The immune microenvironment in gliomas, particularly glioblastoma (GBM), plays a critical role in tumor progression and therapeutic resistance. Recent studies have identified novel targets such as YBX1 and YBX3, which are part of the CHK2-YBX1&YBX3 hub. Targeting this hub in combination with immune checkpoint blockade (ICB) has shown significant improvements in survival in preclinical glioma models, highlighting a potential strategy to overcome immune evasion (ref: Ali doi.org/10.1093/neuonc/). Furthermore, the role of SPP1+ macrophages has been elucidated, showing that their polarization by lactate enhances the progression of hypoxic adaptive tumor cells in the brain. Genetic deficiency of SPP1 in macrophages was found to delay tumor growth and improve responses to anti-PD-1 therapy, suggesting that macrophage-based microenvironment remodeling could be a viable therapeutic approach (ref: Zhang doi.org/10.1093/neuonc/). In contrast, a spatial transcriptomic analysis revealed a lack of response to PD-1 blockade in recurrent GBM, indicating that despite the promise of immune checkpoint inhibitors, they may not elicit measurable responses in this context (ref: Artzi doi.org/10.1007/s00401-025-02937-9/). This inconsistency emphasizes the complexity of the glioma immune microenvironment and the need for further exploration of prognostic markers associated with it (ref: Tokumura doi.org/10.1248/bpb.b25-00219/).

Spatial transcriptomics has emerged as a powerful tool for understanding the heterogeneity and microenvironmental interactions in gliomas. A study demonstrated that PD-1 blockade in recurrent GBM did not induce significant gene expression changes in tumor cells or tumor-associated macrophages (TAMs), suggesting that spatial transcriptomic approaches can reveal the lack of therapeutic efficacy in this setting (ref: Artzi doi.org/10.1007/s00401-025-02937-9/). Another study utilized spatially resolved chimeric analysis to uncover how glioblastoma exploits ATP from leading-edge astrocytes to fuel its infiltrative growth, revealing distinct molecular characteristics of infiltrating GBM cells (ref: Yang doi.org/10.1126/sciadv.adv5673/). Additionally, the development of a novel glioma-on-chip model that recapitulates the tumor biophysical microenvironment allows for better assessment of therapeutic responses, addressing the challenges faced in clinical settings (ref: Terrassoux doi.org/10.1002/smll.202505343/). Furthermore, advancements in spatial transcriptomic methodologies, such as the integration of low-cost tissue capture techniques with full-length mRNA profiling, are paving the way for broader applications in glioma research (ref: Zhou doi.org/10.1016/j.bios.2025.118018/).

Multi-omics approaches are increasingly being utilized to stratify glioma subtypes and understand their complex biology. One study integrated multi-omics data, including genomics and MRI-based radiomics, to classify gliomas into metabolic and immune subtypes, identifying key prognostic factors among 1,720 patients (ref: Li doi.org/10.1200/PO-24-00928/). Another investigation revealed four distinct clusters in IDH-mutant astrocytomas through spatiotemporal multi-omics analysis, highlighting the immune/mesenchymal-enriched subtype as associated with poorer prognosis (ref: Tang doi.org/10.1016/j.ccell.2025.08.006/). This underscores the importance of understanding intertumoral heterogeneity in gliomas, as it complicates treatment strategies and outcomes. Additionally, a novel deep learning approach was developed to integrate anatomical and genomic data for comprehensive glioma profiling, enhancing the precision of clinical management (ref: Abdusalomov doi.org/10.3390/bioengineering12090979/). These multi-omics strategies are crucial for unraveling the complexities of glioma biology and improving therapeutic interventions.

Tumor heterogeneity is a hallmark of glioblastoma, contributing to its aggressive nature and therapeutic resistance. Recent research has highlighted the significant intratumoral heterogeneity within GBM, with studies employing integrative single-cell RNA sequencing to reveal distinct transcriptomic profiles between tumor center and periphery regions. Notably, NUCB2 was identified as a key orchestrator of tumor aggression and immune dysfunction, being significantly upregulated in neural progenitor cell-like tumor cells located in the tumor center (ref: Huang doi.org/10.1111/jcmm.70814/). Furthermore, an optimized tissue sampling scheme guided by MRI features has been proposed to better capture this heterogeneity, addressing the challenges of total resection in complex anatomical locations (ref: Wang doi.org/10.1038/s41598-025-17539-4/). The identification of immune-hot subtypes in IDH-mutant astrocytomas further complicates treatment, as these subtypes are associated with worse prognosis, emphasizing the need for tailored therapeutic strategies (ref: Tang doi.org/10.1016/j.ccell.2025.08.006/). This intricate interplay of tumor heterogeneity and immune response underscores the necessity for innovative approaches in glioma research and treatment.

Therapeutic resistance remains a significant barrier in the treatment of gliomas, particularly glioblastoma. Research has identified the CHK2-YBX1&YBX3 hub as a critical target for enhancing immune checkpoint blockade responses, with combination therapies showing improved survival in preclinical models (ref: Ali doi.org/10.1093/neuonc/). However, the lack of response to PD-1 blockade in recurrent GBM, as revealed through spatial transcriptomic analysis, indicates that current immunotherapies may not be effective in all glioma contexts (ref: Artzi doi.org/10.1007/s00401-025-02937-9/). Additionally, the development of a glioma-on-chip model that incorporates the tumor biophysical microenvironment aims to address the challenges of therapeutic resistance by providing a more accurate preclinical evaluation of treatment efficacy (ref: Terrassoux doi.org/10.1002/smll.202505343/). These findings highlight the complexity of glioma biology and the need for innovative strategies to overcome therapeutic resistance.

Innovative preclinical models are essential for advancing glioma research and improving therapeutic outcomes. The development of a glioma-on-chip model that mimics the biophysical tumor microenvironment has shown promise in assessing the heterogeneity of response to therapies, addressing the limitations of traditional models (ref: Terrassoux doi.org/10.1002/smll.202505343/). Additionally, advancements in spatial transcriptomics, particularly the integration of cost-effective tissue capture techniques with full-length mRNA profiling, are enhancing the ability to study glioma biology in a spatial context (ref: Zhou doi.org/10.1016/j.bios.2025.118018/). These innovative approaches are crucial for understanding the complex interactions within the tumor microenvironment and for evaluating the efficacy of novel therapeutic strategies. As glioma remains a challenging malignancy, the continued development of sophisticated preclinical models will be vital for translating findings into clinical practice.