Metabolic Profiles Point Out Metabolic Pathways Pivotal in Two Glioblastoma (GBM) Cell Lines, U251 and U-87MG

MetaWise: Combined Feature Selection and Weighting Method to Link the Serum Metabolome to Treatment Response and Survival in Glioblastoma

Glioblastoma (GBM) is a highly malignant and devastating brain cancer characterized by its ability to rapidly and aggressively grow, infiltrating brain tissue, with nearly universal recurrence after the standard of care (SOC), which comprises maximal safe resection followed by chemoirradiation (CRT). The metabolic triggers leading to the reprogramming of tumor behavior and resistance are an area increasingly studied in relation to the tumor molecular features associated with outcome. There are currently no metabolomic biomarkers for GBM. Studying the metabolomic alterations in GBM patients undergoing CRT could uncover the biochemical pathways involved in tumor response and resistance, leading to the identification of novel biomarkers and the optimization of the treatment response. The feature selection process identifies key factors to improve the model's accuracy and interpretability. This study utilizes a combined feature selection approach, incorporating both Least Absolute Shrinkage and Selection Operator (LASSO) and Minimum Redundancy-Maximum Relevance (mRMR), alongside a rank-based weighting method (i.e., MetaWise) to link metabolomic biomarkers to CRT and the 12-month and 20-month overall survival (OS) status in patients with GBM. Our method shows promising results, reducing feature dimensionality when employed on serum-based large-scale metabolomic datasets (University of Florida) for all our analyses. The proposed method successfully identified a set of eleven serum biomarkers shared among three datasets. The computational results show that the utilized method achieves 96.711%, 92.093%, and 86.910% accuracy rates with 48, 46, and 33 selected features for the CRT, 12-month, and 20-month OS-based metabolomic datasets, respectively. This discovery has implications for developing personalized treatment plans and improving patient outcomes.

Glutamine Metabolism Heterogeneity in Glioblastoma Unveils an Innovative Combination Therapy Strategy

Treatment of glioblastoma multiforme (GBM) remains challenging. Unraveling the orchestration of glutamine metabolism may provide a novel viewpoint on GBM therapy. The study presented a full and comprehensive comprehending of the glutamine metabolism atlas and heterogeneity in GBM for facilitating the development of a more effective therapeutic choice. Transcriptome data from large GBM cohorts were integrated in this study. A glutamine metabolism-based classification was established through consensus clustering approach, and a classifier by LASSO analysis was defined for differentiating the classification. Prognosis, signaling pathway activity, tumor microenvironment, and responses to immune checkpoint blockade (ICB) and small molecular drugs were characterized in each cluster. A combinational therapy of glutaminase inhibitor CB839 with dihydroartemisinin (DHA) was proposed, and the influence on glutamine metabolism, apoptosis, reactive oxygen species (ROS), and migration was measured in U251 and U373 cells. We discovered that GBM presented heterogeneous glutamine metabolism-based clusters, with unique survival outcomes, activity of signaling pathways, tumor microenvironment, and responses to ICB and small molecular compounds. In addition, the classifier could accurately differentiate the two clusters. Strikingly, the combinational therapy of CB839 with DHA synergistically attenuated glutamine metabolism, triggered apoptosis and ROS accumulation, and impaired migrative capacity in GBM cells, demonstrating the excellent preclinical efficacy. Altogether, our findings unveil the glutamine metabolism heterogeneity in GBM and propose an innovative combination therapy of CB839 with DHA for this malignant disease.

Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas

Gliomas constitute a diverse and complex array of tumors within the central nervous system (CNS), characterized by a wide range of prognostic outcomes and responses to therapeutic interventions. This literature review endeavors to conduct a thorough investigation of gliomas, with a particular emphasis on glioblastoma (GBM), beginning with their classification and epidemiological characteristics, evaluating their relative importance within the CNS tumor spectrum. We examine the immunological context of gliomas, unveiling the intricate immune environment and its ramifications for disease progression and therapeutic strategies. Moreover, we accentuate critical developments in understanding tumor behavior, focusing on recent research breakthroughs in treatment responses and the elucidation of cellular signaling pathways. Analyzing the most novel transcriptomic studies, we investigate the variations in gene expression patterns in glioma cells, assessing the prognostic and therapeutic implications of these genetic alterations. Furthermore, the role of epigenetic modifications in the pathogenesis of gliomas is underscored, suggesting that such changes are fundamental to tumor evolution and possible therapeutic advancements. In the end, this comparative oncological analysis situates GBM within the wider context of neoplasms, delineating both distinct and shared characteristics with other types of tumors.