Clinical scores, molecular markers and cellular phenotypes have been used to predict the clinical outcomes of patients with glioblastoma. However, their clinical use has been hampered by confounders such as patient co-morbidities, by the tumoral heterogeneity of molecular and cellular markers, and by the complexity and cost of high-throughput single-cell analysis. Here, we show that a microfluidic assay for the quantification of cell migration and proliferation can categorize patients with glioblastoma according to progression-free survival. We quantified with a composite score the ability of primary glioblastoma cells to proliferate (via the protein biomarker Ki-67) and to squeeze through microfluidic channels, mimicking aspects of the tight perivascular conduits and white-matter tracts in brain parenchyma. The assay retrospectively categorized 28 patients according to progression-free survival (short-term or long-term) with an accuracy of 86%, predicted time to recurrence and correctly categorized five additional patients on the basis of survival prospectively. RNA sequencing of the highly motile cells revealed differentially expressed genes that correlated with poor prognosis. Our findings suggest that cell-migration and proliferation levels can predict patient-specific clinical outcomes.

临床评分、分子标记和细胞表型已被用于预测胶质母细胞瘤患者的临床结果。然而，它们的临床应用受到诸如患者合并症、分子和细胞标志物的肿瘤异质性以及高通量单细胞分析的复杂性和成本等混杂因素的阻碍。在这里，我们展示了一种用于量化细胞迁移和增殖的微流体测定法可以根据无进展生存期对胶质母细胞瘤患者进行分类。我们用综合评分量化了原发性胶质母细胞瘤细胞增殖（通过蛋白质生物标志物 Ki-67）和挤压微流体通道的能力，模拟了脑实质中紧密血管周围导管和白质束的各个方面。该测定根据无进展生存期（短期或长期）对 28 名患者进行了回顾性分类，准确率为 86%，预测复发时间，并根据前瞻性生存期对另外 5 名患者进行了正确分类。高度运动细胞的 RNA 测序揭示了与预后不良相关的差异表达基因。我们的研究结果表明，细胞迁移和增殖水平可以预测患者特定的临床结果。