Live Organoid Cyclic Imaging

Organoids are becoming increasingly relevant in biology and medicine for their physiological complexity and accuracy in modeling human disease. To fully assess their biological profile while preserving their spatial information, spatiotemporal imaging tools are warranted. While previously developed imaging techniques, such as four-dimensional (4D) live imaging and light-sheet imaging have yielded important clinical insights, these technologies lack the combination of cyclic and multiplexed analysis. To address these challenges, bioorthogonal click chemistry is applied to display the first demonstration of multiplexed cyclic imaging of live and fixed patient-derived glioblastoma tumor organoids. This technology exploits bioorthogonal click chemistry to quench fluorescent signals from the surface and intracellular of labeled cells across multiple cycles, allowing for more accurate and efficient molecular profiling of their complex phenotypes. Herein, the versatility of this technology is demonstrated for the screening of glioblastoma markers in patient-derived human glioblastoma organoids while conserving their viability. It is anticipated that the findings and applications of this work can be broadly translated into investigating physiological developments in other organoid systems.

Intrathecal bivalent CAR T cells targeting EGFR and IL13Rα2 in recurrent glioblastoma: phase 1 trial interim results

Recurrent glioblastoma (rGBM) remains a major unmet medical need, with a median overall survival of less than 1 year. Here we report the first six patients with rGBM treated in a phase 1 trial of intrathecally delivered bivalent chimeric antigen receptor (CAR) T cells targeting epidermal growth factor receptor (EGFR) and interleukin-13 receptor alpha 2 (IL13Rα2). The study's primary endpoints were safety and determination of the maximum tolerated dose. Secondary endpoints reported in this interim analysis include the frequency of manufacturing failures and objective radiographic response (ORR) according to modified Response Assessment in Neuro-Oncology criteria. All six patients had progressive, multifocal disease at the time of treatment. In both dose level 1 (1 ×107 cells; n = 3) and dose level 2 (2.5 × 107 cells; n = 3), administration of CART-EGFR-IL13Rα2 cells was associated with early-onset neurotoxicity, most consistent with immune effector cell-associated neurotoxicity syndrome (ICANS), and managed with high-dose dexamethasone and anakinra (anti-IL1R). One patient in dose level 2 experienced a dose-limiting toxicity (grade 3 anorexia, generalized muscle weakness and fatigue). Reductions in enhancement and tumor size at early magnetic resonance imaging timepoints were observed in all six patients; however, none met criteria for ORR. In exploratory endpoint analyses, substantial CAR T cell abundance and cytokine release in the cerebrospinal fluid were detected in all six patients. Taken together, these first-in-human data demonstrate the preliminary safety and bioactivity of CART-EGFR-IL13Rα2 cells in rGBM. An encouraging early efficacy signal was also detected and requires confirmation with additional patients and longer follow-up time. ClinicalTrials.gov identifier: NCT05168423 .

Brain-wide neuronal circuit connectome of human glioblastoma

Glioblastoma (GBM), a universally fatal brain cancer, infiltrates the brain and can be synaptically innervated by neurons, which drives tumor progression 1-6 . Synaptic inputs onto GBM cells identified so far are largely short-range and glutamatergic 7-9 . The extent of integration of GBM cells into brain-wide neuronal circuitry is not well understood. Here we applied a rabies virus-mediated retrograde monosynaptic tracing approach 10-12 to systematically investigate circuit integration of human GBM organoids transplanted into adult mice. We found that GBM cells from multiple patients rapidly integrated into brain-wide neuronal circuits and exhibited diverse local and long-range connectivity. Beyond glutamatergic inputs, we identified a variety of neuromodulatory inputs across the brain, including cholinergic inputs from the basal forebrain. Acute acetylcholine stimulation induced sustained calcium oscillations and long-lasting transcriptional reprogramming of GBM cells into a more invasive state via the metabotropic CHRM3 receptor. CHRM3 downregulation suppressed GBM cell invasion, proliferation, and survival in vitro and in vivo. Together, these results reveal the capacity of human GBM cells to rapidly and robustly integrate into anatomically and molecularly diverse neuronal circuitry in the adult brain and support a model wherein rapid synapse formation onto GBM cells and transient activation of upstream neurons may lead to a long-lasting increase in fitness to promote tumor infiltration and progression.

Repeated peripheral infusions of anti-EGFRvIII CAR T cells in combination with pembrolizumab show no efficacy in glioblastoma: a phase 1 trial

We previously showed that chimeric antigen receptor (CAR) T-cell therapy targeting epidermal growth factor receptor variant III (EGFRvIII) produces upregulation of programmed death-ligand 1 (PD-L1) in the tumor microenvironment (TME). Here we conducted a phase 1 trial (NCT03726515) of CAR T-EGFRvIII cells administered concomitantly with the anti-PD1 (aPD1) monoclonal antibody pembrolizumab in patients with newly diagnosed, EGFRvIII+ glioblastoma (GBM) (n = 7). The primary outcome was safety, and no dose-limiting toxicity was observed. Secondary outcomes included median progression-free survival (5.2 months; 90% confidence interval (CI), 2.9-6.0 months) and median overall survival (11.8 months; 90% CI, 9.2-14.2 months). In exploratory analyses, comparison of the TME in tumors harvested before versus after CAR + aPD1 administration demonstrated substantial evolution of the infiltrating myeloid and T cells, with more exhausted, regulatory, and interferon (IFN)-stimulated T cells at relapse. Our study suggests that the combination of CAR T cells and PD-1 inhibition in GBM is safe and biologically active but, given the lack of efficacy, also indicates a need to consider alternative strategies.

Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach

Glioblastoma is a highly heterogeneous disease, with variations observed at both phenotypical and molecular levels. Personalized therapies would be facilitated by non-invasive in vivo approaches for characterizing this heterogeneity. In this study, we developed unsupervised joint machine learning between radiomic and genomic data, thereby identifying distinct glioblastoma subtypes. A retrospective cohort of 571 IDH-wildtype glioblastoma patients were included in the study, and pre-operative multi-parametric MRI scans and targeted next-generation sequencing (NGS) data were collected. L21-norm minimization was used to select a subset of 12 radiomic features from the MRI scans, and 13 key driver genes from the five main signal pathways most affected in glioblastoma were selected from the genomic data. Subtypes were identified using a joint learning approach called Anchor-based Partial Multi-modal Clustering on both radiomic and genomic modalities. Kaplan-Meier analysis identified three distinct glioblastoma subtypes: high-risk, medium-risk, and low-risk, based on overall survival outcome (p < 0.05, log-rank test; Hazard Ratio = 1.64, 95% CI 1.17-2.31, Cox proportional hazard model on high-risk and low-risk subtypes). The three subtypes displayed different phenotypical and molecular characteristics in terms of imaging histogram, co-occurrence of genes, and correlation between the two modalities. Our findings demonstrate the synergistic value of integrated radiomic signatures and molecular characteristics for glioblastoma subtyping. Joint learning on both modalities can aid in better understanding the molecular basis of phenotypical signatures of glioblastoma, and provide insights into the biological underpinnings of tumor formation and progression.

