A Patient-Derived Glioblastoma Organoid Model and Biobank Recapitulates Inter- and Intra-tumoral Heterogeneity.

Glioblastomas exhibit vast inter- and intra-tumoral heterogeneity, complicating the development of effective therapeutic strategies. Current in vitro models are limited in preserving the cellular and mutational diversity of parental tumors and require a prolonged generation time. Here, we report methods for generating and biobanking patient-derived glioblastoma organoids (GBOs) that recapitulate the histological features, cellular diversity, gene expression, and mutational profiles of their corresponding parental tumors. GBOs can be generated quickly with high reliability and exhibit rapid, aggressive infiltration when transplanted into adult rodent brains. We further demonstrate the utility of GBOs to test personalized therapies by correlating GBO mutational profiles with responses to specific drugs and by modeling chimeric antigen receptor T cell immunotherapy. Our studies show that GBOs maintain many key features of glioblastomas and can be rapidly deployed to investigate patient-specific treatment strategies. Additionally, our live biobank establishes a rich resource for basic and translational glioblastoma research.

Validation of multiparametric MRI based prediction model in identification of pseudoprogression in glioblastomas.

BACKGROUND: Accurate differentiation of pseudoprogression (PsP) from tumor progression (TP) in glioblastomas (GBMs) is essential for appropriate clinical management and prognostication of these patients. In the present study, we sought to validate the findings of our previously developed multiparametric MRI model in a new cohort of GBM patients treated with standard therapy in identifying PsP cases. METHODS: Fifty-six GBM patients demonstrating enhancing lesions within 6 months after completion of concurrent chemo-radiotherapy (CCRT) underwent anatomical imaging, diffusion and perfusion MRI on a 3 T magnet. Subsequently, patients were classified as TP + mixed tumor (n = 37) and PsP (n = 19). When tumor specimens were available from repeat surgery, histopathologic findings were used to identify TP + mixed tumor (> 25% malignant features; n = 34) or PsP (< 25% malignant features; n = 16). In case of non-availability of tumor specimens, ≥ 2 consecutive conventional MRIs using mRANO criteria were used to determine TP + mixed tumor (n = 3) or PsP (n = 3). The multiparametric MRI-based prediction model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI derived parameters from contrast enhancing regions. In the next step, PP values were used to characterize each lesion as PsP or TP+ mixed tumor. The lesions were considered as PsP if the PP value was < 50% and TP+ mixed tumor if the PP value was ≥ 50%. Pearson test was used to determine the concordance correlation coefficient between PP values and histopathology/mRANO criteria. The area under ROC curve (AUC) was used as a quantitative measure for assessing the discriminatory accuracy of the prediction model in identifying PsP and TP+ mixed tumor. RESULTS: Multiparametric MRI model correctly predicted PsP in 95% (18/19) and TP+ mixed tumor in 57% of cases (21/37) with an overall concordance rate of 70% (39/56) with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.56; p < 0.001). The ROC analyses revealed an accuracy of 75.7% in distinguishing PsP from TP+ mixed tumor. Leave-one-out cross-validation test revealed that 73.2% of cases were correctly classified as PsP and TP + mixed tumor. CONCLUSIONS: Our multiparametric MRI based prediction model may be helpful in identifying PsP in GBM patients.

Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model.

PURPOSE: Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L. METHODS: Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables. RESULTS: Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts. CONCLUSION: Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.

Enhancing CAR T function with the engineered secretion of C. perfringens neuraminidase.

