Citations

Abstract Purpose: Glioblastoma is the most frequent and lethal primary brain tumor. Development of novel therapies relies on the availability of relevant preclinical models. We have established a panel of 96 glioblastoma patient-derived xenografts (PDX) and undertaken its genomic and phenotypic characterization. Experimental Design: PDXs were established from glioblastoma, IDH-wildtype (n = 93), glioblastoma, IDH-mutant (n = 2), diffuse midline glioma, H3 K27M-mutant (n = 1), and both primary (n = 60) and recurrent (n = 34) tumors. Tumor growth rates, histopathology, and treatment response were characterized. Integrated molecular profiling was performed by whole-exome sequencing (WES, n = 83), RNA-sequencing (n = 68), and genome-wide methylation profiling (n = 76). WES data from 24 patient tumors was compared with derivative models. Results: PDXs recapitulate many key phenotypic and molecular features of patient tumors. Orthotopic PDXs show characteristic tumor morphology and invasion patterns, but largely lack microvascular proliferation and necrosis. PDXs capture common and rare molecular drivers, including alterations of TERT, EGFR, PTEN, TP53, BRAF, and IDH1, most at frequencies comparable with human glioblastoma. However, PDGFRA amplification was absent. RNA-sequencing and genome-wide methylation profiling demonstrated broad representation of glioblastoma molecular subtypes. MGMT promoter methylation correlated with increased survival in response to temozolomide. WES of 24 matched patient tumors showed preservation of most genetic driver alterations, including EGFR amplification. However, in four patient–PDX pairs, driver alterations were gained or lost on engraftment, consistent with clonal selection. Conclusions: Our PDX panel captures the molecular heterogeneity of glioblastoma and recapitulates many salient genetic and phenotypic features. All models and genomic data are openly available to investigators.

Abstract Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood–brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. Significance: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment. See related commentary by Tan and Weljie, p. 1231

Abstract INTRODUCTION Neuroimaging dogma for glioblastoma asserts that hyperintensity on T1Gd MRI reveals the bulk of the tumor, while T2/FLAIR signal indicates edema. However, it is unclear whether this edema results from immune response or increased tumor cells. Further, one significant driver of the known sex differences in glioblastoma may be differences in immune response, due to the X-linkage of many immune genes. Based on this, we hypothesized that assumptions regarding tumor cellularity in T2/FLAIR images should be tailored to the biological sex of the patient. METHODS Using a retrospective cohort of 18 primary glioblastoma patients receiving multiple image-localized biopsies (82 total) and standard MRI, we assessed: distance of biopsy from T1Gd and T2 areas; a pathologist’s score of percent tumor cell density; and an imaging-based invasion metric, D/ρ. This metric is derived from the biomathematical Proliferation-Invasion model of glioma growth, which features two parameters, net growth rate (ρ) and net invasion rate (D). Their ratio D/ρ is related to degree of invasion, and is estimated from volumetric measurements of MRI abnormalities. Additionally, 25 patient-derived xenograft models implanted in females were grown until moribund, at which point brains were excised and stained for DAPI (to show all cells) and Lamin (to highlight tumor cells). Image processing of lamin-stained sections defines contours of intensity correlating with cell density. RESULTS Outside both the T1Gd and T2 region, male patient biopsies had higher tumor cell densities than females. Males also tended to have higher invasion metrics. Although each set derived from different patients, preclinical metrics of invasion were positively correlated with clinical invasion in females but negatively correlated in males. CONCLUSION Our preliminary finding that cell distribution patterns correlate with imaging metrics differently between the sexes supports the hypothesis that the degree of tumor cell density represented on certain MRI sequences may be sex-specific.