Optimizing CAR-T Therapy for Glioblastoma

Chimeric antigen receptor T-cell therapies have transformed the management of hematologic malignancies but have not yet demonstrated consistent efficacy in solid tumors. Glioblastoma is the most common primary malignant brain tumor in adults and remains a major unmet medical need. Attempts at harnessing the potential of chimeric antigen receptor T-cell therapy for glioblastoma have resulted in glimpses of promise but have been met with substantial challenges. In this focused review, we discuss current and future strategies being developed to optimize chimeric antigen receptor T cells for efficacy in patients with glioblastoma, including the identification and characterization of new target antigens, reversal of T-cell dysfunction with novel chimeric antigen receptor constructs, regulatable platforms, and gene knockout strategies, and the use of combination therapies to overcome the immune-hostile microenvironment.

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.

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.

Distinguishing Progression from Pseudoprogression in Glioblastoma Using 18F-Fluciclovine PET

Rationale: Accurate differentiation between tumor progression (TP) and pseudoprogression remains a critical unmet need in neuro-oncology. ¹⁸F-fluciclovine is a widely available synthetic amino acid PET radiotracer. In this study, we aimed to assess the value of ¹⁸F-fluciclovine PET for differentiating pseudoprogression from TP in a prospective cohort of patients with suspected radiographic recurrence of glioblastoma. Methods: We enrolled 30 glioblastoma patients with radiographic progression after first-line chemoradiotherapy who were planned for surgical resection. Patients underwent pre-operative ¹⁸F-fluciclovine PET and MRI. Relative percentages of viable tumor and therapy-related changes observed in histopathology were quantified and categorized as TP (≥50% viable tumor), mixed TP (<50% and >10% viable tumor), or pseudoprogression (≤10% viable tumor). Results: Eighteen patients had TP, 4 mixed TP, and 8 pseudoprogression. Patients with TP/mixed TP had significantly higher 40-50 minutes SUV_max (6.64+ 1.88 vs 4.11± 1.52, P = 0.009) compared to patients with pseudoprogression. A 40-50 minutes SUV_max cut-off of 4.66 provided 90% sensitivity and 83% specificity for differentiation of TP/mixed TP from pseudoprogression (Area under the curve (AUC)=0.86). Relative cerebral blood volume (rCBVmax) cut-off 3.672 provided 90% sensitivity and 71% specificity for differentiation of TP/mixed TP from Pseudoprogression (AUC=0.779). Combining a 40-50 minutes SUV_max cut-off of 4.66 and a rCBVmax cut-off of 3.67 on MRI provided 100% sensitivity and 80% specificity for differentiating TP/mixed TP from Pseudoprogression (AUC=0.95). Conclusion: ¹⁸F-fluciclovine PET uptake can accurately differentiate pseudoprogression from TP in glioblastoma, with even greater accuracy when combined with multi-parametric MRI. Given the wide availability of ¹⁸F-fluciclovine, larger, multicenter studies are warranted to determine whether amino acid PET with ¹⁸F-fluciclovine should be used in the routine assessment of post-treatment glioblastoma.

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of: a) number of subjects, b) lack of consistent acquisition protocol, c) data quality, or d) accompanying clinical, demographic, and molecular information. Toward alleviating these limitations, we contribute the "University of Pennsylvania Glioblastoma Imaging, Genomics, and Radiomics" (UPenn-GBM) dataset, which describes the currently largest publicly available comprehensive collection of 630 patients diagnosed with de novo glioblastoma. The UPenn-GBM dataset includes (a) advanced multi-parametric magnetic resonance imaging scans acquired during routine clinical practice, at the University of Pennsylvania Health System, (b) accompanying clinical, demographic, and molecular information, (d) perfusion and diffusion derivative volumes, (e) computationally-derived and manually-revised expert annotations of tumor sub-regions, as well as (f) quantitative imaging (also known as radiomic) features corresponding to each of these regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments.

Risk of intracranial hemorrhage with direct oral anticoagulants versus low molecular weight heparin in glioblastoma: A retrospective cohort study

2015

Background: Glioblastoma (GBM) is associated with a high rate of venous thromboembolism (VTE), but there is little data to guide anticoagulation in GBM patients, in whom the risks of VTE must be balanced against the risk of intracranial hemorrhage (ICH). Methods: We performed a single-institution retrospective cohort study of patients with GBM diagnosed with VTE from 2014-2021 who were treated with low molecular weight heparin (LMWH) or a direct oral anticoagulant (DOAC). The cumulative incidence of ICH was compared between the LMWH and DOAC groups. The primary outcome was clinically relevant ICH within the first 30 days of anticoagulation, defined as any ICH that was fatal, symptomatic, required surgical intervention, and/or led to cessation of anticoagulation. Key secondary outcomes included clinically relevant ICH within 6 months, fatal ICH within 30 days and 6 months, any bleeding within 30 days and 6 months, and recurrent VTE within 6 months. Fisher’s exact test was used for comparison of primary and secondary endpoints between the two groups. Cumulative incidence curves were generated using the Kaplan-Meier method, and the cumulative incidence of clinically relevant ICH at both the 30-day timepoint and 6-month timepoint was compared between the DOAC and LMWH groups using the Gray test to account for death as a competing risk. Results: A total of 121 patients were identified in the primary cohort for 30-day outcome analyses (DOAC, n = 33; LMWH, n = 88). For 6-month outcome analyses, the cohort included only patients who were maintained on their initial anticoagulant (DOAC or LMWH) and did not switch anticoagulants during the 6 months following diagnosis of VTE (DOAC, n = 32; LMWH, n = 75). The cumulative incidence of clinically relevant ICH at 30 days was 0% (0/33) in the DOAC group and 9% (8/88) in the LMWH group (p = 0.11). The cumulative incidence of clinically relevant ICH at 6 months was 0% (0/32) in the DOAC group and 24% (18/75) in the LMWH group (p = 0.001), with 4 fatal ICHs in the LMWH group. Other outcomes are displayed in the Table. Conclusions: Our study suggests that DOACs are associated with a lower incidence of clinically relevant ICH in patients with GBM-associated VTE compared to LMWH. These data support the use of DOACs as a safe alternative to LMWH in patients with GBM.[Table: see text]

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.

Glioblastoma: The Current State of Biology and Therapeutic Strategies

Over the past two decades, there have been advances in surgical technologies and chemoradiation strategies for glioblastoma, yet durable remissions are rarely seen. As the biological challenges and genetic basis of glioblastoma have become more understood, new therapeutic strategies may lead to more durable clinical responses and long-term remissions. We believe specialized academic centers that form meaningful corporate partnerships to complement basic science infrastructure and use adaptive clinical trial designs will achieve more rapid translation of innovative approaches to glioblastoma. Here we outline the core biological challenges to be overcome in the management of glioblastoma.

