Citations

2038 Background: Glioblastoma (GBM) is the most common malignant brain tumor with poor clinical prognosis. Management of GBM is hampered by the lack of an accurate test that can be used for differential diagnosis of tumor progression from inflammatory pseudoprogression. Plasma extracellular vesicles (EVs) has been shown to be a promising source for biomarker identification. In this project, we aimed to identify GBM plasma EV markers that could serve as the basis of a liquid biopsy. Methods: Sample preparation, assay controls and instrument calibration were performed following MIFlowCyt-EV guideline. Plasma samples were subjected to 2-step centrifugations to remove cell debris and platelets. 10ul of plasma sample was diluted with 90ul filtered PBS, then stained for EV surface markers including CD9, CD31, CD45, CD41a and CD11b, as well as actin phalloidin. Stained plasma samples were purified using IZON qEV1/70nm column, then EV fractions were analyzed using full spectrum Cytek Aurora flow cytometer. Clustering analysis was performed on EV events (CD9 +/ actin phalloidin -) using t-SNE and FlowSOM extensions from FlowJo plugins. Results: Compared to normal donors, GBM plasma EVs were bigger in size (higher SSC value) and expressed higher levels of CD9, CD31, CD45 and CD11b while ND plasma EVs had higher CD41a expression. t-SNE and FlowSOM analysis demonstrated that GBM plasma EVs had a unique surface marker expression profile compared to ND EVs. It also showed 10 EV sub-populations that differed in size as well as various surface marker expression levels. Four of these subpopulations were enriched in GBM EVs, while three of these were enriched in ND EVs. Conclusions: This multiparametric analysis revealed that GBM plasma EVs had a unique surface marker expression profile compared to ND plasma EVs. Further separation and molecular profiling analysis based on each sub population could reveal EV biomarkers that are unique to each sample population.

Abstract Glioblastoma (GBM) is a rapidly fatal malignancy typically treated with radiation and temozolomide (TMZ), an alkylating chemotherapeutic. These cytotoxic therapies cause oxidative stress and DNA damage, yielding a senescent-like state of replicative arrest in surviving tumor cells. Unfortunately, recurrence is inevitable and may be driven by surviving tumor cells eventually escaping senescence. A growing number of so-called “senolytic” drugs have been recently identified that are defined by their ability to selectively eliminate senescent cells. A growing inventory of senolytic drugs is under consideration for several diseases associated with aging, inflammation, DNA damage, as well as cancer. Ablation of senescent tumor cells after radiation and chemotherapy could help mitigate recurrence by decreasing the burden of residual tumor cells at risk of recurrence. This strategy has not been previously explored for GBM. We evaluated a panel of 10 previously described senolytic drugs to determine whether any could exhibit selective activity against human GBM persisting after exposure to radiation or TMZ. Three of the 10 drugs have known activity against BCL-XL and preferentially induced apoptosis in radiated or TMZ-treated glioma. This senolytic activity was observed in 12 of 12 human GBM cell lines. Efficacy could not be replicated with BCL-2 inhibition or senolytic agents acting against other putative senolytic targets. Knockdown of BCL-XL decreased survival of radiated GBM cells, whereas knockdown of BCL-2 or BCL-W yielded no senolytic effect. Implications: These findings imply that molecularly heterogeneous GBM lines share selective senescence-induced BCL-XL dependency increase the significance and translational relevance of the senolytic therapy for latent glioma.

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.

