Druggable genomic landscapes of high-grade gliomas

Current Research Trends in Glioblastoma: Focus on Receptor Tyrosine Kinases

Glioblastoma (GBM) is an aggressive brain tumor characterized by molecular complexity and resistance to conventional treatments, including surgery, radiation, and chemotherapy. Despite these challenges, advancements in receptor tyrosine kinase (RTK) research, combined with multi-omics approaches, hold promise for improving patient outcomes and survivability. RTKs are central to GBM progression, influencing cell proliferation, survival, and angiogenesis. However, the complexity of RTK signaling necessitates a broader, integrative perspective, which has been enabled by the emergence of -omics sciences. Multi-omics technologies-including genomics, transcriptomics, proteomics, and metabolomics-offer unprecedented insights into the molecular landscape of GBM and its RTK-driven pathways. Genomic studies have revealed mutations and amplifications in RTK-related genes, while transcriptomics has uncovered alterations in gene expression patterns, providing a clearer picture of how these aberrations drive tumor behavior. Proteomics has further delineated changes in protein expression and post-translational modifications linked to RTK signaling, highlighting novel therapeutic targets. Metabolomics complements these findings by identifying RTK-associated metabolic reprogramming, such as shifts in glycolysis and lipid metabolism, which sustain tumor growth and therapy resistance. The integration of these multi-omics layers enables a comprehensive understanding of RTK biology in GBM. For example, studies have linked metabolic alterations with RTK activity, offering new biomarkers for tumor classification and therapeutic targeting. Additionally, single-cell transcriptomics has unveiled intratumoral heterogeneity, a critical factor in therapy resistance. This article highlights the transformative potential of multi-omics in unraveling the complexity of RTK signaling in GBM. By combining these approaches, researchers are paving the way for precision medicine strategies that may significantly enhance diagnostic accuracy and treatment efficacy, providing new hope for patients facing this devastating disease.

Prognosis prediction via histological evaluation of cellular heterogeneity in glioblastoma

Glioblastomas (GBMs) are the most aggressive types of central nervous system tumors. Although certain genomic alterations have been identified as prognostic biomarkers of GBMs, the histomorphological features that predict their prognosis remain elusive. In this study, following an integrative diagnosis of 227 GBMs based on the 2021 World Health Organization classification system, the cases were histologically fractionated by cellular variations and abundance to evaluate the relationship between cellular heterogeneity and prognosis in combination with O-6-methylguanine-DNA methyltransferase gene promoter methylation (mMGMTp) status. GBMs comprised four major cell types: astrocytic, pleomorphic, gemistocytic, and rhabdoid cells. t-distributed stochastic neighbor embedding analysis using the histological abundance of heterogeneous cell types identified two distinct groups with significantly different prognoses. In individual cell component analysis, the abundance of gemistocytes showed a significantly favorable prognosis but confounding to mMGMTp status. Conversely, the abundance of epithelioid cells was correlated with the unfavorable prognosis. Linear model analysis showed the favorable prognostic utility of quantifying gemistocytic and epithelioid cells, independent of mMGMTp. The evaluation of GBM cell histomorphological heterogeneity is more effective for prognosis prediction in combination with mMGMTp analysis, indicating that histomorphological analysis is a practical and useful prognostication tool in an integrative diagnosis of GBMs.

A critical review of RAF inhibitors in BRAF-mutated glioma treatment

BRAF gliomas have garnered significant attention in research due to the lack of effective treatments and their notable incidence, constituting 3% of all gliomas. This underlines the importance of investigating this area and the impact that targeted therapies could hold. This review discusses the development of targeted therapies for these tumors, examining the effectiveness of first-generation BRAF inhibitors such as Vemurafenib, Dabrafenib and Encorafenib, while addressing the challenges posed by paradoxical ERK activation. The advent of pan-RAF inhibitors, notably Tovorafenib, offers a promising advance, demonstrating enhanced efficacy and better penetration of the blood-brain barrier, without the issue of paradoxical activation. Nevertheless, continued research is essential to refine therapeutic strategies for BRAF-mutated gliomas, given the evolving nature of targeted therapy development.

Diagnostic and theranostic opportunities in Neuro-oncology

Theranostics, the interlinking of diagnostic and therapeutic procedures, can be particularly valuable in neuro-oncology, addressing the challenges posed by the blood-brain and brain-tumor barriers. While it is traditionally associated with nuclear medicine, advances in MR imaging techniques have opened new theranostic frontiers. This review covers the present challenges in neuro-oncology and how these could be overcome utilizing radioligand-based molecular radiotherapy as well as how label-free theranostics employing methods such as chemical exchange saturation transfer (CEST) and MR spectroscopy could advance the field.

Systemic and local immunosuppression in glioblastoma and its prognostic significance

The effectiveness of tumor therapy, especially immunotherapy and oncolytic virotherapy, critically depends on the activity of the host immune cells. However, various local and systemic mechanisms of immunosuppression operate in cancer patients. Tumor-associated immunosuppression involves deregulation of many components of immunity, including a decrease in the number of T lymphocytes (lymphopenia), an increase in the levels or ratios of circulating and tumor-infiltrating immunosuppressive subsets [e.g., macrophages, microglia, myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs)], as well as defective functions of subsets of antigen-presenting, helper and effector immune cell due to altered expression of various soluble and membrane proteins (receptors, costimulatory molecules, and cytokines). In this review, we specifically focus on data from patients with glioblastoma/glioma before standard chemoradiotherapy. We discuss glioblastoma-related immunosuppression at baseline and the prognostic significance of different subsets of circulating and tumor-infiltrating immune cells (lymphocytes, CD4+ and CD8+ T cells, Tregs, natural killer (NK) cells, neutrophils, macrophages, MDSCs, and dendritic cells), including neutrophil-to-lymphocyte ratio (NLR), focus on the immune landscape and prognostic significance of isocitrate dehydrogenase (IDH)-mutant gliomas, proneural, classical and mesenchymal molecular subtypes, and highlight the features of immune surveillance in the brain. All attempts to identify a reliable prognostic immune marker in glioblastoma tissue have led to contradictory results, which can be explained, among other things, by the unprecedented level of spatial heterogeneity of the immune infiltrate and the significant phenotypic diversity and (dys)functional states of immune subpopulations. High NLR is one of the most repeatedly confirmed independent prognostic factors for shorter overall survival in patients with glioblastoma and carcinoma, and its combination with other markers of the immune response or systemic inflammation significantly improves the accuracy of prediction; however, more prospective studies are needed to confirm the prognostic/predictive power of NLR. We call for the inclusion of dynamic assessment of NLR and other blood inflammatory markers (e.g., absolute/total lymphocyte count, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, and systemic immune response index) in all neuro-oncology studies for rigorous evaluation and comparison of their individual and combinatorial prognostic/predictive significance and relative superiority.