High-Affinity Chimeric Antigen Receptor With Cross-Reactive scFv to Clinically Relevant EGFR Oncogenic Isoforms

Tumor heterogeneity is a key reason for therapeutic failure and tumor recurrence in glioblastoma (GBM). Our chimeric antigen receptor (CAR) T cell (2173 CAR T cells) clinical trial (NCT02209376) against epidermal growth factor receptor (EGFR) variant III (EGFRvIII) demonstrated successful trafficking of T cells across the blood–brain barrier into GBM active tumor sites. However, CAR T cell infiltration was associated only with a selective loss of EGFRvIII+ tumor, demonstrating little to no effect on EGFRvIII^- tumor cells. Post-CAR T-treated tumor specimens showed continued presence of EGFR amplification and oncogenic EGFR extracellular domain (ECD) missense mutations, despite loss of EGFRvIII. To address tumor escape, we generated an EGFR-specific CAR by fusing monoclonal antibody (mAb) 806 to a 4-1BB co-stimulatory domain. The resulting construct was compared to 2173 CAR T cells in GBM, using in vitro and in vivo models. 806 CAR T cells specifically lysed tumor cells and secreted cytokines in response to amplified EGFR, EGFRvIII, and EGFR-ECD mutations in U87MG cells, GBM neurosphere-derived cell lines, and patient-derived GBM organoids. 806 CAR T cells did not lyse fetal brain astrocytes or primary keratinocytes to a significant degree. They also exhibited superior antitumor activity in vivo when compared to 2173 CAR T cells. The broad specificity of 806 CAR T cells to EGFR alterations gives us the potential to target multiple clones within a tumor and reduce opportunities for tumor escape via antigen loss.

Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging

Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman's r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p < 0.006). The results of this study demonstrates that PCA analysis of DSC imaging data can provide information about tumor pH in GBM patients, with the strongest association within the peritumoral regions.

Wnt-mediated endothelial transformation into mesenchymal stem cell-like cells induces chemoresistance in glioblastoma

Therapeutic resistance remains a persistent challenge for patients with malignant tumors. Here, we reveal that endothelial cells (ECs) acquire transformation into mesenchymal stem cell (MSC)-like cells in glioblastoma (GBM), driving tumor resistance to cytotoxic treatment. Transcriptome analysis by RNA sequencing (RNA-seq) revealed that ECs undergo mesenchymal transformation and stemness-like activation in GBM microenvironment. Furthermore, we identified a c-Met-mediated axis that induces β-catenin phosphorylation at Ser⁶⁷⁵ and Wnt signaling activation, inducing multidrug resistance-associated protein-1(MRP-1) expression and leading to EC stemness-like activation and chemoresistance. Last, genetic ablation of β-catenin in ECs overcome GBM tumor resistance to temozolomide (TMZ) chemotherapy in vivo. Combination of Wnt inhibition and TMZ chemotherapy eliminated tumor-associated ECs, inhibited GBM growth, and increased mouse survival. These findings identified a cell plasticity-based, microenvironment-dependent mechanism that controls tumor chemoresistance, and suggest that targeting Wnt/β-catenin-mediated EC transformation and stemness activation may overcome therapeutic resistance in GBM.

Molecular and Clinical Characterization of UBE2S in Glioma as a Biomarker for Poor Prognosis and Resistance to Chemo-Radiotherapy

Glioblastoma is the most common and lethal brain cancer globally. Clinically, this cancer has heterogenous molecular and clinical characteristics. Studies have shown that UBE2S is highly expressed in many cancers. But its expression profile in glioma, and the correlation with clinical outcomes is unknown. RNA sequencing data of glioma samples was downloaded from the Chinese Glioma Genome Atlas and The Cancer Genome Atlas. A total of 114 cases of glioma tissue samples (WHO grades II-IV) were used to conduct protein expression assays. The molecular and biological characteristics of UBE2S, and its prognostic value were analyzed. The results showed that high UBE2S expression was associated with a higher grade of glioma and PTEN mutations. In addition, UBE2S affected the degree of malignancy of glioma and the development of chemo-radiotherapy resistance. It was also found to be an independent predictor of worse survival of LGG patients. Furthermore, we identified five UBE2S ubiquitination sites and found that UBE2S was associated with Akt phosphorylation in malignant glioblastoma. The results also revealed that UBE2S expression was negatively correlated with 1p19q loss and IDH1 mutation; positively correlated with epidermal growth factor receptor amplification and PTEN mutation. This study demonstrates that UBE2S expression strongly correlates with glioma malignancy and resistance to chemo-radiotherapy. It is also a crucial biomarker of poor prognosis.

Case Report: Prolonged Survival Following EGFRvIII CAR T Cell Treatment for Recurrent Glioblastoma

Autologous chimeric antigen receptor (CAR) T cells targeted to epidermal growth factor receptor variant III (CAR T-EGFRvIII) have been developed and administered experimentally to treat patients with IDH1 wildtype recurrent glioblastoma (rGBM) (NCT02209376). We report the case of a 59-year-old patient who received a single peripheral infusion of CAR T-EGFRvIII cells and survived 36 months after disease recurrence, exceeding expected survival for recurrent glioblastoma. Post-infusion histopathologic analysis of tissue obtained during a second stage surgical resection revealed immunosuppressive adaptive changes in the tumor tissue as well as reduced EGFRvIII expression. Serial brain imaging demonstrated a significant reduction in relative cerebral blood volume (rCBV), a measure strongly associated with tumor proliferative activity, at early time points following CAR T treatment. Notably, CAR T-EGFRvIII cells persisted in her peripheral circulation during 29 months of follow-up, the longest period of CAR T persistence reported in GBM trials to date. These findings in a long-term survivor show that peripherally administered CAR T-EGFRvIII cells can persist for years in the circulation and suggest that this cell therapy approach could be optimized to achieve broader efficacy in recurrent GBM patients.

CAR T Cells

Chimeric antigen receptor T (CAR-T) cells, an immunotherapy that demonstrates marked success in treatment of hematologic malignancies, are an emergent therapeutic for patients with glioblastoma (GBM). GBM CAR-T trials have focused on targeting well-characterized antigens in the pathogenesis of GBM. Early stage trials demonstrate initial success in terms of safety and tolerability. There is preliminary evidence of antitumor activity and localization of the CAR-T product to tumoral sites. There are mixed results regarding patient outcomes. Ongoing GBM CAR-T trials will target novel antigens, explore CAR-T combination therapy, design multivalent CAR constructs, and assess the impact of lymphodepletion before CAR-T delivery.