Abstract BACKGROUND Efficacy of chimeric antigen receptor T cell (CART) therapy remains limited in solid tumors. Given the heterogeneity of surface receptor expression and immunosuppressive stromal microenvironment, strategies to target tumor neovasculature and tumor stromal cells are needed to help overcome CART inhibition by GBM. Eph receptors are the largest family of receptor tyrosine kinases and are integral to cell adhesion, migration, and axon guidance, during development and homeostasis. EphA3 is a receptor tyrosine kinase which is lowly expressed in adult tissues but is highly expressed in tumor neovasculature and tumor stromal cells in GBM and other solid tumors. EphA3 is over-expressed in up to 40% of GBM samples. We aimed to develop CART cells directed against EphA3 to use in targeting tumor neovasculature and tumor stromal cells in GBM. METHODS we developed a second generation CD28 co-stimulated CAR construct in a third generation lentivirus backbone to generate EphA3 CART cells using the single chain variable fragment of ifabotuzumab, a monoclonal antibody directed against EphA3. Patient derived GBM xenograft cell lines were used in these experiments. RESULTS EphA3 directed CART cells exhibited specific and potent antitumor activity against EphA3+ GBM cell lines with variable transcriptome EphA3 expression indicating its broader applicability in patients with GBM. Killing over 24-hour incubation was significant at low effector: target ratio: 52.5% killing at 1.25:1 against cell lines with 25.05% EphA3 expression and 37.1% killing at 1.25:1and 90% killing at 5:1 ratio against a cell line with 19.28% expression. Conversely, when co-cultured with UTD controls there was significantly lower killing, or growth of tumor cells. CONCLUSION We demonstrate for the first time that targeting EphA3 with CART cells is feasible, efficacious and represents a novel therapeutics strategy to target GBM. Data from in vivo and combinatorial CART experiments will be reported at the meeting.

Abstract Glioblastoma (GBM) is the most common and deadly type of malignant brain cancer in adults. While current standard of care which combines resection, radiation therapy (RT) and Temozolomide (TMZ) effectively eliminates primary disease, recurrence is inevitable, occurs rapidly following treatment and is ultimately lethal due to limited therapeutic opportunities of recurrent GBM. Hypermutation has been reported to occur in a subset of both low and high-grade gliomas and emerges after exposure to TMZ. Mutational inactivation and loss of mismatch repair (MMR) gene expression lead to the accumulation of single nucleotide polymorphisms throughout the genome. To date, the gain of hypermutation and subsequent therapeutic responses are still largely unknown. We hypothesized that hypermutant (HM) and non-hypermutant (NH) tumors represent two recurrent GBM subtypes, which has distinct therapeutic vulnerabilities. In addition, given the lack of concordance between microsatellite instability (MSI) and occurrence of hypermutation in GBM, we sought to derive a limited gene panel which can be used as surrogate biomarker for hypermutation following TMZ to replace whole exome sequencing (WES). Using public datasets, we demonstrated that recurrent GBM can be clustered into two subtypes: HM and NH. We used matched primary and recurrent GBM datasets to derive a gene panel signature, which is uniquely mutated at recurrence in HM GBM and confirmed the specificity of this panel in an independent dataset. Furthermore, we utilized patient derived xenograft (PDX) models to generate pre-clinical models and demonstrated that HM recurrent GBM are more immune responsive while NH recurrent GBM maintained sensitivity to a range of alternate chemotherapies such as cisplatin and RT. Finally, we demonstrated that this signature is represented in exosomes and can be enriched by use of tumor specific antibody capture methods to improve the sensitivity of hypermutation detection in liquid biopsy.

Abstract In glioblastoma (GBM), invasion and proliferation are reciprocally related—e.g., targeting one stimulates the other. Thus, effective therapy for GBM requires finding targets that drive both invasion and proliferation and which are druggable, ideally with FDA approved therapeutics. We find that the atypical protein kinase C isoform, PKCi meets these criteria. Using a human GBM tissue microarray, we find that PKCi protein expression fits a bimodal distribution, with >35% of GBMs showing high levels of PKCi expression. Genetic deletion of Prkci, the gene encoding mouse PKCi, impairs tumor invasion and proliferation both in vitro and in vivo, and significantly prolongs survival in an immunocompetent PDGF-driven orthotopic mouse model of GBM. PKCi can be selectively targeted with Auranofin, a small molecule PKCi inhibitor that has been FDA approved for treatment of inflammatory diseases. Like genetic deletion of Prkci Auranofin treatment significantly prolongs survival in our murine GBM model, and does so to a similar degree. Interestingly, analysis of a panel of human and murine GBM cells reveals that sensitivity to Auranofin inhibition of transformed growth directly correlates with expression of PKCi, indicating that PKCi expression profiling could serve as a predictive biomarker for responsiveness to Auranofin. However, genetically deleting or pharmacologically inactivating PKCi does not permanently arrest tumor growth, implying that GBM cells acquire mechanisms that allow them to compensate for the loss of this important signaling molecule. We are currently examining potential “escape” mechanisms through ‘omics-based approaches, which may enable us to enhance the therapeutic potential of Auranofin. Taken together, our results demonstrate that PKCi is a compelling therapeutic target for treatment of GBM that deserves further investigation.