OBJECTIVE Although it has been shown that surgery for glioblastoma (GBM) at high-volume facilities (HVFs) may be associated with better postoperative outcomes, the use of such hospitals may not be equally distributed. The authors aimed to evaluate racial and socioeconomic differences in access to surgery for GBM at high-volume Commission on Cancer (CoC)–accredited hospitals. METHODS The National Cancer Database was queried for patients with GBM that was newly diagnosed between 2004 and 2015. Patients who received no surgical intervention or those who received surgical intervention at a site other than the reporting facility were excluded. Annual surgical case volume was calculated for each hospital, with volume ≥ 90th percentile defined as an HVF. Multivariable logistic regression was performed to identify patient-level predictors for undergoing surgery at an HVF. Furthermore, multiple subgroup analyses were performed to determine the adjusted odds ratio of the likelihood of undergoing surgery at an HVF in 2016 as compared to 2004 for each patient subpopulation (by age, race, sex, educational group, etc.). RESULTS A total of 51,859 patients were included, with 10.7% (n = 5562) undergoing surgery at an HVF. On multivariable analysis, Hispanic White patients (OR 0.58, 95% CI 0.49–0.69, p < 0.001) were found to have significantly lower odds of undergoing surgery at an HVF (reference = non-Hispanic White). In addition, patients from a rural residential location (OR 0.55, 95% CI 0.41–0.72, p < 0.001; reference = metropolitan); patients with nonprivate insurance status (Medicare [OR 0.78, 95% CI 0.71–0.86, p < 0.001], Medicaid [OR 0.68, 95% CI 0.60–0.78, p < 0001], other government insurance [OR 0.68, 95% CI 0.52–0.86, p = 0.002], or who were uninsured [OR 0.61, 95% CI 0.51–0.72, p < 0.001]); and lower-income patients ($50,354–$63,332 [OR 0.68, 95% CI 0.63–0.74, p < 0.001], $40,227–$50,353 [OR 0.84, 95% CI 0.76–0.92, p < 0.001]; reference = ≥ $63,333) were also found to be significantly associated with a lower likelihood of surgery at an HVF. Subgroup analyses revealed that elderly patients (age ≥ 65 years), both male and female patients and non-Hispanic White patients, and those with private insurance, Medicare, metropolitan residential location, median zip code–level household income in the first and second quartiles, and educational attainment in the first and third quartiles had increased odds of undergoing surgery at an HVF in 2016 compared to 2004 (all p ≤ 0.05). On the other hand, patients with other governmental insurance, patients with a rural residence, and those from a non-White racial category did not show a significant difference in odds of surgery at an HVF over time (all p > 0.05). CONCLUSIONS The present analysis from the National Cancer Database revealed significant disparities in access to surgery at an HVF for GBM within the United States. Furthermore, there was evidence that these racial and socioeconomic disparities may have widened between 2004 and 2016. The findings should assist health policy makers in the development of strategies for improving access to HVFs for racially and socioeconomically disadvantaged populations.

Abstract INTRODUCTION Dendritic cells (DCs) are potent antigen presenting cells that can be exploited to initiate an adaptive anti-tumoral immune response. DC vaccine clinical trials for primary glioblastoma (GBM) have reported prolonged progression-free survival without any impact on overall survival (OS). We report a radiomics approach that identifies a subpopulation of patients with prolonged OS in clinical trial MC1272. METHODS Twenty adults with primary GBM undergoing standard-of-care therapy were enrolled in MC1272. Autologous DCs were pulsed with allogenic GBM cell lines to generate vaccines that were administered for up to twelve cycles. Standard brain imaging was obtained at the initiation of treatment and two months afterwards. An independent cohort of image-localized biopsies underwent RNA sequencing followed by cellular deconvolution to estimate T cell abundance. A machine learning model was trained to predict intratumoral T cell abundance from imaging features, and the model was applied to MC1272 patient imaging. RESULTS Voxelwise predictions of T cell abundance were generated for each patient’s pre- and post-treatment images. The difference in total intratumoral T cell abundance between imaging timepoints classified patients into increasing or decreasing T cell groups. Patients whose T cells increased had longer OS (median, 21 months) than those whose T cells decreased (median, 10 months; p=0.0035). The significance remained in a Cox proportional hazards analysis that adjusted for patient age and sex (p=0.011). CONCLUSIONS A spatially-resolved radiomics model detected that an intratumoral T cell influx after DC vaccine therapy was associated with prolonged OS. The “post-treatment” imaging in this study was obtained a mere two months after DC vaccine initiation, suggesting that our radiomics model can provide an early indication of treatment responsiveness and prognosis in these patients.

Abstract Glioblastoma (GBM) is the most common malignant brain tumor in adults, responsible for approximately 225,000 deaths per year. Despite pre-clinical successes, therapeutic interventions have failed to extend patient survival by more than a few months. Anti-PD-1 checkpoint inhibition monotherapy has had efficacy against some tumor types but not GBM. The aim of this study was to determine whether supplementing anti-PD-1 checkpoint blockade with an engineered extended half-life IL-2 could improve outcomes in a preclinical model of disease. Our enhanced checkpoint blockade (ECB) strategy reliably cures approximately50% of C57BL/6 mice bearing orthotopic GL261 gliomas and extended median survival even in the mice that eventually succumbed. This therapy generates robust immunologic responses, features of which include secondary lymphoid organ enlargement and increased activation status of both CD4 and CD8 T cells. Further, many of the characteristics of brain-tumor mediated peripheral immunosuppression, including MHC class II downregulation on APCs, are prevented by ECB combination therapy. This immunity is durable, with long-term ECB survivors able to resist GL261 rechallenge. Notably, ECB’s efficacy is independent of host MHC class I restricted antigen presentation, being equally efficacious in MHC class I and CD8 T cell deficient mice. Conversely, ECB combination therapy is reliant on CD4 T cells and their depletion abrogates the therapy’s survival benefit. Our data shows ECB combination immunotherapy to be efficacious against the GL261 glioma model through an MHC class I independent mechanism, enhancing its off-the-shelf translational appeal relative to strategies requiring extensive knowledge of tumor-specific antigens.