Multi-institutional noninvasive in vivo characterization of IDH, 1p/19q, and EGFRvIII in glioma using neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk)

Background

Gliomas represent a biologically heterogeneous group of primary brain tumors with uncontrolled cellular proliferation and diffuse infiltration that renders them almost incurable, thereby leading to a grim prognosis. Recent comprehensive genomic profiling has greatly elucidated the molecular hallmarks of gliomas, including the mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), loss of chromosomes 1p and 19q (1p/19q), and epidermal growth factor receptor variant III (EGFRvIII). Detection of these molecular alterations is based on ex vivo analysis of surgically resected tissue specimen that sometimes is not adequate for testing and/or does not capture the spatial tumor heterogeneity of the neoplasm.

Methods

We developed a method for noninvasive detection of radiogenomic markers of IDH both in lower-grade gliomas (WHO grade II and III tumors) and glioblastoma (WHO grade IV), 1p/19q in IDH-mutant lower-grade gliomas, and EGFRvIII in glioblastoma. Preoperative MRIs of 473 glioma patients from 3 of the studies participating in the ReSPOND consortium (collection I: Hospital of the University of Pennsylvania [HUP: n = 248], collection II: The Cancer Imaging Archive [TCIA; n = 192], and collection III: Ohio Brain Tumor Study [OBTS, n = 33]) were collected. Neuro-Cancer Imaging Phenomics Toolkit (neuro-CaPTk), a modular platform available for cancer imaging analytics and machine learning, was leveraged to extract histogram, shape, anatomical, and texture features from delineated tumor subregions and to integrate these features using support vector machine to generate models predictive of IDH, 1p/19q, and EGFRvIII. The models were validated using 3 configurations: (1) 70-30% training-testing splits or 10-fold cross-validation within individual collections, (2) 70-30% training-testing splits within merged collections, and (3) training on one collection and testing on another.

Results

These models achieved a classification accuracy of 86.74% (HUP), 85.45% (TCIA), and 75.15% (TCIA) in identifying EGFRvIII, IDH, and 1p/19q, respectively, in configuration I. The model, when applied on combined data in configuration II, yielded a classification success rate of 82.50% in predicting IDH mutation (HUP + TCIA + OBTS). The model when trained on TCIA dataset yielded classification accuracy of 84.88% in predicting IDH in HUP dataset.

Conclusions

Using machine learning algorithms, high accuracy was achieved in the prediction of IDH, 1p/19q, and EGFRvIII mutation. Neuro-CaPTk encompasses all the pipelines required to replicate these analyses in multi-institutional settings and could also be used for other radio(geno)mic analyses.

Targeting PAK4 to reprogram the vascular microenvironment and improve CAR-T immunotherapy for glioblastoma

Malignant solid tumors are characterized by aberrant vascularity that fuels the formation of an immune-hostile microenvironment and induces resistance to immunotherapy. Vascular abnormalities may be driven by pro-angiogenic pathway activation and genetic reprogramming in tumor endothelial cells (ECs). Here, our kinome-wide screening of mesenchymal-like transcriptional activation in human glioblastoma (GBM)-derived ECs identifies p21-activated kinase 4 (PAK4) as a selective regulator of genetic reprogramming and aberrant vascularization. PAK4 knockout induces adhesion protein re-expression in ECs, reduces vascular abnormalities, improves T cell infiltration and inhibits GBM growth in mice. Moreover, PAK4 inhibition normalizes the tumor vascular microenvironment and sensitizes GBM to chimeric antigen receptor-T cell immunotherapy. Finally, we reveal a MEF2D/ZEB1- and SLUG-mediated mechanism by which PAK4 reprograms the EC transcriptome and downregulates claudin-14 and VCAM-1 expression, enhancing vessel permeability and reducing T cell adhesion to the endothelium. Thus, targeting PAK4-mediated EC plasticity may offer a unique opportunity to recondition the vascular microenvironment and strengthen cancer immunotherapy.

Pathology of macrophage activation syndrome in humanized NSGS mice

"Humanized" immunodeficient mice generated via the transplantation of CD34+ human hematopoietic stem cells (hHSC) are an important preclinical model system. The triple transgenic NOD.Cg-Prkdc^scidIl2rg^tm1Wjl Tg(CMV-IL3,CSF2,KITLG)1Eav/MloySzJ (NSGS) mouse line is increasingly used as recipient for CD34+ hHSC engraftment. NSGS mice combine the features of the highly immunodeficient NSG mice with transgenic expression of the human myeloid stimulatory cytokines GM-CSF, IL-3, and Kit ligand. While generating humanized NSGS (huNSGS) mice from two independent cohorts, we encountered a fatal macrophage activation syndrome (MAS)-like phenotype resulting from the transplantation of CD34+ hHSC. huNSGS mice exhibiting this phenotype declined clinically starting at approximately 10 weeks following CD34+ hHSC engraftment, with all mice requiring euthanasia by 16 weeks. Gross changes comprised small, irregular liver, splenomegaly, cardiomegaly, and generalized pallor. Hematological abnormalities included severe thrombocytopenia and anemia. Pathologically, huNSGS spontaneously developed a disseminated histiocytosis with infiltrates of activated macrophages and hemophagocytosis predominantly affecting the liver, spleen, bone marrow, and pancreas. The infiltrates were chimeric with a mixture of human and mouse macrophages. Immunohistochemistry suggested activation of the inflammasome in both human and murine macrophages. Active Epstein-Barr virus infection was not a feature. Although the affected mice exhibited robust chimerism of the spleen and bone marrow, the phenotype often developed in the face of low chimerism of the peripheral blood. Given the high penetrance and early lethality associated with the MAS-like phenotype here described, we urge caution when considering the use of huNSGS mice for the development of long-term studies.

Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma

PURPOSE

To construct a multi-institutional radiomic model that supports upfront prediction of progression-free survival (PFS) and recurrence pattern (RP) in patients diagnosed with glioblastoma multiforme (GBM) at the time of initial diagnosis.

PATIENTS AND METHODS

We retrospectively identified data for patients with newly diagnosed GBM from two institutions (institution 1, n = 65; institution 2, n = 15) who underwent gross total resection followed by standard adjuvant chemoradiation therapy, with pathologically confirmed recurrence, sufficient follow-up magnetic resonance imaging (MRI) scans to reliably determine PFS, and available presurgical multiparametric MRI (MP-MRI). The advanced software suite Cancer Imaging Phenomics Toolkit (CaPTk) was leveraged to analyze standard clinical brain MP-MRI scans. A rich set of imaging features was extracted from the MP-MRI scans acquired before the initial resection and was integrated into two distinct imaging signatures for predicting mean shorter or longer PFS and near or distant RP. The predictive signatures for PFS and RP were evaluated on the basis of different classification schemes: single-institutional analysis, multi-institutional analysis with random partitioning of the data into discovery and replication cohorts, and multi-institutional assessment with data from institution 1 as the discovery cohort and data from institution 2 as the replication cohort.

RESULTS

These predictors achieved cross-validated classification performance (ie, area under the receiver operating characteristic curve) of 0.88 (single-institution analysis) and 0.82 to 0.83 (multi-institution analysis) for prediction of PFS and 0.88 (single-institution analysis) and 0.56 to 0.71 (multi-institution analysis) for prediction of RP.