Abstract Glioblastoma (GBM) is a common deadly malignant brain cancer of the central nervous system (CNS), with a median survival of 12–15 months. Scientific advancements are lacking in developing effective therapies for both primary GBM, as well as secondary GBMs, that typically originate as malignant transformation of lower-grade isocitrate dehydrogenase (IDH) 1-mutant tumors. The unique metabolomic profile of IDH1-mutant tumors may present opportunities to develop biomarker signatures of therapeutic efficacy. Microdialysis is an extracellular fluid sampling collection technique utilizing a perfused semipermeable catheter to permit diffusion of molecules between brain interstitium and the perfusate. We hypothesized that microdialysis may identify a metabolomics-based biomarker response to therapy in IDH1-mutant tumors. To test this hypothesis, orthotopic xenografts were generated from two patient-derived GBM lines harboring mutations in IDH1. Perfusates were collected from intra-cranial tumors in aythmic nude mice sampled at baseline and 72h post treatment with temozolomide, an oral alkylating agent used to treat IDH1-mutant gliomas, compared with vehicle treatment, and TMZ-treated non-tumor bearing animals. Perfusates were analyzed via unsupervised metabolomic profiling using both gas and liquid chromatography-mass spectrometry (GC/LC-MS). Tumor specific metabolites such as carnitine and pyruvic acid were detected in microdialysate from tumor bearing mice compared to non-tumor bearing mice. Microdialysis is a feasible technology to identify metabolomics-based biomarker in IDH1-mutant PDX. This work is complemented by parallel analysis of non-IDH1-mutant and TMZ resistant xenografts to yield predictive in vivo tissue biomarkers of drug responsiveness translatable to clinical practice.

Abstract EGFR gene amplification and mutation are common in glioblastoma (GBM), but EGFR inhibition is not effective in treating this tumor. EGFR inhibition may fail because EGFR is not a driver of the malignant phenotype in GBM, or because adaptive compensatory mechanisms are triggered by EGFR inhibition that prevent cell death from a loss of EGFR signaling. We have recently identified a TNFα-JNK-Axl-ERK signaling axis that mediates primary resistance to EGFR inhibition in GBM. Temozolomide (TMZ) is the most effective chemotherapy in GBM, although it has only a modest effect on overall survival. The efficacy of TMZ depends on the absence of the DNA repair protein O6-alkylguanine DNA alkyltransferase (MGMT) which reverses the DNA damage induced by TMZ. The MGMT promoter is hypermethylated in about 45% of GBMs, resulting in lack of MGMT expression. TMZ is less effective in MGMT unmethylated GBMs. Moreover, even initially responsive tumors develop a secondary resistance to TMZ. No treatment is effective in recurrent TMZ-resistant GBM. In this study, we compare the efficacy of temozolomide versus EGFR plus TNF inhibition in an orthotopic model of GBM. We find that efficacy of the two treatments is similar in MGMT-methylated GBMs. However, in MGMT-unmethylated GBMs, a combination of EGFR plus TNF inhibition is more effective. We demonstrate that the two treatment approaches target distinct and non-overlapping pathways. Furthermore, and importantly, EGFR plus TNF inhibition remains effective in TMZ-resistant recurrent GBMs and in GBMs rendered experimentally resistant to TMZ. Since the EGFR is expressed in the majority of GBMs, EGFR inhibition combined with a blunting of the accompanying TNF-driven adaptive response could be a broadly applicable and viable therapeutic approach in primary GBMs with MGMT unmethylation and in recurrent GBMs.

