Metabolic Heterogeneity Evidenced by MRS among Patient-Derived Glioblastoma Multiforme Stem-Like Cells Accounts for Cell Clustering and Different Responses to Drugs

Abstract

Clustering of patient-derived glioma stem-like cells (GSCs) through unsupervised analysis of metabolites detected by magnetic resonance spectroscopy (MRS) evidenced three subgroups, namely clusters 1a and 1b, with high intergroup similarity and neural fingerprints, and cluster 2, with a metabolism typical of commercial tumor lines. In addition, subclones generated by the same GSC line showed different metabolic phenotypes. Aerobic glycolysis prevailed in cluster 2 cells as demonstrated by higher lactate production compared to cluster 1 cells. Oligomycin, a mitochondrial ATPase inhibitor, induced high lactate extrusion only in cluster 1 cells, where it produced neutral lipid accumulation detected as mobile lipid signals by MRS and lipid droplets by confocal microscopy. These results indicate a relevant role of mitochondrial fatty acid oxidation for energy production in GSCs. On the other hand, further metabolic differences, likely accounting for different therapy responsiveness observed after etomoxir treatment, suggest that caution must be used in considering patient treatment with mitochondria FAO blockers. Metabolomics and metabolic profiling may contribute to discover new diagnostic or prognostic biomarkers to be used for personalized therapies.

Hypoxia, Inflammation and Necrosis as Determinants of Glioblastoma Cancer Stem Cells Progression

“…It is worth noting that there is a strong heterogeneity among GSCs derived from different patients that accounts for differences in tumor behavior and therapy response [64]. In fact, as previously documented, GSCs #1 and 83 show different metabolic profiles [51]. Finally, we also performed in vivo analysis to validate our in vitro results.…”

“…In fact, in this GSC line, we observed a modulation of VEGF mRNA by hypoxia that was not paralleled by a modulation of VEGF protein expression (compare Figure 1C with Figure 2C). Even if we did not investigate into that, we think that such a discrepancy might be due to: (i) a post-transcriptional control by miRNA that prevent expression of VEGF from mRNA either directly as in the case of miR-16 [49] or indirectly by targeting VHL protein as in the case of miR-566 [50]; (ii) the intratumoral heterogeneity of line #83 that contains tumor cells with different metabolic behavior that when sub-cloned gave rise to cell lines belonging to separate metabolic clusters [51]. In the latter case, this heterogeneity might reflect in opposite trends of VEGF protein expression showing, on average, no significant increase.…”

“…We think that the reasons were: (i) the response to hypoxia was different between these two cell lines in term of HIF-1α protein expression showing, cell line #1, stronger expression than cell line #83; (ii) these two GSC lines are representative of the two GSC clusters, in particular GSC #1 shows the proneural-like phenotype (GSf-like) growing as neurospheres in vitro, whereas GSC #83 shows the mesenchymal-like phenotype (GSr-like) characterized by adherent growth in vitro [36]. It is known that these two clusters have differential expression of a large number of genes and metabolic profiles [51]. Moreover, the results on the four GSC first and on the selected two later, indicate the importance of the patient's tumor history from transformation to progression and the need for a personalized characterization that can be achieved not only genetically or metabolically but also by measuring alarmin receptor expression and response to inflammation in the CSCs as suggested in this work.…”

Enhanced fatty acid oxidation provides glioblastoma cells metabolic plasticity to accommodate to its dynamic nutrient microenvironment

“…The complex, biologic consequence of FAO goes well beyond solely serving as an energy source 8 , including its capacity to provide substrates for NADPH production to modulate redox stress 9 , pyrimidines precursors in endothelial cells 10 , and metabolic intermediates to promote stemness in hematopoietic cells 43 . Accordingly, the potential for this metabolic node to serve as a therapeutic target has gained recent attention 8,[44][45][46] . Although several studies have suggested metabolic programming leading to activation of FAO is involved in tumorigenesis, including in glioma 47 , a majority of these studies have relied upon aberrant expression of genes associated with this pathway.…”

Hypoxic Environment and Paired Hierarchical 3D and 2D Models of Pediatric H3.3-Mutated Gliomas Recreate the Patient Tumor Complexity

“…The hypoxia also induced an altered metabolism, which is considered a feature of adult glioblastoma progression, but the mechanisms by which it contributes to oncogenicity are still unknown, especially in pediatric patients. We [26] and others [27][28][29][30] described this HGG metabolic heterogeneity and how it might impact the response to therapeutic drugs. Our data also explored the process of compensatory metabolism in pHGG tumors and the paired-cellular models.…”