Prior to adoptive transfer, CAR T cells are activated, lentivirally infected with CAR transgenes, and expanded over 9 to 11 days. An unintended consequence of this process is the progressive differentiation of CAR T cells over time in culture. Differentiated T cells engraft poorly, which limits their ability to persist and provide sustained tumor control in hematologic as well as solid tumors. Solid tumors include other barriers to CAR T cell therapies, including immune and metabolic checkpoints that suppress effector function and durability. Sialic acids are ubiquitous surface molecules with known immune checkpoint functions. The enzyme C. perfringens neuraminidase (CpNA) removes sialic acid residues from target cells, with good activity at physiologic conditions. In combination with galactose oxidase (GO), NA has been found to stimulate T cell mitogenesis and cytotoxicity in vitro. Here we determine whether CpNA alone and in combination with GO promotes CAR T cell antitumor efficacy. We show that CpNA restrains CAR T cell differentiation during ex vivo culture, giving rise to progeny with enhanced therapeutic potential. CAR T cells expressing CpNA have superior effector function and cytotoxicity in vitro. In a Nalm-6 xenograft model of leukemia, CAR T cells expressing CpNA show enhanced antitumor efficacy. Arming CAR T cells with CpNA also enhanced tumor control in xenograft models of glioblastoma as well as a syngeneic model of melanoma. Given our findings, we hypothesize that charge repulsion via surface glycans is a regulatory parameter influencing differentiation. As T cells engage target cells within tumors and undergo constitutive activation through their CARs, critical thresholds of negative charge may impede cell-cell interactions underlying synapse formation and cytolysis. Removing the dense pool of negative cell-surface charge with CpNA is an effective approach to limit CAR T cell differentiation and enhance overall persistence and efficacy.

Locally secreted BiTEs complement CAR T cells by enhancing killing of antigen heterogeneous solid tumors.

Bispecific T cell engagers (BiTEs) are bispecific antibodies that redirect T cells to target antigen-expressing tumors. We hypothesized that BiTE-secreting T cells could be a valuable therapy in solid tumors, with distinct properties in mono- or multi-valent strategies incorporating chimeric antigen receptor (CAR) T cells. Glioblastomas represent a good model for solid tumor heterogeneity, representing a significant therapeutic challenge. We detected expression of tumor-associated epidermal growth factor receptor (EGFR), EGFR variant III, and interleukin-13 receptor alpha 2 (IL13Rα2) on glioma tissues and cancer stem cells. These antigens formed the basis of a multivalent approach, using a conformation-specific tumor-related EGFR targeting antibody (806) and Hu08, an IL13Rα2-targeting antibody, as the single chain variable fragments to generate new BiTE molecules. Compared with CAR T cells, BiTE T cells demonstrated prominent activation, cytokine production, and cytotoxicity in response to target-positive gliomas. Superior response activity was also demonstrated in BiTE-secreting bivalent T cells compared with bivalent CAR T cells in a glioma mouse model at early phase, but not in the long term. In summary, BiTEs secreted by mono- or multi-valent T cells have potent anti-tumor activity in vitro and in vivo with significant sensitivity and specificity, demonstrating a promising strategy in solid tumor therapy.

MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma.

PURPOSE: Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients. METHODS: 21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin. RESULTS: Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r = 0.56, p = 0.018) and the combination of tumor's enhancing zone and necrotic core and the L-Ferritin positivity percent (r = 0.72; p = 0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p = 0.034) and CD86 (r = 0.7 p = 0.001), but not for CD206 (ρ = 0.09; p = 0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r = 0.6, p = 0.016). Similarly, mean R2* values significantly correlated with CD86 (r = 0.54, p = 0.03) but not with CD206 (r = 0.15, p = 0.5). CONCLUSIONS: This study demonstrated the potential of MR quantitative susceptibility mapping as a non-invasive method for in vivo TAM quantification and phenotyping. Validation of these findings with large multicenter studies is needed.

Mechanisms of resistance to CAR T cell therapies.

Chimeric antigen receptor (CAR)-engineered T cells have demonstrated remarkable success in the treatment of B cell malignancies. FDA approval of these therapies represents a watershed moment in the development of therapies for cancer. Despite the successes of the last decade, many patients will unfortunately not experience durable responses to CAR therapy. Emerging research has shed light on the biology responsible for these failures, and further highlighted the hurdles to broader success. Here, we review the recent research identifying how interactions between cancer cells and engineered immune cells result in resistance to CAR therapies.

Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma.

