Sims, Peter A.

Abstract While the allure of targeted therapies in oncology has been their high degree of specificity and potency for key tumor drivers, they have been disappointing in glioblastoma (GBM), even for drugs that are blood brain barrier permeable and CNS retained. This point is highlighted by the experience with mitotic spindle inhibitors, drugs which block the G2M transition and induce mitotic catastrophe—a phenotype characterized by cell enlargement and polyploidy that leads to apoptotic cell death. We have shown that one of these, a potent inhibitor of the mitotic kinesin Kif11 (ispinesib), is highly active against GBM tumor initiating cells and prolongs survival in murine models of this disease. However, tumors eventually progress, reflecting the development of drug resistance. Although ispinesib resistant GBM cells develop mitotic catastrophe, they become highly resistant to the apoptosis that typically follows and continue to proliferate. We find that this apoptosis resistance requires phosphorylation of the transcription factor STAT3 at two residues—Y705 and S727. Phosphorylation of Y705, mediated by SRC kinase, translocates STAT3 to the nucleus where it induces transcription of anti-apoptotic proteins. Phosphorylation at S727, mediated by EGFR, translocates STAT3 to the mitochondria where it blocks release of cytochrome c—the penultimate effector in apoptosis. Simultaneously inhibiting both SRC and EGFR with FDA-approved, CNS permeant inhibitors reverses this resistance and significantly prolongs survival in ispinesib-treated GBM-bearing mice. Furthermore, we find that resistance to several other mitotic inhibitors also utilizes this STAT3-driven mechanism and can likewise be reversed with combined EGFR and SRC inhibition. Thus, our work demonstrates how a promising therapeutic approach, which has been disappointing in GBM, can in fact be rendered effective by anticipating and prospectively treating ab initio the mechanism that drives treatment resistance.

Abstract High-grade gliomas (HGGs) nearly always recur after standard initial treatment, and the resulting mixture of recurrent tumor and treatment-induced reactive changes presents major diagnostic challenges. Anatomical imaging, such as MRI, cannot adequately distinguish progressive disease from treatment effect (pseudo-progression). Furthermore, there is marked intra-tumoral heterogeneity, such that some areas of a tumor may demonstrate necrotic treatment effect and others frank recurrence. Due to this difficulty reliably differentiating between these two clinical findings, analytic methods using multiple modalities are necessary to further our understanding of this disease process. To this end, we sought to correlate radiographic, histopathologic and molecular features of surgically sampled post-treatment suspected recurrence to identify markers distinguishing tumor growth from treatment effect. We performed Stimulated Raman Histology (SRH) imaging and highly multiplexed RNA-sequencing (PLATE-seq) on 84 MRI-localized biopsies from 39 patients with clinically suspected recurrent HGG. The SRH images were classified as recurrent tumor or gliotic/reactive tissue using a convolutional neural network trained on an independent cohort including a large set of recurrent HGG, and an automated cell-counting algorithm was used to quantify cellularity from the SRH image of each sample. Differential gene expression analysis of the PLATE-seq data was used to identify gene sets that distinguish recurrent tumor from treatment effect, and single sample gene set variation analysis (GSVA) was used to further assess the molecular and cellular composition of each MRI-localized sample. The histopathologic and molecular features of each sample were also correlated with the MRI features of the corresponding biopsy sites, and this data is currently being used to train machine learning models that predict the distribution of recurrent tumor and treatment-induced reactive changes within a patient’s radiographic lesion. These predictive radiomic models will help to guide neurosurgical sampling, and improve our ability to monitor glioma progression and response to therapy.

Microglia are a major cellular component of gliomas, and abundant in the centre of the tumour and at the infiltrative margins. While glioma is a notoriously infiltrative disease, the dynamics of microglia and glioma migratory patterns have not been well characterized. To investigate the migratory behaviour of microglia and glioma cells at the infiltrative edge, we performed two-colour time-lapse fluorescence microscopy of brain slices generated from a platelet-derived growth factor-B (PDGFB)-driven rat model of glioma, in which glioma cells and microglia were each labelled with one of two different fluorescent markers. We used mathematical techniques to analyse glioma cells and microglia motility with both single cell tracking and particle image velocimetry (PIV). Our results show microglia motility is strongly correlated with the presence of glioma, while the correlation of the speeds of glioma cells and microglia was variable and weak. Additionally, we showed that microglia and glioma cells exhibit different types of diffusive migratory behaviour. Microglia movement fit a simple random walk, while glioma cell movement fits a super diffusion pattern. These results show that glioma cells stimulate microglia motility at the infiltrative margins, creating a correlation between the spatial distribution of glioma cells and the pattern of microglia motility.

Abstract Glioblastoma (GBM) is the most common malignant primary brain cancer. With a median survival of about a year, new approaches to treating this disease are necessary. To identify signaling molecules regulating GBM progression in a genetically engineered murine model of proneural GBM, we quantified phosphotyrosine-mediated signaling using mass spectrometry. Oncogenic signals, including phosphorylated ERK MAPK, PI3K, and PDGFR, were found to be increased in the murine tumors relative to brain. Phosphorylation of CDK1 pY15, associated with the G2 arrest checkpoint, was identified as the most differentially phosphorylated site, with a 14-fold increase in phosphorylation in the tumors. To assess the role of this checkpoint as a potential therapeutic target, syngeneic primary cell lines derived from these tumors were treated with MK-1775, an inhibitor of Wee1, the kinase responsible for CDK1 Y15 phosphorylation. MK-1775 treatment led to mitotic catastrophe, as defined by increased DNA damage and cell death by apoptosis. To assess the extensibility of targeting Wee1/CDK1 in GBM, patient-derived xenograft (PDX) cell lines were also treated with MK-1775. Although the response was more heterogeneous, on-target Wee1 inhibition led to decreased CDK1 Y15 phosphorylation and increased DNA damage and apoptosis in each line. These results were also validated in vivo, where single-agent MK-1775 demonstrated an antitumor effect on a flank PDX tumor model, increasing mouse survival by 1.74-fold. This study highlights the ability of unbiased quantitative phosphoproteomics to reveal therapeutic targets in tumor models, and the potential for Wee1 inhibition as a treatment approach in preclinical models of GBM. Mol Cancer Ther; 15(6); 1332–43. ©2016 AACR.