Q-META: Quantum-Enhanced Multidimensional Platform for Glioblastoma Metabolism

Brain tumors such as glioblastoma multiforme (GBM) pose a major challenge in oncology due to their intrinsic heterogeneity and the complexity of the tumor microenvironment (TME). These features hinder accurate characterization and limit the effectiveness of current therapeutic strategies, ultimately resulting in poor prognosis. Existing experimental approaches face two fundamental limitations. First, conventional two-dimensional models fail to reproduce the intricate cell–cell and cell–matrix interactions that define the GBM microenvironment, preventing an authentic representation of tumor dynamics. Second, standard imaging methods lack the sensitivity required to monitor metabolic reprogramming non-invasively and typically rely on high light intensities that induce phototoxicity, making long-term, real-time in vivo observation difficult.

Q-META aims to overcome these limitations by investigating how mechanotransduction, the process by which cells translate mechanical cues such as pressure and stiffness into biochemical responses, influences GBM behavior and progression. The project combines two complementary innovations that address the principal shortcomings of current models. On one front, Q-META enhances established imaging modalities, including Fluorescence Lifetime Imaging Microscopy (FLIM) and stimulated Raman spectroscopy, through the use of quantum light. FLIM provides detailed information on molecular interactions and the surrounding microenvironment by measuring fluorescence decay times, while stimulated Raman spectroscopy enables label-free biochemical analysis. Incorporating quantum illumination significantly boosts sensitivity and reduces phototoxicity, enabling real-time, in vivo monitoring of metabolic changes in tumor cells with unprecedented precision. On the other front, the project introduces an advanced three-dimensional GBM model generated through bioprinting. This model captures not only the tumor’s architecture but also its TME by integrating immune cells and extracellular matrix components. Such a physiologically relevant system allows for the investigation of metabolic and mechano-biological responses in conditions that closely mimic in vivo tumor behavior, bridging the critical gap left by traditional 2D cultures.

Through this dual approach, Q-META establishes a quantum-empowered, multidimensional platform for the functional study of glioblastoma metabolism, opening new pathways for understanding tumor progression and identifying future therapeutic targets.