Abstract Background: Glioblastoma (GBM) is a highly aggressive brain tumor with a median survival of approximately 14 months, primarily due to its ability to infiltrate healthy brain tissue both as single cells and in collectives. A deeper understanding of GBM cell motility, both individual and collective, is crucial for developing patient-specific therapies. We aimed to characterize migration in patient-derived GBM cells using advanced modeling to identify stratification markers and therapeutic vulnerabilities. Methods: We developed Single-Cell Behavior Live Imaging (ScBLI), an approach integrating live imaging with computational analysis, applied to 28 GBM primary cell cultures. Trajectories and morphological features were tracked and analyzed. Diffusion Entropy Analysis (DEA) was applied to classify trajectories based on the Delta Scaling parameter. We evaluated functional responses (chemotaxis, colony formation) correlating all findings with clinical outcomes and transcriptomic profiles. Results: We analyzed 3, 842 cell trajectories. Based on Delta scaling (range 0. 28–0. 80), we defined three distinct motility groups: Low (L, Delta scaling ≤0. 5), Medium (M, 0. 5 Delta scaling 0. 7), and High (H, Delta scaling 0. 7). High Delta scaling cells exhibited Lévy-like, persistent migration and, despite being paradoxically slower and covering less total distance, displayed the highest migratory efficiency. Targeted functional assays demonstrated that H-group cells are more performant in both positive and negative chemotaxis. Clinically, the three groups showed a clear linear progression with patient survival: High Delta scaling correlated with the shortest survival (poorer prognosis), while Low Δ correlated with the longest survival, suggesting that structured motility drives invasiveness. Finally, transcriptomic analysis revealed distinct gene expression signatures supporting these behavioral clusters. Conclusion: Our study introduces in glioblastoma for the first time migratory efficiency (measured via DEA) as a superior predictor of tumor malignancy compared to traditional motility metrics. We demonstrate a counter-intuitive finding: tumor cells that employ the most efficient exploration strategy, despite exhibiting lower speed and shorter distance traveled, are significantly associated with shorter patient survival. This suggests that the strategy of migration, not just the magnitude (speed/distance), is a critical factor driving malignancy. Our results redefine tumor cell motility, highlighting migratory efficiency as a crucial biomarker for identifying highly aggressive tumors. Citation Format: Mariangela Morelli, Gianmarco Ferri, Francesca Di Lorenzo, Francesca Marchetto, Francesca Lessi, Sara Franceschi, Tim Hohmann, Francesco Pieri, Carlo Gambacciani, Francesco Pasqualetti, Yawer Shah, Jace Singh, Bruce West, Michele Menicagli, Manuel Giacomarra, Lucio Tonello, Orazio Santo. Santonocito, Aldo Pastore, Paolo Aretini, Anna Luisa Di Stefano, Paolo Grigolini, Luigi Palatella, Chiara Maria. Mazzanti. The dual nature of glioblastoma cell motility: Migratory efficiency as a prognostic determinant abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86 (6Suppl): Abstract nr B002.
Morelli et al. (Mon,) studied this question.