显现。然而,不同uEV亚群在正常生理和病理状态下的特征和组成需要严格的阐释。我们最近报道了小(s)-uEVs(<200 nm膜状纳米颗粒)的蛋白质组特征,并描述了与致命的成人原发性脑肿瘤胶质母细胞瘤的诊断、肿瘤负荷和复发相对应的假定生物标记物。在这里,我们利用傅立叶变换红外光谱法和定量数据独立采集质谱法,全面描述了在 100,000 × g(100K-uEVs;较小)和 17,000 × g(17K-uEVs;较大)条件下进行差速离心获得的平均粒径和模式粒径明显不同的 uEV 群体的特征。我们显示了 uEV 群体之间在蛋白质和脂质含量、突出的蛋白质二级结构以及蛋白质组分布方面的明显差异,这些差异可将胶质母细胞瘤患者与健康对照组区分开来,并与临床相关的肿瘤变化(即复发和耐药性)相对应。主要发现之一是与17K-uEV相关的七种假定蛋白生物标记物面板,可将所有胶质母细胞瘤患者与健康对照组区分开来,并对98.2%的胶质母细胞瘤样本进行准确分类。这些新颖而重要的发现表明,这两种 uEV 群体都具有单独和组合生物标记物的潜力。为了阐明经常被忽视的 17K-uEV 群体的完整诊断、预后和预测能力,有必要开展进一步的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Size matters: Biomolecular compositions of small and large extracellular vesicles in the urine of glioblastoma patients

The promise of urinary extracellular vesicles (uEVs) in biomarker discovery is emerging. However, the characteristics and compositions of different uEV subpopulations across normal physiological and pathological states require rigorous explication. We recently reported proteomic signatures of small (s)-uEVs (<200 nm membranous nanoparticles) and described putative biomarkers corresponding to the diagnosis, tumour burden and recurrence of the lethal adult primary brain tumour, glioblastoma. Here, we comprehensively characterise uEV populations with significantly different mean and mode particle sizes obtained by differential centrifugation at 100,000 × g (100K-uEVs; smaller) and 17,000 × g (17K-uEVs; larger) using Fourier-transform infrared spectroscopy and quantitative data-independent acquisition mass spectrometry. We show distinct differences in protein and lipid content, prominent protein secondary structures, and proteome distributions between uEV populations that can distinguish glioblastoma patients from healthy controls and correspond to clinically relevant tumour changes (i.e., recurrence and treatment resistance). Among the key findings is a putative seven-protein biomarker panel associated with 17K-uEVs that could distinguish all glioblastoma patients from healthy controls and accurately classify 98.2% of glioblastoma samples. These novel, significant findings demonstrate that both uEV populations offer individual and combined biomarker potential. Further research is warranted to elucidate the complete diagnostic, prognostic, and predictive capabilities of often-neglected 17K-uEV populations.

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