Glioblastoma (GBM) is the most common and fatal cancer of the adult brain, with an annual incidence rate of 2-3 per 100 000 (US) and a median survival time around 14 months. GBM is characterized by an infiltrative growth pattern that makes its complete surgical resection arduous. Moreover, the presence of a therapy-refractory cancer stem cell (CSC) component has been linked to the unavoidable insurgence of tumor recurrence experienced by patients. The failure of current therapeutic standards at completely eradicate this tumor fuels an intense research effort for the identification and development of new therapeutic strategies. To achieve the cure of this malignancy, while preventing its recurrence, the ideal treatment should target both the invasive behavior of GBM and the cancer stem cell population (the latter with so called “differentiation therapy”). MicroRNAs (endogenous small non-coding RNAs regulating the gene expression at the post transcriptional level) show dysregulated expression in tumors compared to healthy tissues and are involved in several of the “hallmarks of cancer”: hence, they have raised attention for their therapeutic potential. The development of miRNA-based therapies is an expanding field of research: in recent years several formulations entered into clinical trials for treating various malignancies, but none for brain cancers, indicating room for improvement. The functional synergism of multiple, different miRNA, also known as cooperation or convergence, has been proposed as one of the mechanisms that confer robustness to miRNA-mediated regulation of large number of genes, allowing these tiny RNAs to orchestrate essential cellular pathways. MiRNA-based therapies for cancer could benefit from the functional synergism of different miRNAs, especially considering the high intra-tumoral heterogeneity and the number of redundant and compensatory mechanisms of therapy-resistance that characterize refractory tumors as GBM, that are unlikely to be effectively targeted by a single molecule. Our lab previously identified a “pool” of 11 miRNAs necessary and sufficient to sustain neuronal differentiation of adult neural stem cells in mice by the synergic repression of targets involved in cell morphogenesis and neuron differentiation (Pons-Espinal et al., 2017). This pool is conserved in human and dysregulated in GBM. The molecular and cellular similarities between GBM stem cells (GSC) and neural stem cells (NSC) led to the hypothesis to employ the 11-miRNA pool in GBM, with the originary idea to target the GSC component of this tumor with potential benefit. Building on the combinatorial nature of the miRNA pathway and on previous results by the host lab, indicating an essential role of the miRNA pool to control NSCs differentiation, the overarching goal of my PhD project was to deploy the 11-miRNA pool in an anticancer therapy against GBM, to test its tumor-suppressive potential and to identify the molecular mechanisms underlying its therapeutic effects. Main results achieved by this work are: I. The identification of a fundamentally anti-invasive role of the 11 miRNAs, achieved in GBM by synergistic regulation of a wide network of proteins involved in cell-adhesion, cytoskeleton reorganization and extracellular matrix remodeling. Importantly, many of the proteins downregulated by the pool are relevant in GBM pathogenesis and thereby possible targets for future development of conventional drug-based therapies. II. The development of a delivery strategy that possesses a realistic translational potential, taking the example from clinically approved lipid nanoparticles formulations, considered a leading-edge vector for small RNAs delivery. III. The demonstration that the functional synergism of the 11-miRNA pool, enhanced in vivo by nano-delivery, is an effective strategy to slow-down the in vivo growth of an aggressive model of human GBM.
|Titolo della tesi:||A nanoformulated 11-miRNA pool synergistically modulates GBM cells invasion and in vivo growth|
|Data di discussione:||27-apr-2021|
|Appare nelle tipologie:||Tesi di dottorato|