Abstract Glioblastoma (GBM) is the most common and deadly primary brain tumor. Novel therapeutic strategies are urgently needed to improve outcomes, but a number of disease-specific barriers pose challenges to innovation. Tumor-mediated immunosuppression is one such hurdle, and a growing body of evidence suggests that GBM-derived extracellular vesicles (EVs) play an important role in host immunosuppression. GBM-derived EVs have been shown to induce the formation of immunosuppressive monocytes, including myeloid-derived suppressor cells. Work by our group and others has increasingly shown that these immunosuppressive monocytes are a heterogenous group, and that many constellations of surface markers are inadequate to capture the changes wrought by EVs. In order to better understand the effects of GBM-EVs on monocytes, we conducted RNA-seq analysis on monocytes collected from four healthy donors treated with GBM-derived EVs harvested by ultracentrifugation from the patient-derived BT116 cell line. Following 72h of EV conditioning, total RNA was harvested from treated monocytes and untreated controls. RNA-seq was performed using the Illumina HiSeq4000 platform with paired end index reads. Analysis was performed using RNA STAR and the hg19 ENCODE reference sequence. Differential expression analysis was performed using DESeq2. Genes with a false-discovery rate (FDR)-corrected P value &lt; 0.05 and a log2 fold-change value of &gt;|1| were considered significantly different between groups. Pathway analysis was performed using ClueGO in Cytoscape (GO term fusion on, p&lt; 0.05). Unsupervised clustering analysis of the top 500 most differentially-expressed genes demonstrated grouping of BT116 EV-treated monocytes together versus untreated monocytes. Pathway analysis upregulated genes in pathways important for heparan sulfate proteoglycan synthesis and cholesterol synthesis, which could potentially point to positive regulation of EV uptake. Downregulated pathways included regulation of T cell differentiation and chemoattractant activity, underscoring the induction of a potentially immunosuppressive phenotype by GBM-derived EVs.

Abstract Choosing effective chemotherapies for intravenous delivery to brain tumors is challenging, especially given the protective nature of the blood brain barrier (BBB). Connecting drug distribution to non-invasive, pre-surgical magnetic resonance imaging (MRI) could allow for predictive insight into drug distribution. In a previous study, we found that T2Gd images were predictive of a low BBB penetrant drug (Cefazolin), and FLAIR images were predictive of a high BBB penetrant drug (Levetiracetam). While these results are promising, we further seek to explore how advanced MRI sequences might inform image-based models of drug distribution. Prior to surgery, we acquired advanced dynamic contrast enhanced (DCE) and diffusion weighted imaging (DWI) MRI sequences for eight brain tumor patients (7 gliomas and 1 metastatic adenocarcinoma) in addition to the anatomic MRIs. All resulting quantitative maps and acquired images were co-registered. Prior to incision, patients received injections of cefazolin and levetiracetam. Next, multiple blood samples and biopsies were collected during surgery. Biopsies and plasma samples were analyzed for drug concentration using liquid chromatography mass spectrometry (LCMS), and biopsy drug levels were reported as Brain-Plasma Ratio (BPR). Mean image intensity was extracted from a 15x15 voxel window surrounding the biopsy location. We performed linear regression analyses to determine which combination of images were predictive of BPR. We found that considering quantitative imaging improved our initial ability to predict BPR for both drugs. For cefazolin, the third diffusion tensor eigenvalue (L3) map was significantly correlated with BPR (p&lt; 0.001, R2= 0.36). For levetiracetam, the best model consisted of a combination of images and maps with the L3 map and the isotropic diffusion map (P) being the most influential (p= 0.001, R2= 0.63). Advanced MRI-based modeling is a promising tool for forecasting drug distribution in brain tumors and could be of great importance for understanding efficacy and selecting therapeutic strategies.