Aibaidula, Abudumijiti

Glioblastoma (GBM), the most common primary malignant brain tumor in adults, has a median survival of 14–15 months despite aggressive treatment. Monitoring relies on MRI, but differentiating tumor progression from pseudo-progression or radiation necrosis remains difficult. Plasma extracellular vesicles (EVs) are emerging as promising non-invasive biomarkers due to their molecular cargos and accessibility. This review evaluates studies that specifically isolated plasma EVs for molecular profiling in GBM diagnosis and monitoring. Biomarkers (miRNA, RNA, DNA, proteins), EV characterization methods, and advancements in enriching tumor-derived EV subpopulations and assessing their diagnostic and prognostic potential are highlighted. Plasma EVs carry diverse cargos, including miRNAs (e.g., miR-21, miR-15b-3p), mRNAs (e.g., EGFRvIII), circRNAs, and proteins (e.g., CD44, GFAP). Composite molecular signatures have achieved sensitivities of 87–100% and specificities of 73–100% for GBM diagnosis. Tumor-derived EVs, enriched using techniques like SEC-CD44 immunoprecipitation, microfluidic platforms, or 5-ALA-induced PpIX fluorescence, enhance biomarker detection. Non-tumor-derived EVs may also reflect GBM’s systemic effects. Challenges include EV heterogeneity, non-EV contamination, and variable biomarker expression across studies. Plasma-EV-based liquid biopsies offer significant potential for GBM monitoring, with advanced enrichment methods improving tumor-specific biomarker detection. Standardizing isolation protocols and validating biomarkers in larger cohorts are critical for clinical translation.

Abstract INTRODUCTION Glioblastoma (GBM) is the most common primary malignant brain tumor and has a poor clinical outcome. Extracellular vesicles (EVs) are promising biomarkers to assist the differential diagnosis between pseudoprogression and true tumor progression. We aimed to identify non-tumor plasma EV markers that predicted GBM occurrence using trained multiple tree-based machine learning algorithms. METHODS We included plasma samples of 40 GBM and 40 non-GBM (20 brain metastasis, 20 normal donors). Spectral flow cytometry was performed to determine plasma EV subpopulation frequency based on CD9,CD81,CD63,CD11b,CD45,CD31, and CD41a expression. Multiparametric t-SNE and FlowSOM analysis clustered plasma EVs based on these markers. Decision trees and random forest classifiers were trained and tested to predict the disease status (GBM vs non-GBM) based on plasma EV subpopulations. RESULTS Compared to non-GBM, GBM had increased frequency of CD9+ EVs (64.52% vs 40.69%, p< 0.0001), CD9+CD63-CD81- EVs (54.45% vs 37.26%, p< 0.0001) and myeloid-derived EVs (CD9+CD11b+ EVs, 20.77% vs 12.48%, p = 0.0241). In the decision tree analysis, low frequency of CD9+ EVs was found in 44% of all cases and represented a chance of 75% to be classified as non-GBM cases. An algorithm based on random forest analysis (n = 500 trees) using these markers had a sensitivity of 85.71% and specificity of 77.8% with an overall accuracy of 81.25% for identifying GBM. The frequencies of CD9+, CD9+CD63-CD81-, and CD9+CD63+CD81+ were the most critical factors in predicting GBM diagnosis. FlowSOM analysis identified 20 plasma EV subpopulations but had a lower accuracy (62.5%) when combined with our machine learning algorithm. CONCLUSIONS Non-tumor plasma EV expression profile combined with tree-based machine learning demonstrated high accuracy in predicting patient disease status. CD9+ EV frequency was one of the most promising biomarkers to assist in this diagnosis. We will continue to test our established algorithm and further validate our findings in a larger cohort.