Abstract INTRODUCTION Glioblastoma (GBM) is an aggressive primary brain tumor, known for its poor prognosis. Due to its diffuse invasiveness into normal-appearing brain, localized treatments such as surgical resection and radiotherapy are typically supplemented with chemotherapy. However, to reach invading tumor cells, such antineoplastic drugs must cross the blood-brain barrier (BBB). That is, while angiogenesis induces BBB breakdown in dense tumor regions, the BBB remains rather intact for invading GBM cells. As a result, it is unclear whether BBB-impermeable drugs are delivered at a sufficient level to be effective. METHODS In order to study heterogeneity in BBB breakdown, experiments were conducted using both flank and intracranial patient-derived xenografts (PDXs) treated with the EGFR-targeted monoclonal antibody drug conjugate, depatuxizumab mafodotin (ABT-414). Time-series bioluminescence imaging (BLI) data was used to develop a differential equation model of tumor growth for three PDX cell lines. Data from untreated PDXs, both in flank and intracranially, were used to parameterize tumor proliferation rates. Flank PDX data were used to parameterize individual sensitivity to ABT-414, whereas intracranial PDX data were used to determine the proportion of drug exposed to the tumor. RESULTS Each PDX line differed in response to the study drug ABT-414. As expected, such heterogeneous responses can primarily be attributed to differences in both drug sensitivity and the proportion of drug that reached the tumor. Notably, the estimated proportion of drug that reached the tumor was highest in the PDX line with the longest survival times, despite also having higher estimates of resistance. This suggests that PDXs with greater overall BBB breakdown may respond better to this agent. CONCLUSIONS Although more cell lines are needed to validate our approach, parameterizing this model for PDXs gives valuable insight into the extent of BBB breakdown in patient GBMs and may aid in determining optimal therapies for individual patients.

Abstract Therapeutic resistance stemming from inter and intra-tumoral heterogeneity is a significant impediment towards development of effective therapeutics for glioblastoma. We hypothesized that microRNAs can potentially counteract resistance emanating from such heterogeneity as they simultaneously modulate the expression of multiple proteins. We identified microRNA-34a as a unique microRNA which modulates multiple oncoproteins in GBM using two different in silico approaches. We investigated the therapeutic effects of microRNA-34a in three primary patient-derived xenografts (PDX) representing classical (GBM6), proneural (GBM118) and mesenchymal (GBM118) subtypes; four established cell lines (T98G, U251, A172, LN229) and two cell lines with acquired resistance to temozolomide (A172-TR, LN229-TR) in vitro. Glioblastoma cell cultures showed variable responses to temozolomide but microRNA-34a inhibited proliferation in all cell cultures. Furthermore, microRNA-34a also sensitized all tested cell lines to temozolomide (combination index < 0.8, p=.03) and radiation treatment (dose enhancement factor 1.7–2.2, p=0.02). Mechanistically, microRNA 34a down-regulates at least six distinct therapeutic resistance proteins. Importantly, these resistance proteins are expressed in distinct spatial niches and are prognostic for patient survival based on our analysis of the cancer genome atlas (TCGA) data. For in vivo delivery of microRNA-34a, we utilized nanocells which are derived from genetically modified bacteria, loaded with microRNA-34a and tagged with a bispecific antibody targeting EGFR. Nanocells were injected intravenously while temozolomide was administered by oral gavage in an orthotopic PDX model. We confirmed delivery of microRNA-34a to tumor by observing down-regulation of cMet and phosphorylated Akt in treated mice. Importantly, microRNA-34a nanocells resulted in significant reduction in tumor growth (p=0.021), increased survival (p<0.001) with microRNA-34a monotherapy and synergy in combination with temozolomide in vivo. Taken together, our results suggest that delivery of miR-34a may be a powerful new adjuvant for the treatment of glioblastoma in combination with temozolomide that can mitigate both inter- and intra-tumor heterogeneity.