Astrocytes regulate key aspects of the neural microenvironment that can be co-opted by cancer to support tumor growth and invasion. Secreted protein acidic and rich in cysteine-like 1 (SPARCL1) is a matricellular glycoprotein expressed by astrocytes and stromal cells, whose expression varies across cancer types. While SPARCL1 is downregulated in many peripheral cancers, reports of its expression in gliomas, specifically glioblastoma (GBM), are inconsistent. The biological context underlying these divergent findings, and the role of SPARCL1 in GBM malignancy, remains unclear. Publicly available transcriptomic datasets from the Ivy Glioblastoma Atlas Project (Ivy GAP), GlioVis, and TCGA were analyzed to evaluate SPARCL1 expression across GBM cohorts. Spatially resolved gene expression data from Ivy GAP were used to assess SPARCL1 expression from defined tumor regions. Microarray and RNA sequencing datasets from GlioVis and TCGA, respectively, were used to assess SPARCL1 expression across whole-tumor samples. Spatial transcriptomics from Ivy GAP show SPARCL1 expression was upregulated along the leading edge and in infiltrating tumor regions. Microarray datasets showed greater SPARCL1 expression in tumors of astrocyte lineage as opposed to oligodendrocyte lineage. Bulk RNA sequencing showed high SPARCL1 expression in low-grade gliomas, which is consistent with astrocytic lineage, IDH mutation, and spatial averaging effects that might obscure regional associations. These findings demonstrate that SPARCL1 expression in GBM is shaped by tumor architecture, molecular classification, and microenvironment interactions. Enrichment of SPARCl1 at invasive tumor margins is consistent with prior studies linking SPARCL1 to neuron–glioma synapse formation and angiogenesis.

Glioblastoma (GBM) remains the most aggressive primary malignant brain tumor in adults, with poor survival largely driven by diffuse cellular infiltration, profound heterogeneity, and near-universal recurrence following standard therapy. Although maximizing the extent of resection is a key determinant of patient outcome, current clinical imaging modalities lack the spatial resolution necessary to detect microscopic tumor invasion and therapy-resistant cell populations. Emerging in vivo imaging technologies capable of cellular and near-single-cell resolution have therefore become a major focus in preclinical neuro-oncology research, with growing relevance for surgical guidance, treatment adaptation, and translational discovery. This review evaluates multiple optical imaging modalities, including multi-photon microscopy, near-infrared II fluorescence imaging, bioluminescence imaging, photoacoustic imaging, optical coherence tomography, confocal laser endomicroscopy, Raman spectroscopy, autofluorescence microscopy, and fluorescence macroscopy with a focus on their ability to detect residual GBM cells. Despite significant advances, these approaches remain constrained by limitations in molecular target availability, probe delivery across the blood–brain barrier, and signal variability within heterogeneous tumor regions. The biological complexity of GBM further challenges detection, as residual tumor cells are spatially dispersed and phenotypically diverse, limiting the effectiveness of single-marker or single-modality strategies. Together, these findings highlight the need for integrated, biologically informed imaging approaches to improve detection of residual disease and guide surgical decision making.

Background: The gliovascular unit forms the structural and functional basis of the glymphatic system, which facilitates cerebrospinal fluid–interstitial fluid exchange to maintain brain homeostasis. Although disruption of individual astrocytic, vascular, and extracellular matrix (ECM) components has been described in diffuse glioma, it remains unknown whether these alterations represent isolated pathological events or a coordinated remodeling program across glioma grades. Methods: Bulk transcriptomic signatures representing eight components of the gliovascular unit were quantified in The Cancer Genome Atlas (TCGA) and independently validated in the Chinese Glioma Genome Atlas (CGGA). Pathway activity was compared across WHO grades and IDH status, followed by gene-level, network, and grade-specific analyses to characterize the grade-associated patterns of gliovascular remodeling. Laser-capture microdissected RNA sequencing data from the Ivy Glioblastoma Atlas Project was subsequently used to define the anatomical distribution of representative gliovascular markers within glioblastoma (GBM). Finally, multivariable Cox proportional hazards regression was performed to evaluate associations between gliovascular pathway activity and overall survival. Results: Diffuse glioma was characterized by coordinated grade-associated remodeling of the gliovascular unit across independent patient cohorts. Lower-grade tumors were characterized by greater expression of homeostatic astrocyte- and endfoot-associated transcriptional programs, whereas higher-grade tumors showed increasing inflammatory, ECM-remodeling, basement membrane-remodeling, and angiogenic signatures. Regional analysis demonstrated corresponding anatomical compartmentalization of these transcriptional features within GBM. Despite closely reflecting glioma grade, gliovascular remodeling was not independently associated with overall survival. Conclusions: Coordinated grade-associated remodeling of the gliovascular unit provides a unifying framework linking astrocyte-associated, inflammatory, and vascular remodeling transcriptional programs across glioma grades. This systems-level model establishes a foundation for future mechanistic studies examining how disruption of gliovascular homeostasis contributes to glymphatic dysfunction, sleep disturbance, and disease progression.

Background: Interleukin-13 Receptor alpha 2 (IL13Rα2) is an attractive therapeutic target for glioblastoma because of its limited expression in normal brain tissue and overexpression in many tumors. However, the spatial heterogeneity of glioblastoma and limitations of conventional culture models may contribute to the inconsistent translation of IL13Rα2-targeted therapies. This study evaluated IL13Rα2 expression across multiple in vitro glioblastoma models and spatially resolved patient tumors. Methods: IL13Rα2 mRNA and protein expression levels were measured across two-dimensional and three-dimensional glioblastoma culture models, including commercial cell lines (U87MG and T98G), and patient-derived neurospheres. Spatial expression patterns were also characterized using Ivy Glioblastoma Atlas Project. Results: IL13Rα2 expression was highly dependent on glioblastoma model system, with substantial variability observed across commercial cell lines, patient-derived neurospheres, and three-dimensional cultures. Spatial transcriptomic analysis identified significant enrichment of IL13Rα2 expression within perinecrotic tumor regions relative to the leading edge, infiltrating tumor, and cellular tumor. Conclusions: The heterogeneous nature of glioblastoma highlights the limitations of current in vitro modeling and the importance of considering spatial expression patterns when developing IL13Rα2-targeted therapies.