BACKGROUND: Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP. METHODS: We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients. RESULTS: Patients who demonstrate TP on neuropathology are significantly different (P < .0001) from those with PsP, showing imaging features reflecting higher angiogenesis, higher cellularity, and lower water concentration. The accuracy of the proposed signature in leave-one-out cross-validation was 87% for predicting PsP (area under the curve [AUC], 0.92) and 84% for predicting TP (AUC, 0.83), whereas in the discovery/replication cohort, the accuracy was 87% for predicting PsP (AUC, 0.84) and 78% for TP (AUC, 0.80). The accuracy in the interinstitutional cohort was 75% (AUC, 0.80). CONCLUSION: Quantitative mpMRI analysis via machine learning reveals distinctive noninvasive signatures of TP versus PsP after treatment of glioblastoma. Integration of the proposed method into clinical studies can be performed using the freely available Cancer Imaging Phenomics Toolkit.

Multiparametric magnetic resonance imaging in the assessment of anti-EGFRvIII chimeric antigen receptor T cell therapy in patients with recurrent glioblastoma.

EGFRvIII targeted chimeric antigen receptor T (CAR-T) cell therapy has recently been reported for treating glioblastomas (GBMs); however, physiology-based MRI parameters have not been evaluated in this setting. Ten patients underwent multiparametric MRI at baseline, 1, 2 and 3 months after CAR-T therapy. Logistic regression model derived progression probabilities (PP) using imaging parameters were used to assess treatment response. Four lesions from "early surgery" group demonstrated high PP at baseline suggestive of progression, which was confirmed histologically. Out of eight lesions from remaining six patients, three lesions with low PP at baseline remained stable. Two lesions with high PP at baseline were associated with large decreases in PP reflecting treatment response, whereas other two lesions with high PP at baseline continued to demonstrate progression. One patient didn't have baseline data but demonstrated progression on follow-up. Our findings indicate that multiparametric MRI may be helpful in monitoring CAR-T related early therapeutic changes in GBM patients.

Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma.

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T1 -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.

Differentiation of brain infection from necrotic glioblastoma using combined analysis of diffusion and perfusion MRI.

BACKGROUND: Accurate differentiation of brain infections from necrotic glioblastomas (GBMs) may not always be possible on morphologic MRI or on diffusion tensor imaging (DTI) and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) if these techniques are used independently. PURPOSE: To investigate the combined analysis of DTI and DSC-PWI in distinguishing brain injections from necrotic GBMs. STUDY TYPE: Retrospective. POPULATION: Fourteen patients with brain infections and 21 patients with necrotic GBMs. FIELD STRENGTH/SEQUENCE: 3T MRI, DTI, and DSC-PWI. ASSESSMENT: Parametric maps of mean diffusivity (MD), fractional anisotropy (FA), coefficient of linear (CL), and planar anisotropy (CP) and leakage corrected cerebral blood volume (CBV) were computed and coregistered with postcontrast T1 -weighted and FLAIR images. All lesions were segmented into the central core and enhancing region. For each region, median values of MD, FA, CL, CP, relative CBV (rCBV), and top 90th percentile of rCBV (rCBVmax ) were measured. STATISTICAL TESTS: All parameters from both regions were compared between brain infections and necrotic GBMs using Mann-Whitney tests. Logistic regression analyses were performed to obtain the best model in distinguishing these two conditions. RESULTS: From the central core, significantly lower MD (0.90 × 10-3 ± 0.44 × 10-3 mm2 /s vs. 1.66 × 10-3 ± 0.62 × 10-3 mm2 /s, P = 0.001), significantly higher FA (0.15 ± 0.06 vs. 0.09 ± 0.03, P < 0.001), and CP (0.07 ± 0.03 vs. 0.04 ± 0.02, P = 0.009) were observed in brain infections compared to those in necrotic GBMs. Additionally, from the contrast-enhancing region, significantly lower rCBV (1.91 ± 0.95 vs. 2.76 ± 1.24, P = 0.031) and rCBVmax (3.46 ± 1.41 vs. 5.89 ± 2.06, P = 0.001) were observed from infective lesions compared to necrotic GBMs. FA from the central core and rCBVmax from enhancing region provided the best classification model in distinguishing brain infections from necrotic GBMs, with a sensitivity of 91% and a specificity of 93%. DATA CONCLUSION: Combined analysis of DTI and DSC-PWI may provide better performance in differentiating brain infections from necrotic GBMs. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:184-194.