CONCLUSION

Imaging signatures of presurgical MP-MRI scans reveal relatively high predictability of time and location of GBM recurrence, subject to the patients receiving standard first-line chemoradiation therapy. Through its graphical user interface, CaPTk offers easy accessibility to advanced computational algorithms for deriving imaging signatures predictive of clinical outcome and could similarly be used for a variety of radiomic and radiogenomic analyses.

An additive score optimized by a genetic learning algorithm predicts readmission risk after glioblastoma resection

Thirty-day readmission following glioblastoma (GBM) resection is not only correlated with decreased overall survival but also increasingly tied to quality metrics and reimbursement. This study aimed to determine factors linked with 30-day readmission to develop a simple risk stratification score. From 2005 to 2016, 666 unique resections (467 patients) of primary/recurrent tissue-confirmed glioblastoma were retrospectively identified. We recorded patient demographics and medical history, tumor characteristics, post-operative complications and 30-day readmission. Univariate and multivariate logistic regression, optimized using a genetic learning algorithm, were used to determine factors associated with readmission. The multivariate model was converted to a simple additive score. The 30-day readmission rate was 20.3% in our cohort of 666 unique resections (60.7% first resection). Lower pre/post-operative KPS, recurrent resection, surgical-site infection, post-operative VTE, post-operative VPS, and discharge to a rehabilitation facility were significantly associated with an increased readmission risk (p < 0.05). MGMT methylation and chemoradiation were associated with decreased readmission risk (p < 0.05). Medical co-morbidities and past medical history, location of tumor in eloquent areas of the brain, and length of ICU/hospital stay did not predict readmission. The Glioblastoma Readmission Risk Score, developed from the multivariate model, accounts for increased BMI, decreased pre-operative KPS, current smoking, post-operative complications, MGMT methylation, and post-operative radiation. This risk score can be routinely used to stratify risk and assist in clinical decision making and outcome analyses.

Abstract LB-356: Deep immune profiling of de novo and recurrent glioblastoma

To understand potential immune system alterations in glioblastoma patients and provide a foundation for immunotherapy, we profiled intra tumoral leucocytes from newly diagnosed de novo patients as well as patients with recurrent tumor using high dimensional CyTOF. All recurrent patients underwent standard-of-care therapy, including surgical resection, concurrent temozolomide and radiotherapy, and adjuvant temozolomide. We used two immune profiling panels: a broad profiling panel that includes 45 phenotypic markers that together permit the identification and enumeration of the main innate and adaptive immune cell subsets in humans, and a deep profiling panel that includes 45 features focused on T cell phenotype and biology. We report in both de novo and recurrent tumors a predominant infiltration by CD11b+CD14+ monocytes (43.6±13%. of CD45+ cells). These monocytes displayed an immunomodulatory M2 profile (CD163+HLA-DR-/+CD80-CD86-/+). The adaptive compartment was sparse and dominated by alpha beta T cells, although some mucosal associated invariant T cells and gamma delta T cells were also present. T cells were both conventional T cells and regulatory T cells. The latter tended to be more abundant in the de novo as compared to recurrent tumors (22.8±17.9% of CD4+ T cells in de novo vs 12.9±12.5% in recurrent tumors, P=0.09). Conventional T cells were mostly CD27-CD45RA- effectors, with high expression of PD1 (69.9±17.6% of CD8+ T cells). Using high dimensional approaches, we confirmed that this high expression of PD1 reflects T cell exhaustion, as defined by co-expression of other inhibitory receptors such as Tim3, CTLA-4 and LAG-3. Exhausted T cells typically co-expressed PD1 and CD39 in the de novo tumors, and this pattern was less often observed in recurrent tumors (63.4±22.84% of CD8+ T cells in de novo vs 46.3±14.5% in recurrent tumors, P=0.03). Together, our results highlight the potential issue of a substandard T cell compartment at the time of GBM diagnosis. We are now investigating the mechanisms underlying these observations, as well as their impact on T cell immunity of the patients, as well as current immunotherapy strategies. Our studies should provide a foundation for improving therapy in glioblastoma patients.

Citation Format: Cécile Alanio, Zev A. Binder, Donald M. O'Rourke, E. John Wherry. Deep immune profiling of de novo and recurrent glioblastoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-356.

A prospective validation cohort study of baseline plasma cell-free DNA (cfDNA) as a prognostic biomarker in newly diagnosed glioblastoma (GBM)

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Background: Due to significant interpatient heterogeneity, survival outcomes vary widely in patients with GBM. Novel prognostic biomarkers are needed. We aimed to determine the prognostic impact of baseline plasma cfDNA concentration in patients with GBM. Methods: We analyzed 84 patients with newly diagnosed GBM and at least 7 months of follow-up time. The first 41 patients comprised a previously published derivation cohort (Bagley, Clin Cancer Res 2020). The subsequent 43 patients served as an independent validation cohort. cfDNA was extracted from plasma collected prior to initial surgical resection and quantified by qPCR for a 115 bp amplicon of the human ALU repeat element. Receiver operating characteristic (ROC) curve analysis was used in the derivation cohort to (1) assess the accuracy of plasma cfDNA concentration for predicting progression-free survival status at 7 months (PFS-7), a landmark based on the median PFS for newly diagnosed GBM (Stupp, N Engl J Med 2005), and (2) derive the optimal cutoff for dichotomizing patients into high- and low-cfDNA groups. In the validation cohort, logistic regression was used to measure the association of plasma cfDNA concentration (high vs. low) with PFS-7, adjusted for age, isocitrate dehydrogenase ( IDH) 1/2 mutational status, 0-6-methylguanine-methyltransferase ( MGMT) methylation, extent of resection, and performance status. Multivariate Cox regression was used for overall survival (OS) analysis. Results: In the derivation cohort, the optimal cutoff for plasma cfDNA was 25.0 ng/mL (area under the curve [AUC] = 0.663), with inferior PFS and OS in patients with cfDNA above this cutoff (PFS, median 4.9 vs. 9.5 months, log-rank p = 0.001; OS, median 8.5 vs. 15.5 months, log-rank p = 0.03). In the validation cohort, baseline plasma cfDNA concentration over the cutoff was independently associated with a lower likelihood of being alive and progression-free at 7 months (adjusted OR 0.13, 95% CI 0.02 – 0.75, p = 0.02). OS was also worse in in the validation cohort in patients with high plasma cfDNA (adjusted HR 3.0, 95% CI 1.1 – 8.0, p = 0.03). Conclusions: In patients with newly diagnosed GBM, high baseline plasma cfDNA concentration is associated with worse survival outcomes independent of other prognostic factors. Further validation in a larger, multicenter study is warranted.