Abstract Cerebral malaria is the deadliest complication that can arise from Plasmodium infection. CD8 T-cell engagement of brain vasculature is a putative mechanism of neuropathology in cerebral malaria. To define contributions of brain endothelial cell major histocompatibility complex (MHC) class I antigen-presentation to CD8 T cells in establishing cerebral malaria pathology, we developed novel H-2Kb LoxP and H-2Db LoxP mice crossed with Cdh5-Cre mice to achieve targeted deletion of discrete class I molecules, specifically from brain endothelium. This strategy allowed us to avoid off-target effects on iron homeostasis and class I-like molecules, which are known to perturb Plasmodium infection. This is the first endothelial-specific ablation of individual class-I molecules enabling us to interrogate these molecular interactions. In these studies, we interrogated human and mouse transcriptomics data to compare antigen presentation capacity during cerebral malaria. Using the Plasmodium berghei ANKA model of experimental cerebral malaria (ECM), we observed that H-2Kb and H-2Db class I molecules regulate distinct patterns of disease onset, CD8 T-cell infiltration, targeted cell death and regional blood–brain barrier disruption. Strikingly, ablation of either molecule from brain endothelial cells resulted in reduced CD8 T-cell activation, attenuated T-cell interaction with brain vasculature, lessened targeted cell death, preserved blood–brain barrier integrity and prevention of ECM and the death of the animal. We were able to show that these events were brain-specific through the use of parabiosis and created the novel technique of dual small animal MRI to simultaneously scan conjoined parabionts during infection. These data demonstrate that interactions of CD8 T cells with discrete MHC class I molecules on brain endothelium differentially regulate development of ECM neuropathology. Therefore, targeting MHC class I interactions therapeutically may hold potential for treatment of cases of severe malaria.

Abstract Background Glioblastoma (GBM) is the most common malignant brain tumor and has a poor prognosis. Imaging findings at diagnosis and in response to treatment are nonspecific. Developing noninvasive assays to augment imaging would be helpful. Plasma extracellular vesicles (EVs) are a promising biomarker source for this. Here, we develop spectral flow cytometry techniques that demonstrate differences in bulk plasma EV phenotype between GBM patients and normal donors that could serve as the basis of a liquid biopsy. Methods Plasma EVs were stained for EV-associated tetraspanins (CD9/CD63/CD81), markers indicating cell of origin (CD11b/CD31/CD41a/CD45), and actin/phalloidin (to exclude cell debris). EVs were analyzed using spectral flow cytometry. Multiparametric analysis using t-distributed stochastic neighbor embedding (t-SNE) and self-organizing maps on flow cytometry data (FlowSOM) was performed comparing GBM and normal donor (ND) plasma EVs. Results Size exclusion chromatography plus spectral-based flow cytometer threshold settings enriched plasma EVs while minimizing background noise. GBM patients had increased CD9+, CD63+, CD81+, and myeloid-derived (CD11b+) EVs. Multiparametric analysis demonstrated distinct surface marker expression profiles in GBM plasma EVs compared to ND EVs. Fifteen plasma EV sub-populations differing in size and surface marker expression were identified, six enriched in GBM patients and two in normal donors. Conclusions Multiparametric analysis demonstrates that GBM patients have a distinct nonneoplastic plasma EV phenotype compared to ND. This simple rapid analysis can be performed without purifying tumor EVs and may serve as the basis of a liquid biopsy.

OBJECTIVE Glioblastoma (GBM) is a devasting primary brain tumor with less than a 5% 5-year survival. Treatment response assessment can be challenging because of inflammatory pseudoprogression that mimics true tumor progression clinically and on imaging. Developing additional noninvasive assays is critical. In this article, the authors review various biomarkers that could be used in developing liquid biopsies for GBM, along with strengths, limitations, and future applications. In addition, they present a potential liquid biopsy design based on the use of an extracellular vesicle–based liquid biopsy targeting nonneoplastic extracellular vesicles. METHODS The authors conducted a current literature review of liquid biopsy in GBM by searching the PubMed, Scopus, and Google Scholar databases. Articles were assessed for type of biomarker, isolation methodology, analytical techniques, and clinical relevance. RESULTS Recent work has shown that liquid biopsies of plasma, blood, and/or CSF hold promise as noninvasive clinical tools that can be used to diagnose recurrence, assess treatment response, and predict patient outcomes in GBM. Liquid biopsy in GBM has focused primarily on extracellular vesicles, cell-free tumor nucleic acids, and whole-cell isolates as focal biomarkers. GBM tumor signatures have been generated via analysis of tumor gene mutations, unique RNA expression, and metabolic and proteomic alterations. Liquid biopsies capture tumor heterogeneity, identifying alterations in GBM tumors that may be undetectable via surgical biopsy specimens. Finally, biomarker burden can be used to assess treatment response and recurrence in GBM. CONCLUSIONS Liquid biopsy offers a promising avenue for monitoring treatment response and recurrence in GBM without invasive procedures. Although additional steps must be taken to bring liquid biopsy into the clinic, proof-of-principle studies and isolation methodologies are promising. Ultimately, CSF and/or plasma-based liquid biopsy is likely to be a powerful tool in the neurosurgeon’s arsenal in the near future for the treatment and management of GBM patients.