RNA-seq for identification of therapeutically targetable determinants of immune activation in human glioblastoma.

INTRODUCTION: We sought to determine which therapeutically targetable immune checkpoints, costimulatory signals, and other tumor microenvironment (TME) factors are independently associated with immune cytolytic activity (CYT), a gene expression signature of activated effector T cells, in human glioblastoma (GBM). METHODS: GlioVis was accessed for RNA-seq data from The Cancer Genome Atlas (TCGA). For subjects with treatment-naïve, primary GBM, we quantified mRNA expression of 28 therapeutically targetable TME factors. CYT (geometric mean of GZMA and PRF1 expression) was calculated for each tumor. Multiple linear regression was performed to determine the relationship between the dependent variable (CYT) and mRNA expression of each of the 28 factors. Variables associated with CYT in multivariate analysis were subsequently evaluated for this association in an independent cohort of newly diagnosed GBMs from the Chinese Glioma Cooperative Group (CGCG). RESULTS: 109 TCGA tumors were analyzed. The final multiple linear regression model included the following variables, each positively associated with CYT except VEGF-A (negative association): CSF-1 (p = 0.003), CD137 (p = 0.042), VEGF-A (p < 0.001), CTLA4 (p = 0.028), CD40 (p = 0.023), GITR (p = 0.020), IL6 (p = 0.02), and OX40 (p < 0.001). In CGCG (n = 52), each of these variables remained significantly associated with CYT in univariate analysis except for VEGF-A. In multivariate analysis, only CTLA4 and CD40 remained statistically significant. CONCLUSIONS: Using multivariate modeling of RNA-seq gene expression data, we identified therapeutically targetable TME factors that are independently associated with intratumoral cytolytic T-cell activity in human GBM. As a myriad of systemic immunotherapies are now available for investigation, our results could inform rational combinations for evaluation in GBM.

Histopathologic quantification of viable tumor versus treatment effect in surgically resected recurrent glioblastoma.

PURPOSE: The prognostic impact of the histopathologic features of recurrent glioblastoma surgical specimens is unknown. We sought to determine whether key histopathologic characteristics in glioblastoma tumors resected after chemoradiotherapy are associated with overall survival (OS). METHODS: The following characteristics were quantified in recurrent glioblastoma specimens at our institution: extent of viable tumor (accounting for % of specimen comprised of tumor and tumor cellularity), mitoses per 10 high-power fields (0, 1-10, > 10), Ki-67 proliferative index (0-100%), hyalinization (0-6; none to extensive), rarefaction (0-6), hemosiderin (0-6), and % of specimen comprised of geographic necrosis (0-100%; converted to 0-6 scale). Variables associated with OS in univariate analysis, as well as age, eastern cooperative oncology group performance status (ECOG PS), extent of repeat resection, time from initial diagnosis to repeat surgery, and O6-methylguanine-DNA methyltransferase promoter methylation, were included in a multivariable Cox proportional hazards model. RESULTS: 37 specimens were assessed. In a multivariate model, high Ki-67 proliferative index was the only histopathologic characteristic associated with worse OS following repeat surgery for glioblastoma (hazard ratio (HR) 1.3, 95% CI 1.1-1.5, p = 0.003). Shorter time interval from initial diagnosis to repeat surgery (HR 1.11, 95% CI 1.02-1.21, p = 0.016) and ECOG PS ≥ 2 (HR 4.19, 95% CI 1.72-10.21, p = 0.002) were also independently associated with inferior OS. CONCLUSION: In patients with glioblastoma undergoing repeat resection following chemoradiotherapy, high Ki-67 index in the recurrent specimen, short time to recurrence, and poor PS are independently associated with worse OS. Histopathologic quantification of viable tumor versus therapy-related changes has limited prognostic influence.

Negative prognostic impact of epidermal growth factor receptor copy number gain in young adults with isocitrate dehydrogenase wild-type glioblastoma.

PURPOSE: Young adults with isocitrate-dehydrogenase wild-type (IDH-WT) glioblastoma (GBM) represent a rare, understudied population compared to pediatric high-grade glioma, IDH-mutant GBM, or IDH-WT GBM in older patients. We aimed to explore the prognostic impact of epidermal growth factor receptor copy number gain (EGFR CN gain), one of the most common genetic alterations in IDH-WT glioma, in young adults with IDH-WT GBM. METHODS: We performed a retrospective cohort study of patients 18-45 years old with newly diagnosed, IDH-WT GBM whose tumors underwent next-generation sequencing at our institution between 2014 and 2018. The impact of EGFR CN gain on time to tumor progression (TTP) and overall survival (OS) was assessed. A validation cohort of patients 18-45 years old with IDH-WT GBM was analyzed from The Cancer Genome Atlas (TCGA). RESULTS: Ten of 28 patients (36%) from our institution had EGFR CN gain, which was associated with shorter TTP (median 6.5 vs. 11.9 months; p = 0.06) and OS (median 16.3 vs. 23.5 months; p = 0.047). The negative prognostic impact of EGFR CN gain on OS persisted in a multivariate model (HR 6.40, 95% CI 1.3-31.0, p = 0.02). In the TCGA cohort (N = 43), EGFR CN gain was associated with shorter TTP and worse OS, although these did not reach statistical significance (TTP, median 11.5 vs. 14.4 months, p = 0.18; OS, median 23.6 vs. 27.8 months; p = 0.18). CONCLUSIONS: EGFR CN gain may be associated with inferior outcomes in young adults with newly diagnosed, IDH-WT GBM, suggesting a potential role for targeting EGFR in this population.

IDH mutation impairs histone demethylation and results in a block to cell differentiation.

Recurrent mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 have been identified in gliomas, acute myeloid leukaemias (AML) and chondrosarcomas, and share a novel enzymatic property of producing 2-hydroxyglutarate (2HG) from α-ketoglutarate. Here we report that 2HG-producing IDH mutants can prevent the histone demethylation that is required for lineage-specific progenitor cells to differentiate into terminally differentiated cells. In tumour samples from glioma patients, IDH mutations were associated with a distinct gene expression profile enriched for genes expressed in neural progenitor cells, and this was associated with increased histone methylation. To test whether the ability of IDH mutants to promote histone methylation contributes to a block in cell differentiation in non-transformed cells, we tested the effect of neomorphic IDH mutants on adipocyte differentiation in vitro. Introduction of either mutant IDH or cell-permeable 2HG was associated with repression of the inducible expression of lineage-specific differentiation genes and a block to differentiation. This correlated with a significant increase in repressive histone methylation marks without observable changes in promoter DNA methylation. Gliomas were found to have elevated levels of similar histone repressive marks. Stable transfection of a 2HG-producing mutant IDH into immortalized astrocytes resulted in progressive accumulation of histone methylation. Of the marks examined, increased H3K9 methylation reproducibly preceded a rise in DNA methylation as cells were passaged in culture. Furthermore, we found that the 2HG-inhibitable H3K9 demethylase KDM4C was induced during adipocyte differentiation, and that RNA-interference suppression of KDM4C was sufficient to block differentiation. Together these data demonstrate that 2HG can inhibit histone demethylation and that inhibition of histone demethylation can be sufficient to block the differentiation of non-transformed cells.

Rindopepimut with temozolomide for patients with newly diagnosed, EGFRvIII-expressing glioblastoma (ACT IV): a randomised, double-blind, international phase 3 trial.

BACKGROUND: Rindopepimut (also known as CDX-110), a vaccine targeting the EGFR deletion mutation EGFRvIII, consists of an EGFRvIII-specific peptide conjugated to keyhole limpet haemocyanin. In the ACT IV study, we aimed to assess whether or not the addition of rindopepimut to standard chemotherapy is able to improve survival in patients with EGFRvIII-positive glioblastoma. METHODS: In this randomised, double-blind, phase 3 trial, we recruited patients aged 18 years and older with glioblastoma from 165 hospitals in 22 countries. Eligible patients had newly diagnosed glioblastoma confirmed to express EGFRvIII by central analysis, and had undergone maximal surgical resection and completion of standard chemoradiation without progression. Patients were stratified by European Organisation for Research and Treatment of Cancer recursive partitioning analysis class, MGMT promoter methylation, and geographical region, and randomly assigned (1:1) with a prespecified randomisation sequence (block size of four) to receive rindopepimut (500 µg admixed with 150 µg GM-CSF) or control (100 µg keyhole limpet haemocyanin) via monthly intradermal injection until progression or intolerance, concurrent with standard oral temozolomide (150-200 mg/m2 for 5 of 28 days) for 6-12 cycles or longer. Patients, investigators, and the trial funder were masked to treatment allocation. The primary endpoint was overall survival in patients with minimal residual disease (MRD; enhancing tumour <2 cm2 post-chemoradiation by central review), analysed by modified intention to treat. This trial is registered with ClinicalTrials.gov, number NCT01480479. FINDINGS: Between April 12, 2012, and Dec 15, 2014, 745 patients were enrolled (405 with MRD, 338 with significant residual disease [SRD], and two unevaluable) and randomly assigned to rindopepimut and temozolomide (n=371) or control and temozolomide (n=374). The study was terminated for futility after a preplanned interim analysis. At final analysis, there was no significant difference in overall survival for patients with MRD: median overall survival was 20·1 months (95% CI 18·5-22·1) in the rindopepimut group versus 20·0 months (18·1-21·9) in the control group (HR 1·01, 95% CI 0·79-1·30; p=0·93). The most common grade 3-4 adverse events for all 369 treated patients in the rindopepimut group versus 372 treated patients in the control group were: thrombocytopenia (32 [9%] vs 23 [6%]), fatigue (six [2%] vs 19 [5%]), brain oedema (eight [2%] vs 11 [3%]), seizure (nine [2%] vs eight [2%]), and headache (six [2%] vs ten [3%]). Serious adverse events included seizure (18 [5%] vs 22 [6%]) and brain oedema (seven [2%] vs 12 [3%]). 16 deaths in the study were caused by adverse events (nine [4%] in the rindopepimut group and seven [3%] in the control group), of which one-a pulmonary embolism in a 64-year-old male patient after 11 months of treatment-was assessed as potentially related to rindopepimut. INTERPRETATION: Rindopepimut did not increase survival in patients with newly diagnosed glioblastoma. Combination approaches potentially including rindopepimut might be required to show efficacy of immunotherapy in glioblastoma. FUNDING: Celldex Therapeutics, Inc.

SHP2 regulates proliferation and tumorigenicity of glioma stem cells.

SHP2 is a cytoplasmic protein tyrosine phosphatase (PTPase) involved in multiple signaling pathways and was the first identified proto-oncogene PTPase. Previous work in glioblastoma (GBM) has demonstrated the role of SHP2 PTPase activity in modulating the oncogenic phenotype of adherent GBM cell lines. Mutations in PTPN11, the gene encoding SHP2, have been identified with increasing frequency in GBM. Given the importance of SHP2 in developing neural stem cells, and the importance of glioma stem cells (GSCs) in GBM oncogenesis, we explored the functional role of SHP2 in GSCs. Using paired differentiated and stem cell primary cultures, we investigated the association of SHP2 expression with the tumor stem cell compartment. Proliferation and soft agar assays were used to demonstrate the functional contribution of SHP2 to cell growth and transformation. SHP2 expression correlated with SOX2 expression in GSC lines and was decreased in differentiated cells. Forced differentiation of GSCs by removal of growth factors, as confirmed by loss of SOX2 expression, also resulted in decreased SHP2 expression. Lentiviral-mediated knockdown of SHP2 inhibited proliferation. Finally, growth in soft-agar was similarly inhibited by loss of SHP2 expression. Our results show that SHP2 function is required for cell growth and transformation of the GSC compartment in GBM.

Assignment Confidence in Localization of the Hand Motor Cortex: Comparison of Structural Imaging With Functional MRI.

OBJECTIVE: The purpose of this study was to assign confidence levels to structural MRI and functional MRI (fMRI) for localization of the primary motor cortex. MATERIALS AND METHODS: Ninety-one fMRI studies with at least one motor task (178 hemispheres) were identified. Three anatomic assessments were used to localize the primary motor cortex: relation between the superior frontal sulcus and precentral sulcus; cortical thickness; and configuration of the precentral knob. In 105 hemispheres, interreader agreement was assessed for two investigators with different experience levels. Confidence ratings from 0 to 5 (0, no confidence; 5, 100% confidence) were assigned for fMRI and each anatomic localization method. RESULTS: Cortical thickness had the highest confidence rating (mean, 4.90 ± 0.47 [SD]) with only one failure. The relation between the superior frontal sulcus and precentral sulcus had the lowest confidence rating (4.33 ± 0.91) with three failures. The greatest statistical significance was observed for the cortical thickness and superior frontal sulcus-precentral sulcus methods (post hoc Bonferroni test, p < 0.001). Confidence rating scores were significantly higher for the cortical thickness sign than for fMRI results (4.72 ± 0.54) for a single motor task (post hoc Bonferroni test, p = 0.006); however, the mean confidence rating for fMRI improved to 4.87 ± 0.36 when additional motor tasks were performed. Interreader differences were least for the cortical thickness sign (paired t test, t = 4.25, p < 0.001). CONCLUSION: Cortical thickness is a better anatomic landmark than fMRI localization for assigning confidence regarding localization of the primary motor cortex; however, localization of motor function is more specific when combined with fMRI findings. Multiple techniques can be used to increase confidence in identifying the hand motor cortex.

Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes.

Molecular stratification of tumors is essential for developing personalized therapies. Although patient stratification strategies have been successful; computational methods to accurately translate the gene-signature from high-throughput platform to a clinically adaptable low-dimensional platform are currently lacking. Here, we describe PIGExClass (platform-independent isoform-level gene-expression based classification-system), a novel computational approach to derive and then transfer gene-signatures from one analytical platform to another. We applied PIGExClass to design a reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) based molecular-subtyping assay for glioblastoma multiforme (GBM), the most aggressive primary brain tumors. Unsupervised clustering of TCGA (the Cancer Genome Altas Consortium) GBM samples, based on isoform-level gene-expression profiles, recaptured the four known molecular subgroups but switched the subtype for 19% of the samples, resulting in significant (P = 0.0103) survival differences among the refined subgroups. PIGExClass derived four-class classifier, which requires only 121 transcript-variants, assigns GBM patients' molecular subtype with 92% accuracy. This classifier was translated to an RT-qPCR assay and validated in an independent cohort of 206 GBM samples. Our results demonstrate the efficacy of PIGExClass in the design of clinically adaptable molecular subtyping assay and have implications for developing robust diagnostic assays for cancer patient stratification.

Association of dynamic susceptibility contrast enhanced MR Perfusion parameters with prognosis in elderly patients with glioblastomas.

OBJECTIVES: We aimed to evaluate the prognostic value of dynamic susceptibility contrast (DSC) MR perfusion in elderly patients with glioblastomas (GBM). METHODS: Thirty five patients aged ≥65 and 35 aged <65 years old, (referred to as elderly and younger, respectively) were included in this retrospective study. The median relative cerebral volume (rCBV) from the enhancing region (rCBVER-Med) and immediate peritumoral region (rCBVIPR-Med) and maximum rCBV from the enhancing region of the tumor (rCBVER-Max) were compared and correlated with survival data. Analysis was repeated after rCBVs were dichotomized into high and low values and after excluding elderly patients who did not receive postoperative chemoradiation (34.3%). Kaplan-Meyer survival curves and parametric and semi-parametric regression tests were used for analysis. RESULTS: All rCBV parameters were higher in elderly compared to younger patients (p < 0.05). After adjustment for age, none were independently associated with shorter survival (p > 0.05). After rCBV dichotomization into high and low values, high rCBV in elderly was independently associated with shorter survival compared to low rCBV in elderly, or any rCBV in younger patients (p < 0.05). CONCLUSION: rCBV can be an imaging biomarker to identify a subgroup of GBM patients in the elderly with worse prognosis compared to others. KEY POINTS: • GBM perfusion parameters are higher in elderly compared to younger patients. • rCBV can identify a subgroup of elderly patients with worse prognosis. • rCBV can be an imaging biomarker for prognostication in GBM. • The identified elderly patients may benefit from anti-angiogenic treatment.