Multiomics profiling of longitudinal melanoma specimens unravels molecular mechanisms of resistance to sequential targeted and cancer immunotherapies

e22015

Background: We evaluated spatially-resolved protein profiling of longitudinal tumor specimens derived from two patients with metastatic melanoma who progressed on sequential therapies including targeted therapy (TT) and immune checkpoint blockade (ICB) therapy targeting T cell-surface antigens (CTLA-4 and PD-1). The purpose of this study was to identify molecular determinants of resistance to sequential TT and ICB therapies. Methods: We performed multiplexed and multidimensional spatial protein profiling using NanoString’s GeoMx Digital Spatial Profiling (DSP) platform and single-cell level imaging analysis with Cyclic Immunofluorescence (CycIF) to simultaneously determine dynamic changes in tumor intrinsic signaling pathways and immune response in the tumor microenvironment (TME). Results: The first patient presented with a BRAFV600E-positive brain metastasis. This patient was sequentially treated with ipilimumab (Ipi), the combination of dabrafenib and trametinib, and pembrolizumab (Pembro) and progressed despite of high expression of CD56 NK cell after all treatments. In addition, CycIF analysis revealed drug resistance in a subpopulation of cells that had continued activation of mTOR (pS6) and EGFR pathways. The second patient presented with dermal metastases on the flank with NRASQ61K mutation. This patient was sequentially treated with Pembo, Talimogene Laherparepvec, the combination of Ipi plus nivolumab, and two different investigational agents combined with Pembro. This patient displayed stable disease (SD) on Pembro but eventually progressed on the subsequent therapies. DSP analysis demonstrated CD68/CD40 myeloid cell infiltrates as well as HLA-DR and CD44 in the TME after the last treatment. CycIF analysis revealed dynamic changes in tumoral characteristics including DNA damage and proliferation during treatment. Furthermore, the analysis suggested that there might be a resistant subpopulation in the last tumor biopsy, which is in line with progression of the disease. Conclusions: In this study, we conducted detailed analyses on serial specimens from two patients to precisely define the spatial distribution of immune responses and cancer signaling pathways. The findings propose that concurrent proteomics analysis and immune monitoring of longitudinal tumor biopsies can be informative in clinical evaluation in order to identify salvage therapies to overcome drug resistance.

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.

Potential of Glioblastoma-Targeted Chimeric Antigen Receptor (CAR) T-Cell Therapy

Despite the established efficacy of chimeric antigen receptor (CAR) T-cell therapy in hematologic malignancies, translating CAR T therapy to solid tumors has remained investigational. Glioblastoma, the most aggressive and lethal form of primary brain tumor, has recently been among the malignancies being trialed clinically with CAR T cells. Glioblastoma in particular holds several unique features that have hindered clinical translation, including its vast intertumoral and intratumoral heterogeneity, associated immunosuppressive environment, and lack of clear experimental models to predict response and analyze resistant phenotypes. Here, we review the history of CAR T therapy development, its current progress in treating glioblastoma, as well as the current challenges and future directions in establishing CAR T therapy as a viable alternative to the current standard of care. Tremendous efforts are currently ongoing to identify novel CAR targets and target combinations for glioblastoma, to modify T cells to enhance their efficacy and to enable them to resist tumor-mediated immunosuppression, and to utilize adjunct therapies such as lymphodepletion, checkpoint inhibition, and bi-specific engagers to improve CAR T persistence. Furthermore, new preclinical models of CAR T therapy are being developed that better reflect the clinical features seen in human trials. Current clinical trials that rapidly incorporate key preclinical findings to patient translation are emerging.

Clinical Utility of Plasma Cell-Free DNA in Adult Patients with Newly Diagnosed Glioblastoma: A Pilot Prospective Study

PURPOSE

The clinical utility of plasma cell-free DNA (cfDNA) has not been assessed prospectively in patients with glioblastoma (GBM). We aimed to determine the prognostic impact of plasma cfDNA in GBM, as well as its role as a surrogate of tumor burden and substrate for next-generation sequencing (NGS).

EXPERIMENTAL DESIGN

We conducted a prospective cohort study of 42 patients with newly diagnosed GBM. Plasma cfDNA was quantified at baseline prior to initial tumor resection and longitudinally during chemoradiotherapy. Plasma cfDNA was assessed for its association with progression-free survival (PFS) and overall survival (OS), correlated with radiographic tumor burden, and subjected to a targeted NGS panel.

RESULTS

Prior to initial surgery, GBM patients had higher plasma cfDNA concentration than age-matched healthy controls (mean 13.4 vs. 6.7 ng/mL, P < 0.001). Plasma cfDNA concentration was correlated with radiographic tumor burden on patients' first post-radiation magnetic resonance imaging scan (ρ = 0.77, P = 0.003) and tended to rise prior to or concurrently with radiographic tumor progression. Preoperative plasma cfDNA concentration above the mean (>13.4 ng/mL) was associated with inferior PFS (median 4.9 vs. 9.5 months, P = 0.038). Detection of ≥1 somatic mutation in plasma cfDNA occurred in 55% of patients and was associated with nonstatistically significant decreases in PFS (median 6.0 vs. 8.7 months, P = 0.093) and OS (median 5.5 vs. 9.2 months, P = 0.053).

CONCLUSIONS

Plasma cfDNA may be an effective prognostic tool and surrogate of tumor burden in newly diagnosed GBM. Detection of somatic alterations in plasma is feasible when samples are obtained prior to initial surgical resection.

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.

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.

Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients

Glioblastoma, the most frequent primary malignant brain neoplasm, is genetically diverse and classified into four transcriptomic subtypes, i. e., classical, mesenchymal, proneural, and neural. Currently, detection of transcriptomic subtype is based on ex vivo analysis of tissue that does not capture the spatial tumor heterogeneity. In view of accumulative evidence of in vivo imaging signatures summarizing molecular features of cancer, this study seeks robust non-invasive radiographic markers of transcriptomic classification of glioblastoma, based solely on routine clinically-acquired imaging sequences. A pre-operative retrospective cohort of 112 pathology-proven de novo glioblastoma patients, having multi-parametric MRI (T1, T1-Gd, T2, T2-FLAIR), collected from the Hospital of the University of Pennsylvania were included. Following tumor segmentation into distinct radiographic sub-regions, diverse imaging features were extracted and support vector machines were employed to multivariately integrate these features and derive an imaging signature of transcriptomic subtype. Extracted features included intensity distributions, volume, morphology, statistics, tumors' anatomical location, and texture descriptors for each tumor sub-region. The derived signature was evaluated against the transcriptomic subtype of surgically-resected tissue specimens, using a 5-fold cross-validation method and a receiver-operating-characteristics analysis. The proposed model was 71% accurate in distinguishing among the four transcriptomic subtypes. The accuracy (sensitivity/specificity) for distinguishing each subtype (classical, mesenchymal, proneural, neural) from the rest was equal to 88.4% (71.4/92.3), 75.9% (83.9/72.8), 82.1% (73.1/84.9), and 75.9% (79.4/74.4), respectively. The findings were also replicated in The Cancer Genomic Atlas glioblastoma dataset. The obtained imaging signature for the classical subtype was dominated by associations with features related to edge sharpness, whereas for the mesenchymal subtype had more pronounced presence of higher T2 and T2-FLAIR signal in edema, and higher volume of enhancing tumor and edema. The proneural and neural subtypes were characterized by the lower T1-Gd signal in enhancing tumor and higher T2-FLAIR signal in edema, respectively. Our results indicate that quantitative multivariate analysis of features extracted from clinically-acquired MRI may provide a radiographic biomarker of the transcriptomic profile of glioblastoma. Importantly our findings can be influential in surgical decision-making, treatment planning, and assessment of inoperable tumors.

18F-Fluciclovine PET to distinguish treatment-related effects from disease progression in recurrent glioblastoma: PET fusion with MRI guides neurosurgical sampling

Differentiation of true tumor progression from treatment-related effects remains a major unmet need in caring for patients with glioblastoma. Here, we report how the intraoperative combination of MRI with¹⁸F-fluciclovine PET guided surgical sampling in 2 patients with recurrent glioblastoma.¹⁸F-Fluciclovine PET is FDA approved for use in prostate cancer and carries an orphan drug designation in glioma. To investigate its utility in recurrent glioblastoma, we fused PET and MRI images using 2 different surgical navigation systems and performed targeted stereotactic biopsies from the areas of high (“hot”) and low (“cold”) radiotracer uptake. Concordant histopathologic and imaging findings suggest that a combined¹⁸F-fluciclovine PET-MRI–guided approach can guide neurosurgical resection of viable recurrent glioblastoma in the background of treatment-related effects, which can otherwise look similar on MRI.

Rapid and ultrasensitive digital PCR (dPCR) profiling of EGFRvIII in tumor cells and tissues

Background

Amplification of the epidermal growth factor receptor (EGFR) gene is commonly found in glioblastoma (GBM). About 57% GBM overexpresses EGFR and are associated with tumor progression, poor prognosis, and shorter life expectancy. Molecular profiling of solid tumors usually takes several weeks and may be biased by intrinsic tumor heterogeneity.

Methods

The unique sequence created by the fusion of exon 1 and exon 8 in EGFRvIII was used to guide the design of primers and a Minor Groove Binder (MGB) probe. Extracted total RNA was reverse transcribed and pre-amplified by PCR, followed by detection of the EGFRvIII mutation by dPCR.

Results

The lowest limit of quantification of our EGFRvIII assay was 0.003%. The EGFRvIII variant was identified in patient-derived glioma neurosphere cell lines, xenograft mouse model, and patient-derived tumor specimens. The overall workflow can be accomplished within 24 hours. In certain samples, EGFRvIII was detected when next-generation sequencing was unable to identify the variant. This finding highlights the ability of the dPCR assay to identify EGFRvIII mutations in heterogeneous solid tumors such as GBM in a rapid fashion by profiling samples from spatially distinct areas of tumors from the same patient.

Conclusions

In this study, we developed a highly sensitive digital PCR (dPCR) platform and leveraged our assay to detect the variant III alteration of EGFR (EGFRvIII) and amplified EGFR in patient-derived glioma neurosphere cell lines, orthotopic xenograft GBM mouse models, and patient-derived tumor specimens in less than 24 hours from minute quantities of starting material.

Clinical activity of the EGFR tyrosine kinase inhibitor osimertinib in EGFR-mutant glioblastoma

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and carries a dismal prognosis. The EGFR gene is among the most commonly deranged genes in GBM and thus an important therapeutic target. We report the case of a young female with heavily pretreated EGFR-mutated GBM, for whom we initiated osimertinib, an oral, third-generation tyrosine kinase inhibitor that irreversibly inhibits EGFR and has significant brain penetration. We then review some of the main challenges in targeting EGFR, including lack of central nervous system penetration with most tyrosine kinase inhibitors, molecular heterogeneity of GBM and the need for enhanced specificity for the EGFR mutations relevant in GBM.

CAR T-cell therapy for glioblastoma: recent clinical advances and future challenges

In patients with certain hematologic malignancies, the use of autologous T cells genetically modified to express chimeric antigen receptors (CARs) has led to unprecedented clinical responses. Although progress in solid tumors has been elusive, recent clinical studies have demonstrated the feasibility and safety of CAR T-cell therapy for glioblastoma. In addition, despite formidable barriers to T-cell localization and effector function in glioblastoma, signs of efficacy have been observed in select patients. In this review, we begin with a discussion of established obstacles to systemic therapy in glioblastoma and how these may be overcome by CAR T cells. We continue with a summary of previously published CAR T-cell trials in GBM, and end by outlining the key therapeutic challenges associated with the use of CAR T cells in this disease.

A Randomized Double-Blind Placebo-Controlled Phase II Trial of Dendritic Cell Vaccine ICT-107 in Newly Diagnosed Patients with Glioblastoma

PURPOSE

To evaluate the results of the randomized, double-blind, placebo-controlled phase II clinical trial of ICT-107 in patients with newly diagnosed glioblastoma.

PATIENTS AND METHODS

We conducted a double-blinded randomized phase II trial of ICT-107 in newly diagnosed patients with glioblastoma (GBM) and tested efficacy, safety, quality of life (QoL), and immune response. HLA-A1⁺ and/or -A2⁺-resected patients with residual tumor ≤1 cm³ received radiotherapy and concurrent temozolomide. Following completion of radiotherapy, 124 patients, randomized 2:1, received ICT-107 [autologous dendritic cells (DC) pulsed with six synthetic peptide epitopes targeting GBM tumor/stem cell-associated antigens MAGE-1, HER-2, AIM-2, TRP-2, gp100, and IL13Rα2] or matching control (unpulsed DC). Patients received induction ICT-107 or control weekly × 4 followed by 12 months of adjuvant temozolomide. Maintenance vaccinations occurred at 1, 3, and 6 months and every 6 months thereafter.

RESULTS

ICT-107 was well tolerated, with no difference in adverse events between the treatment and control groups. The primary endpoint, median overall survival (OS), favored ICT-107 by 2.0 months in the intent-to-treat (ITT) population but was not statistically significant. Progression-free survival (PFS) in the ITT population was significantly increased in the ICT-107 cohort by 2.2 months (P = 0.011). The frequency of HLA-A2 primary tumor antigen expression was higher than that for HLA-A1 patients, and HLA-A2 patients had higher immune response (via Elispot). HLA-A2 patients achieved a meaningful therapeutic benefit with ICT-107, in both the MGMT methylated and unmethylated prespecified subgroups, whereas only HLA-A1 methylated patients had an OS benefit.

CONCLUSIONS

PFS was significantly improved in ICT-107-treated patients with maintenance of QoL. Patients in the HLA-A2 subgroup showed increased ICT-107 activity clinically and immunologically.