Abstract Background Glioblastoma (GBM), the most common primary brain tumor, has a median survival of 15–16 months. Immunotherapy is promising but GBM-mediated immunosuppression remains a barrier. GBMs express the interferon-gamma (IFN-γ)-responsive immunosuppressive molecules programmed cell death ligand 1 (PD-L1) and indoleamine 2,3-dioxygenase 1 (IDO1). Extracellular vesicles (EVs) have also been implicated in GBM-mediated immunosuppression, in part through PD-L1. We therefore sought to determine if GBM IFN-γ exposure increased GBM EV-mediated immunosuppression and mechanisms underlying this. Methods Human GBM-derived cells were cultured in the presence/absence of IFN-γ. EVs were harvested. PD-L1, IDO1, and EV-associated protein expression was assessed. GBM EVs (+/−IFN-γ) were cultured with healthy donor monocytes. Immunosuppressive myeloid-derived suppressor cell (MDSC) and nonclassical monocyte (NCM) frequency was determined. Impact of GBM (+/−IFN-γ) EV-treated monocytes on CD3/CD28-mediated T cell proliferation was assessed. The impact of PD-L1 and IDO1 knockdown in GBM EVs in this system was evaluated. Results IFN-γ exposure increased PD-L1 and IDO1 expression in GBM cells and EVs without altering EV size or frequency. IFN-γ-exposed GBM EVs induced more MDSC and NCM differentiation in monocytes and these monocytes caused more T cell inhibition than IFN-γ-naive GBM EVs. PD-L1 and/or IDO1 knockdown in GBM cells abrogated the immunosuppressive effects of IFN-γ-exposed GBM EVs on monocytes. Conclusions IFN-γ exposure such as might occur during an antitumor immune response results in superinduction of GBM EVs’ baseline immunosuppressive effects on monocytes. These effects are mediated by increased PD-L1 and IDO1 expression in GBM EVs. These data highlight mechanisms of GBM EV-mediated immunosuppression and identify therapeutic targets (PD-L1, IDO1) to reverse these effects.

Abstract Patients with glioblastoma (GBM) have a median survival of 15 months despite aggressive treatment. Immunosuppressive monocytes are heavily infiltrated in these tumors and in patients’ circulation. Treatment-related pseudo-progression confounds outcome assessment by MRI. Thus, there is a need for additional non-invasive methods to assess treatment response. Extracellular vesicles (EVs) contain tumor-specific microRNA (miRNA) cargo that could serve as a liquid biopsy to distinguish true progression from treatment-related pseudo-progression. We had found significant differences in plasma EVs molecular profile (i.e. miRNA signatures) between GBM patients and healthy donors. Our overall hypothesis is that these differences reflect the EVs cell of origin. Our goal in this project was to develop a fluorescent staining paradigm by flow cytometry to distinguish EVs from different cells in vitro and determine differences in EV miRNA expression profile between GBM and monocytic cell-derived EVs. Gleolan (5-ALA) is an FDA-approved orally available agent for fluorescence-guided resection of GBM tumors. It is metabolized to protoporphyrin IX (PpIX) in GBM cells but not in non-neoplastic cells and has been reported to aid in the detection of GBM-derived EVs by flow cytometry. However, distinguishing between GBM-derived EVs and EVs from other cells of origin has not been described. We co-cultured human GBM cells (dBT114 or dBT116) and CD14+ monocytes for 72 hours in the presence or absence of 5-ALA. EVs were isolated by ultracentrifugation and stained for CD11b (myeloid cell marker). ImageStream Imaging Flow Cytometry was performed showing clear differentiation between PpIX+ EVs from GBM cells and CD11b+ EVs from monocytes. Interestingly, a small number of double-positive EVs (presumably representing monocyte-derived EVs that had taken up PpIX after phagocytizing GBM cells) were also present. Taken together, we were able to optimize a technique to distinguish EVs originating from GBM and monocytes for further characterization by short non-coding RNA sequencing.