Assessing variability in surgical decision making among attending neurosurgeons at an academic center

OBJECTIVE

Although it is known that intersurgeon variability in offering elective surgery can have major consequences for patient morbidity and healthcare spending, data addressing variability within neurosurgery are scarce. The authors performed a prospective peer review study of randomly selected neurosurgery cases in order to assess the extent of consensus regarding the decision to offer elective surgery among attending neurosurgeons across one large academic institution.

METHODS

All consecutive patients who had undergone standard inpatient surgical interventions of 1 of 4 types (craniotomy for tumor [CFT], nonacute redo CFT, first-time spine surgery with/without instrumentation, and nonacute redo spine surgery with/without instrumentation) during the period 2015-2017 were retrospectively enrolled (n = 9156 patient surgeries, n = 80 randomly selected individual cases, n = 20 index cases of each type randomly selected for review). The selected cases were scored by attending neurosurgeons using a need for surgery (NFS) score based on clinical data (patient demographics, preoperative notes, radiology reports, and operative notes; n = 616 independent case reviews). Attending neurosurgeon reviewers were blinded as to performing provider and surgical outcome. Aggregate NFS scores across various categories were measured. The authors employed a repeated-measures mixed ANOVA model with autoregressive variance structure to compute omnibus statistical tests across the various surgery types. Interrater reliability (IRR) was measured using Cohen's kappa based on binary NFS scores.

RESULTS

Overall, the authors found that most of the neurosurgical procedures studied were rated as "indicated" by blinded attending neurosurgeons (mean NFS = 88.3, all p values < 0.001) with greater agreement among neurosurgeon raters than expected by chance (IRR = 81.78%, p = 0.016). Redo surgery had lower NFS scores and IRR scores than first-time surgery, both for craniotomy and spine surgery (ANOVA, all p values < 0.01). Spine surgeries with fusion had lower NFS scores than spine surgeries without fusion procedures (p < 0.01).

CONCLUSIONS

There was general agreement among neurosurgeons in terms of indication for surgery; however, revision surgery of all types and spine surgery with fusion procedures had the lowest amount of decision consensus. These results should guide efforts aimed at reducing unnecessary variability in surgical practice with the goal of effective allocation of healthcare resources to advance the value paradigm in neurosurgery.

Molecular Neuropathology in Practice: Clinical Profiling and Integrative Analysis of Molecular Alterations in Glioblastoma

Molecular profiling of glioblastoma has revealed complex cytogenetic, epigenetic, and molecular abnormalities that are necessary for diagnosis, prognosis, and treatment. Our neuro-oncology group has developed a data-driven, institutional consensus guideline for efficient and optimal workup of glioblastomas based on our routine performance of molecular testing. We describe our institution’s testing algorithm, assay development, and genetic findings in glioblastoma, to illustrate current practices and challenges in neuropathology related to molecular and genetic testing. We have found that coordination of test requisition, tissue handling, and incorporation of results into the final pathologic diagnosis by the neuropathologist improve patient care. Here, we present analysis of O⁶-methylguanine-DNA-methyltransferase promoter methylation and next-generation sequencing results of 189 patients, obtained utilizing our internal processes led by the neuropathology team. Our institutional pathway for neuropathologist-driven molecular testing has streamlined the management of glioblastoma samples for efficient return of results for incorporation of genomic data into the pathological diagnosis and optimal patient care.

Evaluating the Association Between the Extent of Resection and Survival in Gliosarcoma

Introduction: Gliosarcoma (GS) is a rare, malignant mixed tumor of the central nervous system with a median survival of approximately 13 months across multiple studies. Although the value of the extent of resection (EOR) has been confirmed as a prognostic survival factor in glioblastoma, no such association has been defined for GS. The goal of this study was to establish an association between EOR and survival and to determine if a threshold of resection exists for which a survival benefit is conferred in GS.

Methods: The authors identified 11 patients with histologically confirmed GS between January 2005 and January 2015, treated at the Hospital of the University of Pennsylvania. Clinical, radiographic, and outcome data were retrospectively reviewed. Volumetric analysis was completed using semi-automated segmentation to measure the change in contrast-enhancing material based on preoperative T1-contrast (T1c) and postoperative T1 & T1c magnetic resonance imaging (MRI) scans. A log-rank test was completed to confirm an association between EOR and survival, and a series of Kaplan-Meier curves were constructed to determine an EOR threshold. Univariate Cox proportional hazards model (CPHM) followed by multivariate CPHM was also completed to evaluate associations between the prognostic clinical and immunohistochemistry variables under consideration.

Results: Extent of resection categories were defined as gross total resection (GTR >95%), subtotal resection (STR 90%-95%), and partial resection (PR <90%). The median overall survival for the groups were as follows: GTR-17.3 months (n=4), STR-12.6 months (n=5), PR-4.3 months (n=2). A statistically significant association (p=05 level) was found between survival and the PR group with the GTR group as reference. Multivariate CPHM confirmed a statistically significant association between increased survival and age, preoperative Karnofsky Performance Status (KPS) scores, postoperative KPS scores, and KI-67 index. Serial Kaplan-Meier curves suggest a survival benefit with an EOR threshold of 94%.

Conclusion: This study agrees with previous correlations in glioblastoma EOR and prolonged survival. For patients undergoing surgical resection for GS, maximal surgical removal, when safely possible, should be attempted as it appears to translate to longer survival times.

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.

Detection of occult neoplastic infiltration in the corpus callosum and prediction of overall survival in patients with glioblastoma using diffusion tensor imaging

OBJECTIVE

Corpus callosum (CC) involvement is a poor prognostic factor in patients with glioblastoma (GBM). The purpose of this study was to determine whether diffusion tensor imaging (DTI) can quantify occult tumor infiltration in the CC and predict the overall survival in GBM patients.

METHODS

Forty-eight patients with pathologically proven GBM and 17 normal subjects were included in this retrospective study. Patients were divided into four groups based on CC invasion and overall survival: long survivors without CC invasion; short survivors without CC invasion; long survivors with CC invasion; short survivors with CC invasion. All patients underwent DTI at 3T MRI scanner. Fractional anisotropy (FA) and mean diffusivity (MD) values were measured from genu, mid-body, and splenium of the CC. The mean values of these parameters were compared between different groups and Kaplan Meier curves were used for prediction of overall survival.

RESULTS

Patients with short survival and CC invasion had the lowest FA values (0.64 ± 0.05) from the CC compared with other groups (p < 0.05). Receiver operator characteristic curve (ROC) analysis indicated that a FA cutoff value of 0.70 was the best predictor for overall survival with an area under the curve (AUC) of 0.77, sensitivity 1, specificity 0.59. Kaplan-Meier survival curves demonstrated that the mean survival time was significantly longer for patients with high FA (>0.70) compared with those with low FA (<0.70) (p < 0.001).

CONCLUSIONS

FA values from the CC can quantify occult tumor infiltration and serve as a sensitive prognostic marker for prediction of overall survival in GBM patients.